Hydrologic Function: Framework Considerations and ... Documents/NVCA_Hydrologic_Functi… · interaction with the environment including its relation to living things. (OMMAH, 2014).

Hydrologic Function: Framework

Considerations and Approach to

Subwatershed Baseline Characterization

Completed by Angela Mills and Ryan Post

June 2018

Nottawasaga Valley Conservation Authority

Hydrologic Function: Framework Considerations and Approach to Subwatershed Baseline Characterization i

Executive Summary

The concept of hydrologic function has been a specific policy direction in the Provincial Policy Statement (PPS) since 2005. The PPS and provincial plans use the same definition for hydrological function. Hydrologic function is defined in the provincial

land use plans and by the PPS, 2014 as:

the functions of the hydrological cycle that include the occurrence, circulation,

distribution, and chemical and physical properties of water on the surface of

the land, in the soil and underlying rocks, and in the atmosphere, and water’s

interaction with the environment including its relation to living things.

(OMMAH, 2014).

Further, the PPS, 2014 and other provincial land use plans state that the hydrologic

function, particularly of sensitive hydrologic features must be protected, improved, and restored within or near sensitive hydrologic features. Further, “key hydrologic features” are generally defined or described in the plans to include permanent

streams, intermittent streams, kettle and inland lakes and their littoral zones, seepage areas and springs, and wetlands.

Implementing provincial land use planning policy direction in the PPS and provincial

plans requires that hydrologic function be determined or measured as part of the

requirement to improve or restore the quality and quantity of water. Planners and

practitioners need to know the current hydrologic conditions, what needs to be

protected, how the function can be improved, and what the target is for restoration.

The contents and findings of this report support the implementation of provincial

policy by proposing the establishment of an evidence-based approach to the

evaluation of hydrologic function. This report 1) proposes a scale-based framework

approach to evaluate hydrologic function including baseline indicators and 2) applies

a regional baseline characterization approach to four southern Ontario

subwatersheds: Skootamatta River, Innisfil Creek, Whitemans Creek, and Parkhill

Creek to evaluate applicability, and lessons learned.

The proposed hydrologic function assessment is recommended to be completed at

two scales: local/site alteration scale and the broader regional/subwatershed scale.

This spatial-scale approach is based on the premise that if the local hydrologic

function is maintained where development (e.g., a subdivision, commercial

development, etc.) occurs, then the baseline regional/subwatershed relationship

between groundwater and surface water conditions should also be maintained;

excluding climatic alterations.

The local or site alteration scale assessment identifies local hydrologic features and

functions (e.g., surface water features, significant groundwater recharge areas

Hydrologic Function: Framework Considerations and Approach to Subwatershed Baseline Characterization ii

(SGRA), etc.) and their associated connectivity with an associated buffer to the

parcel. This local scale evaluation is complimented by either a Thornthwaite-Mather

water balance where no key hydrologic features are mapped or a feature-based water

balance within the mapped buffers of key hydrologic features and functions are

mapped or observed. The water balance exercise calculates the independently the

pre- and post-development recharge rates, surface water discharge, etc. In order to

maintain pre-alteration hydrologic function following development, the hydrologic

components, notably infiltration/recharge rates need to be maintained.

Thematic and temporal characterization at the subwatershed scale compliments the

local scale evaluation by providing baseline information on land use (thematic)

delineation and groundwater and surface water trends and relationships (time series

and statistical relationships) to which the local scale information can be periodically

assessed against. The thematic land use information consists of significant

groundwater recharge area, surface water features, percent impervious surface, and

forest cover. The subwatershed baseline characterization is fundamentally based on

the evaluation of key time series hydrologic datasets: climate, surface water flow,

and groundwater. For future analysis, at a minimum, one climate, stream gauge, and

groundwater monitoring well is recommended to undertake this analysis, generalized

for subwatersheds less than 500 km2.

A comprehensive evaluation of the subwatershed baseline characterization approach

was completed for four subwatersheds in southern Ontario: Skootamatta River,

Innisfil Creek, Whitemans Creek, and Parkhill Creek. The thematic mapping is

comprised of SGRAs, surface water features, forest cover, and percent impervious

area, using provincially available datasets. To complement the thematic mapping but

not presently readily available, ecologically significant groundwater recharge areas

(ESGRAs) are encouraged to be delineated. The ESGRAs maps the spatial recharge

area extent to groundwater-dependent hydrologic features, allowing for the

protection of the hydrologic function. Further it is envisioned that ESGRA mapping

would complement the SGRA mapping; collectively highlighting where hydrologically-

important recharge areas, whether they discharge to sensitive hydrologic features

(i.e., ESGRAs), or whether they contribute greater volumes of groundwater recharge

to local aquifers (i.e., SGRAs). Further, to streamline the thematic mapping process,

percent forest cover could be obtained through the Watershed Report Card processes,

where available.

The subwatershed baseline characterization analysis, completed on a 10 year

interval, requires a minimum of >10 years of data with >90% completeness at the

monthly interval. As related to the four targeted subwatersheds, major challenges

were identified related to the availability and record length for groundwater e.g., the

use of partial groundwater datasets to unable being groundwater completed (e.g.,

Whitemans Creek). It is noted that other ambient/baseline monitoring wells (e.g.,

conservation authority or municipality) could be used, preferably screened in an

Hydrologic Function: Framework Considerations and Approach to Subwatershed Baseline Characterization iii

unconfined system to assess the impacts of local changes and provided that there is

a minimum 10-year record length with complete dataset. In addition, many climate

stations with long-term data sets are no longer active although gaps in climate data

were filled based on nearby climate station data. Regarding surface water data

availability, the Water Survey of Canada stream gauges were principally used;

however, it is recognized that there are ungauged subwatersheds. To remedy this,

additional stream gauge monitoring stations could be used (e.g., conservation

authority, municipality), based on the quality of available data.

Using the hydrologic data (climate, surface water discharge, and groundwater levels),

a statistical analysis was completed to: 1) assess potential observable temporal

trends through the study period (1981-2016), 2) evaluate the relationship between

hydrologic components, and 3) highlight the relationship and changes in relationship

of a) streamflow as a function of precipitation and b) baseflow as a function of

streamflow in each of the pilot subwatersheds. Determination of time series trends

was statistically evaluated using annual and seasonal data for: 1) time series trends

using the Mann-Kendall trend test (McLeod, 2011), 2) correlation through the

Kendall’s rank (tau, 𝜏; Revelle, 2017), Spearman’s rank (rho, 𝜌; Revelle, 2017), and

3) linear regression, using least squares (𝑅2). All correlations identified through the

Spearman’s Rank were also identified by Kendall’s Rank, but the latter indicated

additional correlations that Spearman’s did not; supporting the use of Spearman’s

Rank and linear regression for future analysis. Linear regression analysis, conducted

in ‘R’, was tested when the Spearman’s Rank and Kendall’s Rank tests both indicated

a strong correlation. It cannot therefore be determined whether there would have

been numerous occasions where linear regression corresponded with only one but

not both of the other correlation analyses. Lastly, double-mass balance analysis was

conducted to highlight a change in the relationship between two variables.

Lessons learned from the application of the subwatershed baseline characterization

to four subwatersheds in southern Ontario are as follows:

Using baseflow as derived from streamflow may not be the most usefulindicator especially when compared to streamflow as indicator

Finding reliable climate stations with full datasets is easier than manuallyfilling whole datasets

Meeting minimum data requirements (e.g., groundwater 10-year datasetfor GW) is important to facilitate comparisons

Geologic setting of groundwater station is important – e.g., the lag in

rebounding after Parkhill sampling impacts seasonal and annual analysis –

GW sites that have such known ‘challenges’ should restrict sampling to

October to avoid needing to omit data from JAS and OND analysis.

Hydrologic Function: Framework Considerations and Approach to Subwatershed Baseline Characterization iv

Further, for future application, the subwatershed baseline characterization is most

applicable in southern Ontario, due primarily to data availability both thematically

and temporally. Due to the requirement for a minimum of 10 years of data for

statistical comparisons, it is recommended to conduct such analyses in 10-year

intervals to further facilitate time series comparison. The 10-year interval aligns with

the Conservation Authority Watershed Report Cards which are issued on a five year

cycle. The site-specific local scale evaluation is on-going and driven based on

proposed development (e.g., proposed subdivision application) would be based on

the locally identified hydrologic features e.g., lakes, rivers, streams, (etc.) and other

types of surface water features (i.e., wetlands, groundwater discharge areas, etc.).

It is recommended that the local planning authority map the development locations

on an annual basis.

Overall conclusions from the regional/subwatershed-scale thematic mapping and

time series analyses are as follows:

The spatial distribution of SGRAs and hydrologic features strongly influencesthe hydrologic response and therefore function of the subwatershed

The climate input variables that detected temporal trends were primarilytemperature-related for most subwatersheds, though precipitation/hydrologic

release trends were observed in one of them

Each subwatershed had parameters with temporal trends and correlations,however, there was no single parameter that was found to be trending nor pair

of parameters that have strong correlations at all four pilot subwatersheds

Temporal trends and statistical correlations detected at one temporal scale

(e.g., annual) do not necessarily correspond to trends and correlations at theother (e.g., seasonal) within the same subwatershed

Each subwatershed will respond differently annually and seasonally, based on

the hydrologic features and land use, therefore it is important to conduct this

analysis of hydrologic function for all subwatersheds

The knowledge gained through application of this framework will enable protection,

improvement, and restoration of hydrologic function in Ontario as per the PPS and

land use plans. The framework would ideally be used before and after development

to assess whether hydrologic functions have been protected, improved, or restored

as per the requirements of the PPS and provincial land use plans.

Hydrologic Function: Framework Considerations and Approach to Subwatershed Baseline Characterization v

Acknowledgements

The project team would link to extend thanks to the members of the Project

Advisory Committee who contributed both time and expertise to the project’s success:

Andy Beaton (MNRF; Surface Water Monitoring Centre)

Victor Doyle (MMA; Provincial Planning Policy Branch)

Scott MacRitchie (MOECC; Groundwater and Stream Water Monitoring Unit)

Matthew Millar (Conservation Ontario)

Stephanie Papadimitriou (MMA; Greater Golden Horseshoe Greenbelt Selection)

Andrew Piggott

Asia Pineau (MMA; Ontario Growth Secretariat)

Eleanor Stainsby (MOECC; Climate Change and Environmental Policy Division)

Magdi Widaatalla (MOECC; Groundwater and Stream Water Monitoring Unit)

Funding for this project was provided by the Ontario Ministry of Environment and

Climate Change (MOECC).

Alternative Formats: If you require this document in an alternative format, please

contact the Nottawasaga Valley Conservation Authority (NVCA) at [email protected]

or 705-424-1479.

mailto:[email protected]

Hydrologic Function: Framework Considerations and Approach to Subwatershed Baseline Characterization vi

Table of Contents

Executive Summary ........................................................................................ i

Acknowledgements ........................................................................................ v

1. Introduction ............................................................................................. 1

2. Policy Framework and Planning Context ...................................................... 2

2.1. The Provincial Policy Statement, 2014 ................................................... 3

2.2. The Provincial Land Use Plans ............................................................... 4

2.2.1. The Growth Plan for the Greater Golden Horseshoe, 2017 and Greenbelt Plan, 2017 ............................................................... 4

2.2.2. The Oak Ridges Moraine Conservation Plan, 2017 .............................. 5

2.2.3. The Niagara Escarpment Plan, 2017 ................................................ 5

2.2.4. Lake Simcoe Protection Plan ........................................................... 6

2.3. Municipal Official Plans ........................................................................ 6

3. Hydrologic Function Overview .................................................................... 7

3.1. Practical Definition .............................................................................. 7

3.2. Water Balance .................................................................................... 8

3.3. Hydrologic Landscape Units and Connectivity ......................................... 8

3.4. Hydrologic Function: Urban vs. Rural Subwatersheds ............................ 10

3.5. Hydrologic Function and Climate Change ............................................. 12

3.5.1. Collection ................................................................................... 12

3.5.2. Storage ...................................................................................... 13

3.5.3 Discharge ................................................................................... 13

4. Jurisdictional Use of Hydrologic Function ................................................... 14

5. Proposed Hydrologic Function Framework .................................................. 16

5.1. Site Alteration/Major Development (Local) Hydrologic Function Evaluation 17

5.2. Subwatershed (Regional) Scale Hydrologic Function Evaluation .............. 17

6. Proposed Subwatershed Baseline Characterization Indicators ....................... 18

6.1. Thematic Land Uses .......................................................................... 19

6.1.1. Significant Groundwater Recharge Areas ........................................ 19

6.1.2. Surface Water Features ................................................................ 20

6.1.3. Percent Impervious Area .............................................................. 21

6.1.4. Forest Cover ............................................................................... 22

Hydrologic Function: Framework Considerations and Approach to Subwatershed Baseline Characterization vii

6.2. Time Series Hydrologic Variables and Indicators ................................... 23

6.2.1. Climate Variables ........................................................................ 24

6.2.2. Hydrologic Indicators ................................................................... 26

6.3. Subwatershed Hydrologic Function Characterization

—Pilot Subwatersheds ....................................................................... 31

6.3.1. Skootamatta River ....................................................................... 33

6.3.2. Innisfil Creek .............................................................................. 33

6.3.3. Whitemans Creek ........................................................................ 34

6.3.4. Parkhill Creek ............................................................................. 35

7. Subwatershed Hydrologic Function Characterization Methodology ................. 37

7.1. Thematic Mapping Methodology .......................................................... 37

7.2. Statistical Analysis Methodology ......................................................... 38

7.3. Data Processing and Infilling Methodology ............................................ 42

7.4. Data Availability by Subwatershed ...................................................... 47

7.4.1. Skootamatta River ....................................................................... 47

7.4.2. Innisfil Creek .............................................................................. 50

7.4.3. Whitemans Creek ........................................................................ 54

7.4.4. Parkhill Creek ............................................................................. 57

8. Results ............................................................................................ 61

8.1. Skootamatta River ............................................................................ 61

8.1.1. Thematic Mapping Analysis ........................................................... 61

8.1.2. Time Series Analysis .................................................................... 66

8.2. Innisfil Creek .................................................................................... 73



8.3. Whitemans Creek .............................................................................. 86



8.4. Parkhill Creek ................................................................................... 96


8.4.2. Time Series Analysis .................................................................. 101

9. Discussion and Comparison between Subwatersheds ................................ 107

10. Conclusions and Recommendations ........................................................ 114

References ............................................................................................. 119

Hydrologic Function: Framework Considerations and Approach to Subwatershed Baseline Characterization viii

Appendix A. Key Parameter Codes and Associated Definitions ...................... 131

Appendix B. Climate Filling Data Adjustment Values ................................... 132

Appendix C. Climate Filling Sample Calculation .......................................... 136

Appendix D. Skootamatta River Complete Analysis Results .......................... 138

Appendix E. Innisfil Creek Complete Analysis Results .................................. 153

Appendix F. Whitemans Creek Complete Analysis Results ........................... 169

Appendix G. Parkhill Creek Complete Analysis Results ................................. 183

Hydrologic Function: Framework Considerations and Approach to Subwatershed Baseline Characterization 1

1. Introduction

Water is an important part of the natural environment as it sustains human life, economies, and natural systems. Ontario’s land use planning system recognizes the fundamental value of water and protects water for present and future use. Provincial

land use interests are set out in the Provincial Policy Statement, 2014 (PPS) issued under the Planning Act. The concept of hydrologic function has been a specific policy

direction in the PPS since 2005. Additionally, there are four provincial land use plans that apply in certain areas of southern Ontario - the Growth Plan for the Greater Golden Horseshoe (the Growth Plan), 2017; Greenbelt Plan, 2017; Oak Ridges

Moraine Conservation Plan (ORMCP), 2017; and Niagara Escarpment Plan (NEP), 2017. These plans work together with the PPS to manage growth, build complete

communities, curb sprawl, and protect the natural environment in the Greater Golden Horseshoe (GGH).

The four provincial plans were updated in 2017 through the Coordinated Land Use Planning Review. As a result of the review, the plans now include aligned terminology

and policies, where appropriate, harmonizing the four plans with each other and the PPS. The Growth Plan, Greenbelt Plan, ORMCP, and NEP all contain terminology and

policies to identify and protect key hydrologic features and functions.

The PPS and provincial plans use the same definition for hydrological function. Hydrologic function is defined in the provincial land use plans and by the PPS, 2014

as:

The functions of the hydrological cycle that include the occurrence, circulation,

distribution, and chemical and physical properties of water on the surface of

the land, in the soil and underlying rocks, and in the atmosphere, and water’s

interaction with the environment including its relation to living things.






A body of knowledge has built up over time as municipalities and approval authorities

have implemented provincial policy. This means that while there is a range of best

practices for implementation currently in use across the region, there is no single,

widely recognized existing framework for benchmarking and evaluating hydrologic

function.

Some research suggests certain gaps in knowledge, such as an understanding of the

aggregated impact of landscape changes on hydrologic function (Brooks, et al.,

2006), as well as of groundwater-surface water exchanges (including quantification,


flow paths, and spatial heterogeneity) and the impact of urbanization on these water

resources (Chu, et al., 2016).

Drawing on current approaches to implementation and lessons learned from the

literature, this report aims to support the implementation of provincial policy by

establishing an evidence-based approach to the evaluation of hydrologic function.

This report:

sets out the legislative provincial planning and policy context for hydrologic

function

examines how hydrologic function is defined within the scientific community

documents the inter-jurisdictional community of practice

proposes a framework and methodology to evaluate hydrologic function at a

defined spatial context including indicators to be used to benchmark.

A subwatershed-scale, baseline evaluation of both thematic and temporal data will

be completed using four test sites across southern Ontario in support of the

hydrologic framework approach.

This knowledge will enable protection, improvement, and restoration of hydrologic

function in Ontario as per the PPS and land use plans. The framework would ideally

be used before and after development to assess whether hydrologic functions have

been protected, improved, or restored as per the requirements of the PPS and

provincial land use plans.

This project focuses exclusively on the physical component of hydrologic function.

Other functions that are dependent on hydrologic functions, such as biogeochemical

cycling and ecological or habitat functions (Maltby, 2009; McLaughlin & Cohen, 2013;

Winter, 2001), are outside the scope of this report.

Funding for this project was provided by the Ontario Ministry of Environment and

Climate Change (MOECC).

2. Policy Framework and Planning Context

Ontario utilizes a “policy-led” land-use planning system, which means that the

province sets the policy framework and municipalities are the primary implementers

(decision-makers). The province’s interests in land use policies are set out in the PPS,

issued under the Planning Act, as well as in provincial plans such as the Growth Plan,

Greenbelt Plan, ORMCP, and NEP. The PPS and four provincial land use plans provide


policy direction on matters of provincial interest related to land use planning,

including policy direction relating to protecting water resources.

Municipalities are responsible for implementing provincial land use policies and plans

through their official plans and zoning by-laws. The Ministry of Municipal Affairs

(MMA) is generally responsible for approving upper- and single- tier municipal official

plans or official plan amendments, with input from partner ministries.

Technical background work including master plans, environmental assessments,

various studies or other research, and preparation of associated documentation (e.g.,

watershed plans, environmental assessments, and water taking permits) are used to

inform land use planning decisions on development, infrastructure, and resource

management. Knowledge of hydrology, hydrologic features, areas, and systems, and

their functions feed into the planning process and guides the development of relevant

policies that conform to the provincial plans and are consistent with the PPS.

2.1. The Provincial Policy Statement, 2014

The PPS is issued under section 3 of the Planning Act and sets out provincial land use

planning policies (Ontario Ministry of Municipal Affairs and Housing, 2014). It applies

province-wide and provides policy direction on a range of provincial interests

including growth management, water, infrastructure, housing, natural hazards,

aggregate resources, natural heritage and agricultural land protection.

The PPS includes policies requiring planning authorities to protect, improve, or restore

the quality and quantity of water (Policy 2.2) by undertaking a range of actions. This

includes using the watershed as the ecologically meaningful scale for integrated and

long-term planning, and identifying water resource systems consisting of ground and

surface water features, hydrologic functions, and natural heritage features and areas

(Policy 2.2.1 c). The PPS also restricts development and site alterations in or near

sensitive water features (both above and below ground), such that the features and

their related hydrologic functions will be protected, improved, or restored.

Municipalities and other land use decision-makers need to be consistent with PPS

policies as they make land use decisions. The PPS policies are to be read in their

entirety and all relevant policies are to be applied to each situation.

The PPS policies represent minimum standards. The policies do not prevent planning

authorities and decision-makers from going beyond the minimum standards

established in specific policies, unless doing so would conflict with any policy of the

PPS.


2.2. The Provincial Land Use Plans

The Growth Plan, Greenbelt Plan, Oak Ridges Moraine Conservation Plan (ORMCP),

and Niagara Escarpment Plan (NEP) build upon the PPS to provide more detailed

policy direction, and in some cases, to specify greater protections in their respective

geographic areas. Each of the four plans reiterates the need to protect, improve, and

restore hydrologic functions and key hydrologic features. Each provincial land use

plan listed above provides the same definition of hydrologic function as the PPS.

Although the four plans differ slightly, “key hydrologic features” are generally defined

or described in the plans to include:

permanent streams, intermittent streams, kettle and inland lakes and their

littoral zones, seepage areas and springs, and wetlands.

The term “key hydrologic area” is defined only by the Growth Plan and Greenbelt Plan

as:

significant groundwater recharge areas, highly vulnerable aquifers, and

significant surface water contribution areas that are necessary for the

ecological and hydrologic integrity of a watershed.

Note: The above is only an overview of definitions and the appropriate plan should

always be consulted for complete policy requirements and definitions.

Other provincial plans, including the Lake Simcoe Protection Plan (LSPP) under the

Lake Simcoe Protection Act, 2008 and some source protection plans under the

Clean Water Act, 2006, also apply within the Greater Golden Horseshoe (GGH).

Each of these plans applies to certain defined parts of the GGH and provides

specific policy on certain matters.

2.2.1. The Growth Plan for the Greater Golden Horseshoe, 2017 and

Greenbelt Plan, 2017

The Growth Plan, 2017 (OMMA, 2017b) and the Greenbelt Plan, 2017 (OMMA, 2017a)

have been harmonized to provide a consistent level of protection for water and

natural heritage across the GGH. For example, the Growth Plan now requires

municipalities to identify and protect key natural heritage features and key hydrologic

features and functions outside settlement areas, whereas previously this was only a

requirement in the Greenbelt Plan. The Province has also recently mapped a Natural

Heritage System (NHS) for the Growth Plan area, which builds on the NHS for the

Greenbelt Plan, and aims to establish a natural heritage system covering for all of

the GGH through the Greenbelt Plan, ORMCP, NEP, and Growth Plan policies. The

NHS for the Growth Plan must be incorporated and protected in local official plans.


The Growth Plan and Greenbelt Plan policies require watershed planning to be

undertaken to inform the protection of water resource systems, decisions related to

planning for growth, and subwatershed planning to inform site-specific land use

planning decisions. The impact of an individual site-specific change may not be

detectible at the watershed scale, however, the cumulative impact of many changes

throughout the watershed can significantly alter the overall hydrologic function.

Water resource systems are also recognized for their importance where protection of

hydrologic functions and natural heritage features is needed for protecting the

ecological and hydrologic integrity of the watershed. Watershed planning

components, as defined in the Growth Plan and Greenbelt Plan, are typical, or

recommended to provide municipalities with flexibility. Watershed plans must always

be properly scoped to reflect local circumstances, capacity and reflect existing

equivalent studies.

In both the Growth Plan and Greenbelt Plan area, most development or site alteration

is prohibited in key natural heritage features that are part of the NHS or in all key

hydrologic features. Additionally, development or site alteration in proximity to

features must complete an environmental study to determine an appropriate

minimum buffer.

2.2.2. The Oak Ridges Moraine Conservation Plan, 2017

The ORMCP is an ecologically-based plan that provides land use and resource

management direction for the land and water within the Moraine (OMMA, 2017c).

The Plan’s objectives include protecting the hydrological integrity of the Oak Ridges

Moraine Area, including the quality and quantity of its water.

ORMCP policies require municipalities to undertake watershed planning. The Plan also

states that outside of Settlement Areas, development and site alteration is prohibited

if it would cause the level of impervious surface cover in a subwatershed to exceed

10%. The Plan also encourages the maintenance of 30% self-sustaining vegetation

cover at the subwatershed scale outside of Settlement Areas. The ORMCP watershed

plan contents, as provided in section 24(3), are required as a minimum. Municipalities

may consider integrating requirements under ORMCP with components outlined in

the Growth Plan and Greenbelt Plan definitions, to ensure adequate consideration of

cross-jurisdictional and cross-watershed impacts of growth, development, and

infrastructure across plan areas.

2.2.3. The Niagara Escarpment Plan, 2017

The NEP is also an example of a geographically-specific provincial plan; however, it

is implemented slightly differently than the other three plans of the review. The NEP


is implemented through a development control system outside of urban areas and is

administered by the Niagara Escarpment Commission (NEC), an agency of the

Government of Ontario (OMNRF, 2017). This system requires that the Commission

regularly make decisions on site specific applications for development permits in the

NEP area based on whether a proposed development is in accordance with Plan

policies. While this is done in consultation with municipalities, the Niagara

Escarpment development permit takes precedence and must be issued prior to any

other municipal approval being granted. The subsequent municipal decisions are

required to “not conflict with” the NEP.

The NEP does not require watershed planning specifically, although approved

watershed planning/subwatershed plans can inform land use, infrastructure, and

development decision-making.

2.2.4. Lake Simcoe Protection Plan

The Lake Simcoe Protection Plan (LSPP) applies to the Lake Simcoe watershed, which

is defined in the Lake Simcoe Protection Act (2008). The Plan speaks in detail about

actions to be taken to protect and restore the ecological health of the Lake Simcoe

watershed and subwatersheds (OMOE, 2009).

Although the LSPP does not specifically mention hydrologic function, the plan does

speak to ecologic features and functions which are defined to encompass hydrologic

functions.

2.3. Municipal Official Plans

Municipalities are the primary implementers of provincial policy and are responsible

for implementing provincial land use policies and plans through their official plans

and zoning by-laws.

Planning tools and processes (e.g., watershed plans, environmental assessments,

and water taking permits) are used to inform decisions on development,

infrastructure, and resource management. Knowledge of hydrology, hydrologic

features, areas, and systems, and their functions feed into the planning tools to

develop policies relevant to these landscapes and functions which can lead to

restriction on development activities and provide guidelines for mitigating

disturbances through design modifications.

The impact of an individual change may not be detectible at the watershed scale,

however, the cumulative impact of many changes throughout the watershed can

significantly alter the overall hydrologic function. It is for this reason that


development must be responsible for maintaining hydrologic function at the local

scale to ensure the protection of the broader watershed’s hydrologic functions.

Hydrologic function is also captured indirectly at the local level via the planning

process. An example is the Evaluation, Classification, and Management of Headwater

Drainage Features Guidelines which classifies the function of headwater areas by

hydrology, riparian community structure, and fish and terrestrial habitat (Toronto

and Region Conservation Authority [TRCA] & Credit Valley Conservation [CVC],

2014). Rather than determining the potential functions performed by the headwater

areas, this method quantifies the significance of the functions being performed.

3. Hydrologic Function Overview

3.1. Practical Definition

The definition of hydrologic function provided in the PPS and provincial plans is broad.

Further, the literature refers to related concepts to hydrologic function such as

watershed or catchment function (the actions of the landscape on water within the

catchment; Wagener, et al., 2007), ecologic function (processes, products, and

services that biotic and abiotic features create or carry out including hydrological

functions; CVC, 2009; OMMA, 2017a), and wetland function (processes or

phenomena that occur within wetlands including flood-flow alteration, groundwater

recharge and discharge, biogeochemical cycling, and habitat maintenance; Brinson,

1993; Novitzki, et al., 1996; Smith, et al., 1995, Wray & Bayley, 2006). Also, some

studies mention hydrological function and simply provide examples, such as

groundwater recharge, flow conveyance, or storage, without providing a definition

(e.g., Barbier, et al., 1997; Del Giudice, n.d.; McLaughlin & Cohen, 2013; Taylor &

Pierson, 1985).

Hydrology is the science that encompasses the occurrence, distribution, movement,

and properties of water and their relationship with the environment within each phase

of the hydrologic cycle. Function is defined as the interaction between the

components of a system or cycle (Barbier, et al., 1997). A practical definition of

hydrologic function is the components (i.e., hydrologic features and areas such as

lakes, streams, or groundwater) and processes (i.e., the way in which water moves

through the environment including precipitation, evapotranspiration, recharge, and

discharge) associated with hydrologic connectivity and water balance within a defined

spatial extent. From this practical definition, the processes of water movement can

be addressed through the application of a water balance.


3.2. Water Balance

Water balance is a term used to describe the accounting of inflow and outflow of

water in a system (e.g., wetland) according to the processes of the hydrologic cycle

(Hendriks, 2010; Mitsch & Gosselink, 2007). The mathematical expression of the

water balance is termed the water budget. In general, precipitation (P) is the primary

input that is collected and then transmitted through surface or subsurface storage

(S) before being discharged. Water leaves the system through evapotranspiration

(ET), groundwater (GW) outflow, and surface water discharge (Q). The relative

importance of each of these processes within the water balance of a given system is

dependent on a number of factors including landscape position. Mathematically, it is

defined as:

P + GWin – (GWout + ET +Q) = ∆S

This can be further layered with hydrologic response of each parameter via watershed

routing, storage, and loss processes (i.e., Figure 1; Fetter, 2001). Climate and land-

use changes strongly impact the water balance components (Mimikou & Baltas,

2013).

Utilizing principles of a water balance, Black (1997) outlines five watershed functions:

collection, storage, discharge, habitat, and chemical functions. Of these, only the

collection, storage, and discharge functions are directly hydrological in nature. The

collection function outlines how water is gathered within the spatial unit and is

dependent on precipitation event properties including its type (e.g., rain vs. snow),

relative size, and position within the spatial unit (Black, 1997). The storage function

is the intermediate stage between the collection and discharge functions. It

encompasses the type, amount, and distribution of storage available within a spatial

unit; including surface storage (depression, channel, detention, and retention

storage, for either short or long-term temporary storage), subsurface and

groundwater storage, and vegetation storage (Black, 1997; Smith, et al., 1995). The

total storage capacity and type of storage available depend on local geology,

topography, geomorphology, and ecological communities for vegetation storage. The

discharge function, depicted through a hydrograph, illustrates how (i.e., duration and

magnitude) water is exported from a system (Black, 1997).

3.3. Hydrologic Landscape Units and Connectivity

The landscape is composed of what Winter (2001) terms fundamental hydrologic

landscape units. These are comprised of an upland area separated from a lowland

area by a sloping area, where each component is variable in width and intervening

slope gradient. Generically, each part of the hydrologic landscape unit will have

dominant hydrologic functions that differ from those of the other components. For


example, upland areas are dominantly a source for groundwater recharge or surface

water runoff, and the base of a slope is often where groundwater discharge occurs.

At the subwatershed scale, the landscape is composed of nested multiples of these

units at multiple scales (Winter, 2001; Wolock, et al., 2004) and by extension

multiple hydrologic functions over a range of scales that are integrated to produce

the overall hydrologic function of the landscape feature.

Landscape-scale hydrology is driven by the dynamics of storage and flow between

surface water and groundwater systems and the connectivity between these systems

controls how hydrologic changes in one area impact behavior in others (McLaughlin,

et al., 2013; Winter, 1988). Hydrologic connections can link hillslopes to channel

networks, streams to lakes, surface to subsurface, land to atmosphere, terrestrial to

aquatic, and upstream to downstream. These connections can develop across

vertical, lateral, and longitudinal dimensions and span spatial and temporal scales.

Each of these dimensions and scales are interconnected, creating a mosaic of nested

hydrologic connections and associated processes (Covino, 2017). However, the

structural complexity of most temperate watersheds (i.e., connections among shallow

soils, deep aquifers, the atmosphere, and streams) and the dynamic seasonal

changes that occur within them (e.g., plant senescence which impacts

evapotranspiration) create significant challenges to characterizing or quantifying

hydrologic connectivity (Figure 2, Gooseff, et al., 2017).

The hydrologic functions of a system are dynamic, change through the year, and

respond to long-term seasonality and short-term event response. For example,

evapotranspiration rates affect the antecedent moisture conditions through the warm

growing season most and less in the non-growing but above zero degrees Celsius

time as reflective in a typical groundwater hydrograph or hydroperiod. In some

systems, the direction of groundwater-surface water exchange is reversed in

response to hydrologic input events (McLaughlin & Cohen, 2013; Taylor, 2016).

Dominant lateral hillslope to riparian zone to stream hydraulic gradients may be

reversed when water levels in the stream are higher than the hydraulic head of the

adjacent riparian zone (Russo, et al., 2012).

Potential hydrologic functions depend on the physical characteristics of the hydrologic

feature or area including: soil structure and permeability, water flow paths and

volume, feature volume, basin size, precipitation, evapotranspiration, and other

climatic factors (Wray & Bayley, 2006). Based on landscape position and disturbance

status, not all potential functions may be activated nor used to their full capacity.

Whether a system will perform a given function, and to what degree largely depends

on climate (i.e., precipitation magnitude, frequency, intensity, seasonality, and air

temperature), topography (i.e., surficial slope and shape), geology (i.e., permeability

of surface and underlying sediments/bedrock), and the presence and type of

vegetation growth (Bullock & Acreman, 2003; Maltby, 2009; Smith, et al., 1995;

Winter, 2001), with human activity able to rapidly modify the latter three


characteristics. Sites that have either been directly disturbed or are down gradient

from disturbed sites will have modified hydrologic functions.

Figure 1: Example of hydrologic response and connectivity on a forested swamp,

British Columbia displaying potential evapotranspiration (top), precipitation

accumulation (middle), and discharge (bottom) and comparing event response over

a range of antecedent moisture conditions. Progression from dry conditions to wet

conditions on October 21 is indicated by the dashed line (Martin, 2011).

3.4. Hydrologic Function: Urban vs. Rural Subwatersheds

Land use change alters hydrological characteristics and functionality by affecting

water flow paths, runoff processes, and the rates of infiltration, erosion, and

evapotranspiration. For example, changes in land use (e.g., rural to urban) can

significantly alter stream and wetland dynamics, potentially involving conversions


between ephemeral or seasonal and perennial or permanent surface features (Hamel,

et al., 2013). Impervious areas, in the form of parking lots, roadways, lawns (due to

soil compaction during construction), and rooftops reduce infiltration and surface

storage of precipitation and increase surface water runoff (Arnold & Gibbons, 1996).

In a watershed undergoing significant urban development, groundwater levels and

quality may also be significantly impacted by the transition to channelized flow

(Gremillion, et al., 2000). Urbanization changes a watershed’s response to

precipitation. The primary effects include less infiltration and reduced travel time,

which increases peak discharge and runoff (Ward, 2013).

Anthropogenic impacts such as landscape conversion, degradation, and alteration of

spatial connectivity will individually have direct effects on the local ecosystem as well

as indirect effects in other systems that can be cumulative over spatial and temporal

scales (Leibowitz, et al., 2000). Table 1 outlines hydrological impacts of urbanization.

Distinguishing the direct effects of anthropogenic actions within the landscape given

the high degree of landscape fragmentation associated with urbanization and

agricultural development on hydrologic function from the climatic variability and the

effects of climate change is becoming ever more complex. Further, landscape

disturbance changes the magnitude and location of hydrologic function processes,

and may alter the dominant functions (Wassen, et al., 2006). The sensitivity of a

landform to change depends on landscape position and size, for example downstream

areas are generally less vulnerable than headwater areas to a comparable land use

change (Brinson, 1993); however downstream areas are impacted by cumulative

upstream changes.

Changes in the distribution and circulation of water may reflect cumulative impacts

of disturbance and are often more pronounced at the local rather than regional scale

(Environment Canada [EC] & U.S. Environmental Protection Agency [USEPA], 2014).

Anthropogenic landscape alteration generally does not have a linear impact on

hydrologic regime and function as site characteristics such as topography and soil

type may maintain a primary control on function (McLaughlin & Cohen, 2013). For

example, development typically results in increased impervious surfaces which

affects infiltration and storage capacity and may directly affect local and regional

groundwater-surface water exchange processes, impacting runoff generating

processes and storm hydrographs (Black, 1997; Saskatchewan PCAP Greencover

Committee, 2008).


Table 1: Common alterations to watershed physical hydrology and in-stream

processes in response to urbanization.

Hydrology/Process Common Alterations in Response to Urbanization

Precipitation and Evapotranspiration

Increased summer rainfall due to urban heat island in large cities (Oke, 1987)

Evapotranspiration may decrease locally due to decrease in vegetation and increase in impermeable surfaces (Oke, 1987)

Stream Hydrology and Peak flows

Increased peak flows and discharge/stage variability (Leopold, 1968; Smith K. , 2006)

Baseflow and Groundwater

Recharge

Decreased baseflow as a per cent of total annual streamflow (Leopold, 1968)

Changes in groundwater recharge mechanisms and spatial distribution (Leopold, 1968)

Channel Geomorphology

Increased channel dimensions and channel homogeneity (Leopold, 1968)

Decreased headwater stream length/ drainage density (Roy, et al., 2009)

Decreased extent of active floodplain and geomorphic

complexity of the channel downstream of dams (Mitsch & Gosselink, 2007; Smith K. , 2006)

3.5. Hydrologic Function and Climate Change

There remains uncertainty surrounding the impacts climate change will have on local

and regional scale hydrologic functions (Boyer, et al., 2010). Projections of impacts

of climate change on landscape hydrology including groundwater properties are

dependent on the quality of the hydrologic and climatic input models and may not

account for direct human influences such as development and groundwater

withdrawals (Chen, et al., 2002).

3.5.1. Collection

The increases in temperature associated with projected changes in Ontario’s climate

is projected to lead to more winter rainfall, less snowfall, delayed lake ice cover,

thinner lake ice, and earlier snow and ice melt (Boyer, et al., 2010; Nickus, et al.,

2010; Zhang, et al., 2001). In the Great Lakes region, this could result in the

increased occurrence of lake-effect precipitation with longer ice-free periods

(Ashmore & Church, 2001; Mortsch, et al., 2000), affecting the timing and magnitude

of spring freshet. Of particular concern is also the impact a changing spring freshet

may have on the annual streamflow cycle (Cohen & Waddell, 2009). Precipitation

intensity is also expected to increase (Intergovernmental Panel on Climate Change

(IPCC), 2008), bringing more heavy precipitation and summer flood events (Zedler,


2010). There is likely to be an increase in 24-hour extreme precipitation event

frequency (Environment and Climate Change Canada, 2016), an increase in winter

precipitation frequency, and a decrease in summer precipitation frequency, leading

to more extreme droughts in southern Ontario (IPCC, 2012; Zedler, 2010). Increased

frequency of high volume rain events could lead to an increase in extreme flood

discharges, particularly during the summer and early autumn (Ashmore & Church,

2001).

3.5.2. Storage

The net impact of changes in climate will result in changes to the distribution of water

within the landscape, primarily impacting shallow groundwater and surface water

resources. Shallow aquifers that are only hydrologically connected to local recharge

and discharge sources will have stronger responses to changes in climate than those

that are connected to regional-scale recharge sources (Chen, et al., 2002; Kløve, et

al., 2014). Groundwater resources are dependent on recharge which is impacted by

the temporal and spatial distribution of precipitation and evapotranspiration,

including from the surface, vadose zone, and saturated zone (Goderniaux, et al.,

2009), but due to the scale of storage capacity, many aquifers are less sensitive to

changes than precipitation-dependent surface water systems (Brinson, 1993).

Projected increases in precipitation and temperature are expected to increase

groundwater recharge, with the impact of changes in temperature primarily occurring

during winter months (Jyrkama & Sykes, 2007). Groundwater discharge rates may

range from a 19% decrease to 3% increase, depending on climate model and

watershed microclimates (Piggott, et al., 2005a). The high diversity of current

groundwater conditions across southern Ontario suggest variable response to climate

change (Piggott, et al., 2005a).

3.5.3 Discharge

Models consistently project decreases in runoff over mid-latitude North America by

the 2020s, expanding through the 2080s, however projections of change in runoff

remain more variable than those of precipitation or evapotranspiration (Cohen &

Waddell, 2009). Changes in precipitation accumulation may cause a correlated, but

greater change in stream discharge and changes in temperature may result in a

negative response in stream discharge (Ashmore & Church, 2001). Changes in

precipitation and temperature also exert greater influence on ephemeral streamflow

generation than topographic and land use characteristics (Brooks, 2009). Streamflow

sensitivity to changes in precipitation and temperature are spatially variable,

dependent on landscape position and dominant hydrologic processes (Ashmore &

Church, 2001). Headwater streams are generally hydrologically connected to local

aquifers which are more sensitive to changes in precipitation patterns (Kløve, et al.,

2014). Baseflow generation in these headwater areas is therefore more sensitive to


changes in groundwater availability (Kløve, et al., 2014). Sites in areas with larger

contributing areas, however, have stronger hydrologic connectivity and restrict the

variability of water table position during dry conditions (Vidon & Hill, 2004).

Stemming from the reduced snow accumulation and earlier spring freshet, maximum

river flows during the late winter and early spring are likely to decrease (Boyer, et

al., 2010). This may result in a loss of riparian wetland area that no longer becomes

inundated during regular peak flows (Ashmore & Church, 2001). Such a change in

riparian wetland extent could have implications on the storage functions within a

watershed. The feedbacks between hydrologic function and climate change will be

spatially diverse, reflecting initial conditions, local geology, hydrology, and the local

changes in the climate system (Cohen & Waddell, 2009). In some parts of Canada,

particularly in areas of increasing urbanization, the effects of development and land

use change on hydrologic systems are expected to remain greater than the effects of

a changing climate regime (Ashmore & Church, 2001; Trenhaile, 2007). For the

remainder of the country, climate change will likely have a greater impact on

hydrologic systems than land use change (Trenhaile, 2007).

Collectively, changes in climate will modify the timing and spatial distribution for

collection functions (precipitation frequency, magnitude, and form – snow vs. rain)

and storage functions (through antecedent moisture conditions).

4. Jurisdictional Use of Hydrologic Function

The broadly used term ‘hydrologic function’ has a wide range of applications and

associated meanings (e.g., wetland function, drainage function, ecological function,

etc.). A search for the application and use of this term throughout other jurisdictions

within Canada, United States, England, and Australia was conducted to determine if

a framework existed which could be considered in the Ontario context. A generalized

email was sent to professionals in the academic, private, and government sectors in

May 2017 to determine if a comparable legislative definition or use of ‘hydrologic

function’ in their respective jurisdiction existed and if so, was supported by a

framework to determine the ‘protect, maintain, and restore’ component as outlined

in the PPS. The responses are summarized in Table 2 below. Additional agencies were

contacted, including the USGS, Lancaster University, and relevant governing bodies

in Alberta, Manitoba, Maryland, New Brunswick, Nova Scotia, Rhode Island, and

Virginia, but no replies were received.

In summary, the use of hydrologic function is not widely recognized in legislation and

is sometime interchangeably used with other comparable water based functions,

wetland functions, etc. No framework or indicators were documented in the replies

received.


Table 2: Summary of interjurisdictional use of hydrological function.

Agency Name Response

Alberta

Geological

Survey,

Alberta Energy

Regulator, AB

Tony Lemay

Senior

Hydrogeologist

Alberta issues Water Act approvals for

water body disturbance provided it does not

create an adverse effect. 'Wetland function'

and 'hydrological functions' of wetlands

(specifically groundwater recharge,

discharge, and storage functions) are used

in Wray and Bayley (2006), prepared for

Alberta Environment.

Battle River

Watershed

Alliance, AB

Susanna Bruneau,

Research and

Stewardship

Coordinator

‘Hydrologic function' used in Alberta

Wetland Policy (as groundwater recharge,

discharge, storage) but no definition

provided, nor any legislative definition.

Township of

Langley, BC

Asher Rizvi,

Hydrogeologist

‘Hydrologic function' is not used in the BC

Water Sustainability Act. It is a general

term that could refer to any activity that is

related or dependent on water. Terms like

drainage function, ecological functions, etc.

are often used interchangeably for

hydrologic function.

Okanagan

Basin Water

Board, BC

Nelson Jatel,

Water Stewardship

Director

Not familiar with 'hydrologic function' in

provincial or local legislative, regulatory, or

policy statement.

Department of

Indigenous

and Municipal

Relations, MB

David Neufeld,

Director

Community and

Regional Planning

Branch

‘Hydrologic function' is not used, but the

province is committed to encouraging

hydrologically sustainable land use and

development

Manitoba

Sustainable

Development

Laurie Frost,

Hydrogeologist,

Groundwater

Management

Section

Not aware of comparable 'hydrologic

function' definition within Manitoba's policy

framework nor legislation

Department of

Natural

Resources, NS

John Drage, Senior

Geologist/

Hydrogeologist

Not aware of 'hydrologic function' within NS

legislation

Lake Simcoe

Region

Conservation

Authority, ON

Bill Thompson,

Manager,

Integrated

Watershed

Management

‘Hydrologic function' not explicitly referred

to in Lake Simcoe Protection Plan, however

there are clear implications for hydrologic

function, encompassed in ecological

functions within this policy


Agency Name Response

Environmental

Sustainability

Research

Centre, Brock

University, ON

Julia Baird,

Research

Associate and

Adjunct Professor

Not familiar with 'hydrologic function'

Hydrology and

Groundwater

Services,

Water Security

Agency, SK

Nolan Shaheen,

Senior

Hydrogeology

Consultant

Not used in formal capacity; not referenced

in Water Security Agency Regulations

University of

Nebraska,

Lincoln, NE

Sarah Michaels,

Professor, Political

Science

Not familiar with 'hydrologic function' within

legislation

SRK

Consulting,

Western

Australia

Brian Luinstra,

Principal

Consultant

(Hydrogeology)

Individual states are quite different in how

they assess function, but generally, the rule

is that existing water uses are to be

protected, including requirements for any

natural systems, i.e. no impact is

acceptable

5. Proposed Hydrologic Function Framework

The objective of this proposed hydrologic function framework is to evaluate the

physical component of hydrologic function (i.e., the occurrence, distribution, and

circulation or movement of water within the landscape, both above and below ground

surface) in the context of the Provincial Policy Statement and associated provincial

plans to ensure that development and site alterations are to be restricted in and

around areas that contain sensitive hydrologic features (both above and below

ground) and, secondly, such that their hydrologic functions will be protected,

improved, or restored (Policy 2.2.2; OMMAH, 2014). (Consult the PPS and four

provincial plan for detailed information regarding development requirements within

each plan’s geography.)

The magnitude of a given disturbance’s impact on hydrologic function is primarily

dependent on the scale at which function is evaluated and its location within the

landscape, in addition to site properties such as geology and topography (Brinson,

1993; Wetland Science Advisory Group, 2005). It is proposed that the framework is

to be completed at two scales: local or site alteration/development level and

regional/subwatershed scale. It is envisioned that the regional hydrologic function

evaluation/ baseline characterization will provide an understanding of hydrologic

conditions at the subwatershed level. The proposed changes at the development and


site alteration/local scale will be evaluated against the regional baseline

characterization values through the application of a water balance approach.

Proposed mitigation/management recommendations will determine the associated

impacts of the proposed changes on the hydrologic functions.

5.1. Site Alteration/Major Development (Local) Hydrologic Function

Evaluation

The local or site evaluation consists of two components: 1) thematic land use

evaluation and 2) water budget calculations. Using the best available data, the study

area should be examined evaluated to determine the degree of hydrologic

connectivity at the local level. Key data layers for the evaluation include: significant

groundwater recharge area (and delineated ecologically significant groundwater

recharge areas where available), percent impervious area, hydrologic features, and

land use (including both natural – watercourses, wetlands, headwater features, seeps

and springs – and developed – agriculture, residential, commercial – land cover).

Maintaining water balance is critical to preventing adverse impacts on the natural

features and their ecological function (Sampson & Del Guidice, 2012). The type of

water budget analysis depends on the presence of sensitive hydrologic features and

key hydrologic areas. If the desktop evaluation indicates that there are sensitive

hydrologic features or key hydrologic areas within the proposed development area

and associated buffer, then a comprehensive feature-based water balance with direct

hydrologic measurements should be undertaken. (For the purpose of this report, a

120 m buffer was used to be consistent with the Growth Plan). Detailed

methodologies for feature-based water balances are provided by the TRCA (2012;

2016). If sensitive or key hydrologic features or areas are not present, then a

Thornthwaite-Mather water balance assessment is encouraged to be completed.

Guidelines for completing a general water balance exercise are provided by Cuddy,

et al. (2013). The objective of protecting, improving and restoring a feature’s specific

water balance is to ensure that the anticipated post-disturbance changes do not

exceed the feature’s capacity to respond and adapt, allowing for its long-term

sustainability, while minimizing the resources and interventions needed to manage

and maintain it (TRCA, 2012). To ensure the water balance conditions are

maintained, Low Impact Development (LID) and management options (e.g., maintain

hydroperiod and baseflow and/or, incorporate shallow groundwater and baseflow

protection techniques such as infiltration treatment, etc.) presented by CVC and TRCA

(2010) should be considered.

5.2. Subwatershed (Regional) Scale Hydrologic Function Evaluation

In order to bench mark and or evaluate hydrologic functionality in a defined spatial

unit, a regional/subwatershed scale baseline evaluation/characterization of physical


hydrologic functionality is recommended. This scale is recommended because

subwatershed-based analyses reflect the culminations of impacts for all activities

within landscape that affect watershed health (Morimoto, et al., 2003) and prevents

planning considerations from ending at municipal boundaries (OMMAH, 2014). This

large-scale evaluation supports various planning processes (e.g., subwatershed

plans, master servicing plans, water and wastewater plans, source protection plans,

etc.).

Similar to the local hydrologic function analysis, land use thematic analysis is to be

undertaken to determine areas of hydrologic importance. This will be combined with

a multivariate statistical evaluation and trend analysis of the temporal indicators

(climate, surface water, and groundwater datasets) to determine relationships,

interactions, and benchmark for hydrologic function at the large scale.

6. Proposed Subwatershed Baseline Characterization Indicators

The European Environment Agency (EEA) defines an indicator as a measure,

generally quantitative, that can be used to illustrate and communicate complex

environmental phenomena simply, including trends and progress over time and thus

helps provide insight into the state of the environment (EEA, 2005). Tracked over

time, an indicator can provide information on the condition of a phenomenon, allow

for comparison between systems, and have significance extending beyond that

associated with the properties of particular statistics (Dunn & Bakker 2009; Dunn &

Bakker, 2011; Koshida, et al., 2015).

The proposed indicators, more comprehensively outlined below, are subdivided into:

1) thematic indicators- corresponding to significant groundwater recharge areas

(SGRA), surface water features, forest cover, and percent impervious surface and 2)

time series indicators- climate, surface water, and groundwater. The thematic

indicators are aimed to provide an overall condition status of the defined spatial area

and are considered either presence/absence (e.g., SGRAs and the surface water

features) or can be ranked (e.g., percent impervious area and forest cover). It is

noted that the presence/absence indicators capture hydrologic input-output

relationships whereas the ranked indicators provide understanding of land use

dynamics. Linking back to the sensitive hydrologic features, the surface water

captures the following sensitive hydrologic features: shoreline areas, water courses

(permanent, intermittent, and ephemeral), inland lakes, kettle lakes, wetlands,

seepage areas, and springs (Greenbelt Plan; Growth Plan; ORMCP) whereas SGRAs

simply capture sensitive hydrologic features related to SGRAs and ecologically

significant groundwater recharge areas (ESGRAs).

Time series indicators are used to determine subwatershed hydrologic behaviour via

the use of the climate variables and surface water and groundwater indicators and


provide a benchmark to determine regionally whether hydrologic characterization is

changing or being maintained. The premise is that if the locally-scaled water balance

shows that post-disturbance recharge values are equal to pre-development

conditions, then the physical aspect of hydrologic function will be largely maintained.

If maintained locally, then the time series indicators for the normalized storage and

discharge outputs should remain unchanged for the regional characterization.

6.1. Thematic Land Uses

Thematic indicators are aimed at demonstrating connectivity of the system and could

include the delineation of significant groundwater recharge areas and ecologically

significant groundwater recharge areas, highly vulnerable aquifers, cold-water

fisheries habitats, wetlands, etc. This report focuses on 4 spatial indicators:

significant groundwater recharge areas, surface water features, percent impervious

surfaces, and forest cover which are to be evaluated for both the local site

alteration/disturbance scale and the regional/subwatershed scale. The SGRA

delineation and the surface water feature thematic layers provide regional

understanding of the groundwater recharge-discharge relationships whereas the

percent impervious area and forest cover provides data on existing land use

conditions which may adversely impact the hydrologic functionality of the defined

spatial unit.

6.1.1. Significant Groundwater Recharge Areas

Recharge areas are the areas of land over which precipitation infiltrates into the

ground and flows to an aquifer. Recharge areas tend to be characterized by

permeable soils, such as sand or gravel, which allow water to percolate downward

and replenish the groundwater system (Figure 2; Marchildon, et al., 2016). A

recharge area can be subdivided into Significant Groundwater Recharge Areas

(SGRAs) and Ecologically Significant Groundwater Recharge Areas (ESGRAs). Under

the Clean Water Act, 2006, Technical Rule 45 (South Georgian Bay-Lake Simcoe

Source Protection Committee, 2015) an area is a SGRA if:

(1) the area annually recharges water to the underlying aquifer at a rate that is

greater than the rate of recharge across the whole of the related groundwater

recharge area by a factor of 1.15 or more; or,

(2) the area annually recharges a volume of water to the underlying aquifer that is

55% or more of the volume determined by subtracting the annual evapotranspiration

for the whole of the related groundwater recharge area from the annual precipitation

for the whole of the related groundwater recharge area.


ESGRAs are defined as areas of land that are responsible for supporting hydraulic

pathways that sustain sensitive groundwater-dependent ecosystems such as cold

water streams and wetlands (through Policy 6.37-SA; Ontario Ministry of

Environment, 2009). SGRAs have been delineated in areas covered by the Source

Protection Planning processes whereas the delineation of ESGRAs within legislation

are limited to the Lake Simcoe watershed. Other jurisdictions including TRCA, CVC,

and Central Lake Ontario Conservation Authority also refer to ESGRAs.

Figure 2: The relationship between ecologically significant groundwater recharge

areas (ESGRA) and hydrologic features within the landscape (LSRCA, 2014).

6.1.2. Surface Water Features

Sensitive surface water features include watercourses (permanent, intermittent, and

ephemeral), inland lakes, kettle lakes, wetlands, seepage areas, and springs. The

objective in mapping these features is hydrologically examining recharge-discharge

relationships and the associated hydrologic connectivity. Further, the surface water

features will be the hydrologically impacted surficial features in which the various

planning documents focus on protecting, restoring, and maintaining. The data


sources for the identified surface water features consist of: source water protection

plans, the State of the Great Lakes Ecosystem Conference (SOLEC; e.g., EC & USEPA,

2009), Conservation Authority mapping and Land Information Ontario. There is no

ranking system associated with this indicator; however, the aim is to provide a spatial

understanding on where these features are present on the landscape using the best

available science and mapping layers.

6.1.3. Percent Impervious Area

Impervious area is an indicator of the impacts of urbanization, resulting in multiple

stressors to a watershed such as increased pollutant loads from stormwater runoff,

increased water temperatures, altered streamflow, increased runoff to receiving

streams, higher peak discharges, greater water export, and higher sediment loads,

especially during the construction phase (Arnold & Gibbons, 1996; Dunne & Leopold,

1978; McMahon & Cuffney, 2000; Nelson & Booth, 2002; Rose & Peters, 2001; Walsh,

et al., 2005; Environment and Climate Change Canada, 2013; USEPA, 2016).

Through the Technical Rules associated with the Clean Water Act, impervious surfaces

include all highways, and other impervious land surfaces used for vehicular traffic,

parking and all pedestrian paths (Ontario Ministry of Environment, 2015).

Environment Canada and the U.S. EPA (2009) include buildings and other areas that

artificially inhibit the infiltration of water.

Schueler (1994) was among the first to identify imperviousness as a simple, easily

measured quantity to be used as an index of environmental disturbance and identifies

threshold ranges of total imperviousness within a watershed associated with different

degrees of stream quality outlined in Table 3 (Moglen, 2009). Arnold and Gibbons

(1996) found similar thresholds of impervious cover to differentiate between

protected, impacted, and degraded stream health. The 2009 State of the Great Lakes

report, however, uses narrower category boundaries (Table 3). The Clean Water Act,

2006, uses a 1 km x 1 km grid centered over each vulnerability area to calculate the

percentage of impermeable surfaces; however, this is limited to the wellhead

protection area and intake protection areas associated to municipal drinking water

system. The ranges for percentage of impervious surfaces per square kilometre

provided in the Table of Drinking Water Threats (Clean Water Act, 2006) are > 80%,

8-80%, 1-8%, and < 1% (R.J. Burnside & Associates Limited, 2010).


Table 3: Examples of percent impervious land use thresholds on hydrologic function

(Arnold & Gibbons, 1996; Schueler, 1994; EC & USEPA, 2009).

Arnold and Gibbons

(1996)

Schueler (1994) State of the Great Lakes

Ecosystem Conference

Category Percent impervious



Protected < 10% Sensitive < 10% Good < 5%

Impacted 10-30% Impacted 11-25% Fair 5-10%

Degraded > 30% Non-

supporting

> 26% Poor > 10%

For this project, it is recommended that the hydrologic function indicator for

impervious surfaces use the State of the Great Lakes Ecosystem Conference ranking.

This ranking system was chosen for the lower threshold values, as the goal of this

framework is to protect, improve, and restore hydrologic function. Additionally, the

10% benchmark that is proposed to be the threshold for poor coincides with the

threshold listed for where systems become impacted according to both Arnold and

Gibbons (1996) and Schueler (1994).

6.1.4. Forest Cover

Although not a specific hydrologic function indicator, forests can be used as an

estimate the amount of unaltered land use, excluding rural/agricultural and urban

development land uses within a spatial unit (e.g., subwatershed). Forests are

valuable within the hydrologic cycle, as up to 25% (deciduous) or 40% (coniferous)

of annual precipitation can be intercepted in the canopy, preventing this water from

reaching the ground for infiltration or runoff generation (Oke, 1987). However, forest

soils promote groundwater recharge for the through fall and stem flow that reaches

the ground. Forest cover is the area percentage that is forested. Environment Canada

(2013) suggests that 30% forest cover is the minimum needed to support healthy

wildlife habitat; more coverage is beneficial. Conservation Ontario developed a

percent forest cover indicator as part of the Conservation Authority Watershed Report

Card initiative. The grading structure of two evaluations is outlined in Table 4.


Table 4: Comparison between forest cover indicator grading in Ontario watersheds

(Conservation Ontario, 2011; EC and USEPA, 2014).

State of the Great Lakes Ecosystem

Conference

Conservation Ontario

Category Percent cover Category Percent cover

Good > 60% A > 35.0%

Fair 30-60% B 25.1-35.0%

Poor < 30% C 15.1-25.0% D 5.0-15.0% F < 5.0%

For this project, it is recommended that the hydrologic function indicator for forest

cover condition use the Conservation Ontario ranking. This ranking was chosen

because the areas facing the largest development pressures (i.e., southern Ontario)

have already been largely disturbed. In addition, the 2011 State of the Great Lakes

Ecosystem Conference report (EC & USEPA, 2014), show that much of southern

Ontario has < 40% forest cover. As such, incorporating the EC and USEPA (2014)

standards in this evaluation framework would not readily highlight changes in forest

cover over time, particularly if there are further decreases in forest cover.

6.2. Time Series Hydrologic Variables and Indicators

The time series variables and indicators are temporal data sets, evaluated exclusively

at the regional/subwatershed scale; defined as follows:

1) Variables specifically climate-derived data which provide the background

conditions for hydrologic function.

2) Indicators correspond to surface water and groundwater-derived data that

respond to the climate variables and associated land use change.

For this analysis, all variables and indicators are evaluated using annual data. In

addition, a subset is evaluated using seasonal data. The specific variables and

indicators, collectively referred to as parameters, that are used for statistical analysis

are described below and are summarized in Table 6. Parameter codes are detailed in

0.


6.2.1. Climate Variables

The climatic and hydrological systems are interactively related and any changes

initiate bidirectional feedbacks (Mimikou & Baltas, 2013). The two principal climatic

variables of the hydrologic cycle are precipitation (P) and temperature (T). Principal

characteristics consist of event magnitude, frequency, and intensity which will be

seasonally variable (Christopherson & Bryne, 2006). Temperature data (i.e.,

maximum, minimum, and mean) influence the type of precipitation (i.e., rain vs.

snow) and evapotranspiration (ET) rates (World Meteorological Organization & Global

Water Partnership, 2016). The following variables were assessed using only annual

data: total precipitation (P), total potential evapotranspiration (PET), Climate

Moisture Index (P-PET), and average temperature (T). Annual and seasonal

extremes of temperature and hydrologic release were further analysed for multi-day

maxima and minima.

6.2.1.1. Temperature

Temperature impacts all processes of the hydrologic cycle. It determines whether

precipitation is liquid or frozen as well as whether evaporation, transpiration, and

infiltration can occur.

Multi-day rolling averaged conditions are used to assess temperature while reducing

the potential impact of outliers in 1-day extreme maximum and minimum conditions.

It is calculated by averaging daily mean temperature of seven consecutive days,

recorded on the seventh day for day of year timing. The annual and seasonal

maximum and minimum values of this 7-day averaged data and the day of year

timing were determined for analysis. When a multi-day annual or seasonal maximum

or minimum value occurs more than once, the day of year timing of the earliest

occurrence of the extreme value is reported.

6.2.1.2. Potential evapotranspiration

The hydrologic cycle has three main pathways for water to leave a system: surface

water flow, groundwater infiltration and flow, and evapotranspiration. Potential

evapotranspiration (PET) is the amount of evapotranspiration that would occur if it

were not limited by water availability. Monthly potential evapotranspiration was

estimated using empirical Thornthwaite (1948) methods (formula provided below).

While these methods may underestimate evapotranspiration rates, this method may

provide the most accurate estimate with the least required instrumentation (Mitsch

& Gosselink, 2007).


𝐸𝑇𝑖 = 16(10𝑇𝑖/𝐼)𝑎

Where 𝐸𝑇𝑖 = potential evapotranspiration for month 𝑖 (mm/month)

𝑇𝑖 = mean monthly temperature (°C)

𝐼 = local heat index ∑ (𝑇𝑖/5)1.51412𝑖=1

𝑎 = (0.675 ∗ 𝐼3 − 77.1 ∗ 𝐼2 + 17920 ∗ 𝐼 + 492390)10−6

The monthly potential evapotranspiration values were summed to obtain annual

potential evapotranspiration. The local heat index values were calculated using day

length from 2017 (Time and Date, 2018). Subwatershed day lengths were estimated

from communities that were situated centrally along the north-south alignment of

the subwatershed in order to calculate the local heat index used to calculate PET.

6.2.1.3. Climate moisture index

A climate moisture index, as outlined by Hogg (1997) was calculated as total

precipitation minus total potential evapotranspiration, where a positive value is

indicative of a water surplus and a negative value is indicative of a water deficit and

to provide an overview of “climate inputs” and whether climate is adding or removing

water from the system. This provides a summary of background climate data to

determine the origin of potential changes to hydrologic function (e.g., if the GW/SW

response is changing, but P-PET is constant, then it can be determined the change in

hydrology is man-made.) This was calculated using only annual data for this study.

6.2.1.4. Precipitation and hydrologic release

Precipitation records are important to highlight the timing, magnitude, and intensity

of hydrologic input events, however, when the precipitation occurs as snow, the water

is stored on the landscape delaying mobilization until snowmelt. The volume of water

released during the spring snowmelt freshet can be important in local hydrology, and

often results in the highest water levels of the year (Fetter, 2001). Hydrologic release

is the amount of water that is released to the system and is equal to the combined

volume of daily rainfall and snowmelt. Comparing surface water and groundwater

response to hydrologic release provides a better understanding of hydrologic function

than using total precipitation.

Total precipitation was used for annual statistical analysis but is replaced by

hydrologic release for seasonal analyses and multi-day extreme conditions. Multi-day

hydrologic release is calculated as the sum of the previous 3 days’ (maximum) and

30 days’ (minimum) total hydrologic release. This was recorded on the 3rd and 30th

day for day of year timing of 3-day maximum and 30-day minimum hydrologic


release. The length of these multi-day totals were chosen to reflect the shorter

duration input events and the longer duration of drought events.

Rainfall and snowfall separation, snowpack storage, and melt output are calculated

for the subwatershed based on the methods of Brown and Braaten (1998) using

subwatershed-averaged daily temperature and precipitation data. Daily rainfall (mm)

is equal to total daily precipitation when mean temperature is greater than 0 °C and

daily snowfall (mm snow water equivalent) is equal to total daily precipitation when

mean temperature is less than or equal to 0 °C. Daily snowpack accumulation (mm

snow water equivalent) is equal to the previous day’s snowpack, plus snow

accumulation minus daily snowmelt water. Daily snowmelt is calculated as:

𝑀 = 𝑘[(1.88 + 0.007𝑅)(9 5𝑇⁄ ) + 1.27]

Where 𝑀 = snowmelt water (mm/day)

𝑘 = locally-calibrated snowmelt factor (previously determined by Dr. Andrew

Piggott to be equal to 1 for southern Ontario)

𝑇 = mean daily air temperature (°C)

𝑅 = total daily snowfall (mm snow water equivalent)

Finally, daily total release (mm) is equal to the sum of daily rainfall and daily

snowmelt water.

6.2.2. Hydrologic Indicators

6.2.2.1 Surface Water Indicators

Surface water flow response is primarily a function of the amount of precipitation,

infiltration characteristics of the soil, antecedent moisture conditions, land cover type,

and surface retention (USEPA, 2016). To date, over 170 hydrologic metrics have been

published to summarize various aspects of the flow regime (Gao, et al., 2009; Olden

& Poff, 2003). These metrics characterize the intra- and inter-annual variations of

timing, duration, magnitude, frequency, and rate of change of flow (Matthews &

Richter, 2007). Generalized surface water indicators consist of maximum, minimum,

and mean discharge and water levels at varying scales (i.e., daily, monthly, and

annual) to determine low flow and high flow conditions in addition to system

flashiness and frequency and duration of low flow events, and seasonal timing

(Environment and Climate Change Canada, 2016; Pyrce, 2004).

Climatic inputs and the physical properties (e.g., geology, topography, land use, etc.)

of a watershed determine surface water discharge patterns that can be characterized


through, multi-day streamflow extremes and timing, baseflow, flashiness, and

extreme flows as outlined in Figure 3.

Each indicator represents a specific aspect/component of the hydrologic function of

the measured surface water system and therefore are considered to be equally

important and not defined hierarchically. Changes in the performance of one indicator

will likely result in a cascading effect with respect to the other indictors.

Figure 3: Skootamatta River 2015 hydrograph with the surface water indicators

consisting of streamflow, hydrologic release (rainfall + snowmelt), baseflow, and

extreme flows.

a. Streamflow

Annual and seasonal streamflow indicators consist of 1) maximum of 3-day average

daily discharge, 2) minimum of 7-day average daily discharge, and 3) the

corresponding day of year (DOY) timing of the multi-day maxima and minima. Multi-

day average values were used to reduce the potential outlier impact that 1-day

extreme maximum and minimum flow data could have. The rationale/purpose of

these indicators using three and seven-day moving averages is to reflect the shorter

duration of response to precipitation events (maximum of 3-day average daily

discharge) and the longer duration of drought events (minimum of 7-day average

daily discharge). The day of year timing of the multi-day annual and seasonal

maximum and minimum streamflow is used to show if there is a shift in trend (e.g.,

annual maximum flows shifting from snowmelt freshet to rain storm event). It is

noted that analyzing both annual and seasonal periods enables differentiation

between precipitation-driven and snowmelt-driven conditions. Seasonal analysis

consists of interannual comparison of each season.

0

10

20

30

40

50

60

70

0

5

10

15

20

25

30

35

0 50 100 150 200 250 300 350

Hyd

rolo

gic

rele

ase

(mm

)

Dai

ly d

isch

arge

(m

3/s

)

DOY

hydrologic release Streamflow Baseflow

Extreme low flow threshold Extreme high flow threshold


It is noted that streamflow and baseflow were converted to depth of water over the

entire subwatershed/study area that would be required to produce the streamflow

and baseflow volumes via a discharge conversion, also referred to as water yield

(OMNRF, 2014). These values are differentiated as water yield and baseflow yield in

this report. This was done to enable the double-mass balance analysis relating flow

(yield) in mm to precipitation, also in mm, by plotting the interannual cumulative

values for each variable (Searcy & Hardison, 1960). This conversion is determined

by dividing streamflow by the catchment area and multiplying a unit conversion

factor. For this study, daily streamflow and baseflow was converted using following

calculation and summed and assessed seasonally and annually:

𝑦𝑖𝑒𝑙𝑑 =𝑄 ∗ 86.4

𝐴

Where 𝑦𝑖𝑒𝑙𝑑 = streamflow or baseflow in mm/day,

𝑄 = daily average streamflow/baseflow discharge in m3/s,

𝐴 = (sub)watershed contributing area in m2

86.4 = conversion factor between m/s to mm/day.

The spatial extent of the subwatershed contributing area used for these calculations

was obtained from the metadata of the hydrometric stations.

b. Richards-Baker Flashiness Index

Flashiness is the day-to-day variability in streamflow; particularly the magnitude,

frequency, and rapidity of response to hydrologic input (precipitation or release)

event (Baker, et al., 2004). Watersheds that have greater flashiness respond faster

and often with greater magnitude than less flashy watersheds for an equal input

event. Factors influencing flashiness includes catchment surface area, soil depth and

type, topography, and percent impervious surfaces.

The Richards-Baker Flashiness Index has been used to characterize subwatershed

flashiness. It is a dimensionless value that relates the sum of absolute values of daily

change in daily discharge, generally for an annual period, divided by the sum of the

daily discharge over the same period:

𝑅 − 𝐵 𝐼𝑛𝑑𝑒𝑥 =∑ |𝑞𝑖 − 𝑞𝑖−1|𝑛

𝑖=1

∑ 𝑞𝑖𝑛𝑖=1

Where: 𝑞 = daily discharge


The values of 𝑞 may be presented as daily discharge volume (m3) or average daily

flow rate (m3/s). The unit of input will not change the output index value (Baker, et

al., 2004). The State of the Great Lakes 2011 report includes tributary flashiness as

an indicator, using the Richards-Baker Flashiness Index, indicating good conditions if

flashiness is decreasing, fair conditions when there is no trend, and poor conditions

if there is an increasing trend (EC & U.S. EPA, 2014), as lower values signify storage

and buffering capacity within the watershed. It should be noted however that this

index does not consider potential change in hydrologic release event magnitude,

frequency, nor intensity, which impact event response flashiness.

c. Extreme flows

Extreme high flow (e.g., flood events) and extreme low flow (e.g., sustained drought

events) indicators correspond to the 10th and 90th exceedance percentile of the flow

duration curve, where annual streamflow exceeds the high and low flow thresholds

10% and 90% of the time, respectively, as indicated by the OMNRF (2014). Where

this ratio of high flow to low flow is smallest, there is less variability between annual

maximum and minimum streamflow, indicating there is long-term storage capacity

to buffer storm events and baseflow generation supplements streamflow during dry

periods.

6.2.2.2. Groundwater indicators

Groundwater indicators for hydrologic function are limited to baseflow and

groundwater table position. The term baseflow is often referred to as the groundwater

contribution to streamflow (e.g., Freeze, 1972; Brutsaert and Nieber, 1977;

Eckhardt, 2005), although it is also referred to as the release from both groundwater

and other natural storages of water that sustain streamflow between rainfall events

(Partington, et al., 2012; Hall, 1968; Smakhtin, 2001; Piggott, et al., 2005b).

Background groundwater level data can be informative on conditions within specific

aquifers. Groundwater discharge continuously contributes to baseflow of streams and

rivers, sustaining flow through dry periods.

a. Baseflow separation

Baseflow is the portion of streamflow that is sustained by groundwater discharge. It

can indicate changes to the hydrologic cycle when the relative proportions of baseflow

to streamflow change (e.g., decrease in groundwater recharge and increase in

surface runoff from increased impermeable surface area). Daily baseflow is derived

from daily streamflow data using the modified UKIH method of Piggott, et al. (2005b)

to remove event response from streamflow, illustrated in Figure 3. For the UKIH

method, streamflow data is recorded as (𝑥, 𝑦) pairs where 𝑥𝑖 is the date of minimum

flow 𝑦𝑖 within five-day segments (Piggott, et al., 2005b). These values are then


compared to those of previous and subsequent segments, and turning points, days

where streamflow is assumed to be entirely baseflow, are defined as:

0.9𝑦𝑖 < 𝑚𝑖𝑛(𝑦𝑖−1, 𝑦𝑖+1)

Baseflow is then estimated to be the linear interpolation between successive turning

points. The UKIH method depends on the timing origin of the five-day segments. To

reduce the uncertainty of the five-day segment timing, Piggott, et al. (2005b)

average the calculated baseflow values of zero to four-day segment displacement.

Piggott, et al. (2005b) also disallow baseflow to exceed recorded streamflow values;

when calculated baseflow exceeds actual streamflow, the actual streamflow value is

used for baseflow. For more details on this method, see Piggott, et al. (2005b).

This method of baseflow separation requires streamflow data beyond the study period

end date. Provisional streamflow data for January 2017 was included for baseflow

separations of late December 2016. Specific dates where this provisional data was

needed for each subwatershed are outlined in Table 5.

Multi-day extremes of seasonal and annual baseflow were analyzed using maximum

of 3-day and minimum of 7-day average flow values, mirroring the methods of

streamflow analysis. Since baseflow is groundwater-derived, there should be

relatively little inter-annual variation. The TRCA (2009) suggests that a threshold of

> 10% change should trigger further investigation into the cause.

Table 5: Dates where calculated baseflow is based on provisional January 2017

streamflow data

Subwatershed Dates with provisional baseflow data

Skootamatta River December 21 – 31, 2016

Innisfil Creek December 17 – 31, 2016

Whitemans Creek December 19 – 31, 2016

Parkhill Creek December 19 – 31, 2016

b. Groundwater levels

The Provincial Groundwater Monitoring Network (PGMN) was established in 2001,

monitoring baseline groundwater level information. Hourly reported groundwater

level data from PGMN wells was obtained from the MOECC as approved for use with

barometric pressure compensation applied and outliers removed. This data was then

averaged to determine daily mean water levels for further statistical analysis.

Similar to surface water discharge, multi-day annual and seasonal maximum

groundwater level and day of year timing was calculated using 3-day averaged

groundwater level, and annual and seasonal minimum groundwater level and timing


were determined using 7-day averaged groundwater level. Where data gaps exist

(i.e., more than several days of data are missing), relevant annual and seasonal data

were removed from analyses.

Table 6: Summary of parameters and indicators for statistical analysis. Day of year

(DOY) timing is also analyzed for all multi-day metrics.

Type Variable /Indicator Metric Time period

Climate Precipitation Total Annual

Potential

Evapotranspiration Total Annual

Climate Moisture

Index P-PET Annual

Temperature Average Annual

7-day max Annual, seasonal

7-day min Annual, seasonal

Hydrologic release 3-day max Annual, seasonal


Total Seasonal

Surface

water

Surface water

discharge 3-day max Annual, seasonal


Water yield Total Annual, seasonal

Baseflow yield Total Annual, seasonal

Flashiness

Richards-Baker

Flashiness Index Annual

Extreme flows

<10th: >90th

exceedance percentile Annual

Groundwater Groundwater level 3-day max Annual, seasonal


6.3. Subwatershed Hydrologic Function Characterization

—Pilot Subwatersheds

Four southern Ontario subwatersheds have been targeted for subwatershed

hydrologic function characterization: Skootamatta River, Innisfil Creek, Whiteman’s

Creek, and Parkhill Creek. See Figure 4 for an overview of the pilot subwatersheds

and the location of their climate, surface water, and groundwater stations.


Figure 4: Map of study subwatersheds, target climate stations, surface water gauges and groundwater wells


6.3.1. Skootamatta River

The subwatershed of the Skootamatta River, a tributary of the Moira River, is

approximately 692 km2, located north of Belleville within Lennox & Addington, and

Hastings counties. There is little development within the subwatershed which is

dominated by secondary growth forest (Skootamatta District Ratepayers Association,

2014), with only small communities of Actinolite and Flinton. There is also little

agricultural activity within this subwatershed dominated by Precambrian bedrock. The

Water Survey of Canada hydrometric station at the Skootamatta River (02HL004) is

included in the Reference Hydrometric Basin Network (RHBN), indicating that there

are stable or pristine hydrological conditions with more than 20 years of data record

(Zhang, et al., 2001) for this subwatershed. In addition, the MOECC has installed the

Skootamatta River Integrated Water and Climate Monitoring Station.

6.3.2. Innisfil Creek

The Innisfil Creek subwatershed is approximately 490 km2 in size and consists of five

main tributaries: Bailey, Beeton, Cookstown, Innisfil, and Penville. Situated partially

within the municipalities of Innisfil, Essa, Bradford West Gwillimbury, New

Tecumseth, Adjala-Tosorontio, and Mono; this area has experienced historical water

abstraction shortages due to meteorological and agricultural related droughts with

related negative socio-economic impacts. Main communities include: Beeton,

Churchill, Cookstown, and Tottenham. It is characterized as largely rural and

dominated by agricultural land use. Collectively, the proportion of land use in the

subwatershed is approximately distributed as 75% Agriculture, 14% Forests, 7%

Wetlands, 3% Built-up Urban, and 1% Extraction. The top four irrigated crops grown

in the Innisfil Creek subwatershed are potato, turf, onion, and cabbage. Wheat-corn-

soybean rotations also predominate in this subwatershed however are not irrigated.

The Innisfil Creek is largely a runoff-dominated system. Water entering the system,

does so via predominantly by precipitation, and monitoring records from stations

around the subwatershed shows annual precipitation ranges from 789 to

912 mm/year. Evapotranspiration was found to be 550 to 600 mm/year and would

consume approximately two thirds of the annual precipitation. The remainder of the

water balance is attributable to surface runoff or groundwater storage.

The surficial overburden is quite deep throughout the area (exceeding 200 m in some

locations), with the central portions of Innisfil Creek being characterized largely by

surficial sands underlain by glaciolacustrine deposits. Although there are limited

groundwater resources associated with these surficial sands, the underlying deposits

result in a regionally extensive and complex aquifer system.


Lastly, the recently completed Innisfil Creek Drought Management Plan aims to

proactively determine the best way to manage limited water supplies during periods

of drought. Pertinent to this project, components of this drought management plan

consist of:

development of an integrated groundwater-surface water MikeSHE numerical 3D water budget model on a subwatershed scale with a drought scenario built

within the model;

assessment of climate change impacts and options to the drought scenarios; and

assessment of environmental flow requirements of Innisfil Creek and its

associated tributaries.

6.3.3. Whitemans Creek

The Whitemans Creek subwatershed is approximately 404 km2. Located in the Grand

River watershed, it is primarily rural, dominated by agricultural land use and also

perennial low water issues. Groundwater is abstracted for the Bright and Paris

(Bethel) municipal systems. The two main tributaries of Whitemans Creek consists of

Horner and Kenny Creeks. The physiography of the subwatershed is dominated by a

till and sand plain interspersed with till moraine, and smaller segments of kame

moraine and wetland areas (Maas, 2011). Till plain dominates the headwaters of both

tributaries; the soils, comprising generally fine, silty clay loam soils, are described as

well to imperfectly drained (Province of Ontario - Conservation Authorities Branch,

1962; Province of Ontario - Conservation Authorities Branch, 1966; GRCA, 2005, as

cited in Maas, 2011). The south-central portion of the subwatershed is largely part

of the formation known as the Norfolk Sand Plain. This area is comprised of well-

drained, highly permeable soils with a shallow sand aquifer (GRCA, 2014).

Flows in lower Whitemans Creek depend highly on groundwater discharged from the

high water table of the Norfolk Sand Plain. Low water conditions are an annual issue

within this subwatershed, with 90% of years (1961-2012) reaching low water

thresholds (GRCA, 2014). There is a high concentration of permits to take water

(PTTW) within the well-drained sandy soils of the Whitemans Creek subwatershed;

most are for agricultural use (GRCA, 2014). Since the aquifer has a high degree of

connectivity with surface water, demand for groundwater extraction negatively

impacts the creek flow (GRCA, 2014).

The GRCA is presently undertaking the Whitemans Creek Tier 3 Water Budget Study.

This detailed scientific technical study is aimed at assessing the water quantity risk

to current and future municipal drinking water sources under a variety of scenarios,

such as future increased municipal water needs due to growth and a sustained


drought. The Whitemans Tier 3 study will utilize an integrated groundwater-surface

water numerical model to simulate groundwater and surface water flow to evaluate

how water levels will change within the municipal wells under the various scenarios

including climate change.

6.3.4. Parkhill Creek

Situated within the Ausable Bayfield Conservation Authority (ABCA), the 127 km2

Upper Parkhill Creek (referred to as the Parkhill Creek throughout this report)

subwatershed is partially located in the municipalities of Bluewater, North Middlesex,

and South Huron. Abstracted groundwater services the communities of Brucefield,

Clinton, Seaforth, Zurich, and Varna, all situated north of the subwatershed. Similar

to the Innisfil Creek subwatershed, the Upper Parkhill Creek is characterized as rural

agriculture as supported by the land use breakdown: 82% agriculture; 13% woodlot;

2% urban; 3% other (ABCA, 2007). Key natural areas in the include: the Dashwood

Area Earth Science (Area of Natural and Scientific Interest); Parkhill Creek Complex

(Provincially Significant Wetland); McGillivray Environmentally Significant Areas 5, 7,

8 and 11; Stanley Environmentally Significant Areas 4 and 5 (ABCA, 2014).

The surficial geology of this typically flat to slightly undulating area is dominated by

till moraine features with corresponding silty clay loan and clay loam soil profiles.

Bedrock is overlain by 10 m to > 70 m of overburden (Singer, et al., 2003). Bedrock

aquifers are the only significant source of groundwater in this subwatershed. A thick

sequence of mostly fine-grained glacial sediment separates Parkhill Creek from the

bedrock aquifer in this area (ABCA, 2007).

The MOECC established Parkhill Creek Integrated Water and Climate Monitoring

Station. Figure 5 outlines the cross section profile of monitoring station

instrumentation for the Parkhill Creek station.


Figure 5: Cross section profile of the Parkhill Creek Integrated Water and Climate Monitoring Station outlining the

various monitoring components.


7. Subwatershed Hydrologic Function Characterization Methodology

7.1. Thematic Mapping Methodology

Thematic mapping of the targeted subwatersheds includes hydrologic and land use

characteristics consist of SGRAs and surface water features (including streams, lakes,

ponds, wetlands, discharge areas, etc.) in addition percent impervious area and

forest cover representing the disturbance and land use change that has occurred

within each of the subwatersheds.

Table 7: Summary of hydrologic function variables and indicators.

Variable/Indicator Data source

Land use

indicators

(regional and

local scale)

Significant groundwater recharge

areas (SGRA) Source water protection plans

Impervious areas LIO

Forest cover condition LIO, CA mapping

Surface water features LIO, CA mapping

Many of the mapping layers that were used were sourced from Land Information

Ontario (LIO; 2018), as displayed in Table 7, in order for consistent application of the

same data source to each study area. These include for Ontario Hydro Network (OHN)

Waterbody, Wetland, Wooded Area, Built-up Area, and Ontario Road Network Road

Net Element. Additional layers, including subwatershed boundaries, SGRAs, and

greater details of surface water features were obtained from each relevant

conservation authority. Much of the Skootamatta River subwatershed is located

within ecoregion 5E and was therefore excluded from the built up areas mapping

layer which was restricted to southern Ontario coverage. Neither the Quinte

Conservation Authority nor the local municipalities were able to provide a substitute

layer. In contrast, there were additional layers available from the Grand River

Conservation Authority for Whiteman’s Creek, such as discharge areas (GRCA, 2018).

Any available and relevant layers were included in the analysis.

To perform mapping analysis, all available data sets for surface water features were

joined to create one layer, using union and dissolve functions in ArcMap (version

10.3.1). For the purposes of this analysis, there is no differentiation between the

types of surface water features (e.g., streams, lakes, wetlands, discharge areas). A

120 m buffer was then applied to this layer and clipped to the subwatershed

boundary. Much of the stream network within each of these subwatersheds were

linear features rather than spatial polygons, meaning that their spatial extent cannot

be accurately estimated. As a result, only the spatial extent of the 120 m buffer was

used in the analysis, with the acknowledgement that it will underestimate the area

of the subwatershed that is within the buffer area, but would provide a better


estimate than omitting the linear features of the stream network. These methods

were replicated and applied to SGRAs and their 120 m buffers. To determine the

extent of land that is within 120 m of any key hydrologic feature, the surface water

features buffer and SGRA buffer were joined using the union and dissolve functions.

There were no ESGRA mapping layers available for these subwatersheds at this time.

Forest cover and road network analysis involved simply clipping the available

datasets to the subwatershed boundaries. For spatial interpretation of road

segments, Toronto recommends that lanes be no more than 4.3 m wide, with most

being 3.5 m (City of Toronto, 2017). With the understanding that much of the area

being evaluated is rural, and mostly limited to 2 lanes wide, but with some wider

areas, this report estimates that a roadway would be approximately 10 m wide. This

also simplifies the road segment length to spatial area conversion as a 1 km length

with 10 m width would cover 1 ha. Divided highways that cross through the

subwatersheds (e.g., Highway 400 – Innisfil Creek and Highways 401 and 403 –

Whitemans Creek) are represented as separate road segments and are therefore

represented herein as 1 ha/km for each direction.

7.2. Statistical Analysis Methodology

In order to maintain hydrologic function, it is envisioned that post-development

recharge rates are to equal pre-development recharge rates, completed through a

water budget exercise via Thornthwaite-Mather methods that may incorporate a

feature based water budget at the local level. The subwatershed baseline hydrologic

function characterization is to evaluate the long term performance of the local scale

water balance exercises. This determines regionally if the hydrologic function is being

‘maintained and/or restored’. Since, if local scale land use changes maintain natural

hydrology at all sites, then the hydrology of the watershed/subwatershed as a whole

should also be maintained. Therefore, baseline conditions of hydrology and climate

must be assessed to determine whether background conditions have been changing,

and whether these changes might be of atmospheric or land use change origin.

Indirect impacts of human activity on hydrologic function are beyond the scope of

this report. Hydrologic function indicators are used to determine temporally the

overall performance, e.g., if being maintained or restored. Hydrologic function

indicators are limited to the regional scale, e.g., subwatershed basis and restricted

to surface water and groundwater. Specific sources of each data type are outlined in

Table 8. A full listing of parameters evaluated and their coding are presented in 0.

Table 8: Data resources

Parameter Source Period Web link

Temperature and

precipitation

Ontario Infilled Climate Database;

MNR

1950-2005 http://waterbudget.ca/climateinfill

http://waterbudget.ca/climateinfill



Parameter Source Period Web link

Temperature and precipitation

Historical climate data (online); ECCC

station start to end or present

http://climate.weather.gc.ca/historical_data/search_historic_data_e.html

Surface water discharge

Historical hydrometric data

(online); Water Survey of Canada

station start to end or

present

https://wateroffice.ec.gc.ca/search/historical_e.html

Groundwater level

Provincial Groundwater

Monitoring Network; MOECC

station start to end or

present

Data received from MOECC staff

The objectives of the statistical analysis are to:

1) Assess whether there are observable temporal trends in hydrologic data

through the study period (1981-2016), and

2) Evaluate the relationship between hydrologic components of climate, surface

water discharge, and groundwater levels using readily available datasets.

Data analysis was conducted on both annual mean or total data as well as interannual

comparison of seasonal data, where at least 10 observations (i.e., 10

annual/seasonal total/mean data values) of each parameter were available. For

correlation analyses, there must be at least 10 years of observations where both

parameters overlap in data availability. Seasonal divisions are based on astronomical

seasons and data was broken into: January-March (JFM) – snow and melt; April-June

(AMJ) – spring and generally wet antecedent conditions; July-September (JAS) – dry

summer period; and October-December (OND) – autumn wet up and limited winter-

like conditions. These divisions were chosen due to the great inter-seasonal variability

in Ontario and to facilitate annual data comparisons between parameters. Other

studies have used water years (October-September); however, this presents

complications in data comparisons when some types of annual data are more

commonly based on the calendar year. Data series (temperature, precipitation,

streamflow, baseflow, and associated annual multi-day maximum and minimum

data, etc.) were analyzed using R software (R Core Team, 2007).

A flow chart outlining statistical analyses is presented in Figure 6. Analysis methods

have been inspired by Gao et al. (2010), but have had some modifications as the

present study aims to evaluate whether there have been temporal trends in any of

the parameters evaluated, and which parameters may be correlated to one another.

This differs from Gao et al. (2010) which compared hydrologic time series data







(groundwater levels, spring and stream discharge, and precipitation data) to historic

groundwater withdrawal records.

Annual and seasonal data were evaluated for time-series trends using the Mann-

Kendall trend test (McLeod, 2011) and correlation through the Kendall’s rank (tau, 𝜏;

Revelle, 2017), Spearman’s rank (rho, 𝜌; Revelle, 2017) and linear regression, using

least squares (𝑅2). Following Gao, et al. (2010), the results of the Mann-Kendall trend

test show “probably trending” (PT) when the two-sided p-value is < 0.05, and

confidence increases to “very certain” (VC) when the two-sided p-value is < 0.025.

Correlation between tested variables can be positive (corresponding increases in both

parameters) or negative (increasing values for one parameter correspond to a

decrease in the other). In order for there to be a strong correlation between the

parameters tested, the correlation coefficient for Kendall’s Rank, Spearman's Rank,

and linear regression must be > 0.5 and the corresponding p-values must be < 0.05

for all tests. Probable correlation is determined by at least one of the correlation

coefficients and associated p-value meeting these requirements. When all of these

correlation coefficients are < 0.5, no correlation is detected. Linear regression

analyses was only conducted when both Kendall’s Rank and Spearman’s rank both

met the threshold to indicate probable correlation. The adjusted 𝑅2 output was used

for this analysis. All parameters (climate variables and hydrologic indicators) were

tested for correlation within each time period (i.e., annual and seasonal). Inter-

seasonal and annual-seasonal correlations were not tested.


Figure 6: Flow chart illustrating statistical analysis methods


Two double mass balance graphing analyses were also used to illustrate the

relationship of 1) streamflow as a function of precipitation and 2) baseflow as a

function of streamflow in each of the pilot subwatersheds. Ideally, there will be a

linear relationship for each of these pairings that remains constant through time, but

where the slope of the relationship changes, there have been changes within the

watershed (e.g., increased surface storage as a result of dam and reservoir

construction). In order to facilitate comparison between streamflow/baseflow and

precipitation/hydrologic release, daily streamflow and baseflow data were converted

to water yield and baseflow yield. These were then plotted as cumulative values along

both axes on both the annual and seasonal scales (replacing precipitation with

hydrologic release for seasonal analyses).

The slope of the linear trend line between cumulative water yield and cumulative

precipitation/hydrologic release can be interpreted as the percent of precipitation

(hydrologic release, seasonally) that becomes streamflow discharge. Based on

previous studies in southern Ontario, it is expected that the slope of this trend line

should be near 0.4 (indicating that streamflow yield is approximately 40% of annual

precipitation; A. Piggott, personal communication). Similarly, the slope of the linear

trend line between baseflow and streamflow data can estimate the baseflow index. A

lesser value could be indicative of net loss of groundwater from the surface water

watershed boundaries or higher groundwater withdrawal rates.

7.3. Data Processing and Infilling Methodology

Raw data was collected from provincial and federal climate, surface water, and

groundwater monitoring stations. A complete time series of daily climate data is

required to determine total annual precipitation, average annual temperature, and

from these, be able to estimate annual evapotranspiration. Many climate datasets

have data gaps in their record, or the length of record may not cover the full time

series. To enable climate data analysis, the Ontario Ministry of Natural Resources

initiated a project where temporal climate data from Environment Canada’s

Atmospheric Environment Service was infilled to create continuous datasets at 339

stations for the 1950 – 2005 period (Ontario Ministry of Natural Resources, 2011;

Schroeter & Associates and AquaResource Inc., 2008). When possible, this infilled

dataset was used in this study. For climate data that were not included in the Infilled

Climate Database (i.e. all data at Egbert Care/Egbert CS stations and data for all

stations for 2006 to 2016) data gaps were filled following the methods of Schroeter

& Associates and AquaResource Inc. (2008), as described below, using historic data

from federal climate stations with published 1981-2010 climate normal data

(Environment and Climate Change Canada, 2018a; 2018b). These climate stations

have averages calculated based on at least 15 years of recorded data and should

have fewer data gaps in their historic record than other stations.


The "target" station is the climate station that is used to estimate climate parameters

in the study subwatershed. Ideally located centrally within the subwatershed, the

target stations were selected for this study based on professional judgment of several

criteria: the proximity of the climate station to the subwatershed, the availability of

infilled climate data (1981-2005), and the availability and completeness climate data

between 2006 and 2016. When more than one climate station is used to estimate

subwatershed climate, the subwatershed would ideally be situated between the

target stations. Due to the spatial distribution of climate stations with long-term

datasets, none of the target stations are located within the targeted subwatersheds.

Where data gaps were observed in the 2006 to 2016 climate data set (and for the

full time series of Egbert Care data), the target station’s record was infilled using

data from "filling" stations. The selected filling station is defined as the nearest

climate station to the target station with published 1981-2010 climate normal data

in combination with either both daily maximum and minimum temperature or total

precipitation for the date of the data gap. This is repeated each day for which data is

missing. Climate parameters are spatially variable; requiring that a filling station

have both precipitation and temperature data for a given day could increase the

distance to the target station, which would increase error in the infilled data. Target

and filling stations for each pilot subwatershed are outlined in Table 9. Special

circumstances surrounding climate filling in this study are outlined in Table 10.

Climate adjustment values are determined using the following calculations based on

1981-2010 climate normal data between each filling station and target station:

𝑇 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡 (°𝐶) = 𝑇𝑎𝑟𝑔𝑒𝑡 𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑚𝑒𝑎𝑛 𝑎𝑛𝑛𝑢𝑎𝑙 𝑇 (°𝐶) − 𝐹𝑖𝑙𝑙𝑖𝑛𝑔 𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑚𝑒𝑎𝑛 𝑎𝑛𝑛𝑢𝑎𝑙 𝑇 (°𝐶)

𝑃 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡 =𝑇𝑎𝑟𝑔𝑒𝑡 𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑡𝑜𝑡𝑎𝑙 𝑎𝑛𝑛𝑢𝑎𝑙 𝑃 (𝑚𝑚)

𝐹𝑖𝑙𝑙𝑖𝑛𝑔 𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑡𝑜𝑡𝑎𝑙 𝑎𝑛𝑛𝑢𝑎𝑙 𝑃 (𝑚𝑚)

The temperature adjustment is recorded in degrees Celsius and is positive/negative

when the target station is warmer/colder, respectively, than the filling station. The

precipitation adjustment is recorded as a decimal proportion and is less than/greater

than 1.0 when the target station receives less/more precipitation, respectively, than

the filling station. These adjustment values are then added to (temperature) or

multiplied by (precipitation) the daily maximum and minimum temperature and total

precipitation data from the filling stations to estimate the target station daily weather.

Mean daily temperature was calculated as the average of the daily maximum and

minimum temperature, matching the methods of the Climate Infill Database as hourly

data was not available for most sites. Days reporting trace precipitation were treated

as 0 mm. The 1981-2010 climate normal data and adjustment values for all stations

are provided in 0. Detailed sample calculations for determining adjustment values

and infilled climate data are in 0.


Where more than one climate station was used to approximate the climate of a

subwatershed, subwatershed-averaged temperature and precipitation values were

determined through spatial proximity to target climate stations. Congruent series of

concentric circles around the target climate stations for each subwatershed were

drawn, e.g., Theisson Polygon method (see Figure 7). A line through the points at

which each pair of circles with equal radius intersect is the dividing line between the

target climate stations, as seen in Figure 7. The proportional area of the

subwatershed that is closest to each of the climate stations was rounded to the

nearest 5% to determine the proportional weighting to determine the average climate

of the subwatershed. The relative weightings of the two target stations for each

subwatershed is shown in Table 9.

Table 9: Climate stations used for climate data filling. Filling stations listed in order

of proximity to target station. See 0 for full station details.

Subwatershed Weight Target

station

Filling stations1

Skootamatta

River

100% Kaladar Centreville, Hartington IHD

Innisfil Creek 80% Egbert Care Egbert CS, Cookstown, Alliston Nelson,

Barrie WPCC, Shanty Bay, Orangeville

MOE

20% Orangeville

MOE

Fergus Shand Dam

Whitemans

Creek

65% Roseville Waterloo Wellington 2, Brantford MOE,

Woodstock, Millgrove, Stratford WWTP,

Glen Allan, Fergus Shand Dam

35% Foldens Woodstock, Culloden Easey, London A,

London Int'l Airport, St Thomas WPCP,

Stratford WWTP, Brantford MOE,

Roseville, Hamilton A

Parkhill Creek 80% Exeter Thedford, Stratford WWTP, Blyth,

London A, London Int'l Airport,

Strathroy-Mullifarry

20% Thedford Strathroy-Mullifarry, London Int'l

Airport, St Thomas WPCP, Stratford

WWTP

1Stations that are both target and filling stations were used as filling stations only if it had recorded climate data on the day requiring data filling


Figure 7: Climate data spatial weighting. Data shown for Whitemans Creek using the

Foldens and Roseville climate stations.


Table 10: Special circumstances related to general climate filling methods.

Subwatershed Climate station

Description of modification

Skootamatta River

Kaladar There are few climate stations meeting target station criteria near this subwatershed. The second

station would have been Bancroft Auto, contributing only 5% of subwatershed climate. It was determined that Kaladar would be the only

target station. This station does not have published 1981-2010

normal data; normal climate was calculated using infilled climate data 1981 to 2005 (Ontario Ministry of Natural Resources, 2011), and observed data

2006-2010 (Environment and Climate Change Canada, 2018b), with minor data gaps (minimum

97.5% of data reported annually) in order to facilitate climate filling.

Innisfil Creek Egbert Care/ Egbert CS

Egbert Care and Egbert CS were not included in the climate infill database. Data for this station was manually filled for 1981-2016.

Egbert Care has climate data until 2007. Egbert CS

(~0.0 km away) overlaps from 2000 onwards. It was assumed that climate normal data from Egbert

Care would be representative of Egbert CS.

Whitemans

Creek

Hamilton A Hamilton A moved in 2011. It is assumed that the

climate normal data would be representative of the new Hamilton A site.

Whitemans

Creek

London

Int'l Airport /

London A

London Int'l Airport records only P data while

London A records only T data. It was assumed that these two stations formed the climate normal data

listed for London Int'l Airport

Whitemans

Creek

Waterloo

Wellington 2

Waterloo Wellington A has climate normal data but

appears to have been replaced with Waterloo Wellington 2 which reports daily data after 2003.

Whitemans

Creek & Parkhill Creek

Stratford

WWTP

This station appears to be manually monitored

Monday-Friday. Uncertainties surround whether the values presented after a gap was actually

reflective of that day’s weather or the average/total from the entire missing period too. Data from this station was only used if P = 0 mm, or if P > 0 mm

and previous day's data available, and T if previous day's data available.

Parkhill Creek Strathroy-Mullifarry

Strathroy has climate normal data but data ended in 1996. Strathroy-Mullifarry is only ~3.4 km away

and it was assumed climate normals from Strathroy would be representative of Strathroy-Mullifarry.


7.4. Data Availability by Subwatershed

Climate data through the MNR Climate Data Gap Filling Project has a period of record

of 1950 to 2005 for all included climate stations and there are no gaps in this dataset.

However many of these stations are no longer active and have no records after 2005.

Individually, climate data collected from both the targeted Parkhill Creek and

Skootamatta River Integrated Water and Climate Monitoring Station have numerous

data gaps, and therefore was not used for analysis. Surface discharge data

downloaded from Environment Canada/ the Water Survey of Canada have few data

gaps. Data for groundwater levels range from having no gaps to having numerous

and long gaps, sometimes spanning several years. Of the potential 12 groundwater

monitoring wells that could have been used for this study, data could not be obtained

from two, and five have less than a 10-year length of record, and many have

considerable data gaps. Data series that are available for each subwatershed of

interest are shown in Figure 8 through Figure 11and detailed in the Table 11 through

Table 18 below.

For data analysis, Dr. Andrew Piggott recommended that datasets should span a

minimum of 10 complete years with at least 90% of data for each month of the year.

Discharge data is available for all sites for 2000 to present, with many of the stations

having more than 40 years of continuous discharge data. The Climate Data Gap Filling

Project ended in 2005 (some stations remain active to 2017) and many of the

groundwater data series do not begin until 2002 at the earliest, and some such as

that of the Skootamatta River and Parkhill Creek Integrated Water and Climate

Monitoring Station do not have data records prior to 2011 and 2012, respectively.

All data analyzed in this study was collected for the period of January 1, 1981 to

December 31, 2016 to coincide with the period of climate normal data (1981-2010)

and extending to the present. Climate data, however, was collected from September

1980 onwards to calculate snowpack storage for January 1, 1981 (thus impacting the

hydrologic release for winter and spring 1981).

7.4.1. Skootamatta River

A climate station has been installed as part of an Integrated Water and Climate

Monitoring Station in proximity to the stream gauge of the Skootamatta River near

Actinolite (02HL004), however, the dataset is unreliable long-term analysis (see

Figure 8). The climate station in Kaladar was used due to length of time series data.

Day length for Flinton was used to estimate the PET for the Skootamatta River

subwatershed. There is only one WSC stream gauge and two PGMN wells (W131-1

and W490-9) within the subwatershed. The period of potential overlap between

climate data (without infilling), surface discharge, and groundwater levels at this

study location is restricted to 2012 through 2015 when including both groundwater

monitoring wells.


Figure 8: Skootamatta River subwatershed and surrounding data sources.

Detailed data availability and percent completeness are listed in Table 11. Climate

data had been previously filled to 2005 (OMNR, 2011) and was further infilled for

2006 to 2016 using nearby climate stations to create a complete dataset. There is a

data gap in the time series groundwater data for W131-1 between 2009 and 2010.


Data for W490-9 could not be obtained from the MOECC for this report.

Table 12 summarizes the number of years that each type of raw data (climate,

surface water, and groundwater) was available for both annual and seasonal

analyses, including the number of years of overlap data for correlation analyses.

Table 11: Time series data availability for the Skootamatta River subwatershed. Light

shading indicates < 100% of data availability, dark shading indicates < 90% of

annual data available.

Year Kaladar Climate Skootamatta River Groundwater Level W131-1 T P Discharge Data

1981 100% 100% 100% -

1982 100% 100% 100% -

1983 100% 100% 100% -

1984 100% 100% 100% -

1985 100% 100% 100% -

1986 100% 100% 100% -

1987 100% 100% 100% -

1988 100% 100% 100% -

1989 100% 100% 100% -

1990 100% 100% 100% -

1991 100% 100% 100% -

1992 100% 100% 100% -

1993 100% 100% 100% -

1994 100% 100% 100% -

1995 100% 100% 100% -

1996 100% 100% 100% -

1997 100% 100% 100% -

1998 100% 100% 100% -

1999 100% 100% 100% -

2000 100% 100% 100% -

2001 100% 100% 100% -

2002 100% 100% 100% 65%

2003 100% 100% 100% 100%

2004 100% 100% 100% 100%

2005 100% 100% 100% 100%

2006 97.5% 99.5% 100% 100%

2007 97.5% 97.5% 100% 100%

2008 98.9% 98.9% 100% 100%

2009 97.5% 97.5% 100% 77%

2010 99.7% 99.7% 100% 12%

2011 99.7% 99.7% 100% 100%


Year Kaladar Climate Skootamatta River Groundwater Level W131-1 T P Discharge Data

2012 99.5% 99.5% 100% 100%

2013 99.7% 99.7% 100% 100%

2014 99.2% 99.2% 100% 100%

2015 92.9% 92.9% 100% 100%

2016 - - 100% 100%

Table 12: Summary of number of years of data availability by source and number of

years of with corresponding data for correlation analyses for the Skootamatta River

subwatershed.

Number of corresponding years’ data points

Time period Raw data type # observations Climate SW W131-1 GW

Annual Climate 36 36

SW 36 36 36

W131-1 GW 12 12 12 12

Winter (JFM) Climate 36 36

SW 36 36 36

W131-1 GW 13 13 13 13

Spring (AMJ) Climate 36 36

SW 36 36 36

W131-1 GW 13 13 13 13

Summer (JAS) Climate 36 36

SW 36 36 36

W131-1 GW 14 14 14 14

Autumn (OND)

Climate 36 36

SW 36 36 36

W131-1 GW 13 13 13 13

7.4.2. Innisfil Creek

There are a number of observation stations in and around the Innisfil Creek

subwatershed (Figure 9). Unfortunately, of the many climate stations in the

surrounding area, most have already been discontinued, including Alliston Nelson

(discontinued in 2008) which had a high quality 35 year history. Day length data for

Beeton was used to estimate PET for the Innisfil Creek subwatershed. There are two

WSC stream gauges, one on the Beeton Creek tributary and the other near the

confluence of the Innisfil Creek with the Nottawasaga River. Only the Innisfil Creek

station (02ED029, installed in 2000) was used in this analysis. There are four PGMN

wells located within the Innisfil Creek subwatershed, with three of them clustered in


one location at varying depths. All of these wells are installed within confined

aquifers, with W224-1 confined by shallow clay and the wells at W323 are confined

by glacial till. Annual percent completeness of raw datasets is shown in Table 13.

Figure 9: Innisfil Creek subwatershed and surrounding data sources.


Table 13: Innisfil Creek data sources and data gaps. Light shading indicates < 100%

of data availability, dark shading indicates < 90% of annual data available.

Egbert Care Egbert CS T/P Orangeville Innisfil Creek Groundwater level

Year T P T P T P Discharge Data W224-1 W323-2 W323-3 W323-4

1981 100% 100% 100% 100% 100% 100% - - - - -

1982 100% 100% 100% 100% 100% 100% - - - - -

1983 100% 100% 100% 100% 100% 100% - - - - -

1984 100% 100% 100% 100% 100% 100% - - - - -

1985 100% 100% 100% 100% 100% 100% - - - - -

1986 100% 100% 100% 100% 100% 100% - - - - -

1987 100% 100% 100% 100% 100% 100% - - - - -

1988 100% 100% 100% 100% 100% 100% - - - - -

1989 100% 100% 100% 100% 100% 100% - - - - -

1990 100% 100% 100% 100% 100% 100% - - - - -

1991 100% 100% 100% 100% 100% 100% - - - - -

1992 100% 100% 100% 100% 100% 100% - - - - -

1993 100% 100% 100% 100% 100% 100% - - - - -

1994 100% 100% 100% 100% 100% 100% - - - - -

1995 100% 100% 100% 100% 100% 100% - - - - -

1996 100% 100% 100% 100% 100% 100% - - - - -

1997 100% 100% 100% 100% 100% 100% - - - - -

1998 100% 100% 100% 100% 100% 100% - - - - -

1999 100% 100% 100% 100% 100% 100% - - - - -

2000 100% 100% 100% 100% 100% 100% 92.6% - - - -

2001 100% 100% 100% 100% 100% 100% 100% - - - -

2002 100% 100% 100% 100% 100% 100% 100% 5.5% - - -

2003 100% 100% 100% 100% 100% 100% 100% 72.3% 61.4% 61.4% 61.4%

2004 100% 100% 100% 100% 100% 100% 100% 0.0% 80.1% 100% 100%

2005 100% 100% 100% 100% 100% 100% 100% 13.2% 16.4% 100% 42.2%

2006 100% 100% 100% 97.3% 100% 99.7% 100% 0.0% 100% 61.6% 0.0%

2007 26% 26% 95.1% 25.8% 99.7% 100% 100% 0.0% 79.5% 100% 24.9%

2008 - - 99.7% 98.1% 91.5% 92.6% 100% 12.0% 100% 100% 100%

2009 - - 99.7% 93.4% 86.8% 86.8% 100% 90.7% 100% 100% 100%

2010 - - 99.5% 99.2% 97.8% 97.8% 80.3% 43.3% 100% 100% 69.6%

2011 - - 96.7% 99.5% 97.3% 97.8% 100% 82.2% 100% 100% 100%

2012 - - 82.8% 91.5% 93.2% 97.0% 100% 65.0% 100% 58.5% 88.8%

2013 - - 78.6% 93.7% 96.2% 97.5% 100% 100% 100% 8.8% 84.7%

2014 - - 99.2% 96.2% 94.5% 96.7% 100% 100% 100% 88.5% 100%

2015 - - 95.6% 93.7% 94.8% 97.3% 100% 100% 100% 83.0% 73.2%

2016 - - 95.6% 95.4% - - 64.5% 100% 100% 100% 100%


The number of years with both annual and seasonal data and the overlap periods

which enable correlation analysis where there are at least 10 years of annual or

seasonal data are outlined in Table 14. Though each of the groundwater wells has

real-time data records from 2002/2003, but that only W323-2 (shallowest well) has

sufficient data to conduct statistical analysis on both annual and seasonal scales,

though not all data types could be included in all analyses.

Table 14: Summary of number of years of data availability by data source and

corresponding observations for statistical analyses for the Innisfil Creek

subwatershed.


Time

period

Raw data

type

#

observations Climate SW

W224-1

GW

W323-2

GW

W323-3

GW

W323-4

GW

An

nu

al

Climate 36 36

SW 14 14 14

W224-1 GW 4 - - -

W323-2 GW 10 10 8 - 10

W323-3 GW 9 - - - - -

W323-4 GW 7 - - - - - -

Win

ter (

JFM

) Climate 36 36

SW 14 14 14

W224-1 GW 7 - - -

W323-2 GW 12 12 10 - 12

W323-3 GW 10 10 8 - 9 10

W323-4 GW 10 10 8 - 9 9 10

Sp

rin

g (

AM

J) Climate 36 36

SW 15 15 15

W224-1 GW 7 - - -

W323-2 GW 12 12 10 - 12

W323-3 GW 11 11 9 - 10 11

W323-4 GW 9 - - - - - -

Su

mm

er (

JA

S) Climate 36 36

SW 17 17 17

W224-1 GW 7 - - -

W323-2 GW 12 12 12 - 12

W323-3 GW 12 12 12 - 10 12

W323-4 GW 10 10 10 - 10 8 10

Au

tum

n

(O

ND

)

Climate 36 36

SW 17 17 17

W224-1 GW 6 - - -

W323-2 GW 11 11 11 - 11

W323-3 GW 12 12 12 - 9 12



Time period

Raw data type

# observations

Climate SW W224-1

GW W323-2

GW W323-3

GW W323-4

GW

W323-4 GW 11 11 11 - 9 10 11

7.4.3. Whitemans Creek

Similar to the Innisfil Creek subwatershed, there are numerous observation stations

surrounding the Whitemans Creek subwatershed (Figure 10). There are no

Environment and Climate Change Canada climate stations within the subwatershed,

however there are numerous stations near the subwatershed that can be used to

approximate climate. Day length for Blandford Station was used to estimate PET for

Whitemans Creek subwatershed. There are also two WSC stream gauges within the

subwatershed, one on the Horner Creek tributary and one upstream of the confluence

of Whitemans Creek and the Grand River. For comparability with the other

subwatershed in this analysis, only data from the stream gauge on the main

Whitemans Creek (02GB008) was used. There are three PGMN wells within the

subwatershed, all of which are confined by overlaying layers of till and clay, however,

data from W065-4 was unavailable from the MOECC. Annual percent completeness

of raw datasets is shown in Table 15.



seasonal data are outlined in Table 16. The groundwater data for both W477-1 and

W478-1 have clean data records, however the record length is insufficient to conduct

statistical analyses on groundwater data.


Figure 10: Whitemans Creek subwatershed and surrounding data sources.


Table 15: Whitemans Creek data sources and data gaps. Light shading indicates

< 100% of data availability, dark shading indicates < 90% of annual data available.

Foldens Roseville Whitemans Creek Discharge Data

Groundwater level

Year T P T P W477-1 W478-1

1981 100% 100% 100% 100% 100% - -

1982 100% 100% 100% 100% 100% - -

1983 100% 100% 100% 100% 100% - -

1984 100% 100% 100% 100% 100% - -

1985 100% 100% 100% 100% 100% - -

1986 100% 100% 100% 100% 100% - -

1987 100% 100% 100% 100% 100% - -

1988 100% 100% 100% 100% 100% - -

1989 100% 100% 100% 100% 100% - -

1990 100% 100% 100% 100% 100% - -

1991 100% 100% 100% 100% 100% - -

1992 100% 100% 100% 100% 100% - -

1993 100% 100% 100% 100% 100% - -

1994 100% 100% 100% 100% 100% - -

1995 100% 100% 100% 100% 100% - -

1996 100% 100% 100% 100% 100% - -

1997 100% 100% 100% 100% 100% - -

1998 100% 100% 100% 100% 100% - -

1999 100% 100% 100% 100% 100% - -

2000 100% 100% 100% 100% 100% - -

2001 100% 100% 100% 100% 100% - -

2002 100% 100% 100% 100% 100% - -

2003 100% 100% 100% 100% 100% - -

2004 100% 100% 100% 100% 100% - -

2005 100% 100% 100% 100% 100% - -

2006 100% 100% 88.8% 96.4% 100% - -

2007 80.3% 80.3% 91.0% 91.0% 100% - -

2008 85.2% 85.2% 86.3% 86.3% 100% 19.1% 19.1%

2009 100% 100% 90.7% 90.7% 100% 100% 100%

2010 97.0% 97.0% 87.7% 87.7% 100% 100% 100%

2011 99.2% 99.2% 91.5% 91.5% 100% 100% 100%

2012 97.0% 97.0% 91.8% 91.5% 100% 100% 100%

2013 97.8% 97.8% 91.2% 91.2% 100% 100% 100%

2014 99.5% 99.5% 94.0% 94.0% 100% 100% 100%

2015 92.3% 92.3% 95.9% 95.9% 100% 100% 100%

2016 44.8% 44.8% 91.5% 91.3% 100% 100% 62.6%


Table 16: Summary of number of years of data availability by data source and

corresponding observations for statistical analyses for the Whitemans Creek

subwatershed.

Number of corresponding years of data points

Time period

Raw data type

# observations Climate SW W477-1 GW W478-1 GW

An

nu

al Climate 36 36

SW 36 36 36

W477-1 GW 8 - - -

W478-1 GW 7 - - - -

Win

ter

(JFM

)

Climate 36 36

SW 36 36 36

W477-1 GW 8 - - -

W478-1 GW 8 - - - -

Spri

ng

(AM

J)

Climate 36 36

SW 36 36 36

W477-1 GW 8 - - -

W478-1 GW 8 - - - -

Sum

mer

(J

AS)

Climate 36 36

SW 36 36 36

W477-1 GW 8 - - -

W478-1 GW 7 - - - -

Au

tum

n

(ON

D)

Climate 36 36

SW 36 36 36

W477-1 GW 8 - - -

W478-1 GW 7 - - - -

7.4.4. Parkhill Creek

There are few observation stations within the Parkhill Creek subwatershed (Figure

11) and several nearby climate stations, however, of these, Strathroy-Mullifarry is

the only one that remains active. Day length from West McGillivray was used to

estimate PET for the Parkhill Creek subwatershed. There is only one WSC stream

gauge in the subwatershed (02FF008), located upstream of the Parkhill reservoir.

There are also three PGMN wells at two locations, with the paired wells (W491-9 and

W492-9) adjacent to the streamflow gauge as part of an Integrated Water and

Climate Monitoring Station. Percent completeness of the available raw datasets is

outlined in Table 17.


Figure 11: Parkhill Creek subwatershed and surrounding data sources.


Table 17: Parkhill Creek data sources and data gaps. Light shading indicates < 100%

of data availability, dark shading indicates < 90% of annual data available.

Exeter Thedford Surface discharge Groundwater level

Year T P T P Parkhill Creek W285-1 W491-9 W492-9

1981 100% 100% 100% 100% 100% - - -

1982 100% 100% 100% 100% 100% - - -

1983 100% 100% 100% 100% 100% - - -

1984 100% 100% 100% 100% 100% - - -

1985 100% 100% 100% 100% 100% - - -

1986 100% 100% 100% 100% 100% - - -

1987 100% 100% 100% 100% 100% - - -

1988 100% 100% 100% 100% 100% - - -

1989 100% 100% 100% 100% 100% - - -

1990 100% 100% 100% 100% 100% - - -

1991 100% 100% 100% 100% 100% - - -

1992 100% 100% 100% 100% 100% - - -

1993 100% 100% 100% 100% 100% - - -

1994 100% 100% 100% 100% 100% - - -

1995 100% 100% 100% 100% 100% - - -

1996 100% 100% 100% 100% 100% - - -

1997 100% 100% 100% 100% 100% - - -

1998 100% 100% 100% 100% 100% - - -

1999 100% 100% 100% 100% 100% - - -

2000 100% 100% 100% 100% 100% - - -

2001 100% 100% 100% 100% 100% - - -

2002 100% 100% 100% 100% 100% - - -

2003 100% 100% 100% 100% 100% 69.0% - -

2004 100% 100% 100% 100% 100% 94.8% - -

2005 100% 100% 100% 100% 100% 100% - -

2006 97.8% 99.5% 100% 100% 100% 93.4% - -

2007 99.5% 99.5% 98.4% 98.4% 100% 97.0% - -

2008 29.0% 29.0% 100% 100% 100% 96.2% - -

2009 - - 100% 100% 100% 96.2% - -

2010 - - 99.2% 99.2% 100% 96.2% - -

2011 - - 99.5% 99.5% 73% 95.9% - -

2012 - - 99.5% 98.9% 78% 98.4% 56.3% 54.1%

2013 - - 96.2% 96.2% 100% 86.6% 99% 100%

2014 - - 5.5% 5.5% 100% 69.0% 99% 98.9%

2015 - - - - 100% 96.2% 91% 92.6%

2016 - - - - 100% 97.8% 83% 80.9%




seasonal data are outlined in Table 18. Groundwater wells W491-9 and W492-9 do

not have sufficient record length for statistical analyses. Data from W285-1 has been

recording data for 14 years, however, there are large gaps that occur annually in the

autumn. This is a result of very slow recharge rates after annual pump tests/sampling

(D. Heinbuck, personal communication, July 26, 2017). Similar anomalies in

groundwater position are visible in the data for other two wells.

Table 18: Summary of number of years of data availability by source and number of

years of with corresponding data for correlation analyses for the Parkhill Creek

subwatershed.

Number of corresponding data points

Time period

Raw data type

# observations

Climate SW W285-1

GW W491-9

GW W492-9

GW

An

nu

al

Climate 36 36

SW 34 34 34

W285-1 GW 10 10 8 10

W491-9 GW 2 - - - -

W492-9 GW 2 - - - - -

Win

ter

(JFM

) Climate 36 36

SW 36 36 36

W285-1 GW 11 11 11 11

W491-9 GW 4 - - - -

W492-9 GW 4 - - - - -

Spri

ng

(AM

J) Climate 36 36

SW 35 35 35

W285-1 GW 14 14 13 14

W491-9 GW 5 - - - -

W492-9 GW 3 - - - - -

Sum

mer

(JA

S) Climate 36 36

SW 34 34 34

W285-1 GW 9 - - -

W491-9 GW 3 - - - -

W492-9 GW 3 - - - - -

Au

tum

n

(ON

D)

Climate 36 36

SW 34 34 34

W285-1 GW 4 - - -

W491-9 GW 2 - - - -

W492-9 GW 2 - - - - -


The soils of Parkhill Creek subwatershed have high clay component which means that

there is a long period of artificial drawdown and subsequent rebounding that has been

removed from the groundwater datasets prior to analysis. This occurs in

September/October annually, and results in data gaps to seasonal data sets for both

summer (JAS) and autumn (OND). Since it is likely that other

watersheds/subwatersheds could have similar challenges, it was determined that this

data could be used in annual comparisons only when the only data gaps are directly

related to this known sampling time, though it would be omitted from seasonal

analyses. When other unrelated data gaps were observed, the dataset was treated

as any other, and removed from annual and season-specific analyses.

8. Results

The results from the thematic evaluation and the time series evaluation for each pilot subwatershed are summarized below. The thematic summary is based on surface water features, SGRAs, forest cover, and the percent area impervious where

information via shapefiles are available. The time series data is presented based on temporal analysis followed by correlation analysis where strong correlation was

determined to exist based on the Spearman’s Rank, Kendall’s Rank, and linear regression. Lastly a double-mass balance analysis was conducted in order to highlight

changes in the relationship between the components.

8.1. Skootamatta River

8.1.1. Thematic Mapping Analysis

The landscape of the Skootamatta River subwatershed is very rural, dominated by

forests and surface water features. Here, these surface water features, are primarily

an extensive network of lakes, streams, and rivers. The spatial extent of the 120 m

buffer around and including surface water features is 54,745 ha, accounting for 79%

of the subwatershed area (Figure 12). It should also be noted that this is likely

underestimated for this subwatershed, due to the extensive network of streams that

are represented as linear features in geospatial data with their width not accurately

represented.

The extent of SGRAs within this subwatershed is relatively small. These areas

generally correspond to the areas of established agricultural land use. There are

1,103 ha of SGRAs covering 1.6% of the subwatershed and 1,691 ha including the

120 m buffer covering 2.4% (Figure 13).

When the spatial extent of the 120 m buffer around the surface water features and

the SGRAs are combined, the total area of the Skootamatta River subwatershed that

is within 120 m of a key hydrologic feature or area is 55,816 ha (80.1%). Any


potential land use change within this area would then require the comprehensive

feature-based water budget analysis at the site-scale, as per the outlined framework

herein.

Forest cover in the Skootamatta River subwatershed is also very extensive, covering

53,438 ha (77%) of the subwatershed (Figure 14). This well exceeds the target

> 35% forest cover of the Conservation Ontario (2011) guidelines for a grading of

“A”.

There is no established impermeable or built-up GIS layer for this area, however, the

total spatial extent of the combined forest and surface water features is > 91% of

the subwatershed and roads cover < 0.5% of the subwatershed. This is summarized

in Table 43 in Section 0. Of the remaining < 9% of the subwatershed, it is unlikely

that more than half would be impermeable, therefore this subwatershed is classified

as “Good” (< 5% impermeable) following the State of the Great Lakes Conference

Guidelines (Environment Canada & U.S. Environmental Protection Agency, 2009).

Impermeable areas for this report focus on anthropogenic features that have

modified natural hydrologic function and therefore exclude bedrock outcroppings

which are likely present throughout this subwatershed.


Figure 12: Surface water features and their 120 m buffer of the Skootamatta River

subwatershed


Figure 13: Significant groundwater recharge areas (SGRAs) and their 120 m buffer

within the Skootamatta River subwatershed.


Figure 14: Forest cover within the Skootamatta River subwatershed.


8.1.2. Time Series Analysis

8.1.2.1. Temporal Analysis

Groundwater generally is lowest in the late autumn and highest early spring,

however, there is considerable variability between years. The water table position

has had a maximum range of 1.5 m since data records began in 2002, with both

maximum and minimum extremes occurring in the last several years. Based on the

available annual average groundwater level from 2003-2016 (though 2009 and 2010

are missing), 2003 and 2012 were the overall driest years and 2006 and 2004 were

the wettest years.

Maximum hydrologic release in the Skootamatta River subwatershed has been

associated with both the spring freshet and summer storm events, while periods of

lowest hydrologic release coincide with the winter period, often with multiple

consecutive days of no hydrologic release. Streamflow is generally highest in the late

winter/early spring, coinciding with snowmelt, and lowest through the summer and

early autumn. Annual maximum daily average discharge is generally between 40 and

80 m3/s, however, extreme events have had daily average discharge > 100 m3/s.

Annual low flow is generally < 1 m3/s.

The results of time series Mann-Kendall trend analyses of the Skootamatta River

subwatershed are provided in Table 19. Only results indicating a potential trend with

> 90% confidence (p-value < 0.05) are shown (see 0 for complete results). This is

the threshold Gao et al. (2010) used to determine whether further analyses would

be conducted. The results indicate that annual climatic parameters have very certain

increasing trends for Total P, Mean T, PET, 30d MIN R, and the DOY timing of both

7d MAX T and 30d MIN R (indicating delayed occurrence; see 0 for coding definitions).

While the annual-scale climate drivers are changing, there were no detected trends

with annual streamflow, baseflow, nor groundwater indicators.

With the annual trends of 30d MIN R and associated DOY timing decreasing, and the

timing of the lowest hydrologic release generally being through the winter, it is not

surprising that the analysis of 30d MIN R JFM also indicates very certain increasing

trends for both volume and associated DOY timing. The only seasonal very certain

temperature trend occurs in the summer, with the 7d MIN T JAS increasing to support

the increasing trend of the annual mean temperature.

Of all the parameters tested both annually and seasonally, the timing of 3d MAX Q

JFM was the only non-climate parameter returning a very certain temporal change,

indicating a decreasing trend. This means that the timing of the greatest winter

streamflow is getting earlier.


Table 19: Results of Mann-Kendall trend tests for the Skootamatta

River subwatershed, where probably trending (PT) indicates p-value < 0.05

(light shading) and very confident (VC) indicates p-value < 0.025 (dark shading).

Type ParameterMann-Kendall

Result τ p-value

Climate

Total P 0.27 0.021 Increasing, VC

Total R OND 0.251 0.032 Increasing, PT

3d MAX R OND DOY 0.243 0.04 Increasing, PT

30d MIN R 0.363 0.008 Increasing, VC

30d MIN R DOY 0.417 0.0005 Increasing, VC

30d MIN R JFM 0.388 0.005 Increasing, VC

30d MIN R JFM DOY 0.416 0.0005 Increasing, VC

30d MIN R AMJ DOY -0.234 0.047 Decreasing, PT

30d MIN R OND 0.257 0.03 Increasing, PT

Mean T 0.283 0.016 Increasing, VC

7d MAX T DOY 0.383 0.001 Increasing, VC

7d MAX T OND DOY -0.25 0.039 Decreasing, PT

7d MIN T JAS 0.305 0.009 Increasing, VC

PET 0.302 0.01 Increasing, VC

Surface water 3d MAX Q JFM -0.244 0.037 Decreasing, PT

3d MAX Q JFM DOY -0.33 0.005 Decreasing, VC

Groundwater BF yield AMJ -0.244 0.037 Decreasing, PT

7d MIN GW JAS DOY 0.465 0.038 Increasing, PT

8.1.2.2. Correlation Analysis

Parameters that were found to have strong correlation, that is where the results from

all three correlation tests (Spearman’s Rank, Kendall’s Rank, and linear regression)

have correlation coefficients greater than an absolute value of 0.5 (> |0.5|), and p-

value < 0.05, are displayed in Table 20 through Table 24. Additional results of these

analyses are found in 0.

Temperature and precipitation variables are correlated at the annual time scale,

however, at the seasonal scale there are few climate variables that have significant

correlation with another parameter (i.e., climatic variable or hydrologic indicator).

The only such instances where the winter 3d MAX R (rain plus snowmelt; negatively

correlated to the 7d MIN GW DOY), the summer 30d MIN R (positively correlated with

the 7d MIN GW) and the autumn total R (negatively correlated with the 7d MIN GW

DOY i.e., the more total hydrologic release, the earlier the groundwater levels begin

to increase after the summer dry period). Also of note is that there are considerably


more parameters that have strong correlations during the summer (July-September;

JAS) and autumn (October-December; OND) months than there are of the annual

and winter (January-March; JFM) and spring (April-June; AMJ).

The parameters that had the most correlations at the seasonal scale were water yield

and baseflow yield. Many of these seasonal correlations are between streamflow,

baseflow, and groundwater. 7d MIN Q is strongly correlated with 7d MIN BF both

annually and seasonally, including the timing except in the autumn. Winter 7d MIN

GW DOY is strongly correlated with 3d MAX R and total and minimum

streamflow/baseflow parameters.

Water yield and baseflow yield are related to minimum multi-day hydrologic

indicators (i.e., Q, BF, and GW) in the winter, maximum multi-day indicators in the

spring, both maximum and minimum multi-day indicators in the summer, and

maximum multi-day parameters in the autumn. Streamflow and baseflow discharge

are often related, and groundwater generally has more correlation with streamflow

discharge than baseflow discharge indicators.

Table 20: Correlation between annual parameters of the Skootamatta River

subwatershed.

Annual Correlation

Spearman's

Rank

Kendall's

Rank Linear Regression

Parameter 1 Parameter 2 ρ

p-

value τ

p-

value R²

p-

value slope

Mean T PET 0.88 0.00 0.68 0.00 0.72 0.00 +

Total P P-PET 0.95 0.00 0.82 0.00 0.91 0.00 +

10:90 exceed 7d MIN Q -0.87 0.00 -0.7 0.00 0.53 0.00 -

10:90 exceed 7d MIN BF -0.86 0.00 -0.7 0.00 0.51 0.00 -

Water yield BF yield 0.86 0.00 0.67 0.00 0.72 0.00 +

3d MAX Q 3d MAX GW 0.83 0.00 0.67 0.02 0.62 0.00 +

7d MIN Q 7d MIN BF 0.98 0.00 0.91 0.00 0.98 0.00 +

7d MIN Q DOY 7d MIN BF DOY 0.75 0.00 0.71 0.00 0.58 0.00 +

Mean GW 7d MIN GW 0.78 0.00 0.64 0.03 0.61 0.00 +

Table 21: Correlation between winter seasonal parameters of the Skootamatta River

subwatershed.

Winter (JFM)

Spearman's

Rank

Kendall's



p-

value τ

p-

value R²

p-

value slope

3d MAX R 7d MIN GW DOY -0.74 0.00 -0.6 0.03 0.58 0.00 -

Water yield 7d MIN GW DOY -0.81 0.00 -0.65 0.02 0.51 0.00 -

BF yield 7d MIN Q 0.73 0.00 0.55 0.00 0.60 0.00 +


Winter (JFM)

Spearman's

Rank

Kendall's



p-

value τ

p-

value R²

p-

value slope

BF yield 7d MIN BF 0.78 0.00 0.6 0.00 0.66 0.00 +

BF yield 7d MIN GW DOY -0.75 0.00 -0.57 0.04 0.65 0.00 -

7d MIN Q 7d MIN BF 0.96 0.00 0.91 0.00 0.94 0.00 +

7d MIN Q 7d MIN GW DOY -0.79 0.00 -0.62 0.02 0.67 0.00 -

7d MIN BF 7d MIN GW DOY -0.79 0.00 -0.65 0.02 0.69 0.00 -

3d MAX GW 7d MIN GW 0.88 0.00 0.74 0.00 0.75 0.00 +

Table 22: Correlation between spring seasonal parameters of the Skootamatta River

subwatershed

Spring (AMJ)

Spearman's

Rank

Kendall's



p-

value τ

p-

value R²

p-

value slope


Water yield 3d MAX GW 0.74 0.00 0.59 0.03 0.53 0.00 +

BF yield 3d MAX BF 0.89 0.00 0.74 0.00 0.82 0.00 +

3d MAX Q 3d MAX GW 0.77 0.00 0.59 0.03 0.61 0.00 +

7d MIN Q 7d MIN BF 0.98 0.00 0.9 0.00 0.96 0.00 +


Table 23: Correlation between summer seasonal parameters of the Skootamatta

River subwatershed.

Summer (JAS)

Spearman's

Rank

Kendall's



p-

value τ

p-

value R²

p-

value slope

30d MIN R 7d MIN GW 0.79 0.00 0.64 0.01 0.58 0.01 +


Water yield 3d MAX Q 0.95 0.00 0.81 0.00 0.74 0.00 +

Water yield 7d MIN Q 0.78 0.00 0.6 0.00 0.60 0.00 +

Water yield 3d MAX BF 0.86 0.00 0.7 0.00 0.70 0.00 +

Water yield 7d MIN BF 0.76 0.00 0.59 0.00 0.59 0.00 +

Water yield 7d MIN GW 0.84 0.00 0.67 0.01 0.60 0.00 +

BF yield 3d MAX Q 0.87 0.00 0.7 0.00 0.57 0.00 +

BF yield 7d MIN Q 0.79 0.00 0.61 0.00 0.61 0.00 +

BF yield 3d MAX BF 0.92 0.00 0.76 0.00 0.80 0.00 +

BF yield 7d MIN BF 0.76 0.00 0.59 0.00 0.58 0.00 +

3d MAX Q DOY 3d MAX GW -0.82 0.00 -0.67 0.01 0.60 0.00 -


Summer (JAS)

Spearman's

Rank

Kendall's



p-

value τ

p-

value R²

p-

value slope

7d MIN Q 7d MIN BF 0.64 0.01 0.91 0.00 0.98 0.00 +


Table 24: Correlation between autumn seasonal parameters of the Skootamatta River

subwatershed.

Autumn (OND)

Spearman's

Rank

Kendall's



p-

value τ

p-

value R²

p-

value slope

Total R 7d MIN GW DOY -0.65 0.02 -0.57 0.04 0.50 0.00 -




Water yield 3d MAX GW 0.86 0.00 0.69 0.01 0.72 0.00 +

BF yield 3d MAX Q 0.8 0.00 0.62 0.00 0.56 0.00 +

BF yield 3d MAX BF 0.85 0.00 0.68 0.00 0.79 0.00 +

BF yield 3d MAX GW 0.82 0.00 0.64 0.02 0.70 0.00 +

3d MAX Q 3d MAX GW 0.74 0.00 0.56 0.04 0.56 0.00 +

3d MAX Q DOY 3d MAX BF DOY 0.72 0.00 0.55 0.00 0.62 0.00 +

7d MIN Q 7d MIN BF 0.93 0.00 0.82 0.00 0.98 0.00 +

7d MIN Q 7d MIN GW 0.79 0.00 0.67 0.01 0.98 0.00 +

3d MAX GW 7d MIN GW 0.77 0.00 0.64 0.02 0.61 0.00 +

3d MAX GW DOY 7d MIN GW DOY -0.81 0.00 -0.62 0.02 0.55 0.00 -

8.1.2.3. Double-Mass Balance Analysis

The relationships between the cumulative baseflow yield to cumulative water yield

(annual analysis is presented in Figure 15) and cumulative water yield to cumulative

precipitation (annual analysis is presented in Figure 17; replaced by hydrologic

release in seasonal analysis) maintain overall similar strong linear relationships

through seasonal analyses. Notable differences to this pattern, however, occur during

the spring baseflow yield to water yield comparison (Figure 16) and summer water

yield to hydrologic release (Figure 18) which becomes slightly less linear, though R2

values remain > 0.98. Additionally, baseflow yield to water yield through the summer

months has less uniform values between years, though the resulting relationship

remains very strong (greater gaps between plotted cumulative values).


Figure 15: Skootamatta River cumulative annual baseflow yield to water yield (1981-

2016). The equation of the line estimates the proportion of water yield that is derived

from baseflow.

Figure 16: Skootamatta River spring cumulative baseflow yield to water yield. The

equation of the line estimates the proportion of water yield that is derived from

baseflow.

y = 0.6081xR² = 0.9996

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

0 2000 4000 6000 8000 10000 12000 14000 16000

Cu

mu

lati

ve B

asef

low

Yie

ld (

mm

)

Cumulative Water Yield (mm)

y = 0.588xR² = 0.9935

0

500

1000

1500

2000

2500

3000

3500

0 1000 2000 3000 4000 5000 6000

AM

J C

um

ula

tive

Bas

eflo

w Y

ield

(m

m)

AMJ Cumulative Water Yield (mm)


Baseflow generation is high in this subwatershed, with approximately 60%

(estimated from the slope of the linear regression presented within the graphs below)

of annual streamflow being comprised of baseflow. While this is higher than what

might have been anticipated for southern Ontario, the geology of this subwatershed

is vastly different. The finding of this higher value is also reflective of higher baseflow

index reported for this part of the province (Neff et al., 2005). Seasonally, this

proportion varies between 59% in the spring to 66% in the autumn.

At the annual time scale, the proportion of precipitation that becomes water yield is

similarly 66%. This however varies greatly in the seasonal comparison (where

precipitation is replaced by hydrologic release to incorporate snowpack accumulation

and snowmelt) with the greatest proportion of 73% occurring during the winter

months, moderate proportions, 57% and 46% in the spring and autumn,

respectively, and the lowest at 8% during the summer (Figure 18). The variability of

the amount of hydrologic release that becomes streamflow is directly related to the

landscape storage capacity, indicating much greater storage capacity during the

summer months where precipitation is not translated into streamflow.

Figure 17: Skootamatta River cumulative annual water yield to precipitation (1981-

2016). The equation of the line estimates the proportion of precipitation that

contributes to streamflow/water yield.

y = 0.6609xR² = 0.9974

0

2000

4000

6000

8000

10000

12000

14000

16000

0 5000 10000 15000 20000 25000

Cu

mu

lati

ve W

ater

Yie

ld (

mm

)

Cumulative Precipitation (mm)


Figure 18: Skootamatta River summer cumulative water yield to hydrologic release.

The equation of the line estimates the proportion of hydrologic release that

contributes to streamflow/water yield

8.2. Innisfil Creek


The Innisfil Creek subwatershed is largely rural, dominated by agricultural land use.

Surface water features in this subwatershed are predominantly wetlands, connected

with by a stream network, with very few open water lakes/ponds. The spatial extent

of the 120 m buffer around and including surface water features is displayed in Figure

19, covering 16,435 ha, or 33% of the subwatershed. The SGRAs within this

subwatershed are widespread, covering 18,072 ha (37%) of the subwatershed, and

when combined with their 120 m buffer, this area spans 24,249 ha covering nearly

50% of the subwatershed (Figure 20). When combining the spatial extent of the

surface water features and SGRAs covers 36,366 ha (or 74%) of the subwatershed.

Any land use change would be required to follow the feature-based water balance

methods, as per this framework.

There are 9,346 ha of forest cover (see Figure 21), covering 19% of the

subwatershed. This would receive a grading of “C” by Conservation Ontario

standards. Further, the forest extent in this subwatershed is decreasing (NVCA,

2013).

y = 0.0772xR² = 0.9843

0

100

200

300

400

500

600

700

800

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

JAS

Cu

mu

lati

ve W

ater

Yie

ld (

mm

)

JAS Cumulative Hydrologic Release (mm)


Most of the impermeable area is closely associated with the communities of

Tottenham, Beeton, and Cookstown, with additional properties and roads (Figure 22).

There are 660 km of road (northbound and southbound Highway 400 are counted

separately; estimated at 660 ha) plus 1,941 ha of built-up land, combining to cover

2,601 ha (5.3%) of the landscape within the Innisfil Creek subwatershed. This is

graded as “Fair” following the SOLEC standards (EC & U.S. EPA, 2009).


Figure 19: Surface water features and their 120 m buffer of the Innisfil Creek

subwatershed.



within the Innisfil Creek subwatershed.


Figure 21: Forest cover within the Innisfil Creek subwatershed.


Figure 22: Impermeable land within the Innisfil Creek subwatershed.




Of the four potential PGMN wells within this subwatershed, only one has sufficient

data for analysis both annual and seasonal. W323-2 generally has the highest

groundwater levels in May-June, and lowest in December-February, though this is

variable between years. Since observations began in 2003, the groundwater levels

have fluctuated within a range of just over 4 m. Based on the annual average data

(2006 and 2008-2016), 2009 and 2011 were the wettest years, and 2006 and 2015

were the driest years.

Maximum annual hydrologic release has occurred in all four seasons, but is most

commonly associated with spring freshet, while lowest hydrologic release generally

coincides with the winter period with multiple consecutive days of no hydrologic

release. Similarly, maximum streamflow is generally associated with the spring

freshet, with lowest flow occurring in the summer. Annual maximum daily average

streamflow is generally between 35 and 55 m3/s, and annual low flow is generally <1

m3/s.

There are only six parameters in the Innisfil Creek subwatershed that indicate greater

than 90% confidence of temporal trending (See Table 25). Of these, only the 10:90

extreme flow exceedance ratio is indicating a decreasing trend. This indicates that

there is decreasing variability in annual extremes. It should be noted, however, that

unlike the data from the hydrometric stations in the other subwatersheds of this

report, this dataset begins in 2000, and had very high outlier values for the first

couple of years, which may skew the results. Additionally, the summer of 2001 was

quite dry (10:90 exceedance ratio value of 41) relative to the range of conditions

since observations began (other values range between 8 and 29). Overall, this is

indicative of increasing capacity to accommodate input events. This could be resulting

from high agricultural withdrawals, which are beyond the scope of this report.

Table 25: Results of Mann-Kendall trend tests for the Innisfil Creek

subwatershed, where probably trending (PT) indicates p-value < 0.05 (light shading) and very confident (VC) indicates p-value < 0.025 (dark shading).

Type ParameterMann-Kendall

Result τ p-value

Climate 7d MAX T DOY 0.305 0.01 Increasing, VC

Surface water

10:90 exceedance -0.626 0.002 Decreasing, VC

7d MIN Q 0.516 0.012 Increasing, VC

7d MIN Q JFM DOY 0.425 0.042 Increasing, PT

Groundwater 7d MIN BF 0.56 0.006 Increasing, VC

W323-2 7d MIN GW OND DOY 0.648 0.01 Increasing, VC


The only climate parameter to indicate a temporal trend is the annual 7d MAX T DOY

timing, indicating that it is occurring later in the year. Note that there is no

corresponding trend in seasonal observations. Since this climate variable is the timing

of the occurrence, and not the input variable (i.e., temperature, precipitation, or

hydrologic release), there is reason to believe that the surface water and groundwater

indicators indicating temporal change may be indicative of additional factors

influencing the hydrology of this subwatershed such as land use change or water

takings.

The DOY timing of the annual minimum groundwater elevation of W323-2 was found

to artificially indicate a statistically significant trend of becoming later in the year,

however this was the result of the lowest groundwater position occurring generally

in December-January. When the December DOY values were modified to negatives

relative to January 1st, there was no temporal trend. There was, however, a temporal

trend in the 7d MIN GW OND DOY for W323-2, indicating overall occurrence later in

the year.


Annual and seasonal correlation results where strong correlation was detected are

presented in Table 26 through Table 30. Additional results are provided in 0. Climate

variables were found to have correlations with both climate variables and hydrologic

indicators at the annual scale, however at the seasonal scale, there are few

correlations between climate variables and another parameter (only correlations are

total R [spring: positive correlation with water yield], 3d MAX R [autumn: positive

correlation with 3d MAX Q], and 7d MIN R [autumn: positive correlation with W323-

3 MAX GW DOY]). Most seasonal correlations are between surface and groundwater

indicators.

Surface water indicators (e.g., water yield and streamflow) have strong correlations

with baseflow (yield and extremes). This should not be surprising as baseflow was

calculated from streamflow data. Groundwater levels were often correlated with those

of other groundwater wells, and had few correlations with baseflow and streamflow

indicators. There are also few correlations with the timing of extreme surface water

and groundwater conditions, but numerous correlations with the extreme values

themselves.


Table 26: Correlation between annual parameters of the Innisfil Creek subwatershed.

Annual Correlation Spearman's Rank

Kendall's Rank Linear Regression

Parameter 1 Parameter 2 ρ p-

value τ p-

value R² p-

value slope sign

Mean T PET 0.89 0.00 0.71 0.00 0.73 0.00 +

Total P P-PET 0.95 0.01 0.83 0.00 0.93 0.00 +

Total P Water yield 0.84 0.00 0.71 0.00 0.72 0.00 +

Total P 3d MAX Q 0.82 0.00 0.69 0.01 0.54 0.00 +

P-PET Water yield 0.82 0.00 0.69 0.01 0.66 0.00 +

P-PET 3d MAX Q 0.82 0.00 0.67 0.01 0.52 0.00 +

P-PET W323-2 7d MIN GW DOY -0.83 0.00 -0.69 0.03 0.50 0.01 -

7d MIN T DOY W323-2 7d MIN GW -0.84 0.00 -0.67 0.03 0.66 0.00 -

10:90 exceed 7d MIN Q -0.88 0.00 -0.71 0.00 0.63 0.00 -

10:90 exceed 7d MIN BF -0.88 0.00 -0.71 0.00 0.55 0.00 -



7d MIN Q 7d MIN BF 0.97 0.00 0.91 0.00 0.97 0.00 +


W323-2 Mean GW W323-2 3d MAX GW 0.84 0.00 0.73 0.02 0.82 0.00 +

W323-2 Mean GW W323-2 7d MIN GW 0.84 0.00 0.73 0.02 0.57 0.01 +

Table 27: Correlation between winter seasonal parameters of the Innisfil Creek

subwatershed.

Winter (JFM) Spearman's

Rank Kendall's



value τ p-

value R² p-

value slope sign




BF yield 7d MIN Q 0.53 0.00 0.74 0.00 0.80 0.00 +

BF yield 3d MAX BF 0.74 0.00 0.6 0.02 0.68 0.00 +

BF yield 7d MIN BF 0.85 0.00 0.67 0.01 0.64 0.00 +

7d MIN Q 7d MIN BF 0.98 0.00 0.93 0.00 0.91 0.00 +

3d MAX BF DOY W323-2 3d MAX GW -0.77 0.01 -0.69 0.03 0.83 0.00 -

W323-2 3d MAX GW W323-2 7d MIN GW 0.93 0.00 0.82 0.00 0.55 0.00 +

W323-3 3d MAX GW W323-3 7d MIN GW 0.88 0.00 0.73 0.02 0.81 0.00 +

W323-4 3d MAX GW W323-4 7d MIN GW 0.99 0.00 0.96 0.00 0.96 0.00 +


Table 28: Correlation between spring seasonal parameters of the Innisfil Creek

subwatershed.

Spring (AMJ) Spearman's

Rank Kendall's Rank Linear Regression


value τ p-

value R² p-

value slope sign

Total R Water yield 0.85 0.00 0.71 0.00 0.62 0.00 +


7d MIN Q 7d MIN BF 0.9 0.00 0.77 0.00 0.77 0.00 +


Table 29: Correlation between summer seasonal parameters of the Innisfil Creek

subwatershed.

Summer (JAS) Spearman's Rank



value τ p-

value R² p-

value slope sign






BF yield 3d MAX Q 0.9 0.00 0.72 0.00 0.72 0.00 +

BF yield 7d MIN Q 0.95 0.00 0.84 0.00 0.89 0.00 +

BF yield 3d MAX BF 0.92 0.00 0.76 0.00 0.73 0.00 +

BF yield 7d MIN BF 0.95 0.00 0.85 0.00 0.91 0.00 +

BF yield W323-4 7d MIN 0.78 0.01 0.64 0.04 0.65 0.00 +

3d MAX Q 7d MIN Q 0.8 0.00 0.59 0.01 0.60 0.00 +

3d MAX Q 3d MAX BF 0.95 0.00 0.84 0.00 0.86 0.00 +

3d MAX Q 7d MIN BF 0.82 0.00 0.6 0.01 0.62 0.00 +

7d MIN Q 3d MAX BF 0.8 0.00 0.6 0.01 0.51 0.00 +

7d MIN Q 7d MIN BF 0.98 0.00 0.93 0.00 0.98 0.00 +

7d MIN Q W323-2 7d MIN GW 0.8 0.00 0.64 0.03 0.57 0.00 +

7d MIN Q W323-4 7d MIN GW 0.78 0.01 0.64 0.04 0.77 0.00 +


3d MAX BF 7d MIN BF 0.83 0.00 0.62 0.01 0.53 0.00 +

7d MIN BF W323-4 7d MIN GW 0.82 0.00 0.69 0.03 0.75 0.00 +

W323-2 3d MAX GW W323-2 7d MIN GW 0.85 0.00 0.67 0.02 0.86 0.00 +

W323-2 3d MAX GW W323-3 3d MAX GW 0.77 0.01 0.64 0.04 0.59 0.01 +

W323-2 7d MIN GW W323-3 3d MAX GW 0.93 0.00 0.82 0.00 0.70 0.00 +

W323-2 7d MIN GW W323-3 7d MIN GW 0.92 0.00 0.78 0.01 0.58 0.01 +

W323-3 3d MAX GW W323-3 7d MIN GW 0.95 0.00 0.85 0.00 0.85 0.00 +


Summer (JAS) Spearman's Rank



value τ p-

value R² p-

value slope sign

W323-4 3d MAX GW W323-4 7d MIN GW 0.84 0.00 0.69 0.03 0.67 0.00 +

Table 30: Correlation between autumn seasonal parameters of the Innisfil Creek

subwatershed.

Autumn (OND) Spearman's

Rank Kendall's



value τ p-

value R² p-

value slope sign

3d MAX R 3d MAX Q 0.72 0.00 0.6 0.01 0.58 0.00 +

7d MIN R W323-3 3d MAX GW DOY 0.76 0.00 0.63 0.03 0.74 0.00 +




BF yield 3d MAX Q 0.8 0.00 0.65 0.00 0.52 0.00 +

BF yield 3d MAX BF 0.88 0.00 0.74 0.00 0.74 0.00 +

BF yield 7d MIN bf 0.79 0.00 0.59 0.01 0.60 0.00 +

3d MAX Q 3d MAX bf 0.85 0.00 0.71 0.00 0.85 0.00 +

7d MIN Q 7d MIN BF 0.95 0.00 0.84 0.00 0.80 0.00 +

7d MIN BF W323-4 3d MAX GW 0.87 0.00 0.67 0.02 0.70 0.00 +

7d MIN BF W323-4 7d MIN GW 0.89 0.00 0.78 0.00 0.68 0.00 +

W323-2 3d MAX GW W323-2 7d MIN GW 0.98 0.00 0.93 0.00 0.97 0.00 +

W323-3 3d MAX GW W323-3 7d MIN GW 0.99 0.00 0.94 0.00 0.97 0.00 +

W323-3 3d MAX GW W323-4 3d MAX GW 0.85 0.00 0.73 0.02 0.59 0.01 +

W323-3 3d MAX GW W323-4 7d MIN GW 0.88 0.00 0.73 0.02 0.65 0.00 +

W323-3 7d MIN GW W323-4 3d MAX GW 0.81 0.00 0.64 0.04 0.66 0.00 +

W323-3 7d MIN GW W323-4 7d MIN GW 0.85 0.00 0.64 0.04 0.69 0.00 +

W323-4 3d MAX GW W323-4 7d MIN GW 0.95 0.00 0.82 0.00 0.91 0.00 +

8.2.2.3. Double-Mass Balance Analysis

Annually, the relationship between cumulative baseflow yield to cumulative water

yield has a strong linear relationship (Figure 23), which remains very strong through

the seasonal analysis. There is a visual discrepancy with the spring pattern for the

first seven years of data, where baseflow yield contribution to water yield was

consistently less than anticipated for the overall relationship (Figure 24). Derived

from the slope of the linear regression of this relationship, approximately 45% of the

annual cumulative water yield in Innisfil Creek is resulting from baseflow yield. This


remains fairly consistent through the year, ranging between 38% in the spring to

57% in the autumn, with moderate proportions of 43% and 46% in the winter and

summer, respectively.

Figure 23: Innisfil Creek cumulative annual baseflow yield to water yield (2000-2016)

Figure 24: Innisfil Creek cumulative spring (AMJ) baseflow yield to water yield (2000-

2016).

y = 0.4502xR² = 0.9998

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Figure 25: Innisfil Creek cumulative annual water yield to cumulative precipitation

Figure 26: Innisfil Creek autumn (OND) cumulative water yield to cumulative

hydrologic release

Annual cumulative water yield to cumulative precipitation also has a strong linear

relationship (Figure 25). Relationships between autumnal cumulative water yield and

y = 0.1946xR² = 0.9969

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cumulative hydrologic release show the greatest difference when compared to the

annual trend (Figure 26), amplifying the overall patterns from annual relationships.

The annual proportion of precipitation that contributes to water yield is 19%, ranging

between 5% of hydrologic release in the summer and 39% in the winter. This is

reflective of greater storage capacity in the summer and frozen/wet conditions

through the winter.

8.3. Whitemans Creek


The Whitemans Creek subwatershed is largely rural, dominated by agricultural land

use. Surface water features in this subwatershed include groundwater discharge

areas, clustered near the headwaters both to the north and south, with wetlands

dominant in the central portion of this subwatershed with interconnecting streams.

There are few lakes or ponds in this subwatershed. The extent of the 120 m buffer

surrounding the surface water features is 54,745 ha, covering 79% of the

subwatershed (Figure 27). The SGRAs of this subwatershed are also quite expansive,

covering 20,422 ha (51%) of the subwatershed and their 120 m buffer encompasses

23,031 ha (57%) of the subwatershed (Figure 28). When combined, 30,321 ha or

75% of the subwatershed is within 120 m of key hydrologic features, and would

require comprehensive feature-based water budget analysis prior to any land use

change, as per the framework herein.

There is limited forest cover within the Whitemans Creek subwatershed, with only

6,913 ha (17%) forested (Figure 29). Much of this area is treed swamp, with only

small patches of upland forest. This would earn a grading of “C” following the

Conservation Ontario (2011) guidelines.

Most of the impermeable area is closely associated with the communities of Burford

and Mount Vernon, with additional small hamlets and the Brantford Municipal Airport

on the eastern edge plus roadways (Figure 30). There are 574 km of road (eastbound

and westbound Highways 401 and 403 are accounted for separately; estimated at

574 ha) plus 632 ha of built-up land, combining to cover 1,206 ha (3%) of the

landscape within the Whitemans Creek subwatershed. This is graded as “Good”

following the SOLEC standards (EC & U.S. EPA, 2009).


Figure 27: Surface water features and their 120 m buffer of the Whitemans Creek

subwatershed.



within the Whitemans Creek subwatershed.


Figure 29: Forest cover within the Whitemans Creek subwatershed.


Figure 30: Impervious land area within the Whitemans Creek subwatershed.




Groundwater levels at both wells (W477-1 and W478-1) are generally highest

through the winter/early spring, and lowest in the autumn. Since real-time

groundwater records began in late 2008, the water table has fluctuated within a range

of 2.5 m and 2 m at these sites, respectively. The observations at W477-1 are noisier

than those of W478-1. Based on average annual water table position, 2015 and 2016

were notably dry while 2009 was notably wet at both sites (though 2016 data is

incomplete at W478-1). Since there are only up to 8 years of groundwater data,

though it is continuous, it is of insufficient length to conduct further statistical analysis

at this time.

Maximum hydrologic release is closely related to both winter freshet and summer

storm events, with 47% of peak events occurring during the winter and 33% of

maximum observations occurring during the summer. Minimum hydrologic release

also often occurs during the winter period, with multiple consecutive days of no

release. Streamflow is also generally highest during the winter freshet, coinciding

with snowmelt, and lowest during the summer and autumn. Annual maximum daily

average discharge is generally 40 to 60 m3/s, with extreme events being recorded

with discharge rates in excess of 80 m3/s. Annual low flow is generally < 1 m3/s.

Table 31: Results of Mann-Kendall trend tests for the Whitemans

Creek subwatershed, where probably trending (PT) indicates p-value < 0.05

(light shading) and very confident (VC) indicates p-value < 0.025 (dark shading).

Type Parameter Mann-Kendall

Result τ p-value

Climate

Mean T 0.283 0.016 Increasing, VC

7d MAX T DOY 0.39 0.001 Increasing, VC



3d MAX R AMJ DOY -0.239 0.042 Decreasing, PT

Surface Water R-B Index 0.267 0.023 Increasing, VC

3d MIN Q OND DOY -0.241 0.044 Decreasing, PT

The highlights of temporal analysis using the Mann-Kendall trend test in provided in

Table 31. For complete results see 0. Annual and seasonal temperature variables and

the Richards-Baker Flashiness Index were found to have very certain increasing

trends. The only parameters that indicated potential trends were 3d MAX R AMJ DOY,

and 7d MIN Q OND DOY, both of which indicated decreasing trends, therefore

becoming earlier in their respective seasons. There were no results indicating


temporal trends of precipitation (hydrologic release), streamflow discharge, nor

baseflow parameters.


All observed instances of strong correlation at both the annual and seasonal scales

indicate positive relationships (Table 32 through Table 36, see 0 for full statistical

results). Annual, winter, and spring analyses indicate correlations between climate

variables and hydrologic indicators. Such correlations were not found during the

summer nor autumn analyses.

Total P (Total R in seasonal analysis) is strongly correlated to water yield in annual,

winter, and spring analyses, and is also strongly correlated to 7d MIN Q and 7d MIN

BF, indicating a relationship between hydrologic inputs and streamflow output. Water

yield is also strongly correlated with baseflow yield and 3d MAX Q at the annual and

each of the seasonal analyses. Similarly, 7d MIN Q and 7d MIN BF as well as their

DOY timings were also strongly correlated at each analysis time scale.

Table 32: Correlation between annual parameters of the Whitemans Creek

subwatershed.

Annual Correlation Spearman's



value τ p-

value R² p-

value slope sign

Mean T PET 0.9 0.00 0.73 0.00 0.76 0.00 +

Total P P-PET 0.97 0.00 0.86 0.00 0.95 0.00 +


P-PET Water yield 0.85 0.00 0.65 0.00 0.71 0.00 +

P-PET BF yield 0.74 0.00 0.54 0.00 0.53 0.00 +



7d MIN Q 7d MIN BF 0.99 0.00 0.95 0.00 0.98 0.00 +


Table 33: Correlation between winter seasonal parameters of the Whitemans Creek

subwatershed.




value τ p-

value R² p-

value slope sign








value τ p-

value R² p-

value slope sign

BF yield 7d MIN Q 0.77 0.00 0.58 0.00 0.54 0.00 +

7d MIN Q 7d MIN BF 0.97 0.00 0.91 0.00 0.93 0.00 +


Table 34: Correlation between spring seasonal parameters of the Whitemans Creek

subwatershed.




value τ p-

value R² p-

value slope sign


Total R 7d MIN Q 0.74 0.00 0.56 0.00 0.5183 0.00 +

Total R 7d MIN BF 0.73 0.00 0.55 0.00 0.5065 0.00 +



BF yield 3d MAX BF 0.8 0.00 0.62 0.00 0.6333 0.00 +

7d MIN Q 7d MIN BF 0.95 0.00 0.82 0.00 0.9293 0.00 +


Table 35: Correlation between summer seasonal parameters of the Whitemans Creek

subwatershed.

Summer (JAS) Spearman's



value τ p-

value R² p-

value slope sign




BF yield 7d MIN Q 0.9 0.00 0.75 0.00 0.61 0.00 +

BF yield 3d MAX BF 0.91 0.00 0.77 0.00 0.85 0.00 +

BF yield 7d MIN BF 0.89 0.00 0.73 0.00 0.59 0.00 +

7d MIN Q 7d MIN BF 0.99 0.00 0.96 0.00 0.98 0.00 +



Table 36: Correlation between autumn seasonal parameters of the Whitemans Creek

subwatershed.




value τ p-

value R² p-

value slope sign






BF yield 3d MAX Q 0.87 0.00 0.68 0.00 0.60 0.00 +

BF yield 7d MIN Q 0.79 0.00 0.6 0.00 0.67 0.00 +

BF yield 3d MAX BF 0.92 0.00 0.79 0.00 0.88 0.00 +

BF yield 7d MIN BF 0.77 0.00 0.58 0.00 0.67 0.00 +

3d MAX Q 3d MAX BF 0.91 0.00 0.75 0.00 0.62 0.00 +

7d MIN Q 7d MIN BF 0.97 0.00 0.89 0.00 0.96 0.00 +


8.3.2.3. Double Mass-Balance

Analysis of annual data (Figure 31) and seasonal data show similar tight linear

relationships between cumulative baseflow and cumulative streamflow. Annually,

baseflow accounts for approximately 54% of streamflow, ranging between 46% in

the winter to 60% in the spring, followed by 57% and 59% through the summer and

autumn, respectively. There is a similar tight relationship for cumulative streamflow

and cumulative precipitation (Figure 32) which is maintained through seasonal

analysis of hydrologic release through the winter and spring, however, there are

greater discrepancies as the year progresses, most notable in the autumn (OND)

period (Figure 33), however there remains a strong linear relationship. Annually, 23%

of precipitation contributes directly to water yield. This varies between 8% and 42%

of hydrologic release in the summer and winter, respectively. Spring and autumn

contribution of hydrologic release to water yield are moderate at 24% and 23%,

respectively.


Figure 31: Whitemans Creek cumulative baseflow yield to cumulative water yield

(1981-2016). The equation of the line estimates the proportion of water yield that is

derived from baseflow.

Figure 32: Whitemans Creek cumulative water yield to cumulative precipitation

(1981-2016). The equation of the line estimates the proportion of precipitation that

contributes to streamflow/water yield

y = 0.5365xR² = 0.9997

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Figure 33: Whitemans Creek autumn cumulative water yield to cumulative hydrologic

release (1981-2016). The equation of the line estimates the proportion of

precipitation that contributes to streamflow/water yield

8.4. Parkhill Creek


The Parkhill Creek subwatershed is dominated by rural and agricultural land use.

Surface water features in this subwatershed are predominantly the tributaries of the

Upper Parkhill Creek and wetlands, with very few open water lakes/ponds aside from

the reservoir at the southern extent of the subwatershed. The spatial extent of the

120 m buffer around surface water features (lakes, streams, wetlands, etc.) is

3,926 ha, encompassing 31% of the subwatershed (Figure 34). There is relatively

little spatial extent of SGRAs within this subwatershed. They cover 8% of the

subwatershed, however, since these areas are small but numerous, the 120 m buffer

surrounding these features cover 4,473 ha (35%) of the subwatershed. Together,

6,168 ha, or 49% of the subwatershed is within 120 m of these key hydrologic

features and would require comprehensive feature-based water budget analysis for

any land use change.

There are 1,690 ha of forest within the Parkhill Creek subwatershed, covering just

13% of the landscape. This would be assigned a grading of “D”, following the

Conservation Ontario (2011) guidelines.

y = 0.232xR² = 0.9892

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Figure 34: Surface water features and their 120 m buffer of the Parkhill Creek

subwatershed.



within the Parkhill Creek subwatershed.


Figure 36: Forest cover within the Parkhill Creek subwatershed.


Figure 37: Impermeable land within the Parkhill Creek subwatershed.

There is very little impermeable area associated with residential communities within

this subwatershed, encompassing just 42 ha (0.3% of the subwatershed). There are


125.9 km of roads within this subwatershed. When combined, the total impermeable

area of the Parkhill Creek subwatershed is 168 ha (1.3%). This would be graded as

“Good” following the SOLEC (EC & U.S. EPA, 2009) guidelines.



Groundwater levels are generally lowest in the late summer/ autumn, and highest in

the winter, however this is variable between years. Water table has had a maximum

range of 2.5 m since records began in 2003, though most years are within a 1 m

range. Minimum and maximum water levels were recorded in early and late 2007,

respectively. Based on annual average water levels, 2004 and 2009 were the wettest

years and 2005, 2008 and 2010 were the driest years (however, data was missing

for 2003, 2006, 2013, and 2014).

Maximum hydrologic release has been associated with both spring freshet and

summer storm events, and lowest hydrologic release often occurs in the winter, with

multiple consecutive days of no hydrologic release. Maximum streamflow is often

associated with the spring freshet, and lowest in the summer. Annual maximum

streamflow is often between 20 and 30 m3/s, however, extreme events have had

daily discharge rates > 40 m3/s. Annual low flow is < 0.1 m3/s.

Results of the Mann-Kendall trend test (Table 37) indicate that there were only 4

parameters that have very certain temporal trends, all of which were increasing: 7d

MIN T JAS, PET, 3d MAX Q OND and 3d MAX BF OND DOY. Due to the methods used

to determine PET, an increase in summer minimum temperature would likely be

associated with increasing PET, as indicated here. While baseflow is used in this report

as a groundwater indicator, it should be noted that no temporal trend in groundwater

observations was reported (data was sufficient for testing). Therefore, there may be

other driving factors within this subwatershed.

Table 37: Results of Mann-Kendall trend tests for the Parkhill Creek subwatershed,

where probably trending (PT) indicates p-value < 0.05 (light shading) and very

confident (VC) indicates p-value < 0.025 (dark shading).


Result τ p-value

Climate

Mean T 0.26 0.026 Increasing, PT



30d MIN R JAS DOY 0.257 0.029 Increasing, PT

Surface water 3d MAX Q OND DOY 0.346 0.004 Increasing, VC

7d MIN Q -0.292 0.028 Decreasing, PT



Result τ p-value

Groundwater

BF yield -0.244 0.044 Decreasing, PT

BF yield OND -0.255 0.035 Decreasing, PT

3d MAX BF OND DOY 0.306 0.013 Increasing, VC

7d MIN BF -0.287 0.030 Decreasing, PT

7d MIN BF OND DOY -0.286 0.032 Decreasing, PT


Only the parameters that were determined to have strong correlation are displayed

in Table 38 through Table 42 below. (All three correlations coefficients are >|0.5|

and have a p-value <0.05.) Additional results are available in 0.

There is insufficient data to conduct correlation analysis for this subwatershed at the

annual timescale between streamflow and groundwater level data (8 years of

corresponding observations), and insufficient seasonal data for statistical analyses

for summer (JAS) and autumn (OND) periods with 9 and 4 observations respectively.

These seasonal observations are impacted most by slow recharge rates after pumping

and sampling that occurs annually in September/October. Annual data was retained

only when data gaps were 1-2 weeks that corresponded to sampling drawdown and

rebound. Any correlations involving groundwater data (levels or timing) were found

to only be correlated with other groundwater indicators, and not to surface water

indicators or climate variables. This could be the result of the clay/silt substrate in

which this well is installed.

Total hydrological release (R, i.e., total precipitation during the growing season) was

found to be correlated with water yield, streamflow, and baseflow through the year,

further supporting the above finding that baseflow in this subwatershed may be less

correlated with groundwater levels and more with climate and surface water

hydrology. Numerous correlations were found between water yield and streamflow

indicators and the corresponding baseflow indicators, with the most correlations

occurring during the summer period and least during the winter/spring period.

Table 38: Correlation between annual parameters of the Parkhill Creek

subwatershed.




value τ p-

value R² p-

value slope sign

Mean T PET 0.89 0.00 0.71 0.00 0.74 0.00 +

Total P P-PET 0.96 0.00 0.84 0.00 0.95 0.00 +





value τ p-

value R² p-

value slope sign


P-PET Water yield 0.85 0.00 0.72 0.00 0.74 0.00 +




BF yield 3d MAX BF 0.75 0.00 0.58 0.00 0.58 0.00 +

7d MIN Q 7d MIN BF 1 0.00 0.98 0.00 0.91 0.00 +

7d MIN Q DOY 7d MIN BF DOY 1 0.00 0.98 0.00 1.00 0.00 +

Table 39: Correlation between winter seasonal parameters of the Parkhill Creek

subwatershed.


Rank Kendall's



value τ p-

value R² p-

value slope sign

BF yield 3d MAX BF 0.7 0.00 0.54 0.00 0.74 0.00 +

7d MIN Q 7d MIN BF 0.99 0.00 0.92 0.00 0.94 0.00 +


W285 3d MAX GW W285 3d MAX GW DOY -0.91 0.00 -0.81 0.00 0.78 0.00 -

W285 3d MAX GW W285 7d MIN GW 0.97 0.00 0.89 0.00 0.88 0.00 +

W285 3d MAX GW DOY W285 7d MIN GW -0.9 0.00 -0.77 0.01 0.62 0.00 -

Table 40: Correlation between winter seasonal parameters of the Parkhill Creek

subwatershed.


Rank Kendall's



value τ p-

value R² p-

value slope sign

Total R 3d MAX R 0.84 0.00 0.66 0.00 0.70 0.00 +



7d MIN Q 7d MIN BF 0.94 0.00 0.8 0.00 0.86 0.00 +

W285 3d MAX GW W285 3d MAX GW DOY -0.83 0.00 -0.66 0.01 0.87 0.00 -

W285 3d MAX GW W285 7d MIN GW 0.74 0.00 0.56 0.04 0.64 0.00 +

W285 3d MAX GW W285 7d MIN GW DOY 0.83 0.00 0.7 0.00 0.80 0.00 +

W285 3d MAX GW DOY W285 7d MIN GW -0.86 0.00 -0.66 0.01 0.58 0.00 -

W285 3d MAX GW DOY W285 7d MIN GW DOY -0.84 0.00 -0.69 0.01 0.77 0.00 -


Table 41: Correlation between summer seasonal parameters of the Parkhill Creek

subwatershed.

Summer (JAS) Spearman's



value τ p-

value R² p-

value slope sign


Total R 3d MAX Q 0.69 0.00 0.51 0.00 0.67 0.00 +

Total R 7d MIN BF 0.72 0.00 0.56 0.00 0.50 0.00 +






BF yield 3d MAX Q 0.85 0.00 0.68 0.00 0.63 0.00 +

BF yield 7d MIN Q 0.72 0.00 0.58 0.00 0.65 0.00 +

BF yield 3d MAX BF 0.88 0.00 0.7 0.00 0.71 0.00 +

BF yield 7d MIN BF 0.72 0.00 0.57 0.00 0.58 0.00 +

3d MAX Q 7d MIN Q 0.67 0.00 0.51 0.00 0.58 0.00 +

3d MAX Q 7d MIN BF 0.65 0.00 0.52 0.00 0.68 0.00 +

7d MIN Q 7d MIN BF 1.00 0.00 0.98 0.00 0.91 0.00 +


Table 42: Correlation between autumn seasonal parameters of the Parkhill Creek

subwatershed.




value τ p-

value R² p-

value slope sign





BF yield 3d MAX BF 0.9 0.00 0.74 0.00 0.76 0.00 +

7d MIN Q 7d MIN BF 0.99 0.00 0.92 0.00 0.82 0.00 +



8.4.2.3. Double Mass-Balance

The relationship between annual cumulative baseflow yield to annual cumulative

water yield and annual cumulative water yield to annual cumulative precipitation

(Figure 38 and Figure 40) have strong relationships, and this is generally mirrored in

the seasonal analyses (where precipitation is replaced with hydrologic release).

Annually, baseflow yield is representative of 22% of water yield for the Parkhill Creek

subwatershed. This ranges from 12% in the summer to 28% in the spring, with

moderate proportions (23% and 20%) in the autumn and winter, respectively. There

is a low proportion of precipitation that contributes to streamflow in the Parkhill Creek

subwatershed, with just 6% annually. This is greatest during the winter (hydrologic

release) where 12% contributes to streamflow, and lowest through the summer,

where only 2% of hydrologic release contributes to streamflow. Spring and autumn

hydrologic release contribute 5 and 8%, respectively, to streamflow.

Generally, the seasonal relationships mirror that of the annual relationships. The only

exception to this is through the summer for both relationships (see Figure 39 for

cumulative baseflow yield to cumulative water yield and Figure 41 for cumulative

water yield to cumulative hydrologic release) which has some notably wet years

(1986, 1990, 1992, and 1996), after which the relationship stabilizes again.

Figure 38: Parkhill Creek cumulative annual baseflow yield to water yield (1981-

2016). Data for 2011-2012 are missing. The equation of the line estimates the

proportion of water yield that is derived from baseflow.

y = 0.216xR² = 0.9924

0

50

100

150

200

250

300

350

400

450

500

0 500 1000 1500 2000 2500

Cu

mu

lati

ve B

asef

low

Yie

ld (

mm

)



Figure 39: Parkhill Creek summer (JAS) cumulative baseflow yield to water yield

(1981-2016). Data for 2011-2012 are missing. The equation of the line indicates the

proportion of streamflow that is derived from baseflow.

Figure 40: Parkhill Creek cumulative water yield to precipitation (1981-2016). Data

for 2011-2012 are missing. The equation of the line estimates the proportion of

precipitation that contributes to streamflow/water yield.

y = 0.1179xR² = 0.9935

0

2

4

6

8

10

12

14

16

18

20

0 20 40 60 80 100 120 140 160 180

JAS

Cu

mu

lati

ve B

asef

low

Yie

ld (

mm

)

JAS Cumulative Water Yield (mm)

y = 0.0638xR² = 0.9985

0

500

1000

1500

2000

2500

0 5000 10000 15000 20000 25000 30000 35000 40000

Cu

mu

lati

ve W

ater

Yie

ld (

mm

)



Figure 41: Parkhill Creek summer (JAS) cumulative water yield to precipitation

(1981-2016). Data for 2011-2012 are missing. The equation of the line indicates the

proportion of streamflow that is derived from baseflow.

9. Discussion and Comparison between Subwatersheds

The four pilot subwatersheds that have been used to test this framework vary in their

geography, geology, size, and disturbance. The same methods were applied to each

of these subwatersheds, though not all had the same data sets available. A summary

of the spatial distribution of the thematic mapping analysis is provided in Table 43.

Skootamatta River has the largest (629 km2) and least disturbed (77% forest cover)

subwatershed of this analysis. Due to its geologic situation, this subwatershed has

the least extent of SGRAs (< 2%). The combination of these factors could have a

strong influence on the precipitation (hydrologic release) and streamflow relationship,

which was found to be quite high overall (66% annually), but also being as low as

8% during the summer, when evapotranspiration is greatest, increasing storage

capacity within the landscape.

In contrast, the Parkhill Creek subwatershed is the smallest of those studied

(127 km2), but with similarly low proportion of SGRAs (8%), and much lower surface

water buffer area of 49% (surrounding mostly the stream network), the precipitation

to water yield relationship is remarkably low (6% of annual precipitation). This

indicates that there are other things occurring in this subwatershed, perhaps

significant water taking for agricultural or domestic use. All communities that source

their municipal water from within the Parkhill Creek subwatershed listed above in the

y = 0.0022xR² = 0.9406

0

5

10

15

20

25

0 2000 4000 6000 8000 10000 12000

JAS

Cu

mu

lati

ve s

trea

mfl

ow

(m

m)

JAS Cumulative Hydrologic Release (mm)


subwatershed characterization are located outside the subwatershed, and therefore

this abstracted water is not returned to the subwatershed.

Table 43: Summary of thematic mapping analysis by subwatershed.

Parameter Skootamatta Innisfil Whitemans Parkhill

ha % ha % ha % ha %

Subwatershed area 69201.3 100.0% 49002.8 100.0% 40394.6 100.0% 12665.5 100.0%

SGRA 1103.5 1.6% 18071.7 36.9% 20422.1 50.6% 1003.2 7.9%

SGRA buffer 1691.3 2.4% 24249.4 49.5% 23030.7 57.0% 4473.5 35.3%

Surface water buffer 54745.3 79.1% 25546.6 52.1% 21300.9 52.7% 3926.1 31.0%

Water + SGRA buffer 55816.7 80.7% 36365.8 74.2% 30320.9 75.1% 6168.0 48.7%

Forest cover 53437.9 77.2% 9345.6 19.1% 6913.5 17.1% 1690.4 13.3%

Urban area N/A N/A 1941.1 4.0% 632.2 1.6% 41.8 0.3%

Road length km 253.5 0.4% 660.2 1.3% 574.2 1.4% 125.9 1.0%

Impermeable area N/A N/A 2601.3 5.3% 1206.4 3.0% 167.7 1.3%

The Innisfil Creek and Whitemans Creek subwatersheds are comparable in size

490 km2 and 404 km2, respectively, are both dominated by agricultural activities,

have similar SGRA extent (52 % and 53 %, respectively), and have comparable

proportion of precipitation that directly translates into water yield (19% and 23%,

respectively).

In a comparison of the temporal trends observed at each of the subwatersheds (Table

44), it was found that none of the parameters/indicators were found to be

consistently trending in all four of the subwatersheds. Climate variables (notably

temperature and PET) were found to be trending in three of the four subwatersheds,

with trends in Whitemans Creek matching confidence (very certain) and direction

(increasing) with Skootamatta River when both indicated a trend for the same

parameter. Parkhill Creek similarly agreed in trend direction, but with less confidence

for mean annual temperature. When a climatic trend was detected for the Innisfil

Creek it also was in agreement with the other subwatersheds. It is also notable that

of the trending climate variables, half of those reported in Table 44 are changes in

DOY timing, and half are changes in the reported value of the variable, however,

there was only one occurrence of both the variable and its associated timing both

changing (Skootamatta River 30d MIN R JFM).

Precipitation and hydrologic release variables were each trending in only in one

subwatershed. Similarly, most surface water and groundwater indicators were found

to be trending in only one of the subwatersheds. Similarly to climate, there was only

one occurrence of both hydrologic indicator and associated timing changing

(Skootamatta River for 3d MAX Q JFM). This highlights the necessity to evaluate each


subwatershed individually, rather than assuming that they all experience similar

conditions and will all respond similarly to changes.

Table 44: Summary of Mann-Kendall test results for each subwatershed. Arrows

indicate trend direction accompanied by trending confidence (probably trending, PT

and very certain, VC). Shaded cells indicate insufficient data to perform analysis.

Type Parameter Skootamatta

River Innisfil Creek

Whitemans Creek

Parkhill Creek

Clim

ate

Mean T ↑, VC ↑, VC ↑, PT

7d MAX T DOY ↑, VC ↑, VC ↑, VC

7d MAX T OND DOY ↓, PT

7d MIN T JAS ↑, VC ↑, VC ↑, VC

PET ↑, VC ↑, VC ↑, VC

Total P ↑, VC

Total R OND ↑, PT

3d MAX R AMJ DOY ↓, PT

3d MAX R OND DOY ↑, PT

30d MIN R ↑, VC

30d MIN R DOY ↑, VC

30d MIN R JFM ↑, VC

30d MIN R JFM DOY ↑, VC

30d MIN R AMJ DOY ↓, PT

30d MIN R JAS DOY ↑, PT

30d MIN R OND ↑, PT

Surf

ace

Wat

er

R-B Index ↑, VC

10:90 exceedance ↓, VC

3d MAX Q JFM ↓, PT

3d MAX Q JFM DOY ↓, VC

3d MAX Q OND DOY ↑, VC

7d MIN Q ↑, VC ↓, PT

7d MIN Q JFM DOY ↑, PT

7d MIN Q OND DOY ↓, PT

Gro

un

dw

ate

r

BF yield ↓, PT

BF yield AMJ ↓, PT

BF yield OND ↓, PT

3d MAX BF OND DOY ↑, VC

7d MIN BF ↑, VC ↓, PT

7d MIN GW JAS DOY ↑, PT

7d MIN GW OND DOY ↑, VC ↓, PT


In an inter-subwatershed comparison of the parameters with strong correlations

(Table 45 through

Table 49), detailed in the individual subwatershed analyses above, it was found that

Mean T to PET and Total P to P-PET are the only climate variables with correlations

at all of the subwatersheds. Since temperature was used to calculate PET and

precipitation for moisture deficit (P-PET), it should be expected that there is

correlation here. Total P and Total R (seasonal analyses) was found to be correlated

with water yield at three of the subwatersheds for both the annual and spring

analyses.

Table 45: Comparison of correlated annual parameters. Shading indicates insufficient

data to conduct analysis.

Annual

Parameter 1

Annual

Parameter 2

Skootamatta

River

Innisfil

Creek

Whitemans

Creek

Parkhill

Creek

Mean T PET + + + +

Min T DOY 7d MIN GW -

Total P P-PET + + + +

Total P Water yield + + +

Total P 3d MAX Q +

P-PET Water yield + + +

P-PET 3d MAX Q +

P-PET BF Yield +

P-PET 7d MIN GW DOY -

10:90 exceed 7d MIN Q - -

10:90 exceed 7d MIN BF - -

Water yield BF yield + + +

Water yield 3d MAX Q + +

Water yield 7d MIN Q +

Water yield 7d MIN BF +

3d MAX Q 3d MAX GW +

7d MIN Q 7d MIN BF + + + +

7d MIN Q DOY 7d MIN BF DOY + + + +

BF yield 3d MAX BF +

Mean GW 3d MAX GW +

Mean GW 7d MIN GW + +

There were 12 occurrences of three subwatersheds having the same correlation in

either annual or seasonal analyses. In each of these instances, Innisfil Creek was

always one of the subwatersheds with correlations. Four of these are between

Skootamatta River, Innisfil Creek, and Whitemans Creek: winter BF yield to 7d MIN

Q, spring 7d MIN Q DOY to 7d MIN BF DOY, summer 7d MIN Q to 7d MIN BF, and

autumn BF yield to 3d MAX Q. Another four of these are between Skootamatta River,


Innisfil Creek, and Parkhill Creek: annual water yield to baseflow yield, summer water

yield to 7d MIN Q, summer water yield to 7d MIN BF, and summer baseflow yield to

7d MIN Q. The final four are between Innisfil Creek, Whitemans Creek, and Parkhill

Creek: annual Total P to water yield, annual P-PET to water yield, spring Total R to

water yield, and spring water yield to 3d MAX Q.

Table 46: Comparison of correlated winter parameters. Shading indicates insufficient


Winter (JFM)

Parameter 1

Winter (JFM)

Parameter 2

Skootamatta

River

Innisfil

Creek

Whitemans

Creek

Parkhill

Creek

Total R water yield +

3d MAX R 7d MIN GW DOY -

water yield BF yield + +

water yield 3d MAX Q + +

water yield 7d MIN Q +

Water yield 7d MIN GW DOY -


7d MIN Q DOY 7d MIN BF DOY + +

7d MIN Q 7d MIN GW DOY -

BF yield 7d MIN Q + + +

BF yield 3d MAX BF + +

BF yield 7d MIN BF + +

BF yield 7d MIN GW DOY -

3d MAX BF DOY 3d MAX GW -

7d MIN BF 7d MIN GW DOY -

3d MAX GW 3d MAX GW DOY -

3d MAX GW 7d MIN GW + + +

3d MAX GW DOY 7d MIN GW -

Table 47: Comparison of correlated spring parameters. Shading indicates insufficient


Spring (AMJ)

Parameter 1

Spring (AMJ)

Parameter 2

Skootamatta

River

Innisfil

Creek

Whitemans

Creek

Parkhill

Creek

Total R 3d MAX R +

Total R water yield + + +

Total R 7d MIN Q +

Total R 7d MIN BF +

water yield 3d MAX Q + + +

Water yield BF yield + +

Water yield 3d MAX GW +




Spring (AMJ)

Parameter 1

Spring (AMJ)

Parameter 2

Skootamatta

River

Innisfil

Creek

Whitemans

Creek

Parkhill

Creek

7d MIN Q DOY 7d MIN BF DOY + + +

BF yield 3d MAX BF + +

3d MAX GW 3d MAX GW DOY -

3d MAX GW 7d MIN GW +

3d MAX GW 7d MIN GW DOY +

3d MAX GW DOY 7d MIN GW -

3d MAX GW DOY 7d MIN GW DOY -

Table 48: Comparison of correlated summer parameters. Shading indicates

insufficient data to conduct analysis.

Summer (JAS)

Parameter 1

Summer (JAS)

Parameter 2

Skootamatta

River

Innisfil

Creek

Whitemans

Creek

Parkhill

Creek

Total R Water yield +

Total R 3d MAX Q +

Total R 7d MIN BF +

30d MIN release 7d MIN GW +

Water yield BF yield + + + +

Water yield 3d MAX Q + + + +

Water yield 7d MIN Q + + +

Water yield 3d MAX BF + + + +

Water yield 7d MIN BF + + +

Water yield 7d MIN GW +

3d MAX Q 7d MIN Q + +

3d MAX Q 3d MAX BF +

3d MAX Q 7d MIN BF + +

3d MAX Q DOY 3d MAX GW -

7d MIN Q 3d MAX BF + +

7d MIN Q 7d MIN BF + + +

7d MIN Q 7d MIN GW +

7d MIN Q DOY 7d MIN BF DOY + + + +

BF yield 3d MAX Q + + + +

BF yield 7d MIN Q + + +

BF yield 3d MAX BF + + + +

BF yield 7d MIN BF + + + +

BF yield 7d MIN GW +

3d MAX BF 7d MIN BF +

7d MIN BF 7d MIN GW +

3d MAX GW 7d MIN GW +


Table 49: Comparison of correlated autumn parameters. Shading indicates

insufficient data to conduct analysis.

Autumn (OND)

Parameter 1

Autumn (OND)

Parameter 2

Skootamatta

River

Innisfil

Creek

Whitemans

Creek

Parkhill

Creek

Total R water yield +

Total R 7d MIN GW DOY -

3d MAX R 3d MAX Q +

7d MIN R 3d MAX GW DOY +

Water yield BF yield + + + +

Water yield 3d MAX Q + + + +

Water yield 7d MIN Q +

Water yield 3d MAX BF + + + +

Water yield 7d MIN BF +

Water yield 3d MAX GW +

3d MAX Q 3d MAX BF + +


3d MAX Q DOY 3d MAX BF DOY +


7d MIN Q 7d MIN GW +

7d MIN Q DOY 7d MIN BF DOY + +

BF yield 3d MAX Q + + +

BF yield 7d MIN Q +

BF yield 3d MAX BF + + + +

BF yield 7d MIN BF + +

BF yield 3d MAX GW +

7d MIN BF 3d MAX GW +

7d MIN BF 7d MIN GW +

3d MAX GW 7d MIN GW + +

3d MAX GW DOY 7d MIN GW DOY -

Overall, these results highlight that while there are similarities between the

parameters tested in each of these subwatersheds, there are also numerous

differences in both temporal trends and correlation between the tested variables and

indicators. It should therefore not be assumed that the relationships between climate

and hydrological processes, hydrologic function, will be the same in all

watersheds/subwatersheds. These relationships will need to be characterized for

each subwatershed in order to assess hydrologic functions and whether they are

being maintained, improved, and restored.


10. Conclusions and Recommendations

As a specific policy direction in the PPS since 2005, hydrologic function is defined in

the provincial land use plans and by the PPS, 2014 as:

the functions of the hydrological cycle that include the occurrence, circulation, distribution, and chemical and physical properties of water on the surface of

the land, in the soil and underlying rocks, and in the atmosphere, and water’s interaction with the environment including its relation to living things.

Further, the PPS, 2014 and other provincial land use plans state that the hydrologic function, particularly of sensitive hydrologic features must be protected, improved,

and restored within or near sensitive hydrologic features. Further, “key hydrologic features” are generally defined or described in the plans to include permanent

streams, intermittent streams, kettle and inland lakes and their littoral zones, seepage areas and springs, and wetlands.






The contents and findings of this report support the implementation of provincial

policy by proposing the establishment of an evidence-based approach to the

evaluation of hydrologic function. This report 1) proposes a scale-based framework

approach to evaluate hydrologic function including baseline indicators and 2) applies

a regional baseline characterization approach to 4 southern Ontario subwatersheds:

Skootamatta River, Innisfil Creek, Whitemans Creek, and Parkhill Creek to evaluate

applicability, and lessons learned.

The proposed hydrologic function assessment is recommended to be completed at

two scales: local/site alteration scale and the broader regional/subwatershed scale.

This spatial-scale approach is based on the premise that if the local hydrologic

function is maintained where development (e.g., a subdivision, commercial

development, etc.) occurs, then the baseline regional/subwatershed relationship

between groundwater and surface water conditions should also be maintained;

excluding climatic alterations.

The local or site alteration scale assessment identifies local hydrologic features and

functions (e.g., surface water features, SGRAs, etc.) and their associated connectivity

with an associated buffer to the parcel. This local scale evaluation is complimented

by either a Thornthwaite-Mather water balance where no key hydrologic features are

mapped or a feature-based water balance within the mapped buffers of key

hydrologic features and functions are mapped or observed. The water balance


exercise calculates the independently the pre- and post-development recharge rates,

surface water discharge, etc. In order to maintain pre-alteration hydrologic function

following development, the hydrologic components, notably infiltration/recharge

rates need to be maintained.

Thematic and temporal characterization at the subwatershed scale compliments the

local scale evaluation by providing baseline information on land use (thematic)

delineation and groundwater and surface water trends and relationships (time series

and statistical relationships) to which the local scale information can be periodically

assessed against. The thematic land use information consists of significant

groundwater recharge area, surface water features, percent impervious surface, and

forest cover. See Table 50 for the recommended climate variables and surface water

and groundwater indicators. The subwatershed baseline characterization is

fundamentally based on the evaluation of key, time series hydrologic datasets:

climate, surface water flow, and groundwater. For future analysis, at a minimum, one

climate, stream gauge, and groundwater monitoring well is recommended to

undertake this analysis, generalized for subwatersheds less than 500 km2.

A comprehensive evaluation of the subwatershed baseline characterization approach

was completed for four subwatersheds in southern Ontario: Skootamatta River,

Innisfil Creek, Whitemans Creek, and Parkhill Creek. The thematic mapping is

comprised of SGRAs, surface water features, forest cover, and percent impervious

area, using provincially available datasets. To complement the thematic mapping but

not presently readily available, ecologically significant groundwater recharge areas

(ESGRAs) are encouraged to be delineated. The ESGRAs maps the spatial recharge

area extent to groundwater-dependent hydrologic features, allowing for the

protection of the hydrologic function. Further it is envisioned that ESGRA mapping

would complement the SGRA mapping; collectively highlighting where hydrologically-

important recharge areas, whether they discharge to sensitive hydrologic features

(i.e., ESGRAs), or whether they contribute greater volumes of groundwater recharge

to local aquifers (i.e., SGRAs). Further, to streamline the thematic mapping process,

percent forest cover could be obtained through the Watershed Report Card processes,

where available.

The subwatershed baseline characterization analysis, completed on a 10 year

interval, requires a minimum of >10 years of data with >90% completeness at the

monthly interval. As related to the four targeted subwatersheds, major challenges

were identified related to the availability and record length for groundwater e.g. the

use of partial groundwater datasets to unable being groundwater completed (e.g.

Whitemans Creek). It is noted that other ambient/baseline monitoring wells (e.g.,

conservation authority or municipality) could be used, preferably screen in an

unconfined system to assess the impacts of local changes and provided that there is

a minimum 10-year record length with complete dataset. In addition, many climate

stations with long-term data sets are no longer active although gaps in climate data


were filled based on nearby climate station data. Regarding surface water data

availability, the Water Survey of Canada stream gauges were principally used;

however, it is recognized that there are ungauged subwatersheds. To remedy this,

additional stream gauge monitoring stations could be used (e.g., conservation

authority, municipality), based on the quality of available data.

Using the hydrologic data (climate, surface water discharge, and groundwater levels),

a statistical analysis was completed to: 1) assess potential observable temporal

trends through the study period (1981-2016), 2) evaluate the relationship between

hydrologic components, and 3) highlight the relationship and changes in relationship

of a) streamflow as a function of precipitation and b) baseflow as a function of

streamflow in each of the pilot subwatersheds. Determination of time series trends

was statistically evaluated using annual and seasonal data for: 1) time series trends

using the Mann-Kendall trend test (McLeod, 2011), 2) correlation through the

Kendall’s rank (tau, 𝜏; Revelle, 2017), Spearman’s rank (rho, 𝜌; Revelle, 2017), and

3) linear regression, using least squares (𝑅2). All correlations identified through the

Spearman’s Rank were also identified by Kendall’s Rank, but the latter indicated

additional correlations that Spearman’s did not; supporting the use of Spearman’s

Rank and linear regression for future analysis. Linear regression analysis, conducted

in ‘R’, was tested when the Spearman’s Rank and Kendall’s Rank tests both indicated

a strong correlation. It cannot therefore be determined whether there would have

been numerous occasions where linear regression corresponded with only one but

not both of the other correlation analyses. Lastly, double-mass balance analysis was

conducted to highlight a change in the relationship between two variables.

A total of 121 combined hydrologic parameters were analyzed per subwatershed: 29

annual time scale parameters and 23 seasonal time scale parameters completed four

times. The parameters include both climate variables and hydrologic indicators. In

order to make the analysis more manageable at 79 distinct parameters (Table 51),

the following salient points were observed through the analysis of the four

subwatersheds:

Streamline the temperature analysis to 21 variables (annual mean, 7d MAX

and 7d MIN and associated DOY both annually and seasonally [4x]) to 5

(annual and seasonal [4x] mean) since multi-day averaged extreme (i.e.,

maximum and minimum) temperature data was not found to have strong

correlations with the other hydrologic parameters.

Baseflow indicators (yield, multi-day extremes, and timing) were often

correlated exclusively with streamflow indicators (water yield, multi-day

extremes, and timing). For future applications, seasonal and annual baseflow

yield should be used only in the double mass balance portion of analysis.

Seasonal analyses must be retained to ensure that the seasonal extremes of

hydrologic function (e.g., winter/spring freshet and summer drying) are being


protected, and not simply maintaining an annual average, while changing the

range of conditions through the year.

Table 50: Summary of variables and indicators recommended for statistical analysis.

Type Variable /Indicator Metric Time period

Climate

Variable

Temperature Average Annual, seasonal

Potential

Evapotranspiration

Total Annual

Precipitation Total Annual

Hydrologic release Total Seasonal


3-day max DOY Annual, seasonal


30-day min DOY Annual, seasonal

Climate Moisture

Index

P-PET Annual

Surface

water

Indicator

Water yield Total Annual, seasonal

Flashiness Richards-Baker

Flashiness Index

Annual

Extreme flows <10th: >90th

exceedance percentile

Annual

Surface water

discharge





Groundwater

Indicator

Baseflow yield2 Total Annual, seasonal

Groundwater level 3-day max Annual, seasonal




Lessons learned from the application of the subwatershed baseline characterization

to four subwatersheds in southern Ontario are as follows:

Using baseflow as derived from streamflow may not be the most useful indicator especially when compared to streamflow as indicator

2To be used for double mass balance analysis only; omitted from Spearman’s Rank and Linear Regression analysis


Finding reliable climate stations with full datasets is easier than manually filling whole datasets

Meeting minimum data requirements (e.g., groundwater 10-year dataset

for GW) is important to facilitate comparisons

Geologic setting of groundwater station is important – e.g., the lag in

rebounding after Parkhill sampling impacts seasonal and annual analysis –

GW sites that have such known ‘challenges’ should restrict sampling to

October to avoid needing to omit data from JAS and OND analysis.

Further, for future application, the subwatershed baseline characterization is most

applicable in southern Ontario, due primarily to data availability both thematically

and temporally. Due to the requirement for a minimum of 10 years of data for

statistical comparisons, it is recommended to conduct such analyses in 10-year

intervals to further facilitate time series comparison. The 10-year interval aligns with

the Conservation Authority Watershed Report Cards which are issued on a five year

cycle. The site-specific local scale evaluation is on-going and driven based on

proposed development (e.g., proposed subdivision application) would be based on

the locally identified hydrologic features e.g. lakes, rivers, streams, (etc.) and other

types of surface water features (i.e., wetlands, groundwater discharge areas, etc.).

It is recommended that the local planning authority map the development locations

on an annual basis.

Overall conclusions from the regional/subwatershed-scale thematic mapping and

time series analyses are as follows:

The spatial distribution of SGRAs and hydrologic features strongly influences

the hydrologic response and therefore function of the subwatershed

The climate input variables that detected temporal trends were primarily temperature-related for most subwatersheds, though precipitation/hydrologic

release trends were observed in one of them

Each subwatershed had parameters with temporal trends and correlations,

however, there was no single parameter that was found to be trending nor pair of parameters that have strong correlations at all four pilot subwatersheds

Temporal trends and statistical correlations detected at one temporal scale

(e.g., annual) do not necessarily correspond to trends and correlations at the other (e.g., seasonal) within the same subwatershed

Each subwatershed will respond differently annually and seasonally, based on

the hydrologic features and land use, therefore it is important to conduct this

analysis of hydrologic function for all subwatersheds


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Appendix A. Key Parameter Codes and Associated Definitions

Parameter

Code

Definition

Mean T Mean annual temperature(°C)

7d MAX T Maximum of 7-day averaged temperature (°C)

7d MIN T Minimum of 7-day averaged temperature(°C)

Total P Total annual precipitation (mm)

Total R Seasonal total hydrologic release (mm)

3d MAX R Maximum of 3-day total hydrologic release (mm)

30d MIN R Minimum of 30-day total hydrologic release (mm)

PET Annual potential evapotranspiration (mm)

P-PET (CMI) Climate moisture index (precipitation minus potential

evapotranspiration; mm)

RBI Richards-Baker Flashiness Index

10:90 exceed 10:90 exceedance percentile ratio

Water yield Water yield of streamflow (mm)

3d MAX Q Maximum of 3-day averaged streamflow discharge (m3/s)

7d MIN Q Minimum of 7-day averaged streamflow discharge (m3/s)

BF yield Water yield of baseflow (mm)

3d MAX BF Maximum of 3-day averaged baseflow discharge (m3/s)

7d MIN BF Minimum of 7-day averaged baseflow discharge (m3/s)

Mean GW Mean annual groundwater elevation (masl)

3d MAX GW Maximum of 3-day averaged groundwater elevation (masl)

7d MIN GW Minimum of 7-day averaged groundwater elevation (masl)

-DOY Suffix: day of year timing

-JFM Suffix: winter seasonal analysis (January, February, March)

-AMJ Suffix: spring seasonal analysis (April, May, June)

-JAS Suffix: summer seasonal analysis (July, August, September)

-OND Suffix: autumn seasonal analysis (October, November,

December)


Appendix B. Climate Filling Data Adjustment Values

Subwatershed Station Name and ID3 Station

Type Distance

(km) Location

Elevation (m)

Data end4

Normal annual T (°C)

Normal annual P (mm)

T adjustment

(°C)

P adjustment

Skootamatta River

Kaladar5 6153935

Target 0.00 km 44°38'52.000" N 77°07'02.040" W

215 m Dec-15 6.7 926.1 0.00 1.00

Centreville 6151309

Filling 31.72 km 44°24'12.090" N 76°54'28.092" W

150 m

7.0 695.6 -0.31 1.33

Hartington

IHD6103367

Filling 41.36 km 44°25'41.028" N 76°41'25.086" W

160 m

7.0 977.7 -0.31 0.95

Innisfil Creek Egbert Care 611KBE0

Target 0.00 km 44°14'00.000" N 79°47'00.000" W

252 m Apr-07 7.0 789.1 0.00 1.00

Egbert CS6 611E001

Filling 0.00 km 44°14'00.000" N 79°47'00.000" W

251 m

0.00 1.00

Cookstown 6111859

Filling 7.50 km 44°12'24.042" N 79°41'41.088" W

244 m Apr-07 6.5 826.3 0.50 0.95

Alliston Nelson 6110218

Filling 11.43 km 44°09'05.028" N 79°52'20.088" W

221 m Jan-08 7.7 834.4 -0.70 0.95

Barrie WPCC 6110557

Filling 17.43 km 44°22'33.012" N 79°41'23.010" W

221 m Jun-09 6.9 932.9 0.10 0.85

Shanty Bay 6117684

Filling 21.87 km 44°23'58.050" N 79°37'58.074" W

250 m

6.8 967.9 0.20 0.82

Orangeville MOE7 6155790

Filling 42.16 km 43°55'06.066" N 80°05'11.064" W

412 m Dec-15 6.3 901.5 0.70 0.88

3Stations grouped by target stations and contributing filling stations, arranged by distance to target station. 4No listed end date indicates station remains active. 51981-2010 climate normal data not published for this station. Values presented here were calculated using annual data. Station meets the United Nation's World Meteorological Organization (WMO) standards (missing no more than 3 consecutive and no more than 5 total observations for either temperature or precipitation). 6 Climate normal data assumed to be the same as Egbert Care. 7Used for climate filling only when this station reported daily values.



Type Distance

(km) Location

Elevation (m)

Data end4



T adjustment

(°C)

P adjustment

Orangeville MOE 6155790

Target 0.00 km 43°55'06.066" N 80°05'11.064" W

412 m Dec-15 6.3 901.5 0.00 1.00

Fergus Shand Dam 6142400

Filling 27.76 km 43°44'05.088" N 80°19'49.098" W

418 m

6.7 945.7 -0.40 0.95

Parkhill Creek Exeter 6122370

Target 0.00 km 43°21'00.000" N 81°30'00.000" W

262 m Apr-08 7.9 998.2 0.00 1.00

Thedford7 612HKLR

Filling 33.39 km 43°10'32.016" N 81°51'21.012" W

200 m Jan-14 8.5 963.3 -0.60 1.04

Stratford WWTP 6148105

Filling 37.97 km 43°22'08.016" N 81°00'17.058" W

345 m Oct-16 7.4 1069.6 0.50 0.93

Blyth 6120819

Filling 41.89 km 43°43'06.024" N 81°23'01.080" W

351 m Jan-10 7.2 1246.9 0.70 0.80

London Int'l Airport8 6144475

Filling 44.14 km 43°01'59.000" N 81°09'04.000" W

278 m Apr-17 7.9 1011.5 0.00 0.99

London A9 6144473

Filling 44.14 km 43°01'59.000" N 81°09'04.000" W

278 m

0.00 0.99

Strathroy-Mullifarry10 6148122

Filling 42.46 km 42°58'50.022" N 81°38'34.086" W

243 m

-0.50 1.03

Strathroy 6148120

Filling 45.89 km 42°57'00.000"N 81°39'00.000" W

229 m Jun-96 8.4 966.9 -0.50 1.03

Thedford 612HKLR

Target 0.00 km 43°10'32.016" N 81°51'21.012" W

200 m Jan-14 8.5 963.3 0.00 1.00

Strathroy-Mullifarry11 6148122

Filling 27.06 km 42°58'50.022" N 81°38'34.086" W

243 m

0.10 1.00

Strathroy 6148120

Filling 28.48 km 42°57'00.000" N 81°39'00.000" W

229 m Jun-96 8.4 966.9 0.10 1.00


Filling 55.98 km 43°01'59.000" N 81°09'04.000" W

278 m Apr-17 7.9 1011.5 0.60 0.95

8Precipitation data only. 9 Temperature data only; assumed this station contributed temperature data for London Int’l Airport’s published climate normal data. 10 Assumed Strathroy published climate normal data would be representative (3.4 km away).



Type Distance

(km) Location

Elevation (m)

Data end4



T adjustment

(°C)

P adjustment

London A9 6144473

Filling 55.98 km 43°01'59.000" N 81°09'04.000" W

278 m

0.60 0.95

St Thomas WPCP 6137362

Filling 67.03 km 42°46'06.006" N 81°12'18.042" W

209 m

8.7 993.0 -0.20 0.97


Filling 68.50 km 43°22'08.016" N 81°00'17.058" W

345 m Oct-16 7.4 1069.6 1.10 0.90

Whitemans Creek

Roseville 6147188

Target 0.00 km 43°21'13.026" N 80°28'25.056" W

328 m Sep-17 7.3 918.7 0.00 1.00

Waterloo Wellington A 6149387

Filling 12.75 km 43°27'00.000" N 80°23'00.000" W

317 m Oct-02 7.0 916.5 0.30 1.00

Waterloo Wellington 211 6149389

Filling 12.75 km 43°27'00.000" N 80°23'00.000" W

314 m

0.30 1.00

Brantford MOE 6140954

Filling 30.59 km 43°08'00.000" N 80°14'00.000" W

196 m Jan-13 8.1 867.3 -0.80 1.06

Woodstock 6149625

Filling 33.14 km 43°08'10.044" N 80°46'14.040" W

282 m

7.8 969.0 -0.50 0.95

Millgrove 6155183

Filling 39.01 km 43°19'00.000" N 79°58'00.000" W

255 m Apr-06 7.9 1004.5 -0.60 0.91


Filling 40.69 km 43°22'08.016" N 81°00'17.058" W

345 m Oct-16 7.4 1069.6 -0.10 0.86

Glen Allan 6142803

Filling 40.95 km 43°41'02.058" N 80°42'37.086" W

400 m Dec-13 6.7 1014.5 0.60 0.91

Fergus Shand Dam 6142400

Filling 43.75 km 43°44'05.088" N 80°19'49.098" W

418 m

6.7 945.7 0.60 0.97

Foldens 6142420

Target 0.00 km 43°01'06.078" N 80°46'51.036" W

328 m Jun-16 8.0 953.8 0.00 1.00

Woodstock 6149625

Filling 13.11 km 43°08'10.044" N 80°46'14.040" W

282 m

7.8 969.0 0.20 0.98

11Waterloo Wellington A station appears to have been replaced by Waterloo Wellington 2. Assumed published climate normal data from Waterloo Wellington A would be representative.



Type Distance

(km) Location

Elevation (m)

Data end4



T adjustment

(°C)

P adjustment

Culloden Easey 6141933

Filling 15.17 km 42°53'22.040" N 80°50'48.060" W

280 m Dec-07 8.0 1045.7 0.00 0.91


Filling 28.22 km 43°01'59.000" N 81°09'04.000" W

278 m Apr-17 7.9 1011.5 0.10 0.94

London A9 6144473

Filling 28.22 km 43°01'59.000" N 81°09'04.000" W

278 m

0.10 0.94

St Thomas WPCP 6137362

Filling 42.52 km 42°46'06.006" N 81°12'18.042" W

209 m

8.7 993.0 -0.70 0.96


Filling 42.53 km 43°22'08.016" N 81°00'17.058" W

345 m Oct-16 7.4 1069.6 0.60 0.89

Brantford MOE 6140954

Filling 43.60 km 43°08'00.000" N 80°14'00.000" W

196 m Jan-13 8.1 867.3 -0.10 1.10

Roseville7 6147188

Filling 44.01 km 43°21'13.026" N 80°28'25.056" W

328 m Sep-17 7.3 918.7 0.70 1.04

Hamilton A12 6153193

Filling 66.70 km 43°10'25.000" N 79°56'06.000" W

238 m

0.10 1.03

Hamilton A 6153194

Filling 66.71 km 43°10'18.072" N 79°56'03.036" W

238 m Dec-11 7.9 929.8 0.10 1.03

12Hamilton A* was replaced in 2011 with a second station “Hamilton A”. Both stations have the same WMO ID 71263. It was assumed the published climate normal data would be representative.


Appendix C. Climate Filling Sample Calculation

There is a gap in the data record for the Exeter climate station for December 2 and

3, 2007. Using the information of in 0, Thedford is the closest station to be used for

filling, followed by Stratford WWTP. Neither of these stations have temperature nor

precipitation data available for December 2, 2007, so data from the Blyth station was

used for filling. Thedford reported data for December 3, 2007 and was used for the

second day of missing data.

Climate normal data for the stations is compared in 0 using the following

calculations to determine temperature and precipitation adjustments:

𝑇 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡 = 𝑇𝑎𝑟𝑔𝑒𝑡 𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑚𝑒𝑎𝑛 𝑎𝑛𝑛𝑢𝑎𝑙 𝑇 − 𝐹𝑖𝑙𝑙𝑖𝑛𝑔 𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑚𝑒𝑎𝑛 𝑎𝑛𝑛𝑢𝑎𝑙 𝑇

𝑃 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡 =𝑇𝑎𝑟𝑔𝑒𝑡 𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑡𝑜𝑡𝑎𝑙 𝑎𝑛𝑛𝑢𝑎𝑙 𝑃

𝐹𝑖𝑙𝑙𝑖𝑛𝑔 𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑡𝑜𝑡𝑎𝑙 𝑎𝑛𝑛𝑢𝑎𝑙 𝑃

These adjustment values are then added to or multiplied by the daily temperature

and precipitation data, respectively, from the filling stations to estimate the target

station daily weather. The 1981-2010 climate normal data and adjustment values for

all stations are provided in 0.

Calculations for filling December 2, 2007 are as follows, using filling data from the

Blyth station:

𝑇 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡𝐵𝑙𝑦𝑡ℎ = 7.9 °𝐶 − 7.2 °𝐶 = 0.7 °𝐶

𝑇max (𝐸𝑥𝑒𝑡𝑒𝑟) = 3.0 °𝐶 + 0.7 °𝐶 = 3.7 °𝐶

𝑇min (𝐸𝑥𝑒𝑡𝑒𝑟) = −5.0 °𝐶 + 0.7 °𝐶 = −4.3 °𝐶

𝑇𝑚𝑒𝑎𝑛(𝐸𝑥𝑒𝑡𝑒𝑟) =𝑇𝑚𝑎𝑥 + 𝑇𝑚𝑖𝑛

2=

3.7 °𝐶 + (−4.3 °𝐶)

2= −0.3 °𝐶

𝑃 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡𝐵𝑙𝑦𝑡ℎ =998.2 𝑚𝑚

1246.9 𝑚𝑚= 0.80

𝑃𝐸𝑥𝑒𝑡𝑒𝑟 = 30.5 𝑚𝑚 ∗ 0.80 = 24.4 𝑚𝑚


Calculations for filling December 3, 2007 are as follows, using filling data from the

Thedford station:

𝑇 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡𝑇ℎ𝑒𝑑𝑓𝑜𝑟𝑑 = 7.9 °𝐶 − 8.5 °𝐶 = −0.6 °𝐶

𝑇max (𝐸𝑥𝑒𝑡𝑒𝑟) = 0.0 °𝐶 + (−0.6 °𝐶) = −0.6 °𝐶

𝑇min (𝐸𝑥𝑒𝑡𝑒𝑟) = −3.5 °𝐶 + (−0.6 °𝐶) = −4.1 °𝐶

𝑇𝑚𝑒𝑎𝑛(𝐸𝑥𝑒𝑡𝑒𝑟) =𝑇𝑚𝑎𝑥 + 𝑇𝑚𝑖𝑛

2=

(−0.6 °𝐶) + (−4.1 °𝐶)

2= −2.35 °𝐶

𝑃 𝑎𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡𝑇ℎ𝑒𝑑𝑓𝑜𝑟𝑑 =998.2 𝑚𝑚

963.3 𝑚𝑚= 1.04

𝑃𝐸𝑥𝑒𝑡𝑒𝑟 = 0 𝑚𝑚 ∗ 1.04 = 0 𝑚𝑚

Table B-1 illustrates how these data gaps are filled with an excerpt of data from the

Exeter station.

Table B-1: Sample calculation for filling Exeter climate data gap of December 2-3, 2007

Observation Date T Filling Station P Filling Station Max T Min T Mean T Total P

01-Dec-07 -5.0 -6.5 -5.75 5.0

02-Dec-07 Blyth Blyth 3.7 -4.3 -0.30 24.4

03-Dec-07 Thedford Thedford -0.6 -4.1 -2.35 0.0

04-Dec-07 -4.0 -5.0 -4.50 15.0


Appendix D. Skootamatta River Complete Analysis Results

Table D-1: Results from Mann-Kendall trend analysis for Skootamatta River. Shading

corresponds to confidence levels of very certain (VC), probably trending (PT) and

warning (W).

Parameter tau 2-sided P-value Confidence

Annual Mean T 0.283 0.016 VC

7-day MAX T -0.102 0.391

7-day MAX T DOY 0.383 0.001 VC

7-day MAX T JFM -0.040 0.744

7-day MAX T JFM DOY -0.183 0.132

7-day MAX T AMJ -0.038 0.754

7-day MAX T AMJ DOY 0.000 1.000

7-day MAX T JAS -0.084 0.479

7-day MAX T JAS DOY 0.003 0.989

7-day MAX T OND 0.221 0.060 W

7-day MAX T OND DOY -0.250 0.039 PT

7-day MIN T 0.027 0.827

7-day MIN T DOY 0.110 0.354

7-day MIN T JFM 0.014 0.913

7-day MIN T JFM DOY 0.083 0.487

7-day MIN T AMJ -0.032 0.796

7-day MIN T AMJ DOY -0.163 0.178

7-day MIN T JAS 0.305 0.009 VC

7-day MIN T JAS DOY -0.044 0.730

7-day MIN T OND -0.068 0.567

7-day MIN T OND DOY -0.016 0.902

Annual Total P 0.381 0.001 VC

JFM Total R 0.111 0.347

AMJ Total R 0.159 0.178

JAS Total R 0.038 0.754

OND Total R 0.251 0.032 PT

3-day MAX R -0.121 0.307

3-day MAX R DOY 0.110 0.354

3-day MAX R JFM -0.102 0.391

3-day MAX R JFM DOY -0.175 0.141

3-day MAX R AMJ 0.013 0.924

3-day MAX R AMJ DOY 0.048 0.692



3-day MAX R JAS -0.025 0.838

3-day MAX R JAS DOY 0.107 0.368

3-day MAX R OND 0.206 0.079 W

3-day MAX R OND DOY 0.243 0.040 PT

30-day MIN R 0.363 0.008 VC

30-day MIN R DOY 0.417 0.000 VC

30-day MIN R JFM 0.388 0.005 VC

30-day MIN R JFM DOY 0.416 0.000 VC

30-day MIN R AMJ 0.127 0.282

30-day MIN R AMJ DOY -0.234 0.047 PT

30-day MIN R JAS 0.094 0.429

30-day MIN R JAS DOY 0.110 0.354

30-day MIN R OND 0.238 0.045 PT

30-day MIN R OND DOY 0.095 0.429

Annual PET 0.270 0.021 VC

Annual P-PET 0.267 0.023 VC

Annual Richards-Baker Flashiness Index 0.121 0.307

Annual 10:90 exceedance 0.000 1.000

Annual water yield -0.133 0.268

water yield JFM -0.038 0.754

water yield AMJ -0.127 0.282

water yield JAS -0.057 0.634

water yield OND -0.025 0.842

3-day MAX Q -0.173 0.147

3-day MAX Q DOY 0.189 0.115

3-day MAX Q JFM -0.244 0.037 PT

3-day MAX Q JFM DOY -0.330 0.005 VC

3-day MAX Q AMJ -0.084 0.479

3-day MAX Q AMJ DOY -0.056 0.643

3-day MAX Q JAS -0.037 0.764

3-day MAX Q JAS DOY 0.057 0.648

3-day MAX Q OND -0.042 0.733

3-day MAX Q OND DOY -0.022 0.865

7-day MIN Q -0.022 0.865

7-day MIN Q DOY 0.074 0.541

7-day MIN Q JFM 0.229 0.051 W

7-day MIN Q JFM DOY 0.117 0.326



7-day MIN Q AMJ -0.110 0.354

7-day MIN Q AMJ DOY 0.007 0.967

7-day MIN Q JAS -0.067 0.577

7-day MIN Q JAS DOY -0.058 0.633

7-day MIN Q OND -0.062 0.609

7-day MIN Q OND DOY -0.010 0.943

Annual BF yield -0.143 0.233

BF yield JFM 0.073 0.540

BF yield AMJ -0.244 0.037 PT

BF yield JAS -0.117 0.320

BF yield OND 0.015 0.910

3-day MAX BF -0.124 0.294

3-day MAX BF DOY 0.013 0.924

3-day MAX BF JFM -0.168 0.153

3-day MAX BF JFM DOY 0.190 0.124

3-day MAX BF AMJ -0.165 0.161

3-day MAX BF AMJ DOY 0.002 1.000

3-day MAX BF JAS -0.070 0.558

3-day MAX BF JAS DOY -0.138 0.279

3-day MAX BF OND 0.029 0.817

3-day MAX BF OND DOY 0.141 0.240

7-day MIN BF -0.102 0.391

7-day MIN BF DOY -0.184 0.120

7-day MIN BF JFM 0.210 0.074 W

7-day MIN BF JFM DOY -0.169 0.156

7-day MIN BF AMJ -0.064 0.595

7-day MIN BF AMJ DOY -0.101 0.430

7-day MIN BF JAS -0.102 0.391

7-day MIN BF JAS DOY -0.211 0.074 W

7-day MIN BF OND -0.048 0.693

7-day MIN BF OND DOY 0.024 0.861

Annual Mean GW level -0.303 0.193

3-day MAX GW 0.152 0.537

3-day MAX GW DOY -0.273 0.244

3-day MAX GW JFM -0.128 0.583

3-day MAX GW JFM DOY 0.195 0.411

3-day MAX GW AMJ 0.179 0.428



3-day MAX GW AMJ DOY -0.271 0.222

3-day MAX GW JAS -0.253 0.228

3-day MAX GW JAS DOY 0.255 0.295

3-day MAX GW OND -0.333 0.127

3-day MAX GW OND DOY 0.150 0.532

7-day MIN GW -0.121 0.631

7-day MIN GW DOY 0.015 1.000

7-day MIN GW JFM -0.179 0.428

7-day MIN GW JFM DOY -0.027 0.950

7-day MIN GW AMJ -0.205 0.360

7-day MIN GW AMJ DOY 0.301 0.228

7-day MIN GW JAS -0.077 0.743

7-day MIN GW JAS DOY 0.465 0.038 PT

7-day MIN GW OND -0.128 0.583

7-day MIN GW OND DOY 0.000 1.000


Table D-2: Annual analysis of Spearman’s Rank for Skootamatta River. Correlation coefficient is above and p-values

are below the diagonal. Correlation coefficient and p-values that meet thresholds for inclusion in analysis are shaded.

M

ean T

Tota

l P

PET

P-P

ET

7d M

AX T

7d M

AX T

DO

Y

7d M

IN T

7d M

IN T

DO

Y

3d M

AX R

3d M

AX R

DO

Y

30d M

IN R

30d M

IN R

DO

Y

R-B

Index

10:9

0

exceedance

Wate

r yie

ld

BF y

ield

3d M

AX Q

3d M

AX Q

DO

Y

7d M

IN Q

7d M

IN Q

DO

Y

3d M

AX B

F

3d M

AX B

F D

OY

7d M

IN B

F

7d M

IN B

F D

OY

Mean G

W

3d M

AX G

W

3d M

AX G

W D

OY

7d M

IN G

W

7d M

IN G

W D

OY

Mean T -0.1 0.88 -0.31 0.47 0.25 0.48 -0.01 -0.17 -0.01 0.36 0.19 0.2 0.14 -0.54 -0.47 0.08 0.09 -0.34 -0.08 -0.33 -0.01 -0.39 -0.22 -0.12 -0.1 -0.32 -0.15 0.26

Total P 0 -0.2 0.95 0.57 0.29 0.22 0.11 -0.33 0.16 0.21 0.21 0.18 0.12 -0.74 -0.65 0 0.03 -0.32 -0.12 -0.4 0.03 -0.35 -0.27 -0.19 -0.24 -0.27 -0.05 0.23

PET 0.18 0.08 -0.45 -0.6 0.24 -0.12 0.11 0.1 -0.05 0.01 0.05 0.39 -0.39 0.54 0.33 0.01 0.24 0.43 0.3 -0.02 0.13 0.42 -0.05 0.39 0.1 0.45 0.56 -0.55

P-PET 0.01 0 0 -0.67 0.1 -0.15 0.11 0.18 -0.08 -0.04 -0.02 0.24 -0.33 0.66 0.47 -0.01 0.19 0.41 0.26 0.11 0.06 0.42 0.01 0.36 0.12 0.48 0.5 -0.46

7d MAX T 0 0 0 0 -0.04 0.16 0.06 -0.22 -0.12 0.1 -0.02 -0.11 0.24 -0.46 -0.37 0.1 -0.04 -0.43 -0.15 -0.23 -0.05 -0.41 -0.04 -0.18 -0.24 0.15 0.01 -0.15

7d MAX T DOY 0.14 0.08 0.16 0.55 0.82 -0.06 0.05 -0.26 0.09 0.06 0.25 0.25 0.09 -0.21 -0.2 -0.3 0.04 -0.23 -0.03 -0.3 0.03 -0.24 -0.26 -0.02 -0.27 -0.08 -0.01 0.71

7d MIN T 0 0.2 0.5 0.39 0.35 0.73 0.13 0.21 -0.13 0.37 0.1 -0.04 0.28 -0.06 -0.04 0.12 -0.01 -0.34 -0.1 -0.06 -0.26 -0.38 -0.19 -0.12 0.14 -0.43 -0.25 -0.14

7d MIN T DOY 0.94 0.5 0.54 0.53 0.72 0.75 0.44 0.02 -0.21 0.2 0.34 0.15 0.16 0.03 0.01 -0.01 -0.08 -0.08 0.07 0.02 -0.14 -0.09 -0.07 0.06 -0.05 0.36 -0.1 -0.18

3d MAX R 0.32 0.05 0.57 0.29 0.19 0.13 0.23 0.9 -0.01 0.01 -0.18 0.16 0.01 0.35 0.2 0.29 -0.06 0.16 -0.1 0.01 -0.05 0.14 -0.03 0.66 0.66 -0.09 0.36 0.13

3d MAX R DOY 0.97 0.35 0.75 0.63 0.5 0.61 0.46 0.21 0.98 -0.19 -0.05 -0.03 -0.11 -0.24 -0.1 -0.47 0.33 0.12 -0.08 0.06 0.17 0.08 -0.21 0.09 -0.34 -0.25 0.19 0.57

30d MIN R 0.03 0.22 0.94 0.82 0.55 0.72 0.03 0.24 0.96 0.27 0.58 -0.11 -0.01 -0.03 0.04 -0.09 0.06 -0.04 -0.03 0.07 -0.3 -0.13 -0.07 -0.33 0.11 -0.21 -0.37 -0.32

30d MIN R DOY 0.26 0.21 0.77 0.89 0.92 0.14 0.55 0.04 0.3 0.78 0 0.07 0.08 -0.22 -0.22 -0.02 -0.04 -0.11 -0.02 -0.15 -0.11 -0.17 -0.07 -0.14 0.25 -0.53 -0.22 -0.02

R-B Index 0.24 0.3 0.02 0.16 0.54 0.14 0.81 0.37 0.35 0.86 0.54 0.69 -0.36 0.03 -0.21 0.25 0.02 0.3 0.17 -0.35 -0.01 0.23 -0.14 0.43 0.08 0.19 0.53 0.2

10:90 exceedance 0.4 0.47 0.02 0.05 0.17 0.6 0.09 0.36 0.95 0.53 0.97 0.64 0.03 -0.16 -0.13 0.06 -0.21 -0.87 -0.02 0.09 -0.01 -0.86 0.09 -0.04 0.36 -0.09 -0.39 0.33

Water yield 0 0 0 0 0.01 0.21 0.73 0.87 0.03 0.15 0.86 0.21 0.85 0.34 0.86 0.2 0.16 0.37 0.14 0.48 0.04 0.37 0.14 0.57 0.5 0.47 0.53 -0.57

BF yield 0 0 0.05 0 0.02 0.23 0.79 0.98 0.25 0.58 0.79 0.19 0.22 0.45 0 -0.11 0.35 0.34 0.14 0.76 0.01 0.36 0.22 0.42 0.24 0.61 0.36 -0.42

3d MAX Q 0.66 0.98 0.98 0.95 0.58 0.08 0.49 0.95 0.09 0 0.62 0.9 0.15 0.74 0.24 0.51 -0.31 0.04 -0.09 -0.13 -0.03 0.02 -0.08 0.2 0.83 -0.29 -0.07 -0.28

3d MAX Q DOY 0.59 0.86 0.17 0.27 0.83 0.82 0.97 0.65 0.72 0.05 0.74 0.81 0.91 0.22 0.35 0.04 0.06 0.22 0.25 0.2 0.35 0.18 0.19 0.73 0.11 0.12 0.61 -0.02

7d MIN Q 0.05 0.06 0.01 0.01 0.01 0.18 0.04 0.64 0.35 0.49 0.82 0.53 0.07 0 0.03 0.04 0.84 0.2 0.22 0.18 0.15 0.98 0.11 0.22 0.03 0.04 0.31 -0.35

7d MIN Q DOY 0.64 0.47 0.08 0.12 0.38 0.86 0.58 0.69 0.58 0.63 0.88 0.9 0.32 0.91 0.41 0.4 0.6 0.14 0.21 0.14 0.2 0.17 0.75 0.27 -0.03 0.48 0.36 -0.33

3d MAX BF 0.05 0.02 0.91 0.53 0.18 0.08 0.74 0.89 0.95 0.73 0.67 0.38 0.04 0.6 0 0 0.46 0.24 0.29 0.42 -0.12 0.19 0.31 -0.06 0.36 0.34 -0.29 -0.26

3d MAX BF DOY 0.93 0.85 0.46 0.74 0.77 0.86 0.12 0.41 0.78 0.32 0.07 0.53 0.94 0.93 0.83 0.97 0.85 0.04 0.38 0.23 0.5 0.16 0.14 0.32 0.03 0.28 0.27 -0.17

7d MIN BF 0.02 0.03 0.01 0.01 0.01 0.16 0.02 0.61 0.4 0.63 0.44 0.31 0.18 0 0.02 0.03 0.9 0.29 0 0.33 0.27 0.36 0.11 0.2 -0.15 0.2 0.36 -0.35

7d MIN BF DOY 0.21 0.11 0.76 0.95 0.81 0.12 0.26 0.68 0.85 0.23 0.7 0.67 0.43 0.61 0.42 0.2 0.64 0.27 0.51 0 0.07 0.43 0.53 0.43 0.06 0.49 0.34 -0.23

Mean GW 0.71 0.56 0.21 0.26 0.57 0.95 0.71 0.85 0.02 0.77 0.3 0.66 0.16 0.9 0.05 0.17 0.54 0.01 0.48 0.4 0.86 0.31 0.54 0.17 0.54 -0.01 0.78 0.12

3d MAX GW 0.76 0.46 0.75 0.71 0.46 0.39 0.66 0.88 0.02 0.28 0.74 0.44 0.8 0.25 0.1 0.44 0 0.73 0.93 0.93 0.26 0.91 0.63 0.85 0.07 -0.43 0.1 0.05

3d MAX GW DOY 0.31 0.4 0.14 0.12 0.63 0.8 0.16 0.25 0.78 0.43 0.52 0.07 0.56 0.78 0.12 0.04 0.35 0.71 0.9 0.11 0.28 0.38 0.54 0.11 0.97 0.17 0.36 -0.47

7d MIN GW 0.63 0.88 0.06 0.1 0.98 0.98 0.44 0.75 0.25 0.56 0.24 0.48 0.08 0.21 0.08 0.25 0.83 0.04 0.32 0.25 0.35 0.39 0.25 0.27 0 0.76 0.25 -0.14

7d MIN GW DOY 0.42 0.46 0.07 0.13 0.65 0.01 0.66 0.57 0.69 0.05 0.32 0.96 0.54 0.3 0.05 0.18 0.37 0.96 0.26 0.3 0.41 0.6 0.27 0.47 0.7 0.89 0.13 0.66


Table D-3: Winter seasonal analysis of Spearman’s Rank for the Skootamatta River. Correlation coefficient is above

and p-value is below the diagonal. Correlation coefficient and p-values that meet thresholds for inclusion in analysis

are shaded.

7d M

AX T

JFM

7d M

AX T

JFM

DO

Y

7d M

IN T

JFM

7d M

IN T

JFM

DO

Y

JFM

tota

l R

3d M

AX R

JFM

3d M

AX R

JFM

DO

Y

30d M

IN R

JFM

30d M

IN R

JFM

DO

Y

JFM

yie

ld

JFM

BF y

ield

3d M

AX Q

JFM

3d M

AX Q

JFM

DO

Y

7d M

IN Q

JFM

7d M

IN Q

JFM

DO

Y

3d M

AX B

F J

FM

3d M

AX B

F J

FM

DO

Y

7d M

IN B

F J

FM

7d M

IN B

F J

FM

DO

Y

3d M

AX G

W J

FM

3d M

AX G

W J

FM

DO

Y

7d M

IN G

W J

FM

7d M

IN G

W J

FM

DO

Y

7d MAX T JFM 0.28 0.24 0.11 0.5 0.54 -0.01 0.05 0.06 0.22 -0.04 0.45 0 0.15 0.11 -0.12 -0.24 0.07 0.18 0.37 0.22 0.26 -0.13

7d MAX T JFM DOY 0.1 -0.19 0.12 0.1 0.22 0.24 -0.29 -0.18 0.09 0.08 0.24 0.06 -0.08 -0.03 0.13 -0.04 -0.07 0.08 0.33 -0.03 0.46 -0.2

7d MIN T JFM 0.15 0.26 0.15 0.2 0.41 0.15 0.37 0.03 0.15 0.28 0.19 0.22 0.58 0.16 0.06 -0.03 0.53 -0.03 0.1 0.38 -0.13 -0.53

7d MIN T JFM DOY 0.51 0.49 0.38 0 0.2 0.26 0.1 0.31 -0.08 0.02 0.11 -0.05 0.02 0.37 -0.03 -0.07 0.05 0.16 0.15 -0.27 -0.02 0.19

JFM total R 0 0.57 0.24 0.99 0.54 0.01 0.25 0 0.46 0.33 0.35 -0.06 0.43 -0.09 0.03 0.07 0.42 -0.46 0.04 0.63 -0.09 -0.69

3d MAX R JFM 0 0.2 0.01 0.24 0 0.17 0.1 -0.01 0.25 0.04 0.44 0.1 0.2 0.23 -0.07 -0.01 0.23 -0.06 -0.15 0.43 -0.29 -0.74

3d MAX R JFM DOY 0.96 0.16 0.38 0.12 0.97 0.33 -0.11 -0.06 -0.12 0 0.13 0.36 -0.14 0.17 0.22 0.03 -0.09 0.22 0.33 -0.01 0.17 0.2

30d MIN R JFM 0.78 0.09 0.03 0.56 0.15 0.57 0.53 0.47 0.12 0.3 -0.13 -0.21 0.48 0.21 0.06 -0.05 0.39 -0.26 -0.21 0.6 -0.4 -0.57

30d MIN R JFM DOY 0.74 0.28 0.85 0.07 1 0.96 0.73 0 0.06 0.17 -0.11 -0.46 0.25 0.3 -0.15 -0.28 0.23 0.1 0.1 0 0.14 0.02

JFM yield 0.19 0.61 0.37 0.64 0 0.14 0.47 0.47 0.74 0.62 0.63 -0.16 0.5 -0.23 0.41 -0.05 0.49 -0.31 0.37 0.62 0.13 -0.81

JFM BF yield 0.84 0.66 0.09 0.89 0.05 0.82 0.99 0.08 0.32 0 0.11 -0.26 0.73 -0.06 0.69 0.04 0.78 -0.37 0.45 0.24 0.29 -0.75

3d MAX Q JFM 0.01 0.16 0.26 0.52 0.04 0.01 0.46 0.44 0.51 0 0.53 0.18 0.11 -0.09 0.12 0.12 0.06 0.13 0.03 0.6 -0.24 -0.25

3d MAX Q JFM DOY 0.98 0.74 0.2 0.78 0.71 0.58 0.03 0.21 0 0.34 0.13 0.29 -0.09 -0.22 0 0.25 -0.14 0.08 -0.35 0.56 -0.57 0.05

7d MIN Q JFM 0.37 0.63 0 0.9 0.01 0.25 0.42 0 0.14 0 0 0.53 0.6 0.08 0.31 0.02 0.96 -0.32 0.19 0.48 -0.01 -0.79

7d MIN Q JFM DOY 0.52 0.86 0.35 0.03 0.61 0.18 0.33 0.22 0.08 0.19 0.75 0.61 0.19 0.65 -0.05 -0.1 0.06 0.5 0.36 -0.17 0.19 -0.09

3d MAX BF JFM 0.48 0.46 0.74 0.88 0.85 0.7 0.19 0.75 0.39 0.01 0 0.5 0.99 0.07 0.79 0.32 0.36 -0.06 0.74 0.26 0.51 -0.53

3d MAX BF JFM DOY 0.16 0.81 0.86 0.68 0.68 0.97 0.87 0.75 0.1 0.79 0.83 0.49 0.14 0.92 0.55 0.06 0.09 -0.16 -0.48 0.41 -0.5 -0.18

7d MIN BF JFM 0.7 0.66 0 0.78 0.01 0.17 0.59 0.02 0.17 0 0 0.72 0.41 0 0.73 0.03 0.61 -0.38 0.26 0.32 0.12 -0.79

7d MIN BF JFM DOY 0.3 0.64 0.88 0.34 0 0.75 0.2 0.12 0.55 0.07 0.03 0.45 0.64 0.06 0 0.73 0.35 0.02 0.35 -0.37 0.47 0.68

3d MAX GW JFM 0.22 0.27 0.74 0.61 0.9 0.62 0.27 0.5 0.75 0.21 0.13 0.91 0.24 0.54 0.22 0 0.1 0.39 0.24 -0.14 0.88 0.03

3d MAX GW JFM DOY 0.46 0.93 0.2 0.37 0.02 0.14 0.97 0.03 0.99 0.02 0.43 0.03 0.05 0.09 0.59 0.4 0.16 0.28 0.22 0.66 -0.37 -0.57

7d MIN GW JFM 0.38 0.12 0.66 0.96 0.76 0.34 0.58 0.18 0.65 0.67 0.34 0.44 0.04 0.97 0.54 0.07 0.08 0.71 0.1 0 0.22 0.16

7d MIN GW JFM DOY 0.68 0.51 0.06 0.54 0.01 0 0.51 0.04 0.96 0 0 0.41 0.86 0 0.76 0.06 0.56 0 0.01 0.91 0.04 0.6


Table D-4: Spring seasonal analysis of Spearman’s Rank for the Skootamatta River. Correlation coefficient is above


are shaded.

7d M

AX T

AM

J

7d M

AX T

AM

J D

OY

7d M

IN T

AM

J

7d M

IN T

AM

J D

OY

AM

J to

tal R

3d M

AX R

AM

J

3d M

AX R

AM

J D

OY

30d M

IN R

AM

J

30d M

IN R

AM

J D

OY

AM

J yie

ld

AM

J BF y

ield

3d M

AX Q

AM

J

3d M

AX Q

AM

J D

OY

7d M

IN Q

AM

J

7d M

IN Q

AM

J D

OY

3d M

AX B

F A

MJ

3d M

AX B

F A

MJ

DO

Y

7d M

IN B

F A

MJ

7d M

IN B

F A

MJ

DO

Y

3d M

AX G

W A

MJ

3d M

AX G

W A

MJ

DO

Y

7d M

IN G

W A

MJ

7d M

IN G

W A

MJ

DO

Y

7d MAX T AMJ 0.04 0.15 -0.21 -0.32 -0.14 -0.02 -0.29 0.21 -0.04 -0.19 0.21 -0.34 -0.23 0.16 -0.22 0 -0.27 0.13 -0.03 -0.12 -0.48 -0.11

7d MAX T AMJ DOY 0.84 -0.13 -0.03 0.17 0.22 0.08 -0.21 -0.1 0.3 0.18 0.31 0.1 0 -0.07 0.01 0.11 -0.03 -0.08 0.24 0.04 -0.01 -0.6

7d MIN T AMJ 0.37 0.46 0.22 -0.18 -0.11 0.4 0.02 -0.19 -0.14 -0.23 0.01 -0.32 -0.12 -0.19 -0.13 -0.28 -0.1 -0.18 0.05 -0.18 0.32 0.07

7d MIN T AMJ DOY 0.22 0.84 0.21 -0.31 -0.23 0.16 -0.04 0.03 -0.17 -0.14 0 0.05 0.02 0.19 -0.1 -0.13 0.02 0.12 0.04 -0.13 0.67 -0.11

AMJ total R 0.05 0.33 0.31 0.06 0.64 0.04 0.46 -0.17 0.65 0.55 0.16 0.39 0.43 -0.37 0.42 0.41 0.41 -0.18 0.25 0.25 -0.3 -0.02

3d MAX R AMJ 0.42 0.2 0.52 0.17 0 -0.17 -0.11 0.08 0.59 0.45 0.45 0.16 0.01 -0.15 0.45 0.24 -0.05 0.01 0.58 -0.33 -0.12 0.33

3d MAX R AMJ DOY 0.91 0.65 0.02 0.36 0.8 0.31 0.33 -0.52 -0.21 -0.24 -0.31 0.06 0.34 -0.35 -0.26 -0.06 0.32 -0.34 -0.24 0.04 -0.04 -0.33

30d MIN R AMJ 0.09 0.21 0.91 0.81 0 0.51 0.05 -0.26 0.25 0.25 -0.18 0.34 0.55 -0.21 0.18 0.15 0.59 -0.15 0.43 -0.01 0.16 -0.33

30d MIN R AMJ DOY 0.23 0.56 0.28 0.86 0.32 0.63 0 0.13 0.23 0.31 0.27 0.01 -0.3 0.24 0.32 0.24 -0.32 0.23 0.62 -0.33 0.18 -0.16

AMJ yield 0.8 0.07 0.41 0.33 0 0 0.22 0.13 0.18 0.82 0.58 0.35 0.37 -0.22 0.67 0.48 0.35 -0.07 0.74 -0.01 0.02 -0.37

AMJ BF yield 0.28 0.28 0.17 0.42 0 0.01 0.16 0.15 0.06 0 0.24 0.4 0.31 -0.06 0.89 0.51 0.28 0.04 0.62 0.12 0.08 -0.34

3d MAX Q AMJ 0.22 0.06 0.98 1 0.35 0.01 0.06 0.29 0.11 0 0.15 -0.18 -0.17 -0.12 0.25 0.08 -0.2 0.01 0.77 -0.27 -0.21 -0.17

3d MAX Q AMJ DOY 0.04 0.54 0.06 0.79 0.02 0.36 0.73 0.04 0.95 0.04 0.02 0.29 0.5 -0.08 0.13 0.59 0.48 -0.04 0.27 0.39 0.24 -0.21

7d MIN Q AMJ 0.17 0.99 0.48 0.91 0.01 0.94 0.04 0 0.07 0.03 0.06 0.31 0 -0.56 0.13 0.25 0.98 -0.45 -0.01 0.44 -0.33 -0.37

7d MIN Q AMJ DOY 0.34 0.68 0.27 0.26 0.03 0.37 0.03 0.23 0.15 0.2 0.74 0.48 0.65 0 -0.03 -0.1 -0.55 0.86 -0.13 -0.42 0.52 0.3

3d MAX BF AMJ 0.2 0.93 0.44 0.57 0.01 0.01 0.12 0.31 0.06 0 0 0.14 0.47 0.44 0.85 0.26 0.09 0.04 0.61 -0.23 0.42 -0.15

3d MAX BF AMJ DOY 0.99 0.52 0.1 0.44 0.01 0.15 0.72 0.38 0.16 0 0 0.65 0 0.15 0.57 0.12 0.25 -0.09 0.27 0.27 -0.45 0.03

7d MIN BF AMJ 0.11 0.86 0.55 0.92 0.01 0.76 0.06 0 0.05 0.04 0.1 0.24 0 0 0 0.61 0.14 -0.48 0.03 0.41 -0.35 -0.37

7d MIN BF AMJ DOY 0.44 0.63 0.29 0.48 0.29 0.95 0.04 0.39 0.18 0.69 0.82 0.95 0.83 0.01 0 0.82 0.59 0 -0.11 -0.41 0.57 0.31

3d MAX GW AMJ 0.91 0.44 0.86 0.89 0.4 0.04 0.43 0.14 0.02 0 0.03 0 0.37 0.96 0.68 0.03 0.38 0.93 0.73 -0.54 0.31 -0.12

3d MAX GW AMJ DOY 0.7 0.9 0.57 0.66 0.41 0.27 0.91 0.99 0.27 0.98 0.69 0.38 0.19 0.13 0.15 0.46 0.38 0.16 0.16 0.06 -0.31 -0.31

7d MIN GW AMJ 0.1 0.99 0.28 0.01 0.32 0.69 0.89 0.59 0.57 0.94 0.79 0.48 0.44 0.27 0.07 0.16 0.12 0.25 0.04 0.31 0.3 -0.24

7d MIN GW AMJ DOY 0.73 0.03 0.82 0.71 0.94 0.28 0.27 0.27 0.61 0.21 0.26 0.58 0.49 0.22 0.32 0.61 0.93 0.22 0.31 0.7 0.3 0.42


Table D-5: Summer seasonal analysis of Spearman’s Rank for the Skootamatta River. Correlation coefficient is above


are shaded.

7d M

AX T

JAS

7d M

AX T

JAS D

OY

7d M

IN T

JAS

7d M

IN T

JAS D

OY

JAS t

ota

l R

3d M

AX R

JAS

3d M

AX R

JAS D

OY

30d M

IN R

JAS

30d M

IN R

JAS D

OY

JAS y

ield

JAS B

F y

ield

3d M

AX Q

JAS

3d M

AX Q

JAS D

OY

7d M

IN Q

JAS

7d M

IN Q

JAS D

OY

3d M

AX B

F J

AS

3d M

AX B

F J

AS D

OY

7d M

IN B

F J

AS

7d M

IN B

F J

AS D

OY

3d M

AX G

W J

AS

3d M

AX G

W J

AS D

OY

7d M

IN G

W J

AS

7d M

IN G

W J

AS D

OY

7d MAX T JAS -0.36 0.06 0.17 -0.36 -0.09 0.08 -0.33 -0.18 -0.46 -0.4 -0.49 -0.24 -0.48 0.07 -0.32 -0.35 -0.48 -0.01 -0.2 0.09 -0.26 -0.06

7d MAX T JAS DOY 0.03 0.09 0.16 0.15 0.17 0 -0.17 0.04 0.01 -0.01 0.02 0.22 -0.05 -0.01 -0.05 0.14 0 0.04 -0.48 -0.1 -0.05 -0.34

7d MIN T JAS 0.72 0.58 -0.06 0 0.08 0.25 0.11 0.27 -0.06 -0.13 0.01 0.26 0.05 -0.19 -0.25 0.04 0.02 -0.21 -0.13 -0.1 -0.05 -0.38

7d MIN T JAS DOY 0.32 0.35 0.73 -0.24 -0.25 0.2 -0.33 -0.13 -0.2 -0.11 -0.25 0.02 -0.29 -0.03 -0.14 0.26 -0.31 0.11 -0.32 -0.07 -0.58 0.17

JAS total R 0.03 0.38 1 0.17 0.75 -0.11 0.43 -0.13 0.47 0.33 0.49 0.52 0.37 -0.3 0.2 0.42 0.4 -0.51 0.02 0.12 0.56 -0.13

3d MAX R JAS 0.62 0.33 0.62 0.13 0 0.01 0.11 -0.27 0.23 0.06 0.31 0.27 0.15 -0.34 -0.02 0.3 0.19 -0.47 0.02 0.02 0.35 -0.24

3d MAX R JAS DOY 0.65 0.98 0.15 0.24 0.52 0.97 -0.14 0.08 0.05 0.07 0.14 0.14 -0.01 -0.27 0.12 0.12 -0.05 -0.16 -0.03 0.04 -0.16 -0.23

30d MIN R JAS 0.05 0.33 0.53 0.05 0.01 0.53 0.41 0.12 0.53 0.49 0.48 0.19 0.64 0.22 0.37 0.16 0.63 0.03 0.45 0.09 0.79 -0.19

30d MIN R JAS DOY 0.29 0.81 0.11 0.47 0.44 0.12 0.63 0.48 0.12 0.09 0.24 0.13 0.11 -0.05 0.06 -0.14 0.11 0.09 -0.09 -0.04 -0.13 -0.51

JAS yield 0 0.96 0.75 0.25 0 0.19 0.75 0 0.49 0.96 0.95 0.21 0.78 -0.05 0.86 0.43 0.76 -0.05 0.45 0.26 0.84 -0.27

JAS BF yield 0.02 0.96 0.46 0.53 0.05 0.71 0.69 0 0.61 0 0.87 0.14 0.79 0.07 0.92 0.37 0.76 0.08 0.48 0.14 0.71 -0.09

3d MAX Q JAS 0 0.92 0.96 0.14 0 0.07 0.42 0 0.15 0 0 0.25 0.68 -0.16 0.79 0.42 0.67 -0.11 0.45 0.17 0.76 -0.3

3d MAX Q JAS DOY 0.16 0.2 0.12 0.9 0 0.1 0.42 0.26 0.46 0.22 0.41 0.13 0.21 -0.42 -0.04 0.47 0.27 -0.51 -0.82 0.32 -0.3 -0.07

7d MIN Q JAS 0 0.79 0.76 0.09 0.03 0.37 0.96 0 0.53 0 0 0 0.21 0.04 0.59 0.39 0.97 -0.01 0.39 0.07 0.64 -0.09

7d MIN Q JAS DOY 0.68 0.97 0.26 0.88 0.08 0.05 0.12 0.2 0.75 0.77 0.67 0.35 0.01 0.8 0.22 -0.56 -0.01 0.8 0.41 -0.46 0.19 0.1

3d MAX BF JAS 0.06 0.76 0.14 0.43 0.25 0.91 0.5 0.03 0.74 0 0 0 0.83 0 0.2 0.14 0.55 0.2 0.53 -0.08 0.59 -0.02

3d MAX BF JAS DOY 0.04 0.42 0.81 0.13 0.01 0.08 0.5 0.36 0.42 0.01 0.03 0.01 0 0.02 0 0.42 0.43 -0.38 -0.1 0.44 0.1 0.16

7d MIN BF JAS 0 0.98 0.9 0.06 0.02 0.26 0.77 0 0.53 0 0 0 0.11 0 0.96 0 0.01 -0.02 0.21 0.11 0.62 -0.16

7d MIN BF JAS DOY 0.94 0.81 0.22 0.54 0 0 0.35 0.85 0.61 0.77 0.63 0.5 0 0.97 0 0.24 0.02 0.9 0.47 -0.36 0.22 -0.05

3d MAX GW JAS 0.5 0.08 0.65 0.27 0.93 0.95 0.93 0.11 0.75 0.11 0.08 0.11 0 0.17 0.15 0.05 0.73 0.46 0.09 -0.24 0.67 -0.17

3d MAX GW JAS DOY 0.76 0.73 0.74 0.81 0.68 0.95 0.88 0.77 0.89 0.37 0.63 0.57 0.27 0.83 0.1 0.78 0.11 0.7 0.2 0.41 0.16 0.39

7d MIN GW JAS 0.37 0.88 0.88 0.03 0.04 0.21 0.59 0 0.66 0 0 0 0.3 0.01 0.52 0.03 0.74 0.02 0.44 0.01 0.58 -0.33

7d MIN GW JAS DOY 0.83 0.24 0.18 0.56 0.67 0.41 0.42 0.51 0.06 0.35 0.76 0.29 0.82 0.76 0.72 0.94 0.59 0.58 0.87 0.55 0.17 0.26


Table D-6: Autumn seasonal analysis of Spearman’s Rank for the Skootamatta River. Correlation coefficient is above


are shaded

7d M

AX T

ON

D

7d M

AX T

ON

D D

OY

7d M

IN T

ON

D

7d M

IN T

ON

D D

OY

ON

D t

ota

l R

3d M

AX R

ON

D

3d M

AX R

ON

D D

OY

30d M

IN R

ON

D

30d M

IN R

ON

D D

OY

ON

D y

ield

ON

D B

F y

ield

3d M

AX Q

ON

D

3d M

AX Q

ON

D D

OY

7d M

IN Q

ON

D

7d M

IN Q

ON

D D

OY

3d M

AX B

F O

ND

3d M

AX B

F O

ND

DO

Y

7d M

IN B

F O

ND

7d M

IN B

F O

ND

DO

Y

3d M

AX G

W O

ND

3d M

AX G

W O

ND

DO

Y

7d M

IN G

W O

ND

7d M

IN G

W O

ND

DO

Y

7d MAX T OND -0.09 -0.05 -0.16 0.09 0.12 0.1 -0.12 0.08 -0.41 -0.37 -0.33 0.18 -0.49 0 -0.18 0.29 -0.47 0.06 -0.36 -0.3 -0.08 0.48

7d MAX T OND DOY 0.62 0 -0.15 -0.11 -0.07 0.13 -0.14 0.02 -0.12 -0.18 -0.05 0.09 -0.21 -0.15 -0.13 0.02 -0.28 0.1 -0.23 -0.08 -0.6 -0.19

7d MIN T OND 0.79 0.99 -0.13 0.06 -0.11 0.03 0.28 -0.06 0.07 0.23 0.03 -0.13 -0.02 0.03 0.18 -0.2 0.08 0.09 -0.07 0.44 -0.03 -0.24

7d MIN T OND DOY 0.35 0.39 0.46 0.07 0.06 0.19 0.14 -0.41 -0.17 -0.18 -0.07 0.16 -0.13 -0.07 -0.1 0.2 -0.11 -0.07 -0.44 0.24 -0.28 -0.11

OND total R 0.62 0.54 0.74 0.7 0.69 0.24 0.53 0.13 0.4 0.36 0.45 -0.09 -0.25 -0.28 0.46 -0.13 -0.22 -0.33 0.3 0.36 -0.12 -0.65

3d MAX R OND 0.49 0.67 0.54 0.73 0 0.24 0.17 0.27 0.36 0.28 0.55 -0.15 -0.14 -0.15 0.41 -0.22 -0.13 -0.01 -0.21 0.12 -0.35 -0.23

3d MAX R OND DOY 0.58 0.45 0.88 0.27 0.15 0.16 0.15 -0.31 0.03 0.02 0.22 0.31 -0.01 -0.06 0.17 0.29 0.03 -0.12 0.29 0.01 0.24 -0.02

30d MIN R OND 0.48 0.43 0.09 0.41 0 0.32 0.37 -0.1 0.21 0.3 0.13 0.06 -0.17 -0.04 0.3 -0.13 -0.11 -0.45 0.15 0.24 -0.16 -0.47

30d MIN R OND DOY 0.63 0.91 0.75 0.01 0.44 0.11 0.06 0.55 0.2 0.12 0.17 -0.35 0.15 -0.15 -0.05 -0.3 0.05 -0.03 -0.15 -0.23 -0.12 0.08

OND yield 0.01 0.48 0.67 0.31 0.01 0.03 0.88 0.22 0.24 0.94 0.89 -0.6 0.59 0.13 0.75 -0.64 0.58 0.01 0.86 0.38 0.53 -0.62

OND BF yield 0.03 0.29 0.17 0.28 0.03 0.1 0.91 0.08 0.49 0 0.8 -0.61 0.52 0.15 0.85 -0.63 0.59 0.08 0.82 0.42 0.51 -0.67

3d MAX Q OND 0.05 0.76 0.88 0.7 0.01 0 0.19 0.44 0.32 0 0 -0.37 0.46 0.11 0.75 -0.5 0.44 0 0.74 0.22 0.32 -0.52

3d MAX Q OND DOY 0.29 0.61 0.43 0.36 0.62 0.38 0.07 0.72 0.04 0 0 0.03 -0.37 -0.13 -0.31 0.72 -0.37 -0.21 -0.5 -0.47 -0.45 0.54

7d MIN Q OND 0 0.23 0.91 0.45 0.15 0.42 0.95 0.31 0.38 0 0 0 0.03 0.49 0.22 -0.3 0.93 0.17 0.67 0.07 0.79 -0.06

7d MIN Q OND DOY 0.98 0.4 0.87 0.68 0.1 0.37 0.74 0.81 0.39 0.45 0.38 0.53 0.46 0 0.13 -0.16 0.44 0.27 0.15 -0.27 0.06 0.2

3d MAX BF OND 0.3 0.44 0.29 0.57 0 0.01 0.31 0.07 0.78 0 0 0 0.07 0.19 0.43 -0.4 0.35 0.08 0.65 0.19 0.15 -0.55

3d MAX BF OND DOY 0.09 0.91 0.23 0.25 0.45 0.19 0.09 0.46 0.08 0 0 0 0 0.08 0.36 0.01 -0.31 -0.05 -0.4 -0.32 -0.16 0.41

7d MIN BF OND 0 0.1 0.66 0.53 0.19 0.46 0.85 0.51 0.78 0 0 0.01 0.02 0 0.01 0.04 0.07 0.31 0.54 0.12 0.73 -0.12

7d MIN BF OND DOY 0.71 0.55 0.61 0.68 0.05 0.95 0.5 0.01 0.88 0.94 0.63 0.98 0.23 0.33 0.11 0.63 0.79 0.07 -0.24 -0.25 0 0.17

3d MAX GW OND 0.23 0.44 0.83 0.13 0.32 0.49 0.33 0.62 0.62 0 0 0 0.08 0.01 0.62 0.02 0.18 0.06 0.42 0.02 0.77 -0.3

3d MAX GW OND DOY 0.32 0.8 0.14 0.42 0.22 0.7 0.96 0.44 0.44 0.21 0.16 0.48 0.11 0.83 0.37 0.53 0.28 0.7 0.41 0.95 -0.19 -0.81

7d MIN GW OND 0.79 0.03 0.93 0.35 0.69 0.24 0.43 0.6 0.71 0.06 0.07 0.28 0.12 0 0.84 0.62 0.61 0.01 0.99 0 0.54 0.08

7d MIN GW OND DOY 0.1 0.53 0.44 0.73 0.02 0.46 0.94 0.11 0.79 0.02 0.01 0.07 0.05 0.84 0.51 0.05 0.17 0.71 0.58 0.32 0 0.8


Table D-7: Annual analysis of Kendall’s Rank for the Skootamatta River. Correlation coefficient is above and p-value

is below the diagonal. Correlation coefficient and p-values that meet thresholds for inclusion in analysis are shaded

Mean T

Tota

l P

PET

P-P

ET

7d M

AX T

7d M

AX T

DO

Y

7d M

IN T

7d M

IN T

DO

Y

3d M

AX R

3d M

AX R

DO

Y

30d M

IN R

30d M

IN R

DO

Y

R-B

Index

10:9

0 e

xceedance

Wate

r yie

ld

BF y

ield

3d M

AX Q

3d M

AX Q

DO

Y

7d M

IN Q

7d M

IN Q

DO

Y

3d M

AX B

F

3d M

AX B

F D

OY

7d M

IN B

F

7d M

IN B

F D

OY

Mean G

W

3d M

AX G

W

3d M

AX G

W D

OY

7d M

IN G

W

7d M

IN G

W D

OY

Mean T -0.08 0.68 -0.23 0.32 0.2 0.33 -0.01 -0.11 0 0.29 0.15 0.14 0.11 -0.39 -0.33 0.03 0.05 -0.21 -0.06 -0.26 0.01 -0.26 -0.15 -0.09 -0.06 -0.18 -0.09 0.17

Total P 0.63 -0.17 0.82 0.38 0.19 0.16 0.08 -0.2 0.09 0.16 0.14 0.12 0.1 -0.55 -0.45 -0.03 0.04 -0.21 -0.08 -0.26 0.02 -0.23 -0.18 -0.15 -0.12 -0.18 -0.03 0.23

PET 0 0.34 -0.35 -0.44 0.19 -0.08 0.08 0.06 -0.03 0.02 0.02 0.27 -0.25 0.39 0.2 0 0.13 0.3 0.22 -0.02 0.1 0.29 -0.04 0.27 0.06 0.3 0.39 -0.41

P-PET 0.18 0 0.04 -0.5 0.1 -0.1 0.06 0.12 -0.07 -0.03 -0.03 0.19 -0.23 0.49 0.31 -0.01 0.11 0.3 0.19 0.07 0.04 0.3 0.01 0.27 0.06 0.3 0.33 -0.35

7d MAX T 0.06 0.02 0.02 0 -0.02 0.12 0.04 -0.16 -0.07 0.09 0.01 -0.07 0.18 -0.32 -0.26 0.08 -0.03 -0.32 -0.11 -0.14 -0.04 -0.32 -0.03 -0.09 -0.12 0.06 -0.03 -0.08

7d MAX T DOY 0.25 0.13 0.26 0.37 0.9 -0.06 0.04 -0.19 0.07 0.05 0.17 0.18 0.05 -0.14 -0.15 -0.22 0.01 -0.16 -0.04 -0.21 0.02 -0.17 -0.19 0 -0.15 -0.03 0 0.56

7d MIN T 0.05 0.88 0.36 0.82 0.47 0.75 0.12 0.15 -0.08 0.29 0.06 -0.02 0.19 -0.03 -0.02 0.08 -0.02 -0.23 -0.08 -0.04 -0.19 -0.26 -0.14 -0.11 0.14 -0.26 -0.17 -0.06

7d MIN T DOY 0.96 0.49 0.64 0.57 0.79 0.82 0.48 0.02 -0.15 0.15 0.24 0.09 0.12 0 0 0 -0.06 -0.07 0.04 0.02 -0.12 -0.07 -0.06 0.02 -0.02 0.26 -0.05 -0.12

3d MAX R 0.53 0.59 0.25 0.33 0.36 0.26 0.38 0.9 -0.02 0 -0.13 0.09 0.02 0.24 0.13 0.18 -0.03 0.11 -0.05 0.01 -0.02 0.09 -0.01 0.55 0.52 -0.03 0.3 0.11

3d MAX R DOY 0.99 0.55 0.58 0.33 0.68 0.7 0.66 0.39 0.89 -0.15 -0.04 -0.04 -0.07 -0.17 -0.07 -0.34 0.26 0.08 -0.05 0.03 0.11 0.04 -0.12 0.06 -0.25 -0.15 0.12 0.45

30d MIN R 0.09 0.32 0.34 0.38 0.6 0.76 0.08 0.37 0.99 0.39 0.49 -0.08 0 -0.02 0.03 -0.07 0.05 -0.03 -0.02 0.06 -0.24 -0.1 -0.06 -0.24 0.08 -0.16 -0.28 -0.26

30d MIN R DOY 0.39 0.53 0.41 0.67 0.94 0.31 0.72 0.16 0.46 0.81 0 0.05 0.06 -0.15 -0.16 0 -0.03 -0.07 -0.04 -0.09 -0.07 -0.13 -0.07 -0.08 0.2 -0.41 -0.2 0.03

R-B Index 0.42 0.07 0.48 0.19 0.68 0.29 0.89 0.58 0.59 0.82 0.63 0.76 -0.24 0.02 -0.14 0.17 -0.01 0.21 0.09 -0.23 -0.02 0.15 -0.11 0.3 0.03 0.15 0.36 0.11

10:90 exceedance 0.53 0.39 0.56 0.5 0.29 0.75 0.28 0.5 0.93 0.69 0.99 0.71 0.15 -0.12 -0.1 0.03 -0.16 -0.7 -0.01 0.05 -0.01 -0.7 0.08 -0.09 0.3 -0.06 -0.27 0.23

Water yield 0.02 0.04 0 0 0.06 0.41 0.88 0.98 0.15 0.32 0.9 0.37 0.9 0.5 0.67 0.13 0.09 0.26 0.09 0.33 -0.01 0.28 0.09 0.42 0.33 0.33 0.36 -0.38

BF yield 0.05 0.27 0.01 0.06 0.13 0.38 0.9 0.99 0.46 0.7 0.84 0.35 0.42 0.56 0 -0.07 0.24 0.24 0.1 0.59 -0.02 0.25 0.14 0.3 0.15 0.45 0.24 -0.26

3d MAX Q 0.84 0.74 0.87 0.66 0.63 0.2 0.62 0.98 0.28 0.04 0.68 0.98 0.34 0.88 0.44 0.7 -0.2 0.01 -0.08 -0.06 -0.03 0.01 -0.07 0.15 0.67 -0.18 -0.03 -0.17

3d MAX Q DOY 0.75 0.54 0.82 0.62 0.85 0.97 0.92 0.73 0.85 0.12 0.77 0.87 0.97 0.36 0.62 0.16 0.25 0.17 0.17 0.12 0.23 0.14 0.13 0.55 0.09 0.09 0.42 -0.05

7d MIN Q 0.21 0.19 0.23 0.21 0.06 0.35 0.18 0.7 0.53 0.65 0.87 0.7 0.22 0 0.13 0.16 0.96 0.33 0.16 0.13 0.12 0.91 0.08 0.15 -0.06 0 0.27 -0.23

7d MIN Q DOY 0.73 0.49 0.63 0.7 0.53 0.82 0.66 0.83 0.77 0.79 0.89 0.8 0.6 0.96 0.62 0.58 0.66 0.32 0.35 0.09 0.14 0.13 0.71 0.21 0 0.3 0.27 -0.23

3d MAX BF 0.13 0.8 0.13 0.46 0.41 0.22 0.83 0.9 0.94 0.85 0.73 0.59 0.17 0.77 0.05 0 0.73 0.47 0.45 0.62 -0.07 0.13 0.18 -0.06 0.27 0.27 -0.24 -0.14

3d MAX BF DOY 0.97 0.84 0.91 0.87 0.82 0.93 0.27 0.49 0.9 0.52 0.16 0.68 0.9 0.96 0.96 0.91 0.88 0.17 0.5 0.42 0.67 0.12 0.09 0.3 0.03 0.15 0.18 -0.14

7d MIN BF 0.13 0.24 0.17 0.24 0.06 0.32 0.12 0.69 0.59 0.8 0.55 0.44 0.39 0 0.1 0.14 0.94 0.43 0 0.45 0.46 0.5 0.08 0.15 -0.18 0.12 0.27 -0.23

7d MIN BF DOY 0.39 0.49 0.29 0.7 0.88 0.27 0.41 0.72 0.96 0.48 0.73 0.69 0.51 0.62 0.61 0.41 0.69 0.46 0.64 0 0.28 0.6 0.65 0.32 0.08 0.35 0.26 -0.15

Mean GW 0.78 0.51 0.64 0.45 0.78 1 0.74 0.96 0.07 0.85 0.45 0.81 0.34 0.78 0.17 0.34 0.64 0.07 0.64 0.51 0.85 0.34 0.64 0.31 0.36 0 0.64 0.14

3d MAX GW 0.85 0.25 0.71 0.21 0.71 0.64 0.67 0.96 0.09 0.44 0.81 0.54 0.93 0.34 0.29 0.64 0.02 0.78 0.85 1 0.39 0.93 0.57 0.81 0.25 -0.33 0.06 0.05

3d MAX GW DOY 0.57 0.85 0.57 0.78 0.85 0.93 0.42 0.42 0.93 0.63 0.62 0.18 0.64 0.85 0.29 0.14 0.57 0.78 1 0.34 0.39 0.64 0.71 0.26 1 0.29 0.3 -0.35

7d MIN GW 0.78 0.64 0.93 0.71 0.93 1 0.6 0.89 0.34 0.7 0.38 0.54 0.25 0.39 0.25 0.45 0.93 0.17 0.39 0.39 0.45 0.57 0.39 0.42 0.03 0.85 0.34 -0.08

7d MIN GW DOY 0.6 0.6 0.47 0.67 0.81 0.06 0.85 0.7 0.74 0.14 0.41 0.92 0.74 0.47 0.22 0.42 0.6 0.89 0.47 0.47 0.67 0.67 0.47 0.63 0.67 0.89 0.26 0.81


Table D-8: Winter seasonal analysis of Kendall’s Rank for the Skootamatta River. Correlation coefficient is above and

p-value is below the diagonal. Correlation coefficient and p-values that meet thresholds for inclusion in analysis are

shaded.

7d M

AX T

JFM

7d M

AX T

JFM

DO

Y

7d M

IN T

JFM

7d M

IN T

JFM

DO

Y

JFM

tota

l R

3d M

AX R

JFM

3d M

AX R

JFM

DO

Y

30d M

IN R

JFM

30d M

IN R

JFM

DO

Y

JFM

yie

ld

JFM

BF y

ield

3d M

AX Q

JFM

3d M

AX Q

JFM

DO

Y

7d M

IN Q

JFM

7d M

IN Q

JFM

DO

Y

3d M

AX B

F J

FM

3d M

AX B

F J

FM

DO

Y

7d M

IN B

F J

FM

7d M

IN B

F J

FM

DO

Y

3d M

AX G

W J

FM

3d M

AX G

W J

FM

DO

Y

7d M

IN G

W J

FM

7d M

IN G

W J

FM

DO

Y

7d MAX T JFM 0.21 0.18 0.09 0.36 0.39 0 0.04 0.05 0.16 -0.03 0.33 0 0.1 0.05 -0.08 -0.17 0.03 0.1 0.23 0.17 0.13 -0.08

7d MAX T JFM DOY 0.22 -0.12 0.09 0.06 0.19 0.19 -0.23 -0.12 0.07 0.04 0.15 0.08 -0.07 -0.03 0.09 -0.03 -0.06 0.05 0.28 -0.06 0.34 -0.14

7d MIN T JFM 0.29 0.48 0.13 0.13 0.31 0.12 0.29 0.02 0.13 0.2 0.13 0.15 0.41 0.12 0.05 -0.04 0.38 -0.01 0.01 0.27 -0.14 -0.37

7d MIN T JFM DOY 0.6 0.61 0.43 0.01 0.15 0.18 0.09 0.22 -0.03 0.03 0.08 -0.04 0.03 0.29 -0.02 -0.06 0.06 0.14 0.07 -0.3 0.01 0.12

JFM total R 0.03 0.74 0.47 0.96 0.38 -0.01 0.2 0.04 0.33 0.23 0.24 -0.05 0.32 -0.07 0 0.06 0.31 -0.31 0.03 0.56 -0.08 -0.49

3d MAX R JFM 0.02 0.27 0.07 0.38 0.02 0.12 0.08 0 0.16 0.03 0.3 0.06 0.14 0.17 -0.08 0 0.17 -0.04 -0.1 0.36 -0.21 -0.6

3d MAX R JFM DOY 0.98 0.27 0.47 0.3 0.96 0.49 -0.08 -0.03 -0.09 -0.01 0.09 0.29 -0.1 0.16 0.15 0.04 -0.06 0.17 0.27 -0.01 0.12 0.16

30d MIN R JFM 0.82 0.17 0.08 0.61 0.24 0.65 0.64 0.4 0.1 0.23 -0.11 -0.17 0.39 0.17 0.04 -0.05 0.31 -0.21 -0.17 0.51 -0.28 -0.48

30d MIN R JFM DOY 0.76 0.47 0.9 0.19 0.84 0.99 0.86 0.02 0.03 0.09 -0.08 -0.32 0.16 0.24 -0.1 -0.21 0.15 0.08 0.09 -0.01 0.14 0.01

JFM yield 0.35 0.69 0.47 0.85 0.05 0.35 0.6 0.55 0.85 0.48 0.46 -0.12 0.4 -0.17 0.31 -0.05 0.38 -0.2 0.26 0.47 0.05 -0.65

JFM BF yield 0.88 0.8 0.25 0.87 0.19 0.88 0.96 0.17 0.58 0 0.09 -0.17 0.55 -0.05 0.52 0.03 0.6 -0.27 0.38 0.2 0.18 -0.57

3d MAX Q JFM 0.05 0.37 0.45 0.64 0.16 0.07 0.59 0.53 0.62 0.01 0.59 0.12 0.08 -0.07 0.09 0.08 0.06 0.07 0.03 0.5 -0.23 -0.19

3d MAX Q JFM DOY 0.99 0.65 0.39 0.84 0.76 0.75 0.09 0.31 0.06 0.5 0.31 0.47 -0.07 -0.17 -0.01 0.2 -0.11 0.07 -0.21 0.42 -0.36 0.1

7d MIN Q JFM 0.57 0.67 0.01 0.88 0.06 0.43 0.58 0.02 0.34 0.02 0 0.63 0.68 0.07 0.2 0 0.91 -0.22 0.13 0.33 -0.03 -0.62

7d MIN Q JFM DOY 0.79 0.87 0.5 0.09 0.7 0.33 0.36 0.31 0.16 0.32 0.76 0.7 0.33 0.69 -0.03 -0.06 0.05 0.48 0.25 -0.15 0.14 -0.1

3d MAX BF JFM 0.65 0.6 0.78 0.93 0.99 0.63 0.39 0.82 0.56 0.06 0 0.62 0.94 0.23 0.85 0.22 0.24 -0.04 0.51 0.2 0.26 -0.41

3d MAX BF JFM DOY 0.32 0.86 0.83 0.73 0.73 0.99 0.83 0.77 0.23 0.77 0.88 0.64 0.24 0.99 0.73 0.2 0.05 -0.1 -0.34 0.36 -0.42 -0.1

7d MIN BF JFM 0.85 0.71 0.02 0.74 0.06 0.31 0.71 0.06 0.4 0.02 0 0.74 0.51 0 0.77 0.16 0.79 -0.27 0.18 0.22 0.08 -0.65

7d MIN BF JFM DOY 0.55 0.77 0.97 0.42 0.06 0.82 0.33 0.21 0.65 0.23 0.12 0.69 0.68 0.2 0 0.82 0.55 0.11 0.21 -0.31 0.34 0.49

3d MAX GW JFM 0.45 0.35 0.97 0.83 0.93 0.74 0.37 0.57 0.77 0.4 0.19 0.93 0.5 0.68 0.42 0.07 0.25 0.56 0.49 -0.11 0.74 0

3d MAX GW JFM DOY 0.58 0.85 0.38 0.32 0.05 0.22 0.96 0.07 0.96 0.1 0.52 0.08 0.15 0.26 0.61 0.52 0.23 0.46 0.29 0.72 -0.31 -0.43

7d MIN GW JFM 0.68 0.26 0.64 0.97 0.8 0.5 0.71 0.35 0.64 0.87 0.56 0.45 0.22 0.93 0.64 0.4 0.15 0.8 0.25 0 0.31 0.11

7d MIN GW JFM DOY 0.79 0.64 0.22 0.69 0.09 0.03 0.59 0.1 0.96 0.02 0.04 0.54 0.76 0.02 0.76 0.17 0.74 0.02 0.09 1 0.15 0.72


Table D-9: Spring seasonal analysis of Kendall’s Rank for the Skootamatta River. Correlation coefficient is above and


shaded.

7d M

AX T

AM

J

7d M

AX T

AM

J D

OY

7d M

IN T

AM

J

7d M

IN T

AM

J D

OY

AM

J to

tal R

3d M

AX R

AM

J

3d M

AX R

AM

J D

OY

30d M

IN R

AM

J

30d M

IN R

AM

J D

OY

AM

J yie

ld

AM

J BF y

ield

3d M

AX Q

AM

J

3d M

AX Q

AM

J D

OY

7d M

IN Q

AM

J

7d M

IN Q

AM

J D

OY

3d M

AX B

F A

MJ

3d M

AX B

F A

MJ

DO

Y

7d M

IN B

F A

MJ

7d M

IN B

F A

MJ

DO

Y

3d M

AX G

W A

MJ

3d M

AX G

W A

MJ

DO

Y

7d M

IN G

W A

MJ

7d M

IN G

W A

MJ

DO

Y

7d MAX T AMJ 0.01 0.09 -0.15 -0.23 -0.1 -0.01 -0.17 0.12 -0.03 -0.14 0.15 -0.24 -0.18 0.12 -0.16 -0.02 -0.19 0.11 0.03 -0.12 -0.36 -0.1

7d MAX T AMJ DOY 0.95 -0.11 -0.03 0.11 0.14 0.06 -0.17 -0.04 0.22 0.13 0.23 0.1 -0.01 -0.07 -0.01 0.07 -0.03 -0.09 0.13 0.01 -0.03 -0.48

7d MIN T AMJ 0.61 0.53 0.15 -0.12 -0.09 0.25 0.02 -0.13 -0.08 -0.17 0 -0.22 -0.06 -0.12 -0.09 -0.18 -0.06 -0.12 0.05 -0.12 0.23 0.07

7d MIN T AMJ DOY 0.39 0.87 0.39 -0.22 -0.17 0.14 -0.04 0.02 -0.13 -0.11 -0.01 0.02 0.02 0.16 -0.08 -0.09 0.01 0.1 0.05 -0.09 0.51 -0.1

AMJ total R 0.17 0.51 0.48 0.19 0.47 0.03 0.34 -0.13 0.47 0.41 0.12 0.29 0.3 -0.26 0.3 0.29 0.29 -0.13 0.15 0.19 -0.23 0

3d MAX R AMJ 0.54 0.4 0.6 0.32 0 -0.14 -0.09 0.05 0.4 0.32 0.3 0.1 0.01 -0.09 0.33 0.17 -0.03 0 0.41 -0.22 -0.13 0.3

3d MAX R AMJ DOY 0.94 0.72 0.14 0.41 0.88 0.43 0.24 -0.35 -0.13 -0.18 -0.23 0.09 0.23 -0.25 -0.19 -0.04 0.21 -0.25 -0.18 0.04 0.03 -0.29

30d MIN R AMJ 0.31 0.33 0.9 0.81 0.04 0.62 0.17 -0.18 0.16 0.17 -0.16 0.23 0.4 -0.14 0.12 0.09 0.42 -0.1 0.33 -0.04 0.21 -0.27

30d MIN R AMJ DOY 0.49 0.83 0.46 0.92 0.46 0.79 0.03 0.29 0.17 0.21 0.18 0.01 -0.21 0.17 0.22 0.16 -0.22 0.16 0.4 -0.23 0.14 -0.1

AMJ yield 0.87 0.2 0.63 0.44 0 0.01 0.45 0.35 0.32 0.63 0.43 0.25 0.24 -0.17 0.49 0.33 0.22 -0.06 0.59 0.01 0 -0.3

AMJ BF yield 0.42 0.44 0.31 0.52 0.01 0.05 0.3 0.34 0.22 0 0.18 0.28 0.22 -0.03 0.74 0.36 0.19 0.04 0.41 0.09 0.03 -0.27

3d MAX Q AMJ 0.39 0.17 0.98 0.93 0.47 0.07 0.19 0.36 0.29 0.01 0.28 -0.13 -0.13 -0.09 0.19 0.03 -0.14 0 0.59 -0.22 -0.15 -0.17

3d MAX Q AMJ DOY 0.15 0.57 0.21 0.9 0.08 0.57 0.62 0.18 0.95 0.14 0.1 0.44 0.35 -0.06 0.08 0.39 0.34 -0.01 0.21 0.32 0.23 -0.17

7d MIN Q AMJ 0.3 0.96 0.73 0.92 0.08 0.96 0.17 0.02 0.22 0.16 0.2 0.44 0.04 -0.42 0.1 0.18 0.9 -0.35 -0.06 0.31 -0.22 -0.3

7d MIN Q AMJ DOY 0.48 0.7 0.49 0.35 0.12 0.61 0.15 0.42 0.31 0.32 0.86 0.61 0.71 0.01 -0.02 -0.07 -0.4 0.77 -0.09 -0.3 0.42 0.21

3d MAX BF AMJ 0.35 0.95 0.61 0.63 0.07 0.05 0.28 0.47 0.2 0 0 0.26 0.65 0.56 0.89 0.22 0.06 0.03 0.46 -0.17 0.28 -0.13

3d MAX BF AMJ DOY 0.89 0.7 0.29 0.59 0.08 0.33 0.81 0.59 0.36 0.05 0.03 0.87 0.02 0.3 0.71 0.2 0.17 -0.06 0.17 0.11 -0.35 0.03

7d MIN BF AMJ 0.27 0.87 0.72 0.95 0.09 0.84 0.21 0.01 0.19 0.2 0.27 0.41 0.04 0 0.02 0.73 0.31 -0.36 -0.03 0.27 -0.21 -0.3

7d MIN BF AMJ DOY 0.53 0.61 0.48 0.55 0.46 1 0.14 0.57 0.35 0.74 0.8 0.98 0.94 0.04 0 0.85 0.72 0.03 -0.1 -0.3 0.46 0.22

3d MAX GW AMJ 0.93 0.67 0.87 0.86 0.62 0.16 0.55 0.27 0.18 0.03 0.16 0.03 0.5 0.83 0.76 0.11 0.58 0.93 0.75 -0.37 0.21 -0.1

3d MAX GW AMJ DOY 0.71 0.97 0.71 0.76 0.53 0.47 0.9 0.9 0.44 0.97 0.77 0.47 0.28 0.3 0.32 0.58 0.73 0.37 0.32 0.21 -0.22 -0.24

7d MIN GW AMJ 0.23 0.93 0.45 0.08 0.45 0.68 0.93 0.5 0.64 1 0.93 0.62 0.45 0.47 0.16 0.35 0.24 0.5 0.11 0.5 0.47 -0.2

7d MIN GW AMJ DOY 0.74 0.1 0.83 0.73 1 0.32 0.33 0.38 0.74 0.32 0.38 0.59 0.59 0.32 0.49 0.66 0.91 0.32 0.47 0.74 0.44 0.51


Table D-10: Summer seasonal analysis of Kendall’s Rank for the Skootamatta River. Correlation coefficient is above


are shaded.

7d M

AX T

JAS

7d M

AX T

JAS D

OY

7d M

IN T

JAS

7d M

IN T

JAS D

OY

JAS t

ota

l R

3d M

AX R

JAS

3d M

AX R

JAS D

OY

30d M

IN R

JAS

30d M

IN R

JAS D

OY

JAS y

ield

JAS B

F y

ield

3d M

AX Q

JAS

3d M

AX Q

JAS D

OY

7d M

IN Q

JAS

7d M

IN Q

JAS D

OY

3d M

AX B

F J

AS

3d M

AX B

F J

AS D

OY

7d M

IN B

F J

AS

7d M

IN B

F J

AS D

OY

3d M

AX G

W J

AS

3d M

AX G

W J

AS D

OY

7d M

IN G

W J

AS

7d M

IN G

W J

AS D

OY

7d MAX T JAS -0.24 0.04 0.13 -0.26 -0.07 0.06 -0.24 -0.12 -0.34 -0.29 -0.37 -0.18 -0.37 0.04 -0.23 -0.27 -0.37 -0.01 -0.14 0.07 -0.19 -0.05

7d MAX T JAS DOY 0.15 0.07 0.11 0.1 0.1 0 -0.12 0.04 -0.01 -0.02 0.01 0.16 -0.07 -0.02 -0.04 0.11 -0.03 0.03 -0.33 -0.09 -0.02 -0.25

7d MIN T JAS 0.82 0.7 -0.05 0 0.07 0.16 0.08 0.17 -0.03 -0.07 0 0.18 0.04 -0.13 -0.17 0.03 0.01 -0.14 -0.1 -0.07 -0.1 -0.28

7d MIN T JAS DOY 0.44 0.53 0.79 -0.16 -0.21 0.12 -0.22 -0.08 -0.16 -0.08 -0.2 0.02 -0.19 -0.02 -0.1 0.21 -0.22 0.08 -0.2 -0.05 -0.43 0.12

JAS total R 0.12 0.57 1 0.34 0.57 -0.09 0.3 -0.1 0.33 0.24 0.37 0.39 0.25 -0.21 0.14 0.33 0.28 -0.38 0.03 0.1 0.38 -0.1

3d MAX R JAS 0.71 0.55 0.69 0.22 0 0.01 0.08 -0.18 0.17 0.04 0.24 0.21 0.11 -0.25 0 0.23 0.13 -0.35 0.01 0.01 0.27 -0.21

3d MAX R JAS DOY 0.73 0.99 0.34 0.49 0.61 0.96 -0.1 0.09 0.04 0.07 0.09 0.12 0 -0.18 0.09 0.1 -0.03 -0.1 0 0.06 -0.09 -0.17

30d MIN R JAS 0.17 0.5 0.64 0.2 0.07 0.64 0.56 0.08 0.38 0.34 0.32 0.15 0.46 0.14 0.26 0.1 0.44 0.02 0.29 0.06 0.64 -0.09

30d MIN R JAS DOY 0.48 0.83 0.33 0.63 0.55 0.28 0.6 0.64 0.09 0.07 0.17 0.1 0.06 -0.02 0.04 -0.09 0.06 0.08 -0.09 -0.03 -0.07 -0.38

JAS yield 0.04 0.96 0.85 0.35 0.05 0.33 0.83 0.02 0.61 0.85 0.81 0.16 0.6 -0.01 0.7 0.34 0.59 -0.03 0.32 0.19 0.67 -0.21

JAS BF yield 0.09 0.9 0.67 0.63 0.16 0.8 0.7 0.04 0.7 0 0.7 0.1 0.61 0.06 0.76 0.29 0.59 0.06 0.34 0.1 0.52 -0.08

3d MAX Q JAS 0.03 0.96 0.99 0.24 0.03 0.16 0.59 0.06 0.32 0 0 0.21 0.51 -0.12 0.64 0.35 0.5 -0.09 0.33 0.12 0.62 -0.23

3d MAX Q JAS DOY 0.31 0.34 0.29 0.93 0.02 0.22 0.48 0.39 0.56 0.34 0.56 0.23 0.15 -0.31 -0.03 0.4 0.19 -0.35 -0.67 0.26 -0.22 -0.01

7d MIN Q JAS 0.03 0.7 0.81 0.27 0.14 0.53 0.99 0.01 0.73 0 0 0 0.39 0.04 0.43 0.3 0.91 0 0.25 0.07 0.47 -0.05

7d MIN Q JAS DOY 0.83 0.9 0.43 0.9 0.22 0.14 0.31 0.4 0.92 0.94 0.72 0.49 0.07 0.81 0.15 -0.42 0.01 0.74 0.3 -0.34 0.16 0.08

3d MAX BF JAS 0.18 0.82 0.32 0.56 0.43 0.99 0.61 0.13 0.83 0 0 0 0.85 0.01 0.37 0.11 0.41 0.14 0.36 -0.07 0.45 0

3d MAX BF JAS DOY 0.11 0.54 0.86 0.23 0.05 0.17 0.56 0.55 0.6 0.04 0.08 0.04 0.02 0.07 0.01 0.51 0.34 -0.29 -0.11 0.4 0.11 0.14

7d MIN BF JAS 0.02 0.88 0.94 0.19 0.09 0.45 0.86 0.01 0.72 0 0 0 0.28 0 0.96 0.01 0.04 -0.01 0.16 0.1 0.47 -0.1

7d MIN BF JAS DOY 0.96 0.85 0.42 0.63 0.02 0.04 0.55 0.93 0.64 0.87 0.74 0.58 0.03 0.99 0 0.42 0.09 0.94 0.38 -0.29 0.13 -0.04

3d MAX GW JAS 0.63 0.25 0.74 0.5 0.91 0.97 1 0.32 0.76 0.27 0.23 0.25 0.01 0.38 0.3 0.2 0.72 0.57 0.19 -0.19 0.47 -0.15

3d MAX GW JAS DOY 0.8 0.76 0.8 0.87 0.72 0.96 0.84 0.84 0.92 0.5 0.72 0.68 0.36 0.8 0.23 0.8 0.16 0.72 0.32 0.5 0.1 0.33

7d MIN GW JAS 0.52 0.94 0.74 0.13 0.17 0.34 0.76 0.01 0.82 0.01 0.06 0.02 0.46 0.09 0.57 0.11 0.72 0.09 0.65 0.09 0.72 -0.26

7d MIN GW JAS DOY 0.86 0.4 0.33 0.68 0.73 0.48 0.56 0.76 0.18 0.48 0.79 0.42 0.96 0.86 0.79 1 0.63 0.73 0.89 0.6 0.24 0.37


Table D-11: Autumn seasonal analysis of Kendall’s Rank for the Skootamatta River. Correlation coefficient is above


are shaded.

7d M

AX T

ON

D

7d M

AX T

ON

D D

OY

7d M

IN T

ON

D

7d M

IN T

ON

D D

OY

ON

D t

ota

l R

3d M

AX R

ON

D

3d M

AX R

ON

D D

OY

30d M

IN R

ON

D

30d M

IN R

ON

D D

OY

ON

D y

ield

ON

D B

F y

ield

3d M

AX Q

ON

D

3d M

AX Q

ON

D D

OY

7d M

IN Q

ON

D

7d M

IN Q

ON

D D

OY

3d M

AX B

F O

ND

3d M

AX B

F O

ND

DO

Y

7d M

IN B

F O

ND

7d M

IN B

F O

ND

DO

Y

3d M

AX G

W O

ND

3d M

AX G

W O

ND

DO

Y

7d M

IN G

W O

ND

7d M

IN G

W O

ND

DO

Y

7d MAX T OND -0.09 -0.03 -0.13 0.06 0.07 0.06 -0.09 0.05 -0.29 -0.24 -0.23 0.12 -0.32 0 -0.12 0.2 -0.31 0.05 -0.26 -0.12 -0.1 0.36

7d MAX T OND DOY 0.62 0 -0.11 -0.07 -0.04 0.08 -0.11 0.01 -0.07 -0.11 -0.03 0.06 -0.15 -0.07 -0.08 0.03 -0.19 0.09 -0.15 -0.06 -0.44 -0.15

7d MIN T OND 0.88 0.99 -0.13 0.03 -0.06 0.01 0.19 -0.03 0.04 0.15 0.01 -0.09 0.01 0.02 0.12 -0.15 0.07 0.04 -0.05 0.29 0 -0.18

7d MIN T OND DOY 0.46 0.5 0.43 0.06 0.05 0.12 0.11 -0.26 -0.18 -0.16 -0.05 0.11 -0.09 -0.05 -0.07 0.14 -0.06 -0.05 -0.33 0.11 -0.2 -0.12

OND total R 0.75 0.69 0.85 0.74 0.49 0.16 0.36 0.09 0.29 0.27 0.32 -0.08 -0.15 -0.18 0.36 -0.12 -0.15 -0.25 0.21 0.31 -0.1 -0.57

3d MAX R OND 0.69 0.8 0.72 0.78 0 0.16 0.08 0.2 0.23 0.19 0.38 -0.11 -0.1 -0.1 0.26 -0.16 -0.09 -0.01 -0.21 0.1 -0.26 -0.18

3d MAX R OND DOY 0.72 0.65 0.93 0.47 0.34 0.35 0.1 -0.21 0.04 0.04 0.17 0.29 -0.01 -0.05 0.14 0.22 0.02 -0.09 0.19 0.03 0.14 -0.01

30d MIN R OND 0.61 0.53 0.26 0.51 0.03 0.64 0.55 -0.08 0.14 0.2 0.06 0.02 -0.14 -0.03 0.2 -0.12 -0.08 -0.35 0.1 0.18 -0.1 -0.34

30d MIN R OND DOY 0.75 0.95 0.87 0.12 0.58 0.23 0.23 0.66 0.14 0.08 0.12 -0.23 0.09 -0.11 -0.03 -0.22 0.02 -0.01 -0.15 -0.18 -0.1 0.05

OND yield 0.09 0.69 0.8 0.28 0.08 0.18 0.82 0.4 0.43 0.84 0.72 -0.41 0.45 0.09 0.58 -0.45 0.43 0 0.69 0.29 0.44 -0.47

OND BF yield 0.16 0.52 0.39 0.36 0.11 0.27 0.81 0.25 0.62 0 0.62 -0.41 0.37 0.09 0.68 -0.44 0.44 0.07 0.64 0.31 0.38 -0.52

3d MAX Q OND 0.18 0.84 0.96 0.76 0.06 0.02 0.32 0.72 0.5 0 0 -0.24 0.33 0.1 0.58 -0.33 0.31 0.02 0.56 0.15 0.26 -0.34

3d MAX Q OND DOY 0.47 0.71 0.62 0.51 0.64 0.53 0.09 0.92 0.18 0.01 0.01 0.15 -0.26 -0.1 -0.21 0.55 -0.25 -0.14 -0.43 -0.33 -0.32 0.38

7d MIN Q OND 0.06 0.38 0.96 0.59 0.39 0.57 0.96 0.43 0.58 0.01 0.03 0.05 0.12 0.38 0.16 -0.23 0.82 0.13 0.51 -0.04 0.67 -0.03

7d MIN Q OND DOY 1 0.66 0.89 0.76 0.28 0.56 0.75 0.86 0.54 0.6 0.59 0.55 0.57 0.02 0.1 -0.1 0.3 0.24 0.13 -0.17 0.03 0.19

3d MAX BF OND 0.5 0.65 0.48 0.69 0.03 0.12 0.41 0.24 0.87 0 0 0 0.23 0.36 0.58 -0.27 0.24 0.08 0.44 0.15 0.08 -0.39

3d MAX BF OND DOY 0.23 0.88 0.38 0.43 0.49 0.36 0.2 0.49 0.19 0.01 0.01 0.05 0 0.18 0.56 0.1 -0.22 -0.01 -0.31 -0.24 -0.09 0.26

7d MIN BF OND 0.07 0.26 0.68 0.72 0.39 0.59 0.9 0.64 0.89 0.01 0.01 0.06 0.15 0 0.07 0.15 0.2 0.24 0.38 0.04 0.54 -0.1

7d MIN BF OND DOY 0.78 0.59 0.81 0.78 0.15 0.96 0.61 0.03 0.97 0.99 0.69 0.92 0.42 0.46 0.15 0.65 0.95 0.16 -0.18 -0.19 -0.01 0.11

3d MAX GW OND 0.4 0.63 0.87 0.28 0.5 0.5 0.53 0.74 0.62 0.01 0.02 0.04 0.15 0.07 0.66 0.14 0.3 0.19 0.56 -0.01 0.64 -0.21

3d MAX GW OND DOY 0.69 0.85 0.34 0.72 0.3 0.76 0.93 0.56 0.56 0.34 0.3 0.62 0.27 0.89 0.58 0.62 0.42 0.89 0.53 0.96 -0.2 -0.62

7d MIN GW OND 0.74 0.14 1 0.52 0.74 0.4 0.64 0.74 0.74 0.14 0.19 0.4 0.28 0.01 0.93 0.8 0.76 0.06 0.96 0.02 0.5 0.05

7d MIN GW OND DOY 0.22 0.63 0.55 0.7 0.04 0.55 0.97 0.26 0.87 0.11 0.07 0.26 0.2 0.93 0.54 0.19 0.39 0.74 0.72 0.5 0.02 0.87


Table D-12: Occurrences of probable correlation where Spearman’s Rank and Kendall’s Rank indicate parameter

correlation but linear regression does not for Skootamatta River.

Spearman's Rank Kendall's Rank Linear Regression

Time scale Parameter 1 Parameter 2 ρ p-value τ p-value R² p-value slope sign

Annual PET Water yield -0.74 0.00 -0.55 0.00 0.41 0.00 +

JFM Total R 3d MAX GW DOY 0.63 0.02 0.56 0.05 0.28 0.04 +

JAS Total R 3d MAX R 0.75 0.00 0.57 0.00 0.47 0.00 +

3d MAX Q 7d MIN Q 0.68 0.00 0.51 0.00 0.40 0.00 +

3d MAX Q 3d MAX BF 0.79 0.00 0.64 0.00 0.49 0.00 +

3d MAX Q 7d MIN GW 0.76 0.00 0.62 0.02 0.33 0.02 +

OND 3d MAX Q 3d MAX BF 0.75 0.00 0.58 0.00 0.49 0.00 +


Appendix E. Innisfil Creek Complete Analysis Results

Table E-1: Results from Mann-Kendall trend analysis for Innisfil Creek. Shading


warning (W).


Annual Mean T 0.111 0.347 7d MAX T 0.016 0.902 7d MAX T DOY 0.305 0.010 VC

7d MAX T JFM -0.092 0.438 7d MAX T JFM DOY -0.092 0.459 7d MAX T AMJ 0.067 0.577 7d MAX T AMJ DOY 0.166 0.167 7d MAX T JAS 0.025 0.838 7d MAX T JAS DOY -0.051 0.672 7d MAX T OND 0.117 0.320 7d MAX T OND DOY 0.034 0.793 7d MIN T 0.089 0.454 7d MIN T DOY 0.029 0.817 7d MIN T JFM 0.048 0.693 7d MIN T JFM DOY 0.090 0.453 7d MIN T AMJ -0.124 0.294 7d MIN T AMJ DOY -0.179 0.141 7d MIN T JAS 0.187 0.111 7d MIN T JAS DOY -0.061 0.621 7d MIN T OND 0.103 0.383 7d MIN T OND DOY -0.065 0.594 Annual Total P 0.016 0.902 JFM Total R -0.056 0.643 AMJ Total R 0.146 0.215 JAS Total R 0.070 0.551 OND Total R -0.130 0.270 3d MAX R -0.022 0.859 3d MAX R DOY 0.065 0.586 3d MAX R JFM 0.044 0.713 3d MAX R JFM DOY 0.110 0.354 3d MAX R AMJ 0.003 0.989 3d MAX R AMJ DOY 0.045 0.713 3d MAX R JAS -0.070 0.558 3d MAX R JAS DOY 0.078 0.513 3d MAX R OND -0.083 0.487



3d MAX R OND DOY 0.223 0.058 W

30d MIN R 0.159 0.216 30d MIN R DOY 0.163 0.169 30d MIN R JFM 0.141 0.273 30d MIN R JFM DOY 0.048 0.693 30d MIN R AMJ 0.025 0.838 30d MIN R AMJ DOY -0.107 0.368 30d MIN R JAS -0.016 0.902 30d MIN R JAS DOY 0.160 0.177 30d MIN R OND -0.011 0.935 30d MIN R OND DOY -0.123 0.310 Annual PET 0.124 0.294 Annual P-PET -0.060 0.614 Annual Richards-Baker Flashiness Index -0.077 0.743 Annual 10:90 exceedance -0.626 0.002 VC

Annual water yield 0.121 0.584 JFM yield 0.055 0.827 AMJ yield 0.010 1.000 JAS yield 0.118 0.537 OND yield -0.015 0.967 3d MAX Q 0.143 0.511 3d MAX Q DOY -0.077 0.743 3d MAX Q JFM -0.055 0.827 3d MAX Q JFM DOY 0.121 0.584 3d MAX Q AMJ 0.096 0.656 3d MAX Q AMJ DOY -0.067 0.766 3d MAX Q JAS 0.147 0.434 3d MAX Q JAS DOY -0.037 0.869 3d MAX Q OND 0.029 0.902 3d MAX Q OND DOY 0.038 0.869 7d MIN Q 0.516 0.012 VC

7d MIN Q DOY -0.011 1.000 7d MIN Q JFM 0.187 0.381 7d MIN Q JFM DOY 0.425 0.042 PT

7d MIN Q AMJ -0.029 0.921 7d MIN Q AMJ DOY -0.069 0.765 7d MIN Q JAS 0.176 0.343 7d MIN Q JAS DOY -0.118 0.537 7d MIN Q OND 0.044 0.837 7d MIN Q OND DOY -0.180 0.341



Annual BF yield 0.231 0.274 JFM BF yield 0.099 0.661 AMJ BF yield 0.219 0.276 JAS BF yield 0.132 0.484 OND BF yield 0.088 0.650 3d MAX BF 0.187 0.381 3d MAX BF DOY -0.121 0.584 3d MAX BF JFM 0.099 0.661 3d MAX BF JFM DOY -0.034 0.912 3d MAX BF AMJ 0.067 0.767 3d MAX BF AMJ DOY -0.020 0.960 3d MAX BF JAS 0.044 0.837 3d MAX BF JAS DOY 0.298 0.126 3d MAX BF OND 0.118 0.537 3d MAX BF OND DOY -0.030 0.901 7d MIN BF 0.560 0.006 VC

7d MIN BF DOY -0.011 1.000 7d MIN BF JFM 0.165 0.443 7d MIN BF JFM DOY 0.408 0.056 W

7d MIN BF AMJ 0.086 0.692 7d MIN BF AMJ DOY 0.065 0.811 7d MIN BF JAS 0.194 0.303 7d MIN BF JAS DOY -0.088 0.650 7d MIN BF OND 0.147 0.434 7d MIN BF OND DOY 0.110 0.608 W323-2 Annual Mean GW level -0.156 0.592 W323-2 3d MAX GW -0.200 0.436 W323-2 3d MAX GW DOY 0.367 0.138 W323-2 3d MAX GW JFM 0.242 0.304 W323-2 3d MAX GW JFM DOY 0.099 0.721 W323-2 3d MAX GW AMJ -0.091 0.732 W323-2 3d MAX GW AMJ DOY 0.046 0.891 W323-2 3d MAX GW JAS -0.030 0.945 W323-2 3d MAX GW JAS DOY 0.051 0.885 W323-2 3d MAX GW OND 0.055 0.876 W323-2 3d MAX GW OND DOY -0.130 0.638 W323-2 7d MIN GW -0.156 0.592 W323-2 7d MIN GW DOY 0.600 0.020 VC

W323-2 7d MIN GW JFM 0.242 0.304 W323-2 7d MIN GW JFM DOY 0.339 0.148



W323-2 7d MIN GW AMJ 0.121 0.631 W323-2 7d MIN GW AMJ DOY 0.152 0.585 W323-2 7d MIN GW JAS 0.061 0.837 W323-2 7d MIN GW JAS DOY 0.017 1.000 W323-2 7d MIN GW OND 0.055 0.876 W323-2 7d MIN GW OND DOY 0.648 0.008 VC

W323-3 3d MAX GW JFM 0.244 0.371 W323-3 3d MAX GW JFM DOY 0.349 0.202 W323-3 3d MAX GW AMJ 0.018 1.000 W323-3 3d MAX GW AMJ DOY 0.018 1.000 W323-3 3d MAX GW JAS 0.182 0.451 W323-3 3d MAX GW JAS DOY -0.174 0.506 W323-3 3d MAX GW OND 0.152 0.537 W323-3 3d MAX GW OND DOY -0.107 0.680 W323-3 7d MIN GW JFM 0.333 0.211 W323-3 7d MIN GW JFM DOY -0.180 0.530 W323-3 7d MIN GW AMJ 0.236 0.350 W323-3 7d MIN GW AMJ DOY 0.019 1.000 W323-3 7d MIN GW JAS 0.212 0.373 W323-3 7d MIN GW JAS DOY -0.050 0.886 W323-3 7d MIN GW OND 0.212 0.373 W323-3 7d MIN GW OND DOY 0.246 0.301 W323-4 3d MAX GW JFM 0.467 0.074 W

W323-4 3d MAX GW JFM DOY 0.046 0.928 W323-4 3d MAX GW JAS 0.244 0.371 W323-4 3d MAX GW JAS DOY -0.256 0.385 W323-4 3d MAX GW OND 0.273 0.276 W323-4 3d MAX GW OND DOY 0.404 0.101 W323-4 7d MIN GW JFM 0.422 0.107 W323-4 7d MIN GW JFM DOY -0.218 0.476 W323-4 7d MIN GW JAS 0.111 0.721 W323-4 7d MIN GW JAS DOY -0.289 0.283 W323-4 7d MIN GW OND 0.236 0.350 W323-4 7d MIN GW OND DOY -0.122 0.680


Table E-2: Annual analysis of Spearman’s Rank for Innisfil Creek. Correlation coefficient is above and p-values are

below the diagonal. Correlation coefficient and p-values that meet thresholds for inclusion in analysis are shaded.

Mean T

Tota

l P

PET

P-P

ET

7d M

AX T

7d M

AX T

DO

Y

7d M

IN T

7d M

IN T

DO

Y

3d M

AX R

3d M

AX R

DO

Y

30d M

IN R

30d M

IN R

DO

Y

RBI

10:9

0 e

xceedance

Annual yie

ld

Annual BF y

ield

3d M

AX Q

3d M

AX Q

DO

Y

7d M

IN Q

7d M

IN Q

DO

Y

3d M

AX B

F

3d M

AX B

F D

OY

7d M

IN B

F

7d M

IN B

F D

OY

323-2

GW

323-2

3d M

AX G

W

323-2

3d M

AX G

W D

OY

323-2

7d M

IN G

W

323-2

7d M

IN G

W D

OY

Mean T -0.24 0.89 -0.47 0.43 -0.05 0.53 -0.12 -0.13 0.37 0.59 -0.04 -0.05 0.44 -0.36 -0.23 -0.46 0.05 -0.63 -0.37 -0.16 -0.3 -0.61 -0.35 -0.45 -0.46 0.11 -0.25 0.36

Total P 0.15 -0.45 0.95 -0.55 0.21 0.02 -0.21 0.43 0.04 -0.14 -0.11 0.28 -0.26 0.84 0.71 0.82 -0.35 0.48 0.08 0.42 0.06 0.47 0.26 -0.01 0.3 -0.74 -0.24 -0.83

PET 0 0.01 -0.68 0.52 -0.06 0.3 -0.07 -0.2 0.28 0.47 0.06 -0.43 0.32 -0.52 -0.38 -0.6 0.24 -0.56 -0.48 -0.29 -0.11 -0.6 -0.46 -0.37 -0.54 0.28 -0.1 0.75

P-PET 0 0 0 -0.57 0.19 -0.04 -0.11 0.38 -0.01 -0.24 -0.06 0.32 -0.29 0.82 0.67 0.82 -0.3 0.53 0.19 0.42 0.09 0.53 0.33 0.24 0.45 -0.52 -0.05 -0.83

7d MAX T 0.01 0 0 0 -0.12 0.13 0.21 -0.31 0.14 0.47 0.24 -0.16 0.38 -0.13 -0.02 -0.27 0.18 -0.48 -0.4 0.01 -0.23 -0.47 -0.26 -0.37 -0.45 -0.16 0.03 -0.04

7d MAX T DOY 0.75 0.23 0.72 0.26 0.49 -0.01 0.1 0.29 -0.02 -0.03 0.12 0.14 -0.05 -0.11 -0.05 0.06 0.03 0.02 0.67 0.06 -0.25 0.11 0.5 -0.3 -0.27 0.22 -0.09 -0.15

7d MIN T 0 0.92 0.07 0.81 0.44 0.97 0.08 -0.09 0.35 0.43 0.15 0.41 0.37 0.18 0.21 0.07 -0.16 -0.32 -0.09 0.29 -0.34 -0.23 -0.12 -0.1 0.15 -0.38 -0.3 -0.14

7d MIN T DOY 0.49 0.21 0.69 0.52 0.23 0.58 0.64 -0.15 0.05 0.24 0.42 0.24 0.08 -0.25 -0.37 -0.05 0.45 -0.1 0.44 -0.22 0.56 0.02 0.34 -0.66 -0.43 0.04 -0.84 0.04

3d MAX R 0.45 0.01 0.25 0.02 0.06 0.09 0.58 0.4 -0.09 -0.22 -0.24 -0.03 0.12 0.53 0.38 0.51 -0.28 0.16 0.05 0.4 0.1 0.11 0.09 0.44 0.73 -0.34 0.12 -0.72

3d MAX R DOY 0.03 0.83 0.1 0.93 0.42 0.93 0.03 0.76 0.62 0.09 0.04 0.02 -0.04 -0.09 0.08 -0.3 0 -0.13 -0.31 0.03 -0.44 0 -0.14 -0.24 -0.36 0.12 -0.04 0.16

30d MIN R 0 0.4 0 0.15 0 0.86 0.01 0.15 0.2 0.62 0.28 0.09 0.14 0.03 0.04 0 0.12 -0.25 -0.22 -0.1 0.06 -0.29 -0.12 -0.68 -0.4 -0.12 -0.68 -0.02

30d MIN R DOY 0.83 0.54 0.72 0.72 0.16 0.5 0.39 0.01 0.17 0.81 0.1 0.08 -0.35 -0.03 -0.02 0.15 -0.25 0.11 -0.08 -0.43 0.07 0.09 -0.13 -0.41 -0.44 -0.02 -0.39 -0.1

RBI 0.85 0.33 0.13 0.27 0.58 0.64 0.14 0.4 0.92 0.96 0.76 0.78 -0.12 0.35 0.31 0.2 -0.53 0.28 0.49 -0.09 -0.24 0.32 0.53 0.33 0.3 0.02 0.29 -0.69

10:90 exceedance 0.11 0.37 0.27 0.31 0.19 0.86 0.19 0.78 0.69 0.89 0.64 0.22 0.68 -0.34 -0.4 -0.38 0.31 -0.88 -0.3 0.08 0.16 -0.88 -0.32 -0.02 0.15 -0.38 -0.19 -0.19

Annual yield 0.21 0 0.06 0 0.66 0.7 0.54 0.39 0.05 0.77 0.93 0.91 0.21 0.24 0.96 0.78 -0.47 0.64 -0.01 0.64 -0.22 0.61 0.19 0.52 0.75 -0.65 0.17 -0.71

Annual BF yield 0.44 0 0.19 0.01 0.95 0.87 0.46 0.19 0.17 0.79 0.88 0.96 0.29 0.16 0 0.71 -0.49 0.66 -0.1 0.7 -0.45 0.64 0.07 0.69 0.82 -0.55 0.48 -0.74

3d MAX Q 0.09 0 0.02 0 0.36 0.85 0.81 0.86 0.06 0.3 0.99 0.6 0.49 0.19 0 0 -0.43 0.56 0.16 0.54 -0.11 0.56 0.09 0.1 0.38 -0.82 -0.19 -0.86

3d MAX Q DOY 0.88 0.23 0.42 0.3 0.54 0.92 0.58 0.11 0.33 0.99 0.67 0.39 0.05 0.28 0.09 0.07 0.12 -0.36 0.02 0 0.56 -0.33 0.02 -0.57 -0.47 -0.13 -0.6 0.45

7d MIN Q 0.02 0.08 0.04 0.05 0.08 0.95 0.26 0.74 0.59 0.66 0.39 0.7 0.33 0 0.01 0.01 0.04 0.2 0.31 0.23 -0.13 0.97 0.37 0.45 0.4 -0.08 0.38 -0.19

7d MIN Q DOY 0.19 0.79 0.08 0.51 0.16 0.01 0.76 0.12 0.85 0.29 0.44 0.78 0.08 0.3 0.97 0.73 0.59 0.93 0.29 -0.22 0.19 0.38 0.87 -0.24 -0.23 0.18 -0.26 -0.17

3d MAX BF 0.58 0.14 0.32 0.13 0.98 0.85 0.32 0.45 0.16 0.91 0.74 0.12 0.76 0.79 0.01 0.01 0.05 0.99 0.44 0.45 -0.34 0.27 -0.21 0.57 0.7 -0.73 0.33 -0.43

3d MAX BF DOY 0.3 0.83 0.71 0.77 0.43 0.4 0.24 0.04 0.74 0.12 0.84 0.82 0.42 0.57 0.45 0.11 0.7 0.04 0.65 0.52 0.23 -0.2 0.25 -0.57 -0.42 -0.07 -0.76 0.26

7d MIN BF 0.02 0.09 0.02 0.05 0.09 0.7 0.43 0.95 0.71 0.99 0.31 0.77 0.27 0 0.02 0.01 0.04 0.25 0 0.19 0.34 0.48 0.42 0.45 0.35 -0.05 0.38 -0.19

7d MIN BF DOY 0.23 0.37 0.1 0.25 0.37 0.07 0.68 0.24 0.76 0.64 0.67 0.66 0.05 0.26 0.52 0.81 0.76 0.95 0.19 0 0.46 0.38 0.14 -0.24 -0.23 0.18 -0.26 -0.17

323-2 GW 0.19 0.99 0.29 0.51 0.29 0.4 0.78 0.04 0.2 0.51 0.03 0.24 0.42 0.96 0.18 0.06 0.82 0.14 0.26 0.57 0.14 0.14 0.26 0.57 0.87 0.01 0.84 -0.25

323-2 3d MAX GW 0.15 0.37 0.09 0.16 0.17 0.42 0.65 0.19 0.01 0.27 0.22 0.18 0.43 0.7 0.02 0.01 0.31 0.21 0.29 0.55 0.04 0.26 0.36 0.55 0 -0.23 0.56 -0.49

323-2 3d MAX GW DOY 0.74 0.01 0.4 0.1 0.63 0.51 0.25 0.91 0.31 0.72 0.72 0.95 0.97 0.31 0.06 0.12 0.01 0.73 0.83 0.64 0.02 0.86 0.9 0.64 0.97 0.5 0.11 0.66

323-2 7d MIN GW 0.49 0.51 0.78 0.88 0.93 0.8 0.4 0 0.75 0.91 0.03 0.26 0.49 0.65 0.69 0.23 0.65 0.12 0.35 0.53 0.42 0.03 0.35 0.53 0 0.09 0.76 -0.1

323-2 7d MIN GW DOY 0.31 0 0.01 0 0.91 0.68 0.7 0.91 0.02 0.65 0.96 0.78 0.06 0.65 0.05 0.04 0.01 0.26 0.65 0.69 0.29 0.53 0.65 0.69 0.49 0.15 0.04 0.78


Table E-3: Winter seasonal analysis of Spearman’s Rank for the Innisfil Creek. Correlation coefficient is above and p-

value is below the diagonal. Correlation coefficient and p-values that meet thresholds for inclusion in analysis are

shaded. Blank cells indicate insufficient data for analysis.

Tota

l R J

FM

7d M

AX T

JFM

7d M

AX T

JFM

DO

Y

7d M

IN T

JFM

7d M

IN T

JFM

DO

Y

3d M

AX R

JFM

3d M

AX R

JFM

DO

Y

30d M

IN R

JFM

30d M

IN R

JFM

DO

Y

wate

r yie

ld J

FM

BF y

ield

JFM

3d M

AX Q

JFM

3d M

AX Q

JFM

DO

Y

7d M

IN Q

JFM

7d M

IN Q

JFM

DO

Y

3d M

AX B

F J

FM

3d M

AX B

F J

FM

DO

Y

7d M

IN B

F J

FM

7d M

IN B

F J

FM

DO

Y

323-2

3d M

AX G

W J

FM

323-2

3d M

AX G

W J

FM

DO

Y

323-2

7d M

IN G

W J

FM

323-2

7d M

IN G

W J

FM

DO

Y

323-3

3d M

AX G

W J

FM

323-3

3d M

AX G

W J

FM

DO

Y

323-3

7d M

IN G

W J

FM

323-3

7d M

IN G

W J

FM

DO

Y

323-4

3d M

AX G

W J

FM

323-4

3d M

AX G

W J

FM

DO

Y

323-4

7d M

IN G

W J

FM

323-4

7d M

IN G

W J

FM

DO

Y

Total R JFM 0.2 0.14 0.14 -0.09 0.47 0.02 0.05 -0.36 0.68 0.48 0.75 -0.63 0.42 -0.13 0.2 -0.16 0.39 -0.44 -0.42 0.57 -0.56 -0.48 -0.18 0.15 -0.49 -0.12 -0.66 0.75 -0.67 0.02

7d MAX T JFM 0.24 0.17 0.33 0.11 0.05 0.06 0.16 0.13 0.17 -0.01 0.31 -0.35 0.01 0.14 -0.28 -0.01 0 0.18 -0.17 0.21 -0.01 -0.08 -0.12 0.53 -0.12 -0.04 -0.16 -0.14 -0.2 0.16

7d MAX T JFM DOY 0.42 0.33 0.05 0.02 0.02 0.14 -0.1 0.04 0.23 0.04 0.66 -0.16 -0.02 0.33 0.05 -0.03 0.07 0.12 -0.1 0.25 -0.04 -0.25 0.08 -0.17 0.02 0.09 -0.27 -0.14 -0.21 0.2

7d MIN T JFM 0.4 0.05 0.77 0.11 -0.2 0.22 0.45 0.14 0.49 0.52 0.16 -0.29 0.39 -0.35 0.27 -0.3 0.39 -0.27 -0.01 0.36 -0.01 -0.57 0.03 0.65 -0.09 -0.64 -0.1 -0.21 -0.12 0.38

7d MIN T JFM DOY 0.59 0.53 0.91 0.53 0.19 0.24 0.2 0.26 -0.3 -0.43 -0.14 0.08 -0.42 0.01 -0.47 0.5 -0.44 0 -0.64 0.21 -0.69 0.05 -0.68 -0.27 -0.55 0.17 -0.37 0.57 -0.43 -0.18

3d MAX R JFM 0 0.78 0.91 0.25 0.27 0.2 -0.36 0.17 0.28 0.05 0.44 -0.43 -0.03 -0.38 0.01 -0.01 -0.13 -0.33 -0.24 0.05 -0.47 -0.3 -0.33 -0.13 -0.65 -0.14 -0.82 0.71 -0.78 -0.08

3d MAX R JFM DOY 0.93 0.72 0.42 0.19 0.15 0.24 -0.13 0.19 -0.03 -0.08 0.03 0.29 -0.16 0.17 -0.09 0.06 -0.12 0.11 0.19 0.44 0.23 -0.04 0.33 0.45 0.25 -0.06 0.31 0.08 0.26 -0.27

30d MIN R JFM 0.75 0.35 0.56 0.01 0.24 0.03 0.46 0.12 0.28 0.38 0.04 -0.31 0.47 0.13 -0.09 -0.23 0.54 -0.15 -0.32 0.62 -0.27 -0.33 -0.03 0.28 0.04 -0.17 -0.11 -0.03 -0.18 0.57

30d MIN R JFM DOY 0.03 0.44 0.8 0.41 0.13 0.32 0.27 0.47 -0.18 -0.13 -0.33 -0.45 -0.01 -0.07 -0.4 -0.32 -0.11 0.12 0.29 -0.25 0.33 0.04 -0.21 -0.33 0.1 0.11 -0.3 -0.46 -0.28 0.69

water yield JFM 0.01 0.56 0.42 0.08 0.31 0.33 0.92 0.33 0.54 0.91 0.75 -0.4 0.72 -0.15 0.69 -0.4 0.68 -0.35 0.14 0.55 -0.04 -0.55

BF yield JFM 0.08 0.97 0.88 0.06 0.13 0.88 0.78 0.18 0.65 0 0.53 -0.37 0.89 -0.11 0.74 -0.59 0.85 -0.39 0.38 0.64 0.22 -0.7

3d MAX Q JFM 0 0.29 0.01 0.58 0.64 0.12 0.92 0.88 0.25 0 0.05 -0.18 0.31 0.01 0.58 -0.11 0.31 -0.2 -0.16 0.54 -0.21 -0.61

3d MAX Q JFM DOY 0.02 0.23 0.58 0.32 0.78 0.12 0.31 0.28 0.11 0.15 0.2 0.54 -0.53 0.28 0.11 0.58 -0.49 0.22 0.01 -0.15 0.18 0.27

7d MIN Q JFM 0.14 0.98 0.96 0.16 0.14 0.92 0.59 0.09 0.97 0 0 0.29 0.05 0.01 0.46 -0.73 0.98 -0.23 0.59 0.5 0.45 -0.7

7d MIN Q JFM DOY 0.66 0.64 0.24 0.22 0.97 0.18 0.56 0.65 0.82 0.61 0.7 0.97 0.34 0.98 -0.14 0.28 0.09 0.63 -0.09 -0.1 0.23 0.31

3d MAX BF JFM 0.49 0.33 0.87 0.35 0.09 0.97 0.76 0.76 0.16 0.01 0 0.03 0.71 0.09 0.62 -0.26 0.42 -0.37 0.3 0.42 0.1 -0.67

3d MAX BF JFM DOY 0.58 0.97 0.91 0.29 0.07 0.97 0.85 0.42 0.26 0.15 0.03 0.72 0.03 0 0.33 0.36 -0.72 0.15 -0.77 -0.57 -0.62 0.66

7d MIN BF JFM 0.16 0.99 0.82 0.16 0.12 0.67 0.69 0.05 0.71 0.01 0 0.27 0.08 0 0.77 0.14 0 -0.17 0.53 0.55 0.44 -0.71

7d MIN BF JFM DOY 0.12 0.53 0.68 0.35 0.99 0.24 0.7 0.61 0.69 0.22 0.16 0.5 0.45 0.44 0.02 0.2 0.61 0.55 0.2 -0.18 0.42 0.49

323-2 3d MAX GW JFM 0.17 0.59 0.75 0.98 0.02 0.46 0.56 0.31 0.35 0.7 0.28 0.65 0.99 0.07 0.8 0.4 0.01 0.12 0.57 -0.11 0.93 -0.24

323-2 3d MAX GW JFM DOY 0.05 0.51 0.44 0.25 0.5 0.88 0.15 0.03 0.43 0.1 0.05 0.11 0.68 0.14 0.79 0.23 0.09 0.1 0.63 0.74 -0.2 -0.51

323-2 7d MIN GW JFM 0.06 0.98 0.91 0.98 0.01 0.12 0.47 0.4 0.3 0.91 0.53 0.56 0.63 0.19 0.53 0.78 0.06 0.2 0.22 0 0.53 -0.06

323-2 7d MIN GW JFM DOY 0.11 0.8 0.44 0.05 0.87 0.35 0.9 0.29 0.9 0.1 0.03 0.06 0.44 0.03 0.38 0.03 0.04 0.02 0.15 0.46 0.09 0.85

323-3 3d MAX GW JFM 0.63 0.75 0.83 0.93 0.03 0.35 0.35 0.93 0.56 0.22 0.88 -0.38

323-3 3d MAX GW JFM DOY 0.67 0.12 0.63 0.04 0.44 0.72 0.19 0.44 0.35 0.55 -0.02 -0.53

323-3 7d MIN GW JFM 0.15 0.75 0.96 0.8 0.1 0.04 0.49 0.91 0.78 0 0.96 -0.19

323-3 7d MIN GW JFM DOY 0.75 0.92 0.8 0.05 0.64 0.7 0.87 0.63 0.76 0.28 0.12 0.6

323-4 3d MAX GW JFM 0.04 0.65 0.44 0.78 0.3 0 0.38 0.76 0.4 -0.48 0.99 -0.34

323-4 3d MAX GW JFM DOY 0.01 0.7 0.71 0.55 0.09 0.02 0.83 0.92 0.18 0.16 -0.5 -0.45

323-4 7d MIN GW JFM 0.03 0.58 0.57 0.75 0.21 0.01 0.48 0.61 0.43 0 0.14 -0.34

323-4 7d MIN GW JFM DOY 0.96 0.65 0.59 0.28 0.63 0.84 0.45 0.08 0.03 0.33 0.19 0.33


Table E-4: Spring seasonal analysis of Spearman’s Rank for the Innisfil Creek. Correlation coefficient is above and p-



AM

J to

tal R

7d M

AX T

AM

J

7d M

AX T

AM

J D

OY

7d M

IN T

AM

J

7d M

IN T

AM

J D

OY

3d M

AX R

AM

J

3d M

AX R

AM

J D

OY

30d M

IN R

AM

J

30d M

IN R

AM

J D

OY

AM

J yie

ld

AM

J BF y

ield

3d M

AX Q

AM

J

3d M

AX Q

AM

J D

OY

7d M

IN Q

AM

J

7d M

IN Q

AM

J D

OY

3d M

AX B

F A

MJ

3d M

AX B

F A

MJ

DO

Y

7d M

IN B

F A

MJ

7d M

IN B

F A

MJ

DO

Y

323-2

3d M

AX G

W A

MJ

323-2

3d M

AX G

W A

MJ

DO

Y

323-2

7d M

IN G

W A

MJ

323-2

7d M

IN G

W A

MJ

DO

Y

323-3

3d M

AX G

W A

MJ

323-3

3d M

AX G

W A

MJ

DO

Y

323-3

7d M

IN G

W A

MJ

323-3

7d M

IN G

W A

MJ

DO

Y

AMJ total R -0.22 0.43 -0.18 -0.27 0.59 0.1 0.48 -0.15 0.85 0.45 0.75 0.02 0.73 -0.72 0.3 0.29 0.69 -0.28 0.48 -0.44 0.03 -0.41 0.19 0.32 -0.06 -0.30

7d MAX T AMJ 0.21 0.18 0.26 -0.15 -0.2 0.15 -0.22 -0.11 -0.2 -0.24 -0.13 -0.29 -0.28 0.24 -0.03 -0.28 -0.31 0.15 -0.2 0.19 -0.01 -0.02 -0.01 -0.66 0.1 -0.23

7d MAX T AMJ DOY 0.01 0.3 -0.15 0.01 0.38 0.11 0.36 -0.21 0.45 0.13 0.36 -0.31 0.3 -0.29 0.25 -0.13 0.29 0.12 0.63 0.02 -0.05 -0.29 0.49 0.17 -0.01 -0.51

7d MIN T AMJ 0.29 0.13 0.37 0.2 -0.12 0.28 -0.14 -0.12 0.18 0.17 0.19 -0.01 0.1 0.29 -0.18 0.17 0.13 0.26 0.17 -0.15 0.07 -0.06 0.25 -0.28 0.19 -0.26

7d MIN T AMJ DOY 0.11 0.38 0.95 0.24 0.01 0.29 -0.08 -0.09 0.03 -0.01 -0.1 -0.11 0.09 0.32 -0.31 0.31 0.12 -0.08 -0.04 0.32 -0.13 -0.1 0.04 -0.14 -0.14 -0.24

3d MAX R AMJ 0 0.24 0.02 0.5 0.94 -0.11 0.08 -0.14 0.65 0.28 0.71 0.04 0.4 -0.4 0.26 0.25 0.29 0.07 0.66 -0.08 -0.08 0.13 0.35 0.64 -0.32 -0.56

3d MAX R AMJ DOY 0.55 0.38 0.51 0.1 0.09 0.52 -0.14 -0.24 0.03 0.1 -0.12 0.67 0.6 -0.35 -0.43 0.21 0.64 -0.25 -0.15 0.18 0.32 0.21 0.17 0.07 0.68 0.3

30d MIN R AMJ 0 0.2 0.03 0.41 0.63 0.63 0.43 0 0.42 0.62 0.22 0.01 0.59 0.01 0.02 0.31 0.42 0.19 0.71 0.04 -0.08 -0.45 0.58 0.3 0.06 -0.48

30d MIN R AMJ DOY 0.39 0.52 0.22 0.48 0.62 0.41 0.16 0.99 0.07 0.24 0.21 -0.57 -0.24 0.27 0.33 0.07 -0.27 0.14 0.36 -0.13 0.33 -0.17 0.05 0.18 -0.24 -0.23

AMJ yield 0 0.47 0.09 0.52 0.92 0.01 0.91 0.11 0.8 0.69 0.93 -0.11 0.65 -0.46 0.18 0.48 0.64 -0.18 0.6 -0.28 -0.19 -0.35

AMJ BF yield 0.09 0.38 0.66 0.54 0.97 0.31 0.72 0.01 0.38 0 0.61 -0.04 0.55 -0.19 0.41 0.22 0.49 0.04 0.64 -0.05 -0.12 -0.66

3d MAX Q AMJ 0 0.64 0.19 0.5 0.72 0 0.68 0.43 0.45 0 0.02 -0.26 0.49 -0.31 0.22 0.33 0.5 0 0.56 -0.08 -0.09 -0.21

3d MAX Q AMJ DOY 0.93 0.3 0.27 0.97 0.69 0.89 0.01 0.97 0.03 0.71 0.88 0.35 0.25 -0.44 -0.31 0.31 0.18 -0.36 -0.32 0.09 -0.16 0.42

7d MIN Q AMJ 0 0.31 0.28 0.71 0.75 0.14 0.02 0.02 0.39 0.01 0.04 0.07 0.36 -0.58 0 0.35 0.9 -0.25 0.52 -0.14 0.18 -0.16

7d MIN Q AMJ DOY 0 0.39 0.29 0.29 0.24 0.14 0.2 0.96 0.33 0.08 0.5 0.26 0.1 0.02 -0.29 -0.16 -0.51 0.72 0.08 0.62 0.09 0.24

3d MAX BF AMJ 0.28 0.92 0.38 0.52 0.26 0.35 0.11 0.95 0.23 0.52 0.12 0.43 0.26 0.99 0.3 -0.51 -0.1 0.01 0.04 -0.37 -0.3 -0.77

3d MAX BF AMJ DOY 0.29 0.32 0.65 0.53 0.26 0.36 0.44 0.27 0.81 0.07 0.43 0.23 0.26 0.2 0.56 0.05 0.33 -0.35 0.38 -0.1 0.18 0.26

7d MIN BF AMJ 0 0.26 0.29 0.64 0.67 0.29 0.01 0.12 0.34 0.01 0.07 0.06 0.52 0 0.05 0.72 0.24 -0.24 0.27 -0.14 -0.05 -0.03

7d MIN BF AMJ DOY 0.31 0.59 0.66 0.35 0.78 0.79 0.36 0.49 0.61 0.52 0.89 1 0.19 0.38 0 0.97 0.2 0.39 0.37 0.51 -0.18 0.41

323-2 3d MAX GW AMJ 0.12 0.54 0.03 0.6 0.91 0.02 0.63 0.01 0.26 0.07 0.05 0.09 0.36 0.13 0.83 0.91 0.29 0.45 0.29 0.15 0.32 -0.11

323-2 3d MAX GW AMJ DOY 0.15 0.55 0.95 0.65 0.32 0.81 0.59 0.9 0.69 0.43 0.88 0.83 0.8 0.7 0.05 0.29 0.79 0.7 0.13 0.63 0.13 0.26

323-2 7d MIN GW AMJ 0.91 0.98 0.89 0.83 0.69 0.81 0.31 0.81 0.3 0.6 0.75 0.8 0.66 0.63 0.8 0.4 0.61 0.88 0.62 0.31 0.7 -0.06

323-2 7d MIN GW AMJ DOY 0.19 0.94 0.35 0.87 0.76 0.68 0.51 0.14 0.59 0.32 0.04 0.57 0.23 0.65 0.51 0.01 0.47 0.93 0.24 0.73 0.42 0.85

323-3 3d MAX GW AMJ 0.57 0.98 0.13 0.47 0.9 0.3 0.61 0.06 0.89 0.27 0.63 -0.56

323-3 3d MAX GW AMJ DOY 0.34 0.03 0.62 0.4 0.68 0.04 0.84 0.37 0.59 0.42 -0.17 -0.38

323-3 7d MIN GW AMJ 0.85 0.77 0.98 0.57 0.68 0.34 0.02 0.85 0.48 0.04 0.61 0.05

323-3 7d MIN GW AMJ DOY 0.38 0.49 0.11 0.44 0.47 0.07 0.37 0.13 0.49 0.07 0.25 0.89


Table E-5: Summer seasonal analysis of Spearman’s Rank for the Innisfil Creek. Correlation coefficient is above and



JAS t

ota

l R

7d M

AX T

JAS

7d M

AX T

JAS D

OY

7d M

IN T

JAS

7d M

IN T

JAS D

OY

3d M

AX R

JAS

3d M

AX R

JAS D

OY

30d M

IN R

JAS

30d M

IN R

JAS D

OY

JAS y

ield

JAS B

F y

ield

3d M

AX Q

JAS

3d M

AX Q

JAS D

OY

7d M

IN Q

JAS

7d M

IN Q

JAS D

OY

3d M

AX B

F J

AS

3d M

AX B

F J

AS D

OY

7d M

IN B

F J

AS

7d M

IN B

F J

AS D

OY

323-2

3d M

AX G

W J

AS

323-2

3d M

AX G

W J

AS D

OY

323-2

7d M

IN G

W J

AS

323-2

7d M

IN G

W J

AS D

OY

323-3

3d M

AX G

W J

AS

323-3

3d M

AX G

W J

AS D

OY

323-3

7d M

IN G

W J

AS

323-3

7d M

IN G

W J

AS D

OY

323-4

3d M

AX G

W J

AS

323-4

3d M

AX G

W J

AS D

OY

323-4

7d M

IN G

W J

AS

323-4

7d M

IN G

W J

AS D

OY

JAS total R -0.41 -0.14 -0.16 -0.07 0.68 -0.06 0.44 -0.05 0.66 0.5 0.39 0.24 0.65 -0.12 0.32 0.41 0.61 0.05 0.63 -0.42 0.45 -0.69 0.38 -0.42 0.36 -0.64 0.19 -0.01 0.37 -0.21

7d MAX T JAS 0.01 -0.19 0.08 0.15 -0.36 0.01 -0.31 0.08 -0.5 -0.49 -0.5 0 -0.49 -0.36 -0.45 -0.19 -0.5 -0.29 -0.34 0.3 -0.31 0.04 -0.09 -0.14 -0.28 0.07 0.55 -0.33 0.18 -0.18

7d MAX T JAS DOY 0.41 0.26 0.17 0.25 0.18 -0.02 -0.21 -0.2 0.07 0.09 0.22 -0.28 -0.02 0.66 0.28 -0.12 0.04 0.54 -0.03 0.01 0.02 0.19 0.09 0.4 0.1 0.23 0.09 0.15 0.05 0.22

7d MIN T JAS 0.34 0.64 0.32 -0.19 0.07 -0.14 -0.06 0.2 -0.08 -0.12 0.08 -0.22 -0.17 0.43 -0.01 0.11 -0.19 0.36 -0.38 0.41 -0.25 0.42 -0.1 0.45 -0.06 0.44 -0.41 0.2 -0.39 0.21

7d MIN T JAS DOY 0.69 0.38 0.14 0.27 -0.01 -0.08 -0.32 0.17 -0.09 -0.21 -0.07 0.11 -0.25 0 -0.08 -0.03 -0.29 0.16 -0.34 -0.08 -0.55 0.41 -0.03 0.38 -0.09 0.31 -0.47 -0.11 -0.45 0.51

3d MAX R JAS 0 0.03 0.29 0.7 0.95 -0.13 0.29 0.02 0.7 0.54 0.66 0.04 0.52 0.39 0.54 0.24 0.52 0.52 0.3 0.04 0.34 -0.17 0.41 0.1 0.49 -0.29 -0.01 0.27 0.1 -0.01

3d MAX R JAS DOY 0.74 0.94 0.9 0.43 0.66 0.46 -0.23 -0.12 -0.21 -0.15 -0.31 0.22 -0.15 -0.35 -0.18 0.38 -0.03 -0.33 0.16 -0.52 -0.16 -0.34 -0.2 -0.01 -0.27 -0.29 -0.02 0.08 -0.12 -0.45

30d MIN R JAS 0.01 0.07 0.21 0.73 0.06 0.09 0.18 0.07 0.46 0.44 0.49 0.19 0.44 0.17 0.5 -0.34 0.41 0.28 -0.06 0.34 0.17 -0.05 0.21 0.11 0.32 -0.17 0.05 0.01 0.1 -0.55

30d MIN R JAS DOY 0.78 0.64 0.24 0.23 0.33 0.9 0.47 0.67 0.25 0.19 0.17 -0.18 0.22 0.35 0.19 -0.3 0.15 0.42 -0.03 0.14 0.05 -0.31 0.14 -0.1 0.13 -0.32 -0.29 -0.21 0.05 0.32

JAS yield 0 0.04 0.79 0.75 0.74 0 0.42 0.06 0.33 0.95 0.89 -0.24 0.94 0.46 0.88 0.06 0.92 0.58 0.53 -0.04 0.73 -0.47 0.64 0.06 0.73 -0.5 0.33 -0.06 0.66 0.19

JAS BF yield 0.04 0.05 0.72 0.65 0.42 0.03 0.57 0.08 0.48 0 0.9 -0.38 0.95 0.49 0.92 -0.08 0.95 0.56 0.45 -0.01 0.75 -0.45 0.69 0.09 0.8 -0.42 0.48 -0.27 0.78 0.19

3d MAX Q JAS 0.12 0.04 0.39 0.77 0.8 0 0.23 0.04 0.52 0 0 -0.33 0.8 0.66 0.95 -0.19 0.82 0.77 0.08 0.37 0.38 -0.04 0.43 0.43 0.6 -0.18 0.15 -0.09 0.39 0.14

3d MAX Q JAS DOY 0.36 1 0.27 0.4 0.67 0.88 0.39 0.46 0.49 0.36 0.13 0.2 -0.32 -0.35 -0.29 0.26 -0.31 -0.31 -0.11 -0.17 -0.4 0.16 -0.49 0.23 -0.42 0.03 -0.58 0.29 -0.49 -0.32

7d MIN Q JAS 0 0.05 0.93 0.52 0.32 0.03 0.57 0.08 0.39 0 0 0 0.21 0.38 0.8 0.01 0.98 0.41 0.58 -0.1 0.8 -0.69 0.66 -0.27 0.74 -0.68 0.45 -0.24 0.79 -0.02

7d MIN Q JAS DOY 0.66 0.16 0 0.08 0.99 0.12 0.16 0.52 0.17 0.06 0.05 0 0.16 0.14 0.68 -0.38 0.43 0.91 -0.1 0.34 0.14 0.07 -0.02 0.5 0.16 0 -0.2 0.03 0.03 0.3

3d MAX BF JAS 0.21 0.07 0.28 0.96 0.75 0.02 0.49 0.04 0.46 0 0 0 0.26 0 0 -0.26 0.83 0.79 0.2 0.2 0.49 -0.18 0.48 0.45 0.64 -0.24 0.21 -0.02 0.48 0.18

3d MAX BF JAS DOY 0.1 0.47 0.64 0.69 0.9 0.34 0.13 0.19 0.24 0.83 0.77 0.46 0.31 0.96 0.13 0.31 0.01 -0.38 0.44 -0.6 0.04 -0.08 -0.05 -0.23 -0.24 -0.11 -0.02 0.59 -0.2 -0.27

7d MIN BF JAS 0.01 0.04 0.87 0.46 0.26 0.03 0.9 0.11 0.56 0 0 0 0.22 0 0.08 0 0.97 0.45 0.57 -0.09 0.76 -0.73 0.55 -0.2 0.64 -0.72 0.49 -0.32 0.82 -0.09

7d MIN BF JAS DOY 0.84 0.26 0.03 0.15 0.55 0.03 0.2 0.27 0.09 0.02 0.02 0 0.23 0.1 0 0 0.13 0.07 -0.1 0.34 0.14 0.07 0.23 0.62 0.39 -0.05 -0.2 0.03 0.03 0.3

323-2 3d MAX GW JAS 0.03 0.29 0.93 0.22 0.28 0.34 0.62 0.85 0.93 0.08 0.14 0.81 0.74 0.05 0.76 0.54 0.15 0.05 0.76 -0.78 0.85 -0.73 0.77 -0.63 0.68 -0.62 0.53 0.23 0.59 -0.19

323-2 3d MAX GW JAS DOY 0.18 0.34 0.96 0.19 0.81 0.91 0.09 0.29 0.67 0.91 0.98 0.24 0.6 0.75 0.29 0.54 0.04 0.79 0.29 0 -0.56 0.44 -0.6 0.53 -0.53 0.27 -0.34 -0.24 -0.3 0.13

323-2 7d MIN GW JAS 0.14 0.33 0.95 0.43 0.07 0.29 0.62 0.6 0.88 0.01 0.01 0.22 0.2 0 0.66 0.11 0.89 0 0.66 0 0.06 -0.66 0.93 -0.59 0.92 -0.47 0.64 0.01 0.78 -0.02

323-2 7d MIN GW JAS DOY 0.01 0.91 0.55 0.17 0.19 0.6 0.28 0.87 0.32 0.13 0.14 0.89 0.63 0.01 0.82 0.58 0.79 0.01 0.82 0.01 0.15 0.02 -0.5 0.76 -0.42 0.91 -0.52 0.18 -0.69 0.37

323-3 3d MAX GW JAS 0.23 0.78 0.77 0.76 0.94 0.18 0.53 0.51 0.67 0.02 0.01 0.16 0.11 0.02 0.95 0.11 0.87 0.07 0.47 0.01 0.07 0 0.14 -0.29 0.95 -0.28

323-3 3d MAX GW JAS DOY 0.17 0.67 0.19 0.14 0.22 0.75 0.99 0.74 0.77 0.86 0.78 0.17 0.48 0.39 0.09 0.15 0.46 0.53 0.03 0.05 0.11 0.07 0.01 0.36 -0.18 0.54

323-3 7d MIN GW JAS 0.25 0.38 0.75 0.85 0.79 0.11 0.4 0.31 0.68 0.01 0 0.04 0.17 0.01 0.62 0.03 0.46 0.02 0.21 0.03 0.12 0 0.23 0 0.58 -0.25

323-3 7d MIN GW JAS DOY 0.02 0.84 0.47 0.16 0.33 0.35 0.35 0.6 0.32 0.1 0.17 0.57 0.94 0.02 0.99 0.46 0.74 0.01 0.88 0.06 0.45 0.17 0 0.39 0.07 0.43

323-4 3d MAX GW JAS 0.6 0.1 0.8 0.24 0.17 0.99 0.96 0.88 0.41 0.35 0.16 0.68 0.08 0.19 0.58 0.56 0.95 0.15 0.58 0.12 0.34 0.05 0.12 -0.31 0.84 -0.16

323-4 3d MAX GW JAS DOY 0.99 0.35 0.68 0.58 0.76 0.46 0.83 0.97 0.56 0.87 0.46 0.8 0.41 0.5 0.93 0.96 0.07 0.37 0.93 0.52 0.51 0.99 0.63 0.38 -0.47 -0.18

323-4 7d MIN GW JAS 0.29 0.63 0.88 0.26 0.19 0.78 0.75 0.78 0.89 0.04 0.01 0.26 0.15 0.01 0.93 0.16 0.58 0 0.93 0.07 0.39 0.01 0.03 0 0.17 0.02

323-4 7d MIN GW JAS DOY 0.56 0.63 0.53 0.56 0.13 0.99 0.19 0.1 0.37 0.6 0.6 0.7 0.37 0.96 0.4 0.63 0.46 0.8 0.4 0.6 0.73 0.96 0.29 0.65 0.63 0.96


Table E-6: Autumn seasonal analysis of Spearman’s Rank for the Innisfil Creek. Correlation coefficient is above and



ON

D t

ota

l R

7d M

AX T

ON

D

7d M

AX T

ON

D D

OY

7d M

IN T

ON

D

7d M

IN T

ON

D D

OY

3d M

AX R

ON

D

3d M

AX R

ON

D D

OY

30d M

IN R

ON

D

30d M

IN R

ON

D D

OY

ON

D y

ield

ON

D B

F y

ield

3d M

AX Q

ON

D

3d M

AX Q

ON

D D

OY

7d M

IN Q

ON

D

7d M

IN Q

ON

D D

OY

3d M

AX B

F O

ND

3d M

AX B

F O

ND

DO

Y

7d M

IN B

F O

ND

7d M

IN B

F O

ND

DO

Y

323-2

3d M

AX G

W O

ND

323-2

3d M

AX G

W O

ND

DO

Y

323-2

7d M

IN G

W O

ND

323-2

7d M

IN G

W O

ND

DO

Y

323-3

3d M

AX G

W O

ND

323-3

3d M

AX G

W O

ND

DO

Y

323-3

7d M

IN G

W O

ND

323-3

7d M

IN G

W O

ND

DO

Y

323-4

3d M

AX G

W O

ND

323-4

3d M

AX G

W O

ND

DO

Y

323-4

7d M

IN G

W O

ND

323-4

7d M

IN G

W O

ND

DO

Y

OND total R -0.01 0.15 0.13 -0.09 0.77 -0.1 0.5 0.03 0.42 0.25 0.54 0.09 -0.11 0.03 0.48 -0.1 -0.25 -0.02 -0.46 0.31 -0.48 -0.64 -0.34 0.71 -0.31 -0.57 -0.3 0.26 -0.4 -0.32

7d MAX T OND 0.95 0.18 0.15 -0.28 -0.03 0.06 -0.04 -0.2 -0.44 -0.52 -0.36 0.51 -0.69 -0.4 -0.25 0.4 -0.64 -0.05 -0.05 -0.01 -0.06 0.17 -0.31 0.09 -0.24 0.04 -0.24 0.21 -0.39 -0.15

7d MAX T OND DOY 0.38 0.29 0.03 -0.03 0.27 0.03 -0.11 -0.08 -0.05 -0.29 0.15 -0.02 -0.44 0.03 -0.09 0.23 -0.52 0.04 -0.43 0.13 -0.41 -0.49 -0.47 0.41 -0.45 -0.47 -0.39 -0.01 -0.48 -0.38

7d MIN T OND 0.45 0.39 0.87 0.18 0.04 0.12 0.46 -0.21 0.06 -0.06 0.21 0.12 -0.24 -0.46 -0.03 -0.09 -0.24 -0.06 -0.05 0 -0.01 -0.06 -0.11 0.23 -0.03 -0.25 -0.13 -0.13 -0.02 -0.08

7d MIN T OND DOY 0.6 0.1 0.87 0.3 0.08 0.05 -0.05 -0.1 0.07 0.17 0.06 -0.33 0.23 0.24 -0.02 0.26 0.23 0.72 0.09 -0.51 0.13 0.49 0.4 0.09 0.4 0.51 0.15 0.49 0.12 0.12

3d MAX R OND 0 0.84 0.11 0.83 0.66 -0.06 0.25 -0.1 0.66 0.48 0.72 -0.24 0.27 0.21 0.6 -0.03 0.15 0.19 -0.1 0.02 -0.11 -0.62 -0.19 0.7 -0.17 -0.66 -0.06 0.12 -0.18 -0.29

3d MAX R OND DOY 0.57 0.74 0.86 0.5 0.78 0.72 -0.04 -0.41 -0.02 -0.11 0.08 0.2 -0.09 0.19 0.07 0.51 -0.08 0.33 -0.23 -0.43 -0.25 -0.42 0.02 -0.14 0.01 -0.01 -0.35 0.01 -0.44 0.57

30d MIN R OND 0 0.81 0.54 0 0.79 0.14 0.8 -0.01 0.21 0.09 0.26 0.49 -0.02 0.08 0.18 -0.29 -0.08 -0.36 -0.32 0.53 -0.4 -0.57 -0.19 0.76 -0.17 -0.51 -0.08 0.38 -0.02 -0.45

30d MIN R OND DOY 0.87 0.25 0.64 0.22 0.57 0.57 0.01 0.94 0.1 0.23 -0.01 -0.02 0.14 -0.14 0.12 -0.71 0.03 -0.66 0.2 0.15 0.23 0.2 -0.01 0.01 -0.09 -0.04 0.41 -0.19 0.49 -0.19

OND yield 0.09 0.08 0.84 0.81 0.8 0 0.93 0.41 0.7 0.94 0.91 -0.36 0.75 0.35 0.92 -0.51 0.68 -0.02 0.19 0.05 0.17 -0.62 0.31 0.63 0.28 -0.66 0.44 0.12 0.41 -0.57

OND BF yield 0.32 0.03 0.27 0.83 0.51 0.05 0.66 0.72 0.37 0 0.8 -0.42 0.85 0.3 0.88 -0.59 0.79 -0.02 0.47 -0.08 0.45 -0.2 0.48 0.5 0.42 -0.44 0.65 0.2 0.62 -0.51

3d MAX Q OND 0.03 0.16 0.57 0.42 0.81 0 0.75 0.31 0.97 0 0 -0.29 0.58 0.22 0.85 -0.39 0.48 -0.03 0.07 -0.23 0.05 -0.69 0.23 0.64 0.2 -0.74 0.32 -0.01 0.28 -0.43

3d MAX Q OND DOY 0.72 0.04 0.93 0.63 0.2 0.36 0.43 0.05 0.93 0.15 0.09 0.26 -0.48 -0.1 -0.23 0.3 -0.41 -0.12 -0.19 0.21 -0.29 -0.05 -0.16 0.23 -0.07 0.2 -0.51 0.42 -0.49 0.2

7d MIN Q OND 0.67 0 0.08 0.35 0.37 0.29 0.74 0.93 0.59 0 0 0.01 0.05 0.41 0.66 -0.45 0.95 0 0.65 -0.03 0.63 -0.08 0.58 0.19 0.52 -0.24 0.83 0.1 0.84 -0.38

7d MIN Q OND DOY 0.92 0.11 0.9 0.06 0.35 0.43 0.47 0.75 0.59 0.17 0.24 0.39 0.72 0.1 0.32 0.11 0.4 0.29 0.02 -0.15 0.05 -0.48 0.23 0.22 0.11 -0.14 0.02 0.1 -0.04 -0.13

3d MAX BF OND 0.05 0.33 0.73 0.92 0.93 0.01 0.79 0.49 0.65 0 0 0 0.37 0 0.21 -0.42 0.58 -0.08 0.33 -0.04 0.31 -0.51 0.28 0.67 0.23 -0.63 0.58 0.19 0.51 -0.59

3d MAX BF OND DOY 0.69 0.11 0.38 0.72 0.31 0.9 0.04 0.27 0 0.04 0.01 0.12 0.24 0.07 0.68 0.09 -0.39 0.67 -0.09 -0.42 -0.1 0.08 -0.09 -0.23 -0.04 0.44 -0.49 0.1 -0.57 0.49

7d MIN BF OND 0.34 0.01 0.03 0.36 0.38 0.57 0.77 0.76 0.92 0 0 0.05 0.1 0 0.11 0.01 0.13 0.1 0.68 0.01 0.63 0.07 0.56 0.27 0.52 -0.25 0.87 0.24 0.89 -0.49

7d MIN BF OND DOY 0.93 0.86 0.87 0.83 0 0.46 0.19 0.16 0 0.94 0.94 0.9 0.64 1 0.26 0.76 0 0.71 -0.09 -0.46 -0.06 0.23 0.3 0.12 0.34 0.38 -0.1 0.4 -0.18 0.19

323-2 3d MAX GW OND 0.15 0.87 0.19 0.89 0.79 0.77 0.49 0.34 0.56 0.57 0.14 0.83 0.57 0.03 0.95 0.33 0.79 0.02 0.8 -0.4 0.98 0.21

323-2 3d MAX GW OND DOY 0.35 0.97 0.7 1 0.11 0.95 0.19 0.1 0.65 0.87 0.81 0.5 0.54 0.94 0.65 0.92 0.2 0.98 0.16 0.22 -0.47 -0.08

323-2 7d MIN GW OND 0.13 0.85 0.21 0.98 0.71 0.75 0.47 0.22 0.49 0.61 0.16 0.87 0.38 0.04 0.88 0.36 0.77 0.04 0.87 0 0.14 0.21

323-2 7d MIN GW OND DOY 0.03 0.62 0.13 0.86 0.12 0.04 0.2 0.07 0.56 0.04 0.56 0.02 0.89 0.81 0.14 0.11 0.81 0.84 0.5 0.53 0.81 0.54

323-3 3d MAX GW OND 0.29 0.32 0.12 0.73 0.2 0.56 0.96 0.56 0.97 0.32 0.12 0.47 0.62 0.05 0.47 0.38 0.79 0.06 0.35 -0.08 0.99 0.4 0.85 0.15 0.88 -0.4

323-3 3d MAX GW OND DOY 0.01 0.77 0.19 0.48 0.78 0.01 0.66 0 0.98 0.03 0.1 0.03 0.47 0.56 0.49 0.02 0.46 0.4 0.71 0.8 -0.03 -0.6 0.12 0.65 0.08 -0.67

323-3 7d MIN GW OND 0.33 0.46 0.15 0.93 0.2 0.6 0.97 0.59 0.77 0.38 0.17 0.53 0.83 0.08 0.73 0.47 0.9 0.08 0.27 0 0.92 0.41 0.81 0.22 0.85 -0.43

323-3 7d MIN GW OND DOY 0.05 0.9 0.12 0.43 0.09 0.02 0.97 0.09 0.91 0.02 0.15 0.01 0.53 0.46 0.67 0.03 0.16 0.43 0.22 0.19 0.04 0.19 0.13 0.01 0.19 0.37

323-4 3d MAX GW OND 0.37 0.48 0.24 0.71 0.65 0.85 0.3 0.81 0.22 0.18 0.03 0.34 0.11 0 0.96 0.06 0.13 0 0.76 0 0.75 0 0.72 0.28 0.95 -0.53

323-4 3d MAX GW OND DOY 0.45 0.54 0.97 0.7 0.12 0.73 0.97 0.25 0.57 0.73 0.55 0.97 0.19 0.78 0.78 0.58 0.76 0.47 0.22 0.69 0.04 0.54 0.97 0.4 0.1 -0.37

323-4 7d MIN GW OND 0.22 0.23 0.14 0.96 0.73 0.59 0.18 0.96 0.13 0.21 0.04 0.4 0.13 0 0.91 0.11 0.07 0 0.6 0 0.83 0 0.6 0 0.76 -0.51

323-4 7d MIN GW OND DOY 0.34 0.65 0.25 0.81 0.72 0.39 0.07 0.17 0.57 0.07 0.11 0.18 0.56 0.25 0.7 0.06 0.12 0.12 0.57 0.26 0.04 0.21 0.3 0.1 0.26 0.11


Table E-7: Annual analysis of Kendall’s Rank for the Innisfil Creek. Correlation coefficient is above and p-value is

below the diagonal. Correlation coefficient and p-values that meet thresholds for inclusion in analysis are shaded

Mean T

Tota

l P

PET

P-P

ET

7d M

AX T

7d M

AX T

DO

Y

7d M

IN T

7d M

IN T

DO

Y

3d M

AX R

3d M

AX R

DO

Y

30d M

IN R

30d M

IN R

DO

Y

RBI

10:9

0 e

xceedance

Annual yie

ld

Annual BF y

ield

3d M

AX Q

3d M

AX Q

DO

Y

7d M

IN Q

7d M

IN Q

DO

Y

3d M

AX B

F

3d M

AX B

F D

OY

7d M

IN B

F

7d M

IN B

F D

OY

323-2

GW

323-2

3d M

AX G

W

323-2

3d M

AX G

W D

OY

323-2

7d M

IN G

W

323-2

7d M

IN G

W D

OY

Mean T -0.15 0.71 -0.3 0.3 -0.04 0.37 -0.08 -0.09 0.25 0.44 -0.02 -0.08 0.3 -0.19 -0.08 -0.34 0.01 -0.49 -0.27 -0.08 -0.25 -0.45 -0.23 -0.38 -0.35 0.07 -0.2 0.29

Total P 0.39 -0.3 0.83 -0.37 0.14 0.01 -0.14 0.3 0.02 -0.12 -0.06 0.16 -0.16 0.71 0.56 0.69 -0.23 0.32 0.1 0.3 0.03 0.27 0.27 -0.02 0.13 -0.59 -0.2 -0.69

PET 0 0.08 -0.46 0.37 -0.03 0.23 -0.04 -0.12 0.19 0.33 0.04 -0.34 0.21 -0.41 -0.3 -0.43 0.14 -0.36 -0.36 -0.16 -0.12 -0.41 -0.32 -0.24 -0.38 0.18 -0.07 0.51

P-PET 0.07 0 0 -0.38 0.13 -0.03 -0.08 0.28 -0.02 -0.19 -0.04 0.19 -0.19 0.69 0.54 0.67 -0.21 0.34 0.16 0.32 0.05 0.34 0.3 0.16 0.31 -0.4 -0.02 -0.69

7d MAX T 0.07 0.03 0.03 0.02 -0.07 0.09 0.14 -0.22 0.1 0.36 0.17 -0.14 0.23 -0.03 0.03 -0.19 0.12 -0.3 -0.3 -0.01 -0.14 -0.3 -0.16 -0.24 -0.35 -0.07 0.02 -0.11

7d MAX T DOY 0.82 0.43 0.85 0.46 0.69 -0.01 0.07 0.21 -0.01 -0.03 0.09 0.1 -0.01 -0.1 -0.03 0.08 0.01 -0.01 0.48 0.06 -0.19 0.08 0.37 -0.24 -0.18 0.13 0.02 -0.2

7d MIN T 0.02 0.97 0.18 0.85 0.61 0.95 0.08 -0.03 0.26 0.33 0.1 0.23 0.21 0.12 0.14 0.05 -0.12 -0.23 -0.05 0.19 -0.16 -0.19 -0.05 -0.07 0.09 -0.33 -0.24 -0.11

7d MIN T DOY 0.64 0.42 0.82 0.66 0.4 0.69 0.66 -0.09 0.03 0.18 0.3 0.17 0.08 -0.19 -0.26 0.06 0.39 -0.06 0.32 -0.17 0.41 0.03 0.28 -0.4 -0.35 0.04 -0.67 0.04

3d MAX R 0.62 0.08 0.5 0.1 0.2 0.22 0.88 0.62 -0.06 -0.15 -0.17 -0.01 0.14 0.41 0.3 0.34 -0.19 0.1 0.05 0.3 0.08 0.05 0.1 0.33 0.56 -0.29 0.16 -0.6

3d MAX R DOY 0.14 0.89 0.27 0.9 0.55 0.97 0.13 0.84 0.73 0.06 0.05 -0.01 0.01 -0.03 0.08 -0.19 0.08 -0.12 -0.21 -0.01 -0.32 -0.03 -0.08 -0.16 -0.31 0.11 -0.07 0.07

30d MIN R 0.01 0.5 0.05 0.28 0.03 0.87 0.05 0.29 0.39 0.73 0.21 0.08 0.1 0 0.03 0 0.08 -0.2 -0.15 -0.08 0.05 -0.23 -0.08 -0.58 -0.34 -0.11 -0.53 -0.03

30d MIN R DOY 0.9 0.71 0.8 0.8 0.33 0.6 0.58 0.08 0.32 0.76 0.21 0.03 -0.3 -0.03 -0.01 0.08 -0.14 0.1 -0.03 -0.27 0.08 0.1 -0.08 -0.29 -0.31 0 -0.29 -0.07

RBI 0.79 0.57 0.23 0.52 0.63 0.73 0.43 0.57 0.97 0.97 0.8 0.91 -0.08 0.23 0.21 0.12 -0.45 0.23 0.36 -0.05 -0.14 0.27 0.41 0.21 0.28 0.06 0.14 -0.43

10:90 exceedance 0.3 0.57 0.47 0.52 0.43 0.97 0.47 0.79 0.63 0.97 0.73 0.3 0.79 -0.23 -0.3 -0.3 0.23 -0.71 -0.19 0.05 0.1 -0.71 -0.19 -0.07 0.11 -0.33 -0.14 -0.14

Annual yield 0.52 0 0.15 0.01 0.91 0.73 0.68 0.52 0.15 0.91 1 0.91 0.43 0.43 0.85 0.63 -0.34 0.47 -0.01 0.45 -0.21 0.43 0.16 0.43 0.56 -0.56 0.21 -0.64

Annual BF yield 0.79 0.04 0.3 0.05 0.91 0.91 0.63 0.38 0.3 0.79 0.93 0.97 0.47 0.3 0 0.52 -0.36 0.49 -0.03 0.52 -0.36 0.45 0.1 0.57 0.72 -0.39 0.36 -0.64

3d MAX Q 0.23 0.01 0.13 0.01 0.52 0.79 0.85 0.85 0.23 0.52 1 0.79 0.68 0.3 0.02 0.06 -0.32 0.41 0.14 0.38 -0.1 0.41 0.1 0.07 0.22 -0.67 -0.14 -0.71

3d MAX Q DOY 0.97 0.43 0.63 0.47 0.68 0.97 0.68 0.17 0.52 0.79 0.8 0.63 0.11 0.43 0.23 0.2 0.27 -0.3 0.05 0.03 0.43 -0.3 0.05 -0.43 -0.39 -0.06 -0.5 0.36

7d MIN Q 0.07 0.27 0.2 0.23 0.3 0.97 0.43 0.85 0.74 0.68 0.49 0.74 0.43 0 0.09 0.07 0.15 0.3 0.16 0.14 -0.12 0.91 0.25 0.36 0.28 -0.06 0.29 -0.14

7d MIN Q DOY 0.34 0.74 0.2 0.57 0.3 0.08 0.85 0.26 0.85 0.47 0.61 0.91 0.2 0.52 0.97 0.91 0.63 0.85 0.57 -0.16 0.14 0.21 0.82 -0.14 -0.11 0.11 -0.21 -0.21

3d MAX BF 0.79 0.3 0.57 0.27 0.97 0.85 0.52 0.57 0.3 0.97 0.8 0.34 0.85 0.85 0.11 0.06 0.17 0.91 0.63 0.57 -0.27 0.19 -0.16 0.36 0.44 -0.56 0.14 -0.29

3d MAX BF DOY 0.38 0.91 0.68 0.85 0.63 0.52 0.57 0.14 0.79 0.27 0.86 0.79 0.63 0.74 0.47 0.2 0.74 0.13 0.68 0.63 0.34 -0.16 0.19 -0.43 -0.33 0 -0.64 0.21

7d MIN BF 0.11 0.34 0.15 0.23 0.3 0.79 0.52 0.91 0.85 0.91 0.44 0.74 0.34 0 0.13 0.11 0.15 0.3 0 0.47 0.52 0 0.25 0.36 0.22 0 0.29 -0.14

7d MIN BF DOY 0.43 0.34 0.27 0.3 0.57 0.2 0.85 0.34 0.74 0.79 0.8 0.79 0.15 0.52 0.57 0.74 0.74 0.85 0.38 0 0.57 0.57 0.38 -0.14 -0.11 0.11 -0.21 -0.21

323-2 GW 0.28 0.95 0.5 0.67 0.5 0.5 0.85 0.25 0.35 0.67 0.08 0.42 0.61 0.87 0.29 0.14 0.87 0.29 0.39 0.74 0.39 0.52 0.39 0.74 0.73 0.04 0.73 -0.2

323-2 3d MAX GW 0.3 0.71 0.25 0.36 0.3 0.59 0.79 0.29 0.07 0.36 0.3 0.36 0.47 0.78 0.12 0.03 0.57 0.3 0.47 0.78 0.23 0.29 0.57 0.78 0.02 -0.15 0.47 -0.38

323-2 3d MAX GW DOY 0.83 0.06 0.59 0.22 0.83 0.7 0.32 0.91 0.38 0.75 0.75 1 0.89 0.38 0.12 0.3 0.05 0.89 0.89 0.78 0.12 0.38 1 0.78 0.9 0.67 0.04 0.54

323-2 7d MIN GW 0.58 0.58 0.85 0.95 0.95 0.95 0.5 0.03 0.67 0.85 0.12 0.42 0.74 0.74 0.61 0.39 0.74 0.21 0.49 0.61 0.74 1 0.49 0.61 0.02 0.17 0.9 -0.11

323-2 7d MIN GW DOY 0.42 0.03 0.13 0.03 0.76 0.58 0.76 0.9 0.07 0.85 0.94 0.85 0.29 0.74 0.09 0.09 0.05 0.39 0.74 0.61 0.49 0.09 0.74 0.61 0.58 0.28 0.11 0.76


Table E-8: Winter seasonal analysis of Kendall’s Rank for the Innisfil Creek. Correlation coefficient is above and p-



JFM

tota

l R

7d M

AX T

JFM

7d M

AX T

JFM

DO

Y

7d M

IN T

JFM

7d M

IN T

JFM

DO

Y

3d M

AX R

JFM

3d M

AX R

JFM

DO

Y

30d M

IN R

JFM

30d M

IN R

JFM

DO

Y

JFM

yie

ld

JFM

BF y

ield

3d M

AX Q

JFM

3d M

AX Q

JFM

DO

Y

7d M

IN Q

JFM

7d M

IN Q

JFM

DO

Y

3d M

AX B

F J

FM

3d M

AX B

F J

FM

DO

Y

7d M

IN B

F J

FM

7d M

IN B

F J

FM

DO

Y

323-2

3d M

AX G

W J

FM

323-2

3d M

AX G

W J

FM

DO

Y

323-2

7d M

IN G

W J

FM

323-2

7d M

IN G

W J

FM

DO

Y

323-3

3d M

AX G

W J

FM

323-3

3d M

AX G

W J

FM

DO

Y

323-3

7d M

IN G

W J

FM

323-3

7d M

IN G

W J

FM

DO

Y

323-4

3d M

AX G

W J

FM

323-4

3d M

AX G

W J

FM

DO

Y

323-4

7d M

IN G

W J

FM

323-4

7d M

IN G

W J

FM

DO

Y

JFM total R 0.14 0.11 0.08 -0.09 0.32 0 0.04 -0.26 0.52 0.34 0.54 -0.47 0.3 -0.07 0.16 -0.15 0.27 -0.31 -0.27 0.43 -0.39 -0.37 -0.11 0.12 -0.38 -0.04 -0.51 0.64 -0.56 0

7d MAX T JFM 0.41 0.11 0.24 0.11 0.03 0.04 0.12 0.08 0.12 -0.01 0.19 -0.25 0.03 0.11 -0.14 0.01 0.01 0.15 -0.12 0.2 0 -0.03 -0.02 0.4 -0.11 0 -0.16 -0.09 -0.2 0.11

7d MAX T JFM DOY 0.54 0.51 0.04 0.03 0.01 0.11 -0.08 0.04 0.16 0 0.45 -0.14 -0.02 0.3 0 -0.05 0.05 0.11 0.03 0.12 -0.03 -0.24 0.18 -0.14 0 0.07 -0.27 -0.12 -0.22 0.19

7d MIN T JFM 0.65 0.15 0.81 0.09 -0.13 0.16 0.34 0.11 0.36 0.36 0.12 -0.19 0.27 -0.29 0.14 -0.19 0.3 -0.2 -0.03 0.3 -0.03 -0.4 -0.02 0.54 -0.11 -0.45 -0.07 -0.14 -0.11 0.33

7d MIN T JFM DOY 0.59 0.53 0.87 0.6 0.15 0.17 0.14 0.21 -0.23 -0.3 -0.08 0.1 -0.3 0.03 -0.34 0.36 -0.32 -0.01 -0.46 0.2 -0.55 0.06 -0.49 -0.19 -0.45 0.14 -0.3 0.47 -0.34 -0.14

3d MAX R JFM 0.05 0.85 0.94 0.46 0.38 0.16 -0.28 0.1 0.19 -0.03 0.25 -0.32 -0.03 -0.31 0.01 -0.01 -0.1 -0.24 -0.15 0 -0.33 -0.22 -0.29 -0.12 -0.56 -0.13 -0.64 0.55 -0.6 -0.05

3d MAX R JFM DOY 0.98 0.82 0.52 0.35 0.31 0.35 -0.09 0.15 -0.02 -0.07 0 0.25 -0.16 0.15 -0.09 0.05 -0.13 0.07 0.11 0.35 0.14 -0.02 0.18 0.38 0.13 0 0.2 0.07 0.16 -0.22

30d MIN R JFM 0.83 0.48 0.64 0.04 0.43 0.1 0.59 0.1 0.25 0.35 0.03 -0.2 0.43 0.1 -0.05 -0.22 0.5 -0.13 -0.28 0.52 -0.24 -0.28 0 0.17 0 -0.14 -0.05 0 -0.11 0.5

30d MIN R JFM DOY 0.12 0.63 0.82 0.53 0.23 0.56 0.37 0.56 -0.14 -0.05 -0.25 -0.34 -0.01 -0.07 -0.27 -0.28 -0.08 0.13 0.21 -0.2 0.27 0 -0.16 -0.26 0.02 0.04 -0.24 -0.37 -0.2 0.6

JFM yield 0.06 0.68 0.58 0.2 0.42 0.52 0.94 0.39 0.63 0.78 0.58 -0.25 0.56 -0.09 0.6 -0.26 0.49 -0.27 -0.02 0.43 -0.11 -0.43

JFM BF yield 0.23 0.97 1 0.2 0.3 0.91 0.82 0.22 0.85 0 0.41 -0.25 0.74 -0.11 0.6 -0.4 0.67 -0.31 0.16 0.48 0.07 -0.57

3d MAX Q JFM 0.05 0.52 0.11 0.68 0.79 0.38 1 0.93 0.38 0.03 0.15 -0.1 0.23 0.02 0.41 -0.1 0.25 -0.13 -0.16 0.38 -0.16 -0.48

3d MAX Q JFM DOY 0.09 0.38 0.63 0.52 0.73 0.27 0.4 0.49 0.23 0.38 0.38 0.74 -0.38 0.2 0.1 0.44 -0.32 0.17 -0.02 -0.08 0.16 0.2

7d MIN Q JFM 0.3 0.91 0.94 0.34 0.3 0.91 0.59 0.13 0.97 0.04 0 0.43 0.17 -0.02 0.34 -0.58 0.93 -0.17 0.38 0.33 0.29 -0.61

7d MIN Q JFM DOY 0.82 0.7 0.3 0.31 0.91 0.28 0.61 0.73 0.82 0.76 0.7 0.94 0.49 0.94 -0.13 0.21 0.04 0.57 -0.05 -0.05 0.14 0.24

3d MAX BF JFM 0.57 0.63 1 0.63 0.23 0.97 0.76 0.86 0.34 0.02 0.02 0.15 0.74 0.23 0.65 -0.17 0.27 -0.31 0.2 0.33 0.11 -0.52

3d MAX BF JFM DOY 0.61 0.97 0.87 0.51 0.21 0.97 0.88 0.45 0.32 0.37 0.16 0.73 0.11 0.03 0.48 0.56 -0.6 0.13 -0.69 -0.42 -0.51 0.56

7d MIN BF JFM 0.34 0.97 0.87 0.3 0.26 0.74 0.65 0.07 0.79 0.07 0.01 0.38 0.27 0 0.88 0.34 0.02 -0.13 0.38 0.38 0.29 -0.61

7d MIN BF JFM DOY 0.27 0.61 0.7 0.5 0.97 0.4 0.81 0.65 0.66 0.35 0.27 0.66 0.55 0.55 0.03 0.27 0.65 0.66 0.18 -0.13 0.32 0.33

323-2 3d MAX GW JFM 0.39 0.71 0.92 0.93 0.13 0.64 0.74 0.39 0.51 0.95 0.67 0.67 0.95 0.28 0.9 0.58 0.03 0.28 0.61 -0.1 0.82 -0.18

323-2 3d MAX GW JFM DOY 0.17 0.54 0.71 0.35 0.53 1 0.27 0.08 0.54 0.22 0.16 0.28 0.84 0.36 0.89 0.36 0.23 0.28 0.72 0.76 -0.16 -0.25

323-2 7d MIN GW JFM 0.21 1 0.92 0.93 0.06 0.29 0.67 0.46 0.39 0.76 0.85 0.67 0.67 0.42 0.7 0.76 0.14 0.42 0.36 0 0.61 -0.06

323-2 7d MIN GW JFM DOY 0.24 0.92 0.45 0.2 0.85 0.5 0.96 0.38 1 0.21 0.09 0.16 0.57 0.06 0.51 0.12 0.09 0.06 0.35 0.57 0.43 0.85

323-3 3d MAX GW JFM 0.76 0.95 0.61 0.95 0.15 0.42 0.62 1 0.67 0.07 0.73 -0.36

323-3 3d MAX GW JFM DOY 0.75 0.26 0.69 0.11 0.6 0.75 0.28 0.64 0.48 0.85 -0.02 -0.33

323-3 7d MIN GW JFM 0.28 0.76 1 0.76 0.19 0.1 0.71 1 0.95 0.02 0.95 -0.13

323-3 7d MIN GW JFM DOY 0.9 1 0.85 0.19 0.71 0.71 1 0.7 0.9 0.31 0.35 0.71

323-4 3d MAX GW JFM 0.13 0.67 0.45 0.85 0.41 0.04 0.57 0.88 0.5 -0.32 0.96 -0.27

323-4 3d MAX GW JFM DOY 0.04 0.8 0.75 0.7 0.17 0.1 0.85 1 0.3 0.36 -0.37 -0.37

323-4 7d MIN GW JFM 0.1 0.58 0.53 0.76 0.33 0.07 0.66 0.76 0.58 0 0.3 -0.27

323-4 7d MIN GW JFM DOY 1 0.76 0.59 0.36 0.7 0.88 0.54 0.14 0.07 0.45 0.3 0.45


Table E-9: Spring seasonal analysis of Kendall’s Rank for the Innisfil Creek. Correlation coefficient is above and p-



AM

J to

tal R

7d M

AX T

AM

J

37 M

AX T

AM

J D

OY

7d M

IN T

AM

J

7d M

IN T

AM

J D

OY

3d M

AX R

AM

J

3d M

AX R

AM

J D

OY

30d M

IN R

AM

J

30d M

IN R

AM

J D

OY

AM

J yie

ld

AM

J BF y

ield

3d M

AX Q

AM

J

3d M

AX Q

AM

J D

OY

7d M

IN Q

AM

J

7d M

IN Q

AM

J D

OY

3d M

AX B

F A

MJ

3d M

AX B

F A

MJ

DO

Y

7d M

IN B

F A

MJ

7d M

IN B

F A

MJ

DO

Y

323-2

3d M

AX G

W A

MJ

323-2

3d M

AX G

W A

MJ

DO

Y

323-2

7d M

IN G

W A

MJ

323-2

7d M

IN G

W A

MJ

DO

Y

323-3

3d M

AX G

W A

MJ

323-3

3d M

AX G

W A

MJ

DO

Y

323-3

7d M

IN G

W A

MJ

323-3

7d M

IN G

W A

MJ

DO

Y

AMJ total R -0.14 0.31 -0.13 -0.18 0.4 0.06 0.34 -0.09 0.71 0.35 0.56 0.03 0.6 -0.54 0.2 0.22 0.52 -0.22 0.3 -0.32 -0.03 -0.3 0.16 0.24 0.02 -0.21

7d MAX T AMJ 0.42 0.12 0.18 -0.11 -0.14 0.08 -0.15 -0.08 -0.12 -0.18 -0.1 -0.13 -0.2 0.19 -0.03 -0.22 -0.2 0.14 -0.15 0.17 0 -0.04 -0.02 -0.45 0.05 -0.17

7d MAX T AMJ DOY 0.06 0.5 -0.12 0 0.28 0.1 0.24 -0.14 0.33 0.13 0.26 -0.23 0.23 -0.22 0.15 -0.08 0.21 0.11 0.51 -0.02 0 -0.24 0.45 0.15 0.07 -0.36

7d MIN T AMJ 0.46 0.29 0.47 0.15 -0.07 0.22 -0.13 -0.08 0.12 0.14 0.13 -0.03 0.09 0.19 -0.16 0.12 0.16 0.19 0.09 -0.08 0 -0.04 0.13 -0.24 0.05 -0.17

7d MIN T AMJ DOY 0.29 0.53 0.99 0.39 0.01 0.21 -0.05 -0.06 0.02 -0.02 -0.05 -0.08 0.08 0.26 -0.24 0.23 0.08 -0.07 -0.06 0.18 -0.13 -0.1 0 -0.12 -0.08 -0.21

3d MAX R AMJ 0.02 0.43 0.1 0.67 0.95 -0.07 0.06 -0.1 0.45 0.2 0.56 0.07 0.26 -0.28 0.16 0.18 0.18 0.06 0.45 -0.05 0 0.08 0.24 0.38 -0.2 -0.48

3d MAX R AMJ DOY 0.71 0.64 0.56 0.19 0.22 0.7 -0.08 -0.16 0.06 0.04 -0.05 0.56 0.44 -0.23 -0.29 0.19 0.52 -0.17 -0.11 0.12 0.11 0.17 0.09 0.09 0.46 0.26

30d MIN R AMJ 0.04 0.37 0.16 0.46 0.77 0.74 0.64 0.01 0.28 0.45 0.13 0.03 0.43 -0.01 -0.01 0.22 0.31 0.14 0.58 0.02 -0.06 -0.34 0.42 0.27 0.05 -0.33

30d MIN R AMJ DOY 0.58 0.65 0.41 0.65 0.71 0.57 0.35 0.96 0.02 0.19 0.12 -0.43 -0.11 0.24 0.25 0.11 -0.17 0.12 0.33 -0.05 0.24 -0.15 0.05 0.05 -0.24 -0.21

AMJ yield 0 0.66 0.22 0.66 0.94 0.09 0.84 0.32 0.95 0.49 0.78 -0.11 0.5 -0.32 0.1 0.34 0.47 -0.14 0.38 -0.24 -0.2 -0.3

AMJ BF yield 0.2 0.52 0.64 0.61 0.94 0.47 0.89 0.09 0.49 0.07 0.42 -0.09 0.37 -0.17 0.28 0.16 0.33 0.01 0.47 -0.07 -0.11 -0.58

3d MAX Q AMJ 0.03 0.73 0.34 0.63 0.86 0.03 0.86 0.63 0.66 0 0.12 -0.17 0.33 -0.18 0.17 0.21 0.33 0 0.38 -0.16 -0.11 -0.19

3d MAX Q AMJ DOY 0.92 0.66 0.4 0.92 0.78 0.81 0.03 0.92 0.11 0.71 0.76 0.54 0.2 -0.31 -0.22 0.26 0.24 -0.27 -0.22 0.09 -0.18 0.31

7d MIN Q AMJ 0.02 0.47 0.4 0.76 0.78 0.35 0.1 0.11 0.68 0.05 0.17 0.24 0.47 -0.42 -0.01 0.26 0.77 -0.19 0.38 -0.07 0.16 -0.14

7d MIN Q AMJ DOY 0.04 0.51 0.43 0.51 0.34 0.3 0.42 0.97 0.4 0.24 0.55 0.53 0.27 0.12 -0.25 -0.16 -0.4 0.64 0.07 0.52 0.02 0.2

3d MAX BF AMJ 0.47 0.92 0.59 0.56 0.4 0.56 0.3 0.97 0.37 0.71 0.32 0.54 0.43 0.97 0.38 -0.35 -0.12 0.01 -0.02 -0.29 -0.24 -0.69

3d MAX BF AMJ DOY 0.44 0.44 0.77 0.67 0.4 0.53 0.5 0.44 0.7 0.22 0.57 0.46 0.35 0.36 0.56 0.19 0.28 -0.28 0.3 -0.07 0.12 0.23

7d MIN BF AMJ 0.05 0.47 0.45 0.56 0.78 0.52 0.05 0.25 0.54 0.08 0.22 0.24 0.39 0 0.14 0.66 0.32 -0.19 0.2 -0.07 -0.02 -0.03

7d MIN BF AMJ DOY 0.43 0.61 0.7 0.49 0.81 0.82 0.55 0.61 0.68 0.61 0.96 1 0.32 0.49 0.01 0.96 0.31 0.49 0.32 0.43 -0.14 0.39

323-2 3d MAX GW AMJ 0.34 0.64 0.09 0.78 0.84 0.14 0.74 0.05 0.29 0.28 0.17 0.28 0.53 0.28 0.85 0.95 0.4 0.58 0.37 0.14 0.24 -0.08 0.6 0.02 0.29 -0.44

323-2 3d MAX GW AMJ DOY 0.31 0.6 0.96 0.81 0.58 0.89 0.7 0.96 0.89 0.5 0.85 0.67 0.8 0.85 0.12 0.42 0.85 0.85 0.21 0.67 0.08 0.21 0.18 -0.18 0.13 0.05

323-2 7d MIN GW AMJ 0.93 1 1 1 0.69 1 0.74 0.85 0.45 0.58 0.76 0.76 0.62 0.67 0.95 0.5 0.75 0.95 0.69 0.45 0.81 -0.04 0.16 -0.33 0.64 0.26

323-2 7d MIN GW AMJ DOY 0.34 0.91 0.45 0.91 0.75 0.81 0.59 0.28 0.64 0.39 0.08 0.59 0.39 0.7 0.58 0.03 0.52 0.94 0.26 0.81 0.51 0.91 -0.21 0.16 -0.05 0.17

323-3 3d MAX GW AMJ 0.63 0.96 0.17 0.71 1 0.48 0.79 0.2 0.87 0.07 0.62 0.67 0.56 0.2 0.49 -0.44

323-3 3d MAX GW AMJ DOY 0.48 0.16 0.66 0.48 0.73 0.25 0.79 0.42 0.87 0.95 0.62 0.35 0.66 0.56 -0.09 -0.21

323-3 7d MIN GW AMJ 0.96 0.87 0.83 0.87 0.82 0.56 0.15 0.87 0.48 0.42 0.71 0.04 0.89 0.13 0.79 0.06

323-3 7d MIN GW AMJ DOY 0.53 0.61 0.28 0.61 0.54 0.13 0.45 0.33 0.53 0.2 0.9 0.48 0.65 0.17 0.53 0.87


Table E-10: Summer seasonal analysis of Kendall’s Rank for the Innisfil Creek. Correlation coefficient is above and p-



JAS t

ota

l R

7d M

AX T

JAS

7d M

AX T

JAS D

OY

7d M

IN T

JAS

7d M

IN T

JAS D

OY

3d M

AX R

JAS

3d M

AX R

JAS D

OY

30d M

IN R

JAS

30d M

IN R

JAS D

OY

JAS y

ield

JAS B

F y

ield

3d M

AX Q

JAS

3d M

AX Q

JAS D

OY

7d M

IN Q

JAS

7d M

IN Q

JAS D

OY

3d M

AX B

F J

AS

3d M

AX B

F J

AS D

OY

7d M

IN B

F J

AS

7d M

IN B

F J

AS D

OY

323-2

3d M

AX G

W J

AS

323-2

3d M

AX G

W J

AS D

OY

323-2

7d M

IN G

W J

AS

323-2

7d M

IN G

W J

AS D

OY

323-3

3d M

AX G

W J

AS

323-3

3d M

AX G

W J

AS D

OY

323-3

7d M

IN G

W J

AS

323-3

7d M

IN G

W J

AS D

OY

323-4

3d M

AX G

W J

AS

323-4

3d M

AX G

W J

AS D

OY

323-4

7d M

IN G

W J

AS

323-4

7d M

IN G

W J

AS D

OY

JAS total R -0.29 -0.11 -0.11 -0.05 0.49 -0.03 0.31 -0.03 0.49 0.35 0.31 0.17 0.43 -0.04 0.26 0.33 0.38 0.07 0.52 -0.32 0.36 -0.58 0.3 -0.35 0.27 -0.48 0.11 -0.05 0.24 -0.16

7d MAX T JAS 0.09 -0.13 0.06 0.11 -0.27 0.01 -0.2 0.04 -0.34 -0.35 -0.37 -0.05 -0.34 -0.25 -0.32 -0.1 -0.35 -0.19 -0.18 0.25 -0.15 -0.02 0.03 -0.1 -0.12 0.08 0.42 -0.2 0.11 -0.2

7d MAX T JAS DOY 0.53 0.47 0.13 0.19 0.13 -0.02 -0.16 -0.16 0.01 0.03 0.15 -0.2 -0.04 0.49 0.18 -0.11 0.03 0.4 -0.02 0 0.02 0.12 0.05 0.33 0.02 0.17 0.09 0.13 0.04 0.09

7d MIN T JAS 0.51 0.74 0.47 -0.13 0.03 -0.11 -0.02 0.14 -0.04 -0.09 0.04 -0.19 -0.13 0.31 0 0.07 -0.15 0.25 -0.27 0.29 -0.18 0.32 0.03 0.35 0 0.28 -0.24 0.15 -0.2 0.2

7d MIN T JAS DOY 0.75 0.51 0.27 0.44 -0.01 -0.03 -0.23 0.12 -0.11 -0.21 -0.08 0.1 -0.3 0.02 -0.09 -0.03 -0.3 0.13 -0.24 -0.05 -0.5 0.3 -0.05 0.29 -0.12 0.16 -0.32 -0.11 -0.41 0.37

3d MAX R JAS 0 0.11 0.47 0.88 0.95 -0.08 0.18 0.02 0.5 0.4 0.44 0.04 0.35 0.24 0.37 0.15 0.34 0.35 0.21 -0.02 0.24 -0.08 0.24 0.1 0.33 -0.25 -0.07 0.2 -0.02 0.02

3d MAX R JAS DOY 0.85 0.96 0.92 0.53 0.85 0.65 -0.17 -0.1 -0.15 -0.1 -0.24 0.17 -0.1 -0.27 -0.16 0.24 -0.03 -0.24 0.09 -0.36 -0.18 -0.2 -0.18 0 -0.18 -0.24 -0.07 0.05 -0.11 -0.33

30d MIN R JAS 0.06 0.25 0.35 0.9 0.18 0.28 0.33 0.04 0.34 0.26 0.34 0.14 0.34 0.07 0.32 -0.2 0.29 0.16 -0.06 0.29 0.21 -0.05 0.18 0.07 0.27 -0.08 0.02 0.05 0.07 -0.42

30d MIN R JAS DOY 0.85 0.82 0.36 0.42 0.48 0.93 0.54 0.8 0.21 0.13 0.12 -0.14 0.21 0.31 0.13 -0.26 0.13 0.37 0 0.12 -0.03 -0.25 0.06 -0.11 0.09 -0.22 -0.27 -0.13 0.04 0.22

JAS yield 0.05 0.18 0.95 0.87 0.67 0.04 0.57 0.18 0.42 0.84 0.74 -0.19 0.79 0.26 0.69 0.01 0.78 0.41 0.36 -0.05 0.58 -0.38 0.48 0.07 0.58 -0.45 0.29 -0.05 0.51 0.02

JAS BF yield 0.16 0.16 0.91 0.74 0.43 0.11 0.69 0.3 0.61 0 0.72 -0.29 0.84 0.31 0.76 -0.09 0.85 0.4 0.33 -0.02 0.55 -0.38 0.55 0.1 0.64 -0.38 0.42 -0.15 0.64 0.07

3d MAX Q JAS 0.23 0.15 0.57 0.87 0.76 0.08 0.36 0.18 0.65 0 0 -0.23 0.59 0.44 0.84 -0.15 0.6 0.59 0.06 0.29 0.33 -0.05 0.33 0.31 0.42 -0.18 0.16 -0.1 0.29 0.07

3d MAX Q JAS DOY 0.51 0.84 0.43 0.48 0.69 0.89 0.51 0.59 0.59 0.48 0.26 0.37 -0.25 -0.26 -0.19 0.2 -0.23 -0.23 -0.05 -0.2 -0.32 0.13 -0.35 0.19 -0.32 0.03 -0.4 0.23 -0.36 -0.27

7d MIN Q JAS 0.09 0.18 0.86 0.61 0.24 0.16 0.69 0.18 0.42 0 0 0.01 0.34 0.21 0.6 -0.01 0.93 0.26 0.42 -0.08 0.64 -0.55 0.48 -0.17 0.58 -0.51 0.33 -0.1 0.64 -0.02

7d MIN Q JAS DOY 0.87 0.33 0.04 0.23 0.95 0.36 0.3 0.78 0.22 0.3 0.23 0.08 0.31 0.43 0.49 -0.3 0.25 0.85 0.03 0.25 0.12 0.02 0 0.42 0.09 0.02 -0.16 0 0.07 0.2

3d MAX BF JAS 0.3 0.21 0.49 1 0.72 0.15 0.53 0.21 0.61 0 0 0 0.48 0.01 0.05 -0.2 0.62 0.6 0.15 0.15 0.36 -0.18 0.36 0.38 0.45 -0.22 0.16 0 0.38 0.07

3d MAX BF JAS DOY 0.19 0.69 0.68 0.78 0.92 0.56 0.36 0.44 0.31 0.98 0.73 0.56 0.43 0.98 0.24 -0.2 -0.02 -0.3 0.34 -0.44 0.11 -0.09 0.03 -0.14 -0.14 -0.09 0 0.46 -0.14 -0.19

7d MIN BF JAS 0.13 0.16 0.91 0.57 0.24 0.18 0.91 0.25 0.61 0 0 0.01 0.37 0 0.33 0.62 0.93 0.28 0.42 -0.08 0.58 -0.61 0.36 -0.14 0.45 -0.58 0.38 -0.15 0.69 -0.07

7d MIN BF JAS DOY 0.78 0.46 0.11 0.33 0.63 0.16 0.36 0.54 0.14 0.1 0.11 0.01 0.37 0.3 0 0.6 0.24 0.28 0.03 0.25 0.12 0.02 0.21 0.52 0.3 -0.05 -0.16 0 0.07 0.2

323-2 3d MAX GW JAS 0.09 0.57 0.96 0.39 0.45 0.51 0.78 0.85 1 0.25 0.29 0.85 0.89 0.17 0.93 0.15 0.28 0.17 0.93 -0.66 0.67 -0.61 0.64 -0.48 0.51 -0.44 0.38 0.2 0.42 -0.07

323-2 3d MAX GW JAS DOY 0.31 0.43 1 0.36 0.87 0.96 0.25 0.36 0.71 0.88 0.96 0.36 0.52 0.79 0.43 0.15 0.16 0.79 0.43 0.02 -0.42 0.31 -0.45 0.46 -0.35 0.18 -0.3 -0.2 -0.25 0.05

323-2 7d MIN GW JAS 0.25 0.64 0.96 0.57 0.1 0.45 0.57 0.51 0.92 0.05 0.07 0.29 0.31 0.03 0.71 0.36 0.72 0.05 0.71 0.02 0.17 -0.55 0.82 -0.44 0.78 -0.3 0.47 0 0.6 -0.07

323-2 7d MIN GW JAS DOY 0.05 0.96 0.72 0.32 0.35 0.8 0.53 0.88 0.43 0.22 0.22 0.88 0.68 0.07 0.96 -0.18 0.78 0.03 0.96 0.03 0.32 0.07 -0.39 0.63 -0.34 0.81 -0.44 0.17 -0.58 0.34

323-3 3d MAX GW JAS 0.34 0.93 0.89 0.93 0.88 0.45 0.57 0.57 0.85 0.11 0.07 0.29 0.26 0.11 1 0.36 0.92 0.25 0.51 0.04 0.2 0 0.27 -0.21 0.85 -0.22

323-3 3d MAX GW JAS DOY 0.27 0.75 0.29 0.27 0.37 0.75 1 0.83 0.74 0.83 0.75 0.32 0.55 0.59 0.18 0.38 0.67 0.67 0.08 0.16 0.18 0.21 0.05 0.51 -0.17 0.42

323-3 7d MIN GW JAS 0.39 0.71 0.96 1 0.72 0.29 0.57 0.39 0.78 0.05 0.03 0.17 0.31 0.05 0.78 0.45 0.67 0.14 0.34 0.13 0.32 0.01 0.34 0 0.59 -0.18

323-3 7d MIN GW JAS DOY 0.11 0.8 0.6 0.37 0.61 0.44 0.46 0.8 0.49 0.14 0.22 0.57 0.92 0.09 0.96 -0.22 0.77 0.05 0.88 0.2 0.61 0.4 0 0.5 0.17 0.57

323-4 3d MAX GW JAS 0.76 0.22 0.8 0.5 0.36 0.85 0.85 0.95 0.45 0.42 0.22 0.67 0.25 0.35 0.67 0.16 1 0.28 0.67 0.28 0.4 0.17 0.21 -0.31 0.69 -0.16

323-4 3d MAX GW JAS DOY 0.89 0.57 0.72 0.67 0.77 0.57 0.89 0.89 0.72 0.89 0.67 0.78 0.52 0.78 1 0 0.18 0.67 1 0.57 0.58 1 0.64 0.39 -0.41 -0.15

323-4 7d MIN GW JAS 0.5 0.76 0.9 0.58 0.23 0.95 0.76 0.85 0.9 0.13 0.04 0.42 0.31 0.04 0.85 0.38 0.7 0.03 0.85 0.22 0.49 0.07 0.08 0.03 0.24 -0.02

323-4 7d MIN GW JAS DOY 0.67 0.58 0.8 0.58 0.3 0.95 0.35 0.22 0.53 0.95 0.85 0.85 0.45 0.95 0.58 0.07 0.6 0.85 0.58 0.85 0.89 0.85 0.34 0.67 0.67 0.95


Table E-11: Autumn seasonal analysis of Kendall’s Rank for the Innisfil Creek. Correlation coefficient is above and p-



ON

D t

ota

l R

7d M

AX T

ON

D

7d M

AX T

ON

D D

OY

7d M

IN T

ON

D

7d M

IN T

ON

D D

OY

3d M

AX R

ON

D

3d M

AX R

ON

D D

OY

30d M

IN R

ON

D

30d M

IN R

ON

D D

OY

ON

D y

ield

ON

D B

F y

ield

3d M

AX Q

ON

D

3d M

AX Q

ON

D D

OY

7d M

IN Q

ON

D

7d M

IN Q

ON

D D

OY

3d M

AX B

F O

ND

3d M

AX B

F O

ND

DO

Y

7d M

IN B

F O

ND

7d M

IN B

F O

ND

DO

Y

323-2

3d M

AX G

W O

ND

323-2

3d M

AX G

W O

ND

DO

Y

323-2

7d M

IN G

W O

ND

323-2

7d M

IN G

W O

ND

DO

Y

323-3

3d M

AX G

W O

ND

323-3

3d M

AX G

W O

ND

DO

Y

323-3

7d M

IN G

W O

ND

323-3

7d M

IN G

W O

ND

DO

Y

323-4

3d M

AX G

W O

ND

323-4

3d M

AX G

W O

ND

DO

Y

323-4

7d M

IN G

W O

ND

323-4

7d M

IN G

W O

ND

DO

Y

OND total R 0 0.12 0.06 -0.04 0.54 -0.06 0.33 0.03 0.28 0.15 0.35 0.1 -0.07 0.06 0.32 -0.09 -0.15 0 -0.35 0.2 -0.35 -0.5 -0.21 0.5 -0.15 -0.4 -0.2 0.18 -0.24 -0.24

7d MAX T OND 0.99 0.12 0.1 -0.19 -0.02 0.02 -0.02 -0.12 -0.29 -0.37 -0.22 0.35 -0.56 -0.27 -0.16 0.3 -0.46 -0.05 0.02 -0.02 0.02 0.09 -0.21 0.02 -0.15 0.03 -0.2 0.15 -0.31 -0.12

7d MAX T OND DOY 0.49 0.48 0.01 -0.02 0.19 0.02 -0.07 -0.06 -0.05 -0.21 0.08 -0.02 -0.32 0.02 -0.03 0.16 -0.36 0.05 -0.32 0.1 -0.32 -0.4 -0.33 0.32 -0.3 -0.34 -0.27 -0.02 -0.39 -0.33

7d MIN T OND 0.71 0.58 0.94 0.06 0.04 0.08 0.3 -0.15 0.06 -0.01 0.19 0.08 -0.15 -0.33 -0.01 -0.06 -0.16 -0.07 -0.09 -0.02 -0.02 -0.06 -0.15 0.17 -0.09 -0.25 -0.09 -0.04 -0.05 -0.08

7d MIN T OND DOY 0.81 0.28 0.89 0.71 0.05 0.01 -0.04 -0.07 0.04 0.12 0.03 -0.24 0.18 0.17 -0.01 0.17 0.18 0.59 0.09 -0.43 0.09 0.35 0.35 0.03 0.35 0.39 0.09 0.33 0.13 0.12

3d MAX R OND 0 0.91 0.25 0.81 0.76 -0.05 0.15 -0.06 0.53 0.37 0.6 -0.16 0.24 0.15 0.49 0.02 0.13 0.16 -0.05 0.06 -0.05 -0.35 -0.15 0.5 -0.15 -0.49 -0.05 0.11 -0.09 -0.2

3d MAX R OND DOY 0.73 0.93 0.9 0.66 0.94 0.75 -0.04 -0.3 -0.05 -0.13 0.05 0.17 -0.05 0.13 -0.01 0.37 -0.04 0.28 -0.15 -0.34 -0.15 -0.34 0.02 -0.09 0.02 -0.02 -0.31 0 -0.35 0.45

30d MIN R OND 0.05 0.89 0.68 0.08 0.83 0.38 0.8 0 0.13 0.03 0.15 0.34 -0.01 0.06 0.12 -0.23 -0.09 -0.27 -0.24 0.43 -0.31 -0.46 -0.12 0.63 -0.12 -0.34 -0.05 0.26 -0.02 -0.37

30d MIN R OND DOY 0.86 0.48 0.74 0.39 0.69 0.73 0.08 0.98 0.09 0.16 0.01 -0.05 0.1 -0.11 0.09 -0.53 0.03 -0.5 0.15 0.15 0.22 0.11 -0.02 0.03 -0.08 -0.02 0.29 -0.13 0.37 -0.12

OND yield 0.28 0.25 0.86 0.82 0.86 0.03 0.84 0.61 0.73 0.84 0.78 -0.28 0.56 0.27 0.81 -0.35 0.49 0 0.16 0.09 0.16 -0.35 0.24 0.44 0.18 -0.49 0.35 0.15 0.31 -0.28

OND BF yield 0.57 0.15 0.41 0.96 0.65 0.15 0.63 0.91 0.53 0 0.65 -0.31 0.69 0.23 0.74 -0.44 0.59 0 0.31 -0.06 0.31 -0.13 0.36 0.32 0.3 -0.31 0.49 0.22 0.45 -0.28

3d MAX Q OND 0.16 0.39 0.77 0.46 0.91 0.01 0.84 0.57 0.95 0 0 -0.23 0.4 0.15 0.71 -0.21 0.32 0 0.02 -0.13 0.02 -0.5 0.12 0.44 0.12 -0.62 0.16 0.04 0.13 -0.24

3d MAX Q OND DOY 0.71 0.17 0.93 0.75 0.36 0.55 0.51 0.19 0.84 0.28 0.23 0.37 -0.32 -0.07 -0.2 0.22 -0.28 -0.07 -0.09 0.13 -0.17 -0.02 -0.08 0.22 -0.02 0.18 -0.35 0.26 -0.35 0.12

7d MIN Q OND 0.78 0.02 0.21 0.57 0.49 0.36 0.84 0.96 0.69 0.02 0 0.11 0.21 0.29 0.46 -0.32 0.84 0.02 0.53 -0.02 0.45 -0.06 0.48 0.14 0.42 -0.12 0.6 0.04 0.71 -0.28

7d MIN Q OND DOY 0.82 0.29 0.95 0.19 0.52 0.56 0.62 0.82 0.66 0.29 0.38 0.56 0.79 0.27 0.26 0.06 0.3 0.22 -0.02 -0.04 -0.02 -0.33 0.17 0.22 0.11 -0.11 0.04 0.06 0 -0.06

3d MAX BF OND 0.21 0.54 0.91 0.96 0.95 0.05 0.98 0.65 0.73 0 0 0 0.44 0.07 0.32 -0.3 0.41 -0.07 0.2 -0.02 0.2 -0.31 0.15 0.47 0.09 -0.46 0.38 0.26 0.35 -0.33

3d MAX BF OND DOY 0.73 0.24 0.55 0.82 0.52 0.95 0.14 0.38 0.03 0.17 0.08 0.42 0.39 0.22 0.81 0.24 -0.27 0.55 -0.09 -0.28 -0.09 0.06 -0.13 -0.17 -0.06 0.32 -0.43 0.07 -0.43 0.41

7d MIN BF OND 0.57 0.07 0.15 0.54 0.49 0.61 0.89 0.74 0.91 0.05 0.01 0.21 0.28 0 0.24 0.1 0.29 0.07 0.56 0.02 0.49 0.06 0.45 0.17 0.39 -0.15 0.67 0.18 0.78 -0.37

7d MIN BF OND DOY 1 0.83 0.86 0.78 0.01 0.53 0.28 0.29 0.04 1 1 1 0.8 0.94 0.39 0.78 0.02 0.78 -0.07 -0.38 -0.07 0.2 0.3 0.09 0.33 0.34 -0.11 0.28 -0.11 0.22

323-2 3d MAX GW OND 0.3 0.96 0.34 0.79 0.79 0.87 0.67 0.48 0.67 0.63 0.36 0.96 0.79 0.1 0.96 0.56 0.79 0.07 0.85 -0.31 0.93 0.17

323-2 3d MAX GW OND DOY 0.55 0.96 0.78 0.96 0.19 0.87 0.31 0.19 0.66 0.79 0.87 0.7 0.7 0.96 0.91 0.96 0.41 0.96 0.24 0.35 -0.39 -0.04

323-2 7d MIN GW OND 0.3 0.96 0.34 0.96 0.79 0.87 0.67 0.36 0.52 0.63 0.36 0.96 0.62 0.16 0.96 0.56 0.79 0.13 0.85 0 0.24 0.17

323-2 7d MIN GW OND DOY 0.12 0.79 0.22 0.87 0.29 0.29 0.31 0.15 0.74 0.29 0.7 0.12 0.96 0.87 0.33 0.35 0.87 0.87 0.55 0.62 0.91 0.62

323-3 3d MAX GW OND 0.51 0.51 0.29 0.64 0.26 0.64 0.96 0.71 0.96 0.45 0.25 0.71 0.81 0.11 0.6 0.64 0.7 0.14 0.35 -0.08 0.94 0.28 0.73 0.09 0.73 -0.29

323-3 3d MAX GW OND DOY 0.09 0.96 0.31 0.6 0.92 0.09 0.78 0.03 0.92 0.15 0.31 0.15 0.49 0.67 0.49 0.12 0.59 0.6 0.77 0.81 -0.02 -0.43 0.09 0.48 0 -0.56

323-3 7d MIN GW OND 0.64 0.64 0.34 0.78 0.26 0.64 0.96 0.71 0.81 0.57 0.34 0.71 0.96 0.17 0.74 0.78 0.85 0.21 0.29 0 0.96 0.28 0.64 0.09 0.64 -0.34

323-3 7d MIN GW OND DOY 0.2 0.92 0.29 0.44 0.21 0.1 0.96 0.28 0.96 0.1 0.33 0.03 0.58 0.7 0.73 0.13 0.31 0.63 0.28 0.38 0.16 0.38 0.02 0 0.11 0.3

323-4 3d MAX GW OND 0.56 0.56 0.42 0.79 0.79 0.87 0.36 0.87 0.38 0.3 0.13 0.63 0.29 0.05 0.91 0.25 0.19 0.02 0.75 0.02 0.8 0.04 0.95 0.22 0.82 -0.41

323-4 3d MAX GW OND DOY 0.59 0.67 0.95 0.91 0.32 0.75 1 0.45 0.7 0.67 0.52 0.91 0.44 0.91 0.87 0.45 0.83 0.59 0.4 0.8 0.16 0.8 1 0.52 0.04 -0.25

323-4 7d MIN GW OND 0.48 0.36 0.24 0.87 0.71 0.79 0.3 0.96 0.27 0.36 0.16 0.71 0.29 0.01 1 0.3 0.19 0 0.75 0.02 1 0.04 0.75 0 0.91 -0.37

323-4 7d MIN GW OND DOY 0.47 0.72 0.33 0.81 0.72 0.55 0.17 0.27 0.72 0.4 0.4 0.47 0.72 0.4 0.85 0.33 0.21 0.27 0.52 0.42 0.09 0.34 0.4 0.21 0.47 0.27


Table E-12: Occurrences of probable correlation where Spearman’s Rank and Kendall’s Rank indicate parameter

correlation but linear regression does not for Innisfil Creek.


Time Scale Parameter 1 Parameter 2 ρ p-value τ p-value R² p-value slope sign

JFM Total R W323-4 3d MAX GW DOY 0.75 0.01 0.64 0.04 0.48 0.11 +


7d MIN Q 3d MAX BF DOY -0.73 0.00 -0.58 0.03 0.35 0.01 -


3d MAX BF DOY 7d MIN BF -0.72 0.00 -0.6 0.02 0.45 0.00 -

AMJ Total R 3d MAX Q 0.75 0.00 0.56 0.03 0.43 0.01 +

Total R 7d MIN Q 0.73 0.00 0.6 0.02 0.40 0.01 +

Total R 7d MIN Q DOY -0.72 0.00 -0.54 0.04 0.36 0.01 -

3d MAX R 3d MAX Q 0.71 0.00 0.56 0.03 0.35 0.01 +

3d MAX R DOY 3d MAX Q DOY 0.67 0.01 0.56 0.03 0.44 0.00 +

3d MAX BF W323-2 7d MIN GW DOY -0.77 0.01 -0.69 0.03 0.12 0.17 -

W323-2 7d MIN GW W323-3 7d MIN GW 0.75 0.01 0.64 0.04 0.47 0.02 +

JAS BF yield W323-3 7d MIN 0.8 0.00 0.64 0.03 0.49 0.01 +

3d MAX Q 7d MIN BF DOY 0.77 0.02 0.59 0.01 0.46 0.00 +

3d MAX BF 7d MIN BF DOY 0.79 0.00 0.6 0.01 0.43 0.00 +

7d MIN BF W323-2 7d MIN GW DOY -0.73 0.01 -0.61 0.03 0.41 0.01 -

W323-2 3d MAX GW W323-2 3d MAX GW DOY 0.78 0.00 -0.66 0.02 0.05 0.24 +

W323-2 3d MAX GW W323-2 7d MIN GW DOY -0.73 0.01 -0.61 0.03 0.46 0.01 -

W323-2 7d MIN GW DOY W323-3 7d MIN GW DOY 0.91 0.00 0.63 0.00 -0.01 0.37 +

OND Total R 3d MAX R 0.77 0.00 0.54 0.00 0.37 0.00 +

7d MAX T 7d MIN Q -0.69 0.00 -0.56 0.02 0.37 0.01 -

7d MIN T DOY 7d MIN BF DOY 0.72 0.00 0.59 0.01 0.21 0.03 +

3d MAX R Water yield 0.66 0.00 0.53 0.03 0.46 0.00 +

7d MIN R DOY 3d MAX BF DOY -0.71 0.00 -0.53 0.03 0.20 0.04 -


BF yield 7d MIN Q 0.85 0.00 0.69 0.00 0.45 0.00 +




3d MAX Q W323-2 7d MIN GW DOY -0.74 0.01 -0.62 0.03 0.25 0.07 -

7d MIN Q W323-4 7d MIN GW DOY 0.84 0.00 0.71 0.01 -0.11 0.88 +

3d MAX BF DOY 7d MIN BF DOY 0.67 0.00 0.55 0.02 0.12 0.10 +


Appendix F. Whitemans Creek Complete Analysis Results

Table F-1: Results from Mann-Kendall trend analysis for Whitemans Creek. Shading


warning (W). Note insufficient data record length for groundwater analysis.


Annual Mean T 0.283 0.016 VC

7d MAX T 0.089 0.454

7d MAX T DOY 0.390 0.001 VC

7d MAX T JFM -0.054 0.653

7d MAX T JFM DOY -0.090 0.467

7d MAX T AMJ 0.122 0.300

7d MAX T AMJ DOY 0.135 0.263

7d MAX T JAS 0.098 0.406

7d MAX T JAS DOY 0.058 0.633

7d MAX T OND 0.181 0.124

7d MAX T OND DOY 0.111 0.369

7d MIN T 0.143 0.225

7d MIN T DOY 0.071 0.557

7d MIN T JFM 0.044 0.713

7d MIN T JFM DOY 0.165 0.168

7d MIN T AMJ -0.070 0.558

7d MIN T AMJ DOY -0.128 0.291

7d MIN T JAS 0.337 0.004 VC

7d MIN T JAS DOY -0.017 0.902

7d MIN T OND 0.105 0.376

7d MIN T OND DOY -0.023 0.859

Annual Total P -0.013 0.924

JFM Total R 0.073 0.540

AMJ Total R 0.044 0.713

JAS Total R -0.124 0.294

OND Total R 0.060 0.614

3d MAX R -0.102 0.391

3d MAX R DOY -0.038 0.754

3d MAX R JFM -0.025 0.838

3d MAX R JFM DOY -0.014 0.913

3d MAX R AMJ 0.105 0.376

3d MAX R AMJ DOY -0.239 0.042 PT

3d MAX R JAS -0.152 0.196

3d MAX R JAS DOY -0.128 0.281

3d MAX R OND 0.022 0.859



3d MAX R OND DOY 0.097 0.414

30d MIN R 0.152 0.243

30d MIN R DOY 0.230 0.051 W

30d MIN R JFM 0.117 0.368

30d MIN R JFM DOY 0.093 0.437

30d MIN R AMJ 0.083 0.487

30d MIN R AMJ DOY 0.056 0.643

30d MIN R JAS -0.092 0.438

30d MIN R JAS DOY -0.003 0.989

30d MIN R OND 0.038 0.754

30d MIN R OND DOY -0.006 0.967

Annual PET 0.337 0.004 VC

Annual P-PET -0.098 0.406

Annual Richards Baker Flashiness Index 0.267 0.023 VC

Annual 10:90 exceedance 0.092 0.438

Annual yield -0.083 0.487

JFM yield -0.019 0.881

AMJ yield 0.086 0.470

JAS yield -0.165 0.161

OND yield -0.095 0.422

3d MAX Q -0.076 0.522

3d MAX Q DOY -0.062 0.606

3d MAX Q JFM -0.057 0.634

3d MAX Q JFM DOY 0.070 0.558

3d MAX Q AMJ 0.079 0.505

3d MAX Q AMJ DOY 0.018 0.891

3d MAX Q JAS -0.146 0.215

3d MAX Q JAS DOY -0.124 0.299

3d MAX Q OND -0.032 0.796

3d MAX Q OND DOY 0.090 0.453

7d MIN Q 0.022 0.859

7d MIN Q DOY 0.144 0.225

7d MIN Q JFM 0.067 0.577

7d MIN Q JFM DOY 0.042 0.733

7d MIN Q AMJ -0.019 0.881

7d MIN Q AMJ DOY 0.129 0.285

7d MIN Q JAS 0.016 0.902

7d MIN Q JAS DOY 0.118 0.320

7d MIN Q OND -0.111 0.347

7d MIN Q OND DOY -0.241 0.044 PT



Annual BF yield -0.143 0.225

JFM BF yield 0.016 0.881

AMJ BF yield -0.051 0.673

JAS BF yield -0.111 0.347

OND BF yield -0.146 0.215

3d MAX BF -0.098 0.406

3d MAX BF DOY -0.158 0.182

3d MAX BF JFM 0.010 0.946

3d MAX BF JFM DOY -0.125 0.307

3d MAX BF AMJ -0.130 0.270

3d MAX BF AMJ DOY -0.193 0.117

3d MAX BF JAS -0.168 0.153

3d MAX BF JAS DOY -0.041 0.750

3d MAX BF OND -0.114 0.334

3d MAX BF OND DOY 0.144 0.229

7d MIN BF 0.025 0.838

7d MIN BF DOY 0.172 0.145

7d MIN BF JFM 0.032 0.796

7d MIN BF JFM DOY -0.042 0.733

7d MIN BF AMJ -0.041 0.733

7d MIN BF AMJ DOY 0.103 0.433

7d MIN BF JAS 0.029 0.817

7d MIN BF JAS DOY 0.140 0.236

7d MIN BF OND -0.143 0.225

7d MIN BF OND DOY -0.166 0.197


Table F-2: Annual analysis of Spearman’s Rank for Whitemans Creek. Correlation coefficient is above and p-values

are below the diagonal. Correlation coefficient and p-values that meet thresholds for inclusion in analysis are shaded.

Mean T

Tota

l P

PET

P-P

ET

Tota

l R

7d M

AX T

7d M

AX T

DO

Y

7d M

IN T

7d M

IN T

DO

Y

3d M

AX R

3d M

AX R

DO

Y

30d M

IN R

30d M

IN R

DO

Y

R B

Index

10:9

0 e

xceedance

Annual yie

ld

Annual BF y

ield

3d M

AX Q

3d M

AX Q

DO

Y

7d M

IN Q

7d M

IN Q

DO

Y

3d M

AX B

F

3d M

AX B

F D

OY

7d M

IN B

F

7d M

IN B

F D

OY

Mean T -0.2 0.9 -0.37 -0.22 0.47 0.3 0.68 0 -0.42 0.08 0.66 0.02 -0.06 0.37 -0.35 -0.28 -0.32 -0.21 -0.34 -0.21 -0.03 -0.14 -0.36 -0.18

Total P 0.25 -0.35 0.97 0.96 -0.39 0.21 0.09 -0.08 0.33 0.18 -0.15 -0.2 0.69 -0.18 0.82 0.69 0.49 0.37 0.62 -0.06 0.29 0.21 0.61 -0.13

PET 0 0.04 -0.54 -0.41 0.55 0.31 0.48 0.12 -0.36 -0.01 0.6 0.23 -0.15 0.4 -0.52 -0.47 -0.45 -0.26 -0.45 -0.1 -0.16 -0.25 -0.46 -0.07

P-PET 0.03 0 0 0.94 -0.46 0.1 -0.02 -0.11 0.38 0.12 -0.26 -0.24 0.66 -0.25 0.85 0.74 0.55 0.37 0.66 -0.05 0.31 0.22 0.65 -0.13

Total R 0.2 0 0.01 0 -0.42 0.21 0.09 -0.15 0.37 0.16 -0.2 -0.28 0.66 -0.13 0.85 0.75 0.58 0.31 0.62 0.05 0.37 0.2 0.61 -0.01

7d MAX T 0 0.02 0 0 0.01 -0.08 0.2 0.13 -0.21 0.24 0.57 0.26 -0.15 0.27 -0.37 -0.32 -0.26 -0.22 -0.49 0.04 -0.16 -0.18 -0.49 0.03

7d MAX T DOY 0.08 0.22 0.06 0.55 0.23 0.62 0.07 0.05 0.09 0 0.1 0.02 0.42 0.34 0.09 -0.01 -0.01 -0.02 0.05 0.05 0.05 -0.1 0.08 0.08

7d MIN T 0 0.62 0 0.92 0.62 0.24 0.67 0.08 -0.43 0.12 0.47 0.09 0.19 0.11 -0.02 0.06 0 -0.16 -0.03 -0.3 0.05 0.03 -0.03 -0.28

7d MIN T DOY 0.98 0.62 0.48 0.53 0.39 0.44 0.77 0.66 -0.33 0.12 0.15 0.4 -0.07 -0.13 -0.08 -0.05 -0.27 0.24 -0.04 0.06 -0.13 0.01 -0.01 0.11

3d MAX R 0.01 0.05 0.03 0.02 0.03 0.21 0.6 0.01 0.05 -0.24 -0.35 -0.26 0.37 0.05 0.51 0.38 0.66 -0.16 0.35 0.25 0.27 -0.06 0.33 0.2

3d MAX R DOY 0.63 0.28 0.95 0.5 0.34 0.16 0.99 0.48 0.47 0.16 0.14 -0.18 -0.03 0.03 0.09 0.11 -0.18 0.31 -0.14 -0.1 0.04 0.25 -0.14 -0.14

30d MIN R 0 0.38 0 0.13 0.25 0 0.56 0 0.38 0.04 0.42 0.3 -0.01 0.41 -0.25 -0.17 -0.28 -0.16 -0.5 -0.32 -0.08 -0.08 -0.5 -0.26

30d MIN R DOY 0.91 0.25 0.18 0.17 0.09 0.12 0.9 0.59 0.01 0.13 0.29 0.08 0.08 0 -0.27 -0.33 -0.27 -0.07 -0.21 -0.09 -0.23 -0.16 -0.18 -0.06

R B Index 0.73 0 0.38 0 0 0.37 0.01 0.28 0.69 0.03 0.85 0.95 0.63 -0.09 0.63 0.47 0.51 0.07 0.52 0.04 0.22 0.11 0.53 0.02

10:90 exceedance 0.03 0.3 0.02 0.15 0.46 0.11 0.04 0.53 0.44 0.79 0.88 0.01 0.99 0.61 -0.09 0.01 0.04 -0.44 -0.61 0.04 0.43 -0.15 -0.61 0.02

Annual yield 0.04 0 0 0 0 0.03 0.62 0.92 0.65 0 0.59 0.15 0.11 0 0.6 0.93 0.72 0.14 0.7 0.04 0.56 -0.06 0.69 -0.04

Annual BF yield 0.1 0 0 0 0 0.06 0.95 0.72 0.79 0.02 0.53 0.32 0.05 0 0.97 0 0.67 0.08 0.62 0.08 0.66 -0.09 0.61 0.01

3d MAX Q 0.06 0 0.01 0 0 0.13 0.97 0.99 0.11 0 0.31 0.09 0.11 0 0.83 0 0 -0.19 0.45 0.22 0.59 -0.11 0.43 0.16

3d MAX Q DOY 0.22 0.03 0.12 0.03 0.07 0.19 0.92 0.35 0.16 0.36 0.07 0.35 0.7 0.7 0.01 0.4 0.63 0.28 0.22 -0.13 -0.03 0.39 0.21 -0.14

7d MIN Q 0.04 0 0.01 0 0 0 0.79 0.86 0.83 0.04 0.43 0 0.22 0 0 0 0 0.01 0.2 0.11 0.11 -0.06 0.99 0.07

7d MIN Q DOY 0.23 0.73 0.56 0.77 0.78 0.82 0.79 0.07 0.72 0.14 0.55 0.06 0.59 0.8 0.83 0.84 0.63 0.2 0.44 0.52 0 -0.17 0.13 0.97

3d MAX BF 0.86 0.08 0.36 0.06 0.03 0.35 0.76 0.76 0.44 0.11 0.83 0.63 0.17 0.21 0.01 0 0 0 0.85 0.52 0.98 -0.06 0.09 -0.07

3d MAX BF DOY 0.41 0.22 0.14 0.19 0.23 0.29 0.54 0.85 0.96 0.71 0.14 0.64 0.35 0.53 0.4 0.74 0.58 0.53 0.02 0.74 0.33 0.73 -0.07 -0.14

7d MIN BF 0.03 0 0.01 0 0 0 0.65 0.85 0.95 0.05 0.41 0 0.29 0 0 0 0 0.01 0.21 0 0.46 0.61 0.71 0.1

7d MIN BF DOY 0.29 0.45 0.67 0.46 0.95 0.84 0.64 0.09 0.53 0.24 0.41 0.12 0.71 0.92 0.9 0.81 0.97 0.34 0.4 0.67 0 0.68 0.4 0.57


Table F-3: Winter seasonal analysis of Spearman’s Rank for the Whitemans Creek. Correlation coefficient is above


are shaded.

JFM

tota

l R

7d M

AX T

JFM

7d M

AX T

JFM

DO

Y

7d M

IN T

JFM

7d M

IN T

JFM

DO

Y

3d M

AX R

JFM

3d M

AX R

JFM

DO

Y

30d M

IN R

JFM

30d M

IN R

JFM

DO

Y

JFM

yie

ld

JFM

BF y

ield

3d M

AX Q

JFM

3d M

AX Q

JFM

DO

Y

7d M

IN Q

JFM

7d M

IN Q

JFM

DO

Y

3d M

AX B

F J

FM

3d M

AX B

F J

FM

DO

Y

7d M

IN B

F J

FM

7d M

IN B

F J

FM

DO

Y

JFM total R 0.01 0.16 0.16 -0.03 0.51 0.06 0.13 -0.41 0.79 0.55 0.62 -0.26 0.39 -0.33 0.52 -0.22 0.35 -0.35

7d MAX T JFM 0.94 0.31 0.38 0.12 -0.13 -0.13 0.16 0.23 -0.09 -0.09 -0.16 -0.13 0.06 0.3 -0.34 -0.03 0.09 0.19

7d MAX T JFM DOY 0.35 0.07 -0.01 0.06 0.15 0.28 0.06 0 0.15 0.04 0.29 0.07 0.04 0.27 -0.15 -0.1 0.11 0.25

7d MIN T JFM 0.37 0.02 0.96 0.07 -0.36 -0.2 0.52 0.03 0.15 0.38 -0.08 -0.17 0.38 0.09 0.06 -0.15 0.37 0.1

7d MIN T JFM DOY 0.88 0.48 0.71 0.69 0 0.14 0 0.33 -0.01 -0.08 -0.08 0.13 0.12 0.54 -0.1 0.14 0.11 0.32

3d MAX R JFM 0 0.45 0.37 0.03 0.99 0.26 -0.33 0.04 0.41 0.19 0.58 -0.07 0.07 -0.14 0.34 0.04 0 -0.15

3d MAX R JFM DOY 0.72 0.44 0.1 0.24 0.42 0.13 -0.09 0.05 0.08 0.06 0.26 0.27 -0.03 0.15 0.21 0.15 0.02 0.17

30d MIN R JFM 0.45 0.34 0.71 0 0.99 0.05 0.6 0.01 -0.05 0.18 -0.3 -0.18 0.29 -0.06 0.06 -0.14 0.32 -0.11

30d MIN R JFM DOY 0.01 0.18 0.98 0.86 0.05 0.81 0.78 0.94 -0.36 -0.15 -0.34 -0.06 0.04 0.46 -0.21 -0.06 -0.02 0.25

JFM yield 0 0.6 0.37 0.37 0.95 0.01 0.66 0.79 0.03 0.75 0.79 -0.51 0.64 -0.19 0.6 -0.24 0.62 -0.16

JFM BF yield 0 0.58 0.8 0.02 0.64 0.28 0.73 0.3 0.39 0 0.39 -0.43 0.77 -0.02 0.8 -0.39 0.75 0.09

3d MAX Q JFM 0 0.36 0.08 0.62 0.64 0 0.13 0.07 0.05 0 0.02 -0.29 0.3 -0.2 0.36 -0.03 0.28 -0.16

3d MAX Q JFM DOY 0.12 0.44 0.69 0.31 0.44 0.68 0.11 0.3 0.75 0 0.01 0.09 -0.47 0.13 -0.13 0.48 -0.45 0.19

7d MIN Q JFM 0.02 0.73 0.8 0.02 0.5 0.69 0.85 0.09 0.8 0 0 0.08 0 0.17 0.51 -0.29 0.97 0.23

7d MIN Q JFM DOY 0.05 0.08 0.11 0.59 0 0.43 0.4 0.72 0 0.26 0.92 0.25 0.46 0.31 -0.2 -0.04 0.23 0.78

3d MAX BF JFM 0 0.04 0.38 0.71 0.57 0.04 0.22 0.72 0.22 0 0 0.03 0.46 0 0.24 -0.07 0.49 -0.04

3d MAX BF JFM DOY 0.19 0.85 0.57 0.38 0.43 0.81 0.39 0.42 0.73 0.16 0.02 0.88 0 0.09 0.82 0.68 -0.28 0.06

7d MIN BF JFM 0.04 0.61 0.51 0.03 0.53 1 0.91 0.06 0.9 0 0 0.09 0.01 0 0.18 0 0.1 0.31

7d MIN BF JFM DOY 0.04 0.26 0.13 0.55 0.05 0.38 0.33 0.54 0.14 0.34 0.6 0.35 0.26 0.18 0 0.81 0.72 0.07


Table F-4: Spring seasonal analysis of Spearman’s Rank for the Whitemans Creek. Correlation coefficient is above


are shaded.

AM

J to

tal R

7d M

AX T

AM

J

7d M

AX T

AM

J D

OY

7d M

IN T

AM

J

7d M

IN T

AM

J D

OY

3d M

AX R

AM

J

3d M

AX R

AM

J D

OY

30d M

IN R

AM

J

30d M

IN R

AM

J D

OY

AM

J yie

ld

AM

J BF y

ield

3d M

AX Q

AM

J

3d M

AX Q

AM

J D

OY

7d M

IN Q

AM

J

7d M

IN Q

AM

J D

OY

3d M

AX B

F A

MJ

3d M

AX B

F A

MJ

DO

Y

7d M

IN B

F A

MJ

7d M

IN B

F A

MJ

DO

Y

AMJ total R -0.27 0 -0.32 -0.38 0.7 -0.04 0.49 -0.09 0.72 0.5 0.38 0.2 0.74 -0.48 0.25 0.22 0.73 -0.22

7d MAX T AMJ 0.11 0.37 0.14 -0.11 -0.14 -0.17 -0.19 0.19 -0.25 -0.2 -0.2 -0.16 -0.35 0.14 -0.09 -0.17 -0.39 -0.07

7d MAX T AMJ DOY 0.99 0.02 -0.03 0.09 -0.17 -0.24 -0.01 0.01 0.01 -0.11 -0.04 0.1 0.04 0.25 -0.31 0.08 0.04 0.02

7d MIN T AMJ 0.06 0.41 0.88 0.28 -0.21 0.29 -0.11 -0.06 -0.45 -0.55 -0.4 0.2 -0.1 0.06 -0.5 -0.22 -0.16 0.28

7d MIN T AMJ DOY 0.02 0.52 0.61 0.09 -0.36 0.14 -0.22 -0.35 -0.23 -0.28 -0.08 0 -0.11 0.1 -0.18 0.1 -0.04 -0.02

3d MAX R AMJ 0 0.41 0.33 0.21 0.03 -0.08 0.1 -0.1 0.48 0.22 0.33 0.28 0.36 -0.16 0.12 0.32 0.37 -0.07

3d MAX R AMJ DOY 0.8 0.31 0.16 0.08 0.42 0.63 0.01 -0.22 -0.24 -0.26 -0.33 0.33 0.01 -0.17 -0.24 -0.1 0.02 -0.03

30d MIN R AMJ 0 0.28 0.95 0.53 0.21 0.56 0.96 0.03 0.46 0.43 0.08 0.04 0.5 -0.08 0.18 -0.12 0.47 0.25

30d MIN R AMJ DOY 0.61 0.27 0.96 0.74 0.04 0.55 0.21 0.03 0.12 0.16 0.07 -0.44 -0.14 0.09 0.15 -0.36 -0.11 0.1

AMJ yield 0 0.14 0.95 0.01 0.17 0 0.16 0.86 0.5 0.8 0.77 -0.12 0.66 -0.29 0.53 0.11 0.69 -0.1

AMJ BF yield 0 0.23 0.52 0 0.1 0.2 0.13 0 0.36 0 0.57 -0.32 0.61 -0.22 0.8 0.03 0.62 -0.15

3d MAX Q AMJ 0.02 0.25 0.82 0.01 0.63 0.05 0.05 0.01 0.7 0 0 -0.34 0.32 -0.31 0.54 0.17 0.36 -0.13

3d MAX Q AMJ DOY 0.25 0.37 0.55 0.25 1 0.1 0.05 0.63 0.01 0.47 0.06 0.04 0.09 0.27 -0.46 0.12 0.03 0.16

7d MIN Q AMJ 0 0.03 0.79 0.56 0.53 0.03 0.97 0.83 0.42 0 0 0.06 0.6 -0.44 0.35 -0.12 0.95 -0.11

7d MIN Q AMJ DOY 0 0.41 0.14 0.74 0.56 0.34 0.34 0 0.62 0.08 0.19 0.06 0.11 0.01 -0.36 0.01 -0.48 0.6

3d MAX BF AMJ 0.14 0.58 0.06 0 0.28 0.47 0.16 0.66 0.38 0 0 0 0 0.03 0.03 -0.08 0.34 -0.23

3d MAX BF AMJ DOY 0.19 0.34 0.65 0.19 0.55 0.06 0.56 0.3 0.03 0.51 0.86 0.31 0.49 0.47 0.94 0.65 -0.08 -0.11

7d MIN BF AMJ 0 0.02 0.83 0.37 0.83 0.03 0.89 0.5 0.54 0 0 0.03 0.88 0 0 0.04 0.65 -0.21

7d MIN BF AMJ DOY 0.21 0.69 0.9 0.1 0.91 0.71 0.86 0 0.56 0.55 0.39 0.47 0.36 0.54 0 0.18 0.54 0.23


Table F-5: Summer seasonal analysis of Spearman’s Rank for the Whitemans Creek. Correlation coefficient is above


are shaded.

JAS t

ota

l R

7d M

AX T

JAS

7d M

AX T

JAS D

OY

7d M

IN T

JAS

7d M

IN T

JAS D

OY

3d M

AX R

JAS

3d M

AX R

JAS D

OY

30d M

IN R

JAS

30d M

IN R

JAS D

OY

JAS y

ield

JAS B

F y

ield

3d M

AX Q

JAS

3d M

AX Q

JAS D

OY

7d M

IN Q

JAS

7d M

IN Q

JAS D

OY

3d M

AX B

F J

AS

3d M

AX B

F J

AS D

OY

7d M

IN B

F J

AS

7d M

IN B

F J

AS D

OY

JAS total R -0.23 -0.33 -0.2 0.09 0.69 -0.06 0.65 -0.28 0.65 0.63 0.59 0.45 0.52 -0.19 0.55 0.62 0.51 -0.18

7d MAX T JAS 0.18 -0.15 0.13 -0.01 -0.04 0.26 -0.51 -0.13 -0.46 -0.55 -0.26 -0.26 -0.48 -0.27 -0.45 -0.15 -0.46 -0.28

7d MAX T JAS DOY 0.05 0.38 0.13 0.16 -0.15 0.11 -0.1 0.02 -0.09 -0.05 -0.12 -0.02 -0.02 0.06 0.05 -0.26 -0.01 0.09

7d MIN T JAS 0.24 0.44 0.45 -0.07 -0.3 -0.25 -0.11 0.2 -0.12 -0.15 -0.07 -0.14 -0.14 0.02 -0.2 0.04 -0.13 0.02

7d MIN T JAS DOY 0.58 0.94 0.34 0.7 0.08 -0.09 -0.14 -0.05 0 -0.03 0.05 0.04 -0.07 -0.19 0.02 -0.06 -0.09 -0.12

3d MAX R JAS 0 0.82 0.39 0.08 0.65 0.1 0.33 -0.21 0.38 0.29 0.37 0.44 0.14 -0.48 0.29 0.36 0.12 -0.45

3d MAX R JAS DOY 0.71 0.12 0.54 0.14 0.59 0.55 -0.14 -0.21 -0.32 -0.22 -0.39 0.3 -0.2 0.01 -0.07 -0.16 -0.2 -0.04

30d MIN R JAS 0 0 0.58 0.53 0.41 0.05 0.43 -0.16 0.62 0.68 0.51 0.29 0.67 0.06 0.61 0.25 0.64 0.08

30d MIN R JAS DOY 0.1 0.46 0.92 0.24 0.76 0.23 0.23 0.34 0.07 0.09 -0.02 0.01 0.07 0.37 -0.02 0.07 0.07 0.4

JAS yield 0 0 0.59 0.47 0.99 0.02 0.06 0 0.67 0.92 0.91 0.29 0.79 0.01 0.82 0.55 0.78 -0.01

JAS BF yield 0 0 0.77 0.4 0.87 0.09 0.2 0 0.61 0 0.74 0.23 0.9 0.15 0.91 0.5 0.89 0.12

3d MAX Q JAS 0 0.12 0.5 0.67 0.76 0.03 0.02 0 0.93 0 0 0.15 0.58 -0.11 0.66 0.5 0.57 -0.11

3d MAX Q JAS DOY 0.01 0.13 0.93 0.41 0.82 0.01 0.08 0.08 0.94 0.09 0.18 0.38 0.13 -0.18 0.2 0.33 0.12 -0.17

7d MIN Q JAS 0 0 0.9 0.43 0.69 0.42 0.25 0 0.68 0 0 0 0.45 0.34 0.77 0.36 0.99 0.31

7d MIN Q JAS DOY 0.26 0.11 0.73 0.91 0.27 0 0.94 0.73 0.03 0.97 0.39 0.52 0.3 0.04 0.08 -0.08 0.36 0.97

3d MAX BF JAS 0 0.01 0.75 0.25 0.89 0.08 0.67 0 0.93 0 0 0 0.24 0 0.64 0.35 0.75 0.01

3d MAX BF JAS DOY 0 0.37 0.13 0.81 0.71 0.03 0.36 0.14 0.68 0 0 0 0.05 0.03 0.66 0.04 0.37 -0.04

7d MIN BF JAS 0 0 0.94 0.46 0.62 0.49 0.25 0 0.68 0 0 0 0.48 0 0.03 0 0.03 0.34

7d MIN BF JAS DOY 0.3 0.1 0.6 0.9 0.5 0.01 0.83 0.64 0.02 0.94 0.48 0.54 0.32 0.07 0 0.94 0.83 0.04


Table F-6: Autumn seasonal analysis of Spearman’s Rank for the Whitemans Creek. Correlation coefficient is above


are shaded.

ON

D t

ota

l R

7d M

AX T

ON

D

7d M

AX T

ON

D D

OY

7d M

IN T

ON

D

7d M

IN T

ON

D D

OY

3d M

AX R

ON

D

3d M

AX R

ON

D D

OY

30d M

IN R

ON

D

30d M

IN R

ON

D D

OY

ON

D y

ield

ON

D B

F y

ield

3d M

AX Q

ON

D

3d M

AX Q

ON

D D

OY

7d M

IN Q

ON

D

7d M

IN Q

ON

D D

OY

3d M

AX B

F O

ND

3d M

AX B

F O

ND

DO

Y

7d M

IN B

F O

ND

7d M

IN B

F O

ND

DO

Y

OND total R -0.12 0.06 0.15 -0.04 0.47 0.04 0.47 -0.06 0.57 0.53 0.67 0.04 0.11 -0.18 0.58 -0.31 0.03 -0.12

7d MAX T OND 0.5 0.14 0.15 -0.16 0.13 0.25 -0.01 -0.19 -0.13 -0.16 -0.03 0.19 -0.2 0.11 -0.1 0.19 -0.21 -0.18

7d MAX T OND DOY 0.73 0.42 0.07 0 0.25 0.23 0.11 0.12 -0.01 -0.04 0.01 0.24 -0.14 -0.04 0.06 0.2 -0.12 -0.03

7d MIN T OND 0.38 0.37 0.67 0.06 0.11 -0.02 0.35 -0.38 0.16 0.2 0.23 0.21 0.19 0.24 0.2 0.32 0.17 0.05

7d MIN T OND DOY 0.82 0.34 0.98 0.72 -0.36 -0.18 0.22 -0.19 -0.07 -0.08 -0.08 0.17 -0.12 0.08 -0.05 0.16 -0.1 0.12

3d MAX R OND 0 0.44 0.14 0.53 0.03 0.3 0.01 -0.01 0.33 0.28 0.45 -0.05 0.02 0.09 0.3 -0.1 0.03 0

3d MAX R OND DOY 0.8 0.14 0.18 0.89 0.29 0.08 0.02 -0.21 0.01 -0.08 0.14 0.43 0.04 0.03 0.02 0.06 0.09 0.07

30d MIN R OND 0 0.94 0.54 0.04 0.2 0.95 0.91 -0.28 0.4 0.35 0.47 0.3 0.32 -0.13 0.39 0.17 0.22 -0.27

30d MIN R OND DOY 0.75 0.27 0.48 0.02 0.26 0.96 0.21 0.09 0.18 0.16 0.09 -0.3 0.12 0.01 0.17 -0.32 0.12 0.13

OND yield 0 0.44 0.94 0.36 0.7 0.05 0.94 0.02 0.29 0.96 0.94 -0.22 0.74 0.13 0.95 -0.34 0.71 -0.04

OND BF yield 0 0.34 0.81 0.24 0.66 0.09 0.63 0.04 0.34 0 0.87 -0.34 0.79 0.18 0.92 -0.38 0.77 -0.01

3d MAX Q OND 0 0.87 0.94 0.19 0.66 0.01 0.43 0 0.62 0 0 -0.05 0.61 0.03 0.91 -0.27 0.57 -0.12

3d MAX Q OND DOY 0.8 0.27 0.15 0.22 0.32 0.79 0.01 0.07 0.07 0.19 0.04 0.79 -0.37 -0.11 -0.15 0.42 -0.33 0.07

7d MIN Q OND 0.53 0.24 0.43 0.27 0.47 0.89 0.82 0.06 0.49 0 0 0 0.03 0.26 0.63 -0.21 0.97 0.02

7d MIN Q OND DOY 0.29 0.53 0.83 0.16 0.63 0.62 0.87 0.45 0.96 0.44 0.3 0.87 0.54 0.13 0.16 0.23 0.32 0.57

3d MAX BF OND 0 0.56 0.71 0.23 0.79 0.07 0.91 0.02 0.33 0 0 0 0.39 0 0.36 -0.29 0.63 0.03

3d MAX BF OND DOY 0.07 0.26 0.25 0.06 0.35 0.56 0.73 0.33 0.06 0.05 0.02 0.11 0.01 0.23 0.19 0.09 -0.16 0.16

7d MIN BF OND 0.85 0.22 0.48 0.31 0.55 0.87 0.6 0.19 0.47 0 0 0 0.05 0 0.06 0 0.35 0.17

7d MIN BF OND DOY 0.49 0.3 0.84 0.78 0.5 0.99 0.69 0.11 0.44 0.83 0.96 0.48 0.69 0.9 0 0.86 0.35 0.33


Table F-7: Annual analysis of Kendall’s Rank for the Whitemans Creek. Correlation coefficient is above and p-value is


Mean T

Tota

l P

PET

P-P

ET

Tota

l R

7d M

AX T

7d M

AX T

DO

Y

7d M

IN T

7d M

IN T

DO

Y

3d M

AX R

3d M

AX R

DO

Y

30d M

IN R

30d M

IN R

DO

Y

R B

Index

10:9

0 e

xceedance

Annual yie

ld

Annual BF y

ield

3d M

AX Q

3d M

AX Q

DO

Y

7d M

IN Q

7d M

IN Q

DO

Y

3d M

AX B

F

3d M

AX B

F D

OY

7d M

IN B

F

7d M

IN B

F D

OY

Mean T -0.13 0.73 -0.26 -0.16 0.29 0.2 0.5 0.02 -0.28 0.04 0.5 0.01 -0.03 0.26 -0.24 -0.2 -0.2 -0.15 -0.24 -0.13 -0.01 -0.1 -0.25 -0.12

Total P 0.44 -0.23 0.86 0.84 -0.28 0.14 0.07 -0.05 0.23 0.14 -0.11 -0.12 0.52 -0.13 0.63 0.49 0.35 0.27 0.44 -0.04 0.21 0.16 0.43 -0.08

PET 0 0.17 -0.37 -0.3 0.34 0.22 0.35 0.07 -0.23 -0.02 0.45 0.15 -0.12 0.27 -0.36 -0.34 -0.3 -0.18 -0.3 -0.04 -0.1 -0.18 -0.3 -0.04

P-PET 0.13 0 0.02 0.8 -0.34 0.07 -0.01 -0.07 0.27 0.09 -0.18 -0.16 0.49 -0.18 0.65 0.54 0.38 0.28 0.47 -0.01 0.22 0.17 0.46 -0.07

Total R 0.36 0 0.07 0 -0.3 0.14 0.06 -0.11 0.26 0.13 -0.14 -0.18 0.49 -0.08 0.67 0.55 0.42 0.23 0.43 0.04 0.25 0.16 0.42 -0.01

7d MAX T 0.08 0.09 0.04 0.04 0.08 -0.06 0.13 0.08 -0.14 0.15 0.42 0.19 -0.1 0.18 -0.24 -0.2 -0.17 -0.17 -0.35 0.01 -0.1 -0.14 -0.34 0.02

7d MAX T DOY 0.24 0.42 0.19 0.7 0.41 0.71 0.05 0.05 0.09 -0.01 0.06 0.03 0.3 0.25 0.07 -0.02 -0.01 -0.02 0.05 0.03 0.04 -0.08 0.07 0.05

7d MIN T 0 0.69 0.04 0.96 0.74 0.46 0.78 0.08 -0.28 0.06 0.35 0.06 0.11 0.07 -0.04 0.02 -0.03 -0.1 -0.01 -0.22 0.01 0.04 -0.02 -0.2

7d MIN T DOY 0.93 0.75 0.68 0.69 0.52 0.63 0.78 0.63 -0.25 0.1 0.13 0.3 -0.05 -0.1 -0.08 -0.05 -0.22 0.19 -0.03 0.01 -0.09 0 0 0.05

3d MAX R 0.1 0.17 0.17 0.12 0.12 0.43 0.62 0.1 0.14 -0.18 -0.27 -0.19 0.26 0.03 0.36 0.27 0.48 -0.1 0.25 0.17 0.18 -0.05 0.23 0.14

3d MAX R DOY 0.83 0.42 0.9 0.59 0.46 0.37 0.96 0.73 0.55 0.3 0.1 -0.11 0.01 0.01 0.06 0.07 -0.12 0.22 -0.08 -0.08 0.03 0.15 -0.08 -0.11

30d MIN R 0 0.52 0.01 0.28 0.4 0.01 0.74 0.04 0.46 0.11 0.57 0.21 -0.01 0.32 -0.18 -0.14 -0.22 -0.14 -0.38 -0.23 -0.07 -0.06 -0.38 -0.18

30d MIN R DOY 0.97 0.49 0.37 0.35 0.3 0.27 0.85 0.71 0.08 0.26 0.54 0.21 0.06 -0.01 -0.19 -0.22 -0.16 -0.04 -0.15 -0.07 -0.15 -0.09 -0.13 -0.04

R B Index 0.85 0 0.5 0 0 0.54 0.07 0.51 0.75 0.13 0.97 0.94 0.71 -0.04 0.43 0.32 0.38 0.05 0.38 0.03 0.14 0.09 0.38 0.01

10:90 exceedance 0.13 0.46 0.11 0.29 0.63 0.28 0.14 0.67 0.55 0.85 0.97 0.06 0.96 0.8 -0.05 0 0.03 -0.29 -0.43 0.01 0.31 -0.1 -0.42 -0.01

Annual yield 0.16 0 0.03 0 0 0.15 0.7 0.83 0.65 0.03 0.74 0.28 0.26 0.01 0.77 0.79 0.57 0.09 0.52 0.02 0.39 -0.03 0.51 -0.04

Annual BF yield 0.24 0 0.04 0 0 0.23 0.93 0.9 0.79 0.11 0.67 0.42 0.2 0.06 0.99 0 0.51 0.06 0.45 0.05 0.47 -0.08 0.44 -0.01

3d MAX Q 0.25 0.04 0.07 0.02 0.01 0.33 0.96 0.88 0.21 0 0.48 0.19 0.35 0.02 0.88 0 0 -0.11 0.32 0.14 0.42 -0.09 0.31 0.09

3d MAX Q DOY 0.39 0.12 0.29 0.1 0.18 0.33 0.89 0.57 0.28 0.55 0.2 0.42 0.8 0.78 0.08 0.59 0.72 0.51 0.15 -0.08 -0.01 0.32 0.15 -0.08

7d MIN Q 0.15 0.01 0.08 0 0.01 0.04 0.78 0.96 0.88 0.15 0.64 0.02 0.39 0.02 0.01 0 0.01 0.06 0.39 0.1 0.06 -0.03 0.95 0.06

7d MIN Q DOY 0.46 0.84 0.8 0.96 0.84 0.94 0.85 0.19 0.97 0.31 0.66 0.19 0.7 0.85 0.96 0.91 0.75 0.4 0.64 0.58 0.01 -0.12 0.11 0.92

3d MAX BF 0.96 0.22 0.56 0.2 0.14 0.56 0.84 0.96 0.6 0.3 0.88 0.69 0.38 0.42 0.06 0.02 0 0.01 0.96 0.73 0.96 -0.05 0.04 -0.05

3d MAX BF DOY 0.55 0.36 0.28 0.31 0.36 0.41 0.63 0.83 0.98 0.79 0.39 0.74 0.58 0.61 0.55 0.85 0.64 0.61 0.06 0.87 0.47 0.79 -0.04 -0.1

7d MIN BF 0.14 0.01 0.07 0.01 0.01 0.04 0.67 0.91 0.99 0.19 0.66 0.02 0.45 0.02 0.01 0 0.01 0.07 0.38 0 0.53 0.8 0.83 0.09

7d MIN BF DOY 0.49 0.63 0.82 0.7 0.94 0.93 0.77 0.24 0.76 0.41 0.52 0.3 0.82 0.97 0.97 0.84 0.97 0.59 0.65 0.71 0 0.75 0.56 0.62


Table F-8: Winter seasonal analysis of Kendall’s Rank for the Whitemans Creek. Correlation coefficient is above and



JFM

tota

l R

7d M

AX T

JFM

7d M

AX T

JFM

DO

Y

7d M

IN T

JFM

7d M

IN T

JFM

DO

Y

3d M

AX R

JFM

3d M

AX R

JFM

DO

Y

30d M

IN R

JFM

30d M

IN R

JFM

DO

Y

JFM

yie

ld

JFM

BF y

ield

3d M

AX Q

JFM

3d M

AX Q

JFM

DO

Y

7d M

IN Q

JFM

7d M

IN Q

JFM

DO

Y

3d M

AX B

F J

FM

3d M

AX B

F J

FM

DO

Y

7d M

IN B

F J

FM

7d M

IN B

F J

FM

DO

Y

JFM total R 0.03 0.14 0.1 -0.02 0.36 0.04 0.1 -0.27 0.6 0.39 0.44 -0.18 0.29 -0.22 0.34 -0.17 0.26 -0.25

7d MAX T JFM 0.87 0.2 0.26 0.1 -0.09 -0.09 0.12 0.14 -0.06 -0.07 -0.11 -0.11 0.03 0.21 -0.23 -0.04 0.06 0.12

7d MAX T JFM DOY 0.42 0.24 -0.02 0.05 0.1 0.22 0.05 0.01 0.11 0.04 0.22 0.05 0.04 0.19 -0.11 -0.08 0.08 0.18

7d MIN T JFM 0.56 0.13 0.91 0.08 -0.28 -0.16 0.39 0.01 0.11 0.25 -0.07 -0.11 0.29 0.09 0.04 -0.09 0.28 0.08

7d MIN T JFM DOY 0.9 0.56 0.79 0.65 -0.02 0.1 0 0.24 -0.01 -0.06 -0.06 0.1 0.06 0.42 -0.07 0.1 0.06 0.24

3d MAX R JFM 0.03 0.61 0.57 0.09 0.9 0.18 -0.26 0.04 0.26 0.14 0.42 -0.08 0.03 -0.1 0.22 0.02 -0.01 -0.11

3d MAX R JFM DOY 0.8 0.6 0.19 0.34 0.56 0.3 -0.07 0.03 0.05 0.05 0.19 0.3 -0.02 0.1 0.14 0.13 0.01 0.15

30d MIN R JFM 0.54 0.47 0.79 0.02 0.98 0.12 0.69 0.02 -0.03 0.13 -0.24 -0.14 0.22 -0.04 0.03 -0.1 0.24 -0.07

30d MIN R JFM DOY 0.12 0.42 0.98 0.94 0.16 0.82 0.87 0.91 -0.25 -0.1 -0.2 -0.04 0.02 0.4 -0.12 -0.05 -0.02 0.21

JFM yield 0 0.71 0.53 0.52 0.97 0.12 0.79 0.86 0.14 0.56 0.58 -0.34 0.48 -0.12 0.43 -0.17 0.46 -0.12

JFM BF yield 0.02 0.69 0.82 0.14 0.75 0.41 0.77 0.44 0.56 0 0.26 -0.31 0.58 -0.02 0.59 -0.26 0.56 0.06

3d MAX Q JFM 0.01 0.51 0.19 0.67 0.71 0.01 0.27 0.16 0.23 0 0.12 -0.21 0.21 -0.14 0.24 -0.02 0.2 -0.1

3d MAX Q JFM DOY 0.3 0.52 0.78 0.52 0.57 0.64 0.08 0.41 0.82 0.04 0.07 0.21 -0.32 0.1 -0.07 0.34 -0.31 0.18

7d MIN Q JFM 0.09 0.87 0.82 0.08 0.71 0.85 0.92 0.2 0.9 0 0 0.22 0.06 0.08 0.33 -0.19 0.91 0.15

7d MIN Q JFM DOY 0.2 0.21 0.26 0.62 0.01 0.58 0.54 0.81 0.02 0.47 0.91 0.43 0.56 0.63 -0.11 -0.02 0.15 0.66

3d MAX BF JFM 0.04 0.17 0.52 0.83 0.69 0.19 0.41 0.84 0.47 0.01 0 0.16 0.7 0.05 0.5 -0.05 0.3 -0.03

3d MAX BF JFM DOY 0.31 0.82 0.65 0.58 0.56 0.89 0.46 0.56 0.79 0.33 0.12 0.89 0.04 0.26 0.89 0.77 -0.2 0.06

7d MIN BF JFM 0.13 0.74 0.64 0.1 0.71 0.96 0.93 0.15 0.91 0 0 0.24 0.06 0 0.38 0.08 0.25 0.21

7d MIN BF JFM DOY 0.14 0.48 0.31 0.66 0.16 0.52 0.38 0.67 0.21 0.5 0.74 0.55 0.28 0.39 0 0.87 0.75 0.22


Table F-9: Spring seasonal analysis of Kendall’s Rank for the Whitemans Creek. Correlation coefficient is above and


shaded.

AM

J to

tal R

7d M

AX T

AM

J

7d M

AX T

AM

J D

OY

7d M

IN T

AM

J

7d M

IN T

AM

J D

OY

3d M

AX R

AM

J

3d M

AX R

AM

J D

OY

30d M

IN R

AM

J

30d M

IN R

AM

J D

OY

AM

J yie

ld

AM

J BF y

ield

3d M

AX Q

AM

J

3d M

AX Q

AM

J D

OY

7d M

IN Q

AM

J

7d M

IN Q

AM

J D

OY

3d M

AX B

F A

MJ

3d M

AX B

F A

MJ

DO

Y

7d M

IN B

F A

MJ

7d M

IN B

F A

MJ

DO

Y

AMJ total R -0.17 -0.01 -0.23 -0.27 0.53 -0.04 0.38 -0.08 0.53 0.33 0.29 0.11 0.56 -0.34 0.17 0.15 0.55 -0.16

7d MAX T AMJ 0.31 0.24 0.09 -0.06 -0.11 -0.12 -0.12 0.11 -0.18 -0.14 -0.12 -0.11 -0.23 0.1 -0.04 -0.12 -0.23 -0.06

7d MAX T AMJ DOY 0.93 0.16 -0.01 0.07 -0.13 -0.19 -0.01 0.01 -0.01 -0.09 0 0.08 0.04 0.19 -0.23 0.06 0.02 0.02

7d MIN T AMJ 0.19 0.62 0.96 0.19 -0.14 0.21 -0.06 -0.05 -0.3 -0.38 -0.28 0.14 -0.07 0.03 -0.37 -0.17 -0.11 0.21

7d MIN T AMJ DOY 0.11 0.75 0.67 0.27 -0.25 0.13 -0.14 -0.24 -0.17 -0.2 -0.06 0 -0.09 0.07 -0.15 0.07 -0.03 -0.02

3d MAX R AMJ 0 0.51 0.44 0.42 0.14 -0.07 0.06 -0.08 0.33 0.13 0.24 0.18 0.25 -0.09 0.09 0.22 0.23 -0.05

3d MAX R AMJ DOY 0.82 0.49 0.27 0.23 0.47 0.67 0 -0.1 -0.17 -0.16 -0.23 0.23 -0.01 -0.1 -0.19 -0.06 0.01 -0.03

30d MIN R AMJ 0.02 0.5 0.93 0.73 0.41 0.71 1 0.01 0.32 0.3 0.04 0.04 0.34 -0.06 0.11 -0.1 0.3 0.21

30d MIN R AMJ DOY 0.62 0.51 0.97 0.79 0.17 0.65 0.56 0.96 0.09 0.12 0.06 -0.3 -0.11 0.05 0.1 -0.24 -0.07 0.08

AMJ yield 0 0.3 0.96 0.07 0.31 0.05 0.33 0.06 0.6 0.62 0.59 -0.1 0.5 -0.2 0.38 0.06 0.5 -0.08

AMJ BF yield 0.05 0.43 0.6 0.02 0.24 0.44 0.34 0.08 0.49 0 0.38 -0.21 0.46 -0.17 0.62 0.01 0.47 -0.12

3d MAX Q AMJ 0.08 0.48 0.99 0.1 0.75 0.16 0.18 0.8 0.75 0 0.02 -0.23 0.22 -0.23 0.39 0.14 0.24 -0.11

3d MAX Q AMJ DOY 0.54 0.53 0.65 0.42 0.98 0.3 0.18 0.8 0.07 0.57 0.21 0.17 0.07 0.2 -0.3 0.1 0.02 0.12

7d MIN Q AMJ 0 0.19 0.83 0.7 0.59 0.15 0.96 0.04 0.52 0 0 0.19 0.69 -0.31 0.27 -0.1 0.82 -0.07

7d MIN Q AMJ DOY 0.04 0.56 0.27 0.86 0.68 0.59 0.56 0.73 0.76 0.23 0.33 0.18 0.25 0.06 -0.27 0 -0.35 0.54

3d MAX BF AMJ 0.32 0.8 0.19 0.03 0.39 0.62 0.26 0.51 0.57 0.02 0 0.02 0.08 0.12 0.11 -0.04 0.26 -0.19

3d MAX BF AMJ DOY 0.4 0.48 0.71 0.31 0.67 0.2 0.72 0.56 0.15 0.71 0.94 0.41 0.58 0.57 0.99 0.82 -0.07 -0.06

7d MIN BF AMJ 0 0.17 0.9 0.53 0.85 0.17 0.94 0.08 0.66 0 0 0.16 0.89 0 0.04 0.13 0.7 -0.15

7d MIN BF AMJ DOY 0.35 0.73 0.91 0.21 0.91 0.76 0.87 0.22 0.64 0.64 0.49 0.53 0.47 0.68 0 0.27 0.71 0.38


Table F-10: Summer seasonal analysis of Kendall’s Rank for the Whitemans Creek. Correlation coefficient is above


are shaded.

JA

S t

ota

l R

7d M

AX T

JAS

7d M

AX T

JAS D

OY

7d M

IN T

JAS

7d M

IN T

JAS D

OY

3d M

AX R

JAS

3d M

AX R

JAS D

OY

30d M

IN R

JAS

30d M

IN R

JAS D

OY

JAS y

ield

JAS B

F y

ield

3d M

AX Q

JAS

3d M

AX Q

JAS D

OY

7d M

IN Q

JAS

7d M

IN Q

JAS D

OY

3d M

AX B

F J

AS

3d M

AX B

F J

AS D

OY

7d M

IN B

F J

AS

7d M

IN B

F J

AS D

OY

JAS total R -0.14 -0.22 -0.15 0.08 0.53 -0.04 0.48 -0.18 0.47 0.45 0.42 0.32 0.37 -0.15 0.4 0.46 0.36 -0.15

7d MAX T JAS 0.41 -0.11 0.09 0.01 -0.01 0.21 -0.37 -0.11 -0.32 -0.37 -0.2 -0.2 -0.35 -0.21 -0.3 -0.11 -0.33 -0.21

7d MAX T JAS DOY 0.19 0.54 0.11 0.12 -0.12 0.05 -0.07 0.02 -0.06 -0.03 -0.07 -0.01 0.01 0.05 0.02 -0.18 0.01 0.07

7d MIN T JAS 0.4 0.61 0.54 -0.05 -0.24 -0.18 -0.08 0.14 -0.09 -0.11 -0.04 -0.1 -0.1 0.03 -0.13 0.01 -0.08 0.01

7d MIN T JAS DOY 0.66 0.95 0.48 0.77 0.05 -0.09 -0.09 -0.03 0.02 -0.01 0.05 0.03 -0.03 -0.14 0.04 -0.04 -0.05 -0.09

3d MAX R JAS 0 0.94 0.48 0.16 0.79 0.1 0.24 -0.14 0.28 0.2 0.24 0.31 0.11 -0.32 0.2 0.25 0.11 -0.3

3d MAX R JAS DOY 0.81 0.22 0.78 0.3 0.61 0.55 -0.11 -0.13 -0.21 -0.13 -0.28 0.22 -0.13 0 -0.07 -0.11 -0.13 -0.01

30d MIN R JAS 0 0.03 0.7 0.63 0.59 0.16 0.52 -0.12 0.45 0.5 0.36 0.21 0.51 0.06 0.43 0.19 0.49 0.06

30d MIN R JAS DOY 0.3 0.54 0.9 0.42 0.88 0.42 0.46 0.5 0.03 0.05 -0.02 0.02 0.03 0.31 -0.02 0.06 0.03 0.33

JAS yield 0 0.06 0.72 0.59 0.92 0.09 0.21 0.01 0.85 0.8 0.73 0.2 0.63 0.02 0.65 0.41 0.62 0.02

JAS BF yield 0.01 0.03 0.85 0.51 0.97 0.23 0.46 0 0.77 0 0.57 0.16 0.75 0.12 0.77 0.39 0.73 0.1

3d MAX Q JAS 0.01 0.23 0.67 0.81 0.76 0.15 0.1 0.03 0.91 0 0 0.09 0.43 -0.07 0.49 0.36 0.43 -0.05

3d MAX Q JAS DOY 0.06 0.25 0.95 0.56 0.85 0.06 0.19 0.22 0.9 0.25 0.36 0.59 0.09 -0.1 0.12 0.27 0.07 -0.1

7d MIN Q JAS 0.03 0.04 0.97 0.58 0.85 0.53 0.45 0 0.85 0 0 0.01 0.61 0.25 0.59 0.26 0.96 0.22

7d MIN Q JAS DOY 0.38 0.22 0.79 0.87 0.43 0.05 0.99 0.72 0.07 0.93 0.5 0.7 0.55 0.15 0.04 -0.05 0.26 0.92

3d MAX BF JAS 0.02 0.07 0.91 0.46 0.83 0.25 0.7 0.01 0.91 0 0 0 0.48 0 0.8 0.25 0.57 0.01

3d MAX BF JAS DOY 0.01 0.53 0.3 0.95 0.83 0.14 0.51 0.28 0.72 0.01 0.02 0.03 0.11 0.13 0.79 0.15 0.27 -0.02

7d MIN BF JAS 0.03 0.05 0.94 0.63 0.79 0.53 0.45 0 0.85 0 0 0.01 0.69 0 0.12 0 0.11 0.25

7d MIN BF JAS DOY 0.38 0.23 0.7 0.94 0.62 0.07 0.94 0.71 0.05 0.93 0.55 0.78 0.58 0.19 0 0.97 0.93 0.14


Table F-11: Autumn seasonal analysis of Kendall’s Rank for the Whitemans Creek. Correlation coefficient is above and


shaded.

ON

D t

ota

l R

7d M

AX T

ON

D

7d M

AX T

ON

D D

OY

7d M

IN T

ON

D

7d M

IN T

ON

D D

OY

3d M

AX R

ON

D

3d M

AX R

ON

D D

OY

30d M

IN R

ON

D

30d M

IN R

ON

D D

OY

ON

D y

ield

ON

D B

F y

ield

3d M

AX Q

ON

D

3d M

AX Q

ON

D D

OY

7d M

IN Q

ON

D

7d M

IN Q

ON

D D

OY

3d M

AX B

F O

ND

3d M

AX B

F O

ND

DO

Y

7d M

IN B

F O

ND

7d M

IN B

F O

ND

DO

Y

OND total R -0.09 0.04 0.08 -0.03 0.34 0.02 0.34 -0.05 0.43 0.39 0.49 0.03 0.07 -0.11 0.42 -0.21 0.02 -0.09

7d MAX T OND 0.59 0.1 0.1 -0.11 0.09 0.16 -0.02 -0.11 -0.09 -0.12 0 0.13 -0.14 0.06 -0.08 0.14 -0.13 -0.15

7d MAX T OND DOY 0.8 0.57 0.05 0 0.17 0.16 0.09 0.09 0 -0.02 0 0.18 -0.09 -0.03 0.04 0.15 -0.07 -0.03

7d MIN T OND 0.65 0.57 0.79 0 0.07 -0.01 0.25 -0.24 0.09 0.13 0.15 0.13 0.15 0.13 0.13 0.22 0.1 0.01

7d MIN T OND DOY 0.87 0.52 0.99 1 -0.25 -0.12 0.14 -0.11 -0.06 -0.06 -0.09 0.13 -0.09 0.06 -0.05 0.13 -0.07 0.1

3d MAX R OND 0.04 0.62 0.33 0.7 0.14 0.22 0.01 -0.02 0.22 0.19 0.3 -0.03 0 0.07 0.2 -0.08 0 0

3d MAX R OND DOY 0.9 0.35 0.34 0.96 0.48 0.19 0.01 -0.14 -0.02 -0.08 0.06 0.32 0.04 0.01 -0.02 0.06 0.07 0.04

30d MIN R OND 0.04 0.91 0.61 0.14 0.43 0.97 0.96 -0.18 0.28 0.26 0.32 0.19 0.23 -0.1 0.3 0.11 0.17 -0.2

30d MIN R OND DOY 0.75 0.52 0.62 0.16 0.52 0.9 0.42 0.3 0.12 0.1 0.04 -0.19 0.1 0.01 0.12 -0.16 0.1 0.11

OND yield 0.01 0.61 1 0.61 0.74 0.19 0.9 0.09 0.5 0.87 0.8 -0.16 0.54 0.1 0.83 -0.24 0.52 -0.02

OND BF yield 0.02 0.48 0.89 0.44 0.75 0.27 0.65 0.13 0.55 0 0.68 -0.24 0.6 0.12 0.79 -0.27 0.58 0

3d MAX Q OND 0 1 1 0.4 0.6 0.07 0.73 0.06 0.8 0 0 -0.02 0.41 0.03 0.75 -0.19 0.38 -0.08

3d MAX Q OND DOY 0.85 0.45 0.3 0.45 0.44 0.87 0.05 0.26 0.26 0.34 0.16 0.91 -0.27 -0.08 -0.09 0.31 -0.25 0.03

7d MIN Q OND 0.67 0.43 0.59 0.39 0.61 0.99 0.83 0.18 0.56 0 0 0.01 0.3 0.18 0.44 -0.14 0.89 0.02

7d MIN Q OND DOY 0.53 0.73 0.87 0.45 0.71 0.66 0.96 0.56 0.94 0.55 0.48 0.87 0.01 0.3 0.11 0.18 0.22 0.51

3d MAX BF OND 0.01 0.66 0.82 0.46 0.78 0.25 0.92 0.08 0.48 0 0 0 0.42 0.01 0.52 -0.2 0.44 0.03

3d MAX BF OND DOY 0.21 0.41 0.4 0.2 0.45 0.66 0.75 0.53 0.34 0.16 0.12 0.28 0 0.42 0.29 0.24 -0.1 0.12

7d MIN BF OND 0.9 0.45 0.67 0.54 0.69 0.99 0.7 0.34 0.55 0 0 0.02 0.9 0 0.19 0.01 0.55 0.12

7d MIN BF OND DOY 0.62 0.39 0.86 0.95 0.58 1 0.81 0.23 0.52 0.93 0.98 0.65 0.84 0.9 0 0.84 0.47 0.47


Table F-12: Occurrences of probable correlation where Spearman’s Rank and Kendall’s Rank indicate parameter

correlation but linear regression does not for Whitemans Creek.



Annual Total P RBI 0.69 0.00 0.52 0.00 0.49 0.00 +

Annual yield 7d MIN Q 0.70 0.00 0.52 0.00 0.46 0.00 +

Annual yield 7d MIN BF 0.69 0.00 0.51 0.00 0.41 0.00 +

BF yield 3d MAX Q 0.67 0.00 0.51 0.00 0.38 0.00 +

JFM BF yield 3d MAX BF 0.80 0.00 0.59 0.00 0.46 0.00 +

BF yield 7d MIN BF 0.75 0.00 0.56 0.00 0.50 0.00 +

AMJ Total R 3d MAX R 0.70 0.00 0.53 0.00 0.43 0.00 +

JAS Total R 3d MAX R 0.69 0.00 0.53 0.00 0.44 0.00 +

7d MIN R 7d MIN Q 0.67 0.00 0.51 0.00 0.41 0.00 +

water yield 7d MIN Q 0.79 0.00 0.63 0.00 0.46 0.00 +

water yield 7d MIN BF 0.78 0.00 0.62 0.00 0.43 0.00 +

BF yield 3d MAX Q 0.74 0.00 0.57 0.00 0.43 0.00 +

7d MIN Q 3d MAX BF 0.77 0.00 0.59 0.00 0.34 0.00 +

3d MAX BF 7d MIN BF 0.75 0.00 0.57 0.00 0.31 0.00 +


Appendix G. Parkhill Creek Complete Analysis Results

Table G-1: Results from Mann-Kendall trend analysis for Parkhill Creek. Shading


warning (W).


Annual Mean T 0.26 0.026 PT

7d MAX T 0.111 0.347 7d MAX T DOY 0.228 0.053 W

7d MAX T JFM -0.083 0.487 7d MAX T JFM DOY -0.073 0.559 7d MAX T AMJ 0.140 0.236 7d MAX T AMJ DOY 0.217 0.067 W

7d MAX T JAS 0.137 0.247 7d MAX T JAS DOY -0.021 0.870 7d MAX T OND 0.162 0.169 7d MAX T OND DOY 0.008 0.956 7d MIN T 0.159 0.178 7d MIN T DOY 0.039 0.754 7d MIN T JFM 0.108 0.361 7d MIN T JFM DOY 0.114 0.339 7d MIN T AMJ -0.041 0.733 7d MIN T AMJ DOY -0.155 0.198 7d MIN T JAS 0.321 0.006 VC

7d MIN T JAS DOY 0.012 0.934 7d MIN T OND 0.076 0.522 7d MIN T OND DOY -0.021 0.870 Annual Total P -0.032 0.796 Total R JFM 0.035 0.775 Total R AMJ 0.098 0.406 Total R JAS -0.073 0.540 Total R OND -0.041 0.733 3d MAX R 0.013 0.924 3d MAX R DOY 0.011 0.935 3d MAX R JFM -0.095 0.422 3d MAX R JFM DOY -0.107 0.368 3d MAX R AMJ 0.067 0.577 3d MAX R AMJ DOY -0.056 0.643 3d MAX R JAS -0.019 0.881 3d MAX R JAS DOY -0.090 0.453



3d MAX R OND 0.029 0.817 3d MAX R OND DOY 0.148 0.320 30d MIN R 0.236 0.070 W

30d MIN R DOY 0.208 0.077 W

30d MIN R JFM 0.232 0.075 W

30d MIN R JFM DOY 0.121 0.307 30d MIN R AMJ 0.052 0.663 30d MIN R AMJ DOY -0.005 0.978 30d MIN R JAS 0.137 0.247 30d MIN R JAS DOY 0.257 0.029 PT

30d MIN R OND -0.035 0.775 30d MIN R OND DOY -0.090 0.453 Annual PET 0.340 0.004 VC

Annual P-PET -0.073 0.540 Annual Richards-Baker Flashiness Index 0.137 0.260 Annual 10:90 exceedance -0.016 0.906 Annual yield -0.055 0.657 JFM yield 0.060 0.614 AMJ yield 0.109 0.363 JAS yield -0.087 0.477 OND yield -0.166 0.173 3d MAX Q 0.127 0.299 3d MAX Q DOY -0.005 0.976 3d MAX Q JFM 0.149 0.205 3d MAX Q JFM DOY 0.090 0.453 3d MAX Q AMJ 0.052 0.670 3d MAX Q AMJ DOY 0.003 0.989 3d MAX Q JAS -0.098 0.423 3d MAX Q JAS DOY -0.220 0.072 W

3d MAX Q OND -0.152 0.213 3d MAX Q OND DOY 0.346 0.004 VC

7d MIN Q -0.292 0.028 PT

7d MIN Q DOY 0.217 0.075 W

7d MIN Q JFM 0.076 0.522 7d MIN Q JFM DOY 0.123 0.300 7d MIN Q AMJ -0.042 0.733 7d MIN Q AMJ DOY 0.152 0.210 7d MIN Q JAS -0.246 0.062 W

7d MIN Q JAS DOY 0.217 0.075 W

7d MIN Q OND -0.173 0.169



7d MIN Q OND DOY -0.207 0.099 W

Annual BF yield -0.244 0.044 PT

JFM BF yield -0.032 0.796 AMJ BF yield -0.146 0.222 JAS BF yield -0.059 0.635 OND BF yield -0.255 0.035 PT

3d MAX BF -0.095 0.441 3d MAX BF DOY -0.009 0.953 3d MAX BF JFM -0.006 0.967 3d MAX BF JFM DOY -0.073 0.547 3d MAX BF AMJ -0.129 0.280 3d MAX BF AMJ DOY -0.121 0.339 3d MAX BF JAS -0.059 0.635 3d MAX BF JAS DOY -0.031 0.818 3d MAX BF OND -0.176 0.146 3d MAX BF OND DOY 0.306 0.013 VC

7d MIN BF -0.287 0.030 PT

7d MIN BF DOY 0.211 0.083 W

7d MIN BF JFM 0.051 0.673 7d MIN BF JFM DOY 0.119 0.319 7d MIN BF AMJ 0.015 0.910 7d MIN BF AMJ DOY -0.057 0.674 7d MIN BF JAS -0.242 0.067 W

7d MIN BF JAS DOY 0.211 0.083 W

7d MIN BF OND -0.188 0.135 7d MIN BF OND DOY -0.286 0.032 PT

Annual Average W285 GW 0.111 0.721 W285 3d MAX GW -0.111 0.721 W285 3d MAX GW DOY 0.067 0.858 W285 3d MAX GW JFM -0.091 0.756 W285 3d MAX GW JFM DOY 0.110 0.696 W285 3d MAX GW AMJ 0.121 0.584 W285 3d MAX GW AMJ DOY -0.189 0.380 W285 7d MIN GW 0.244 0.371 W285 7d MIN GW DOY 0.045 0.928 W285 7d MIN GW JFM -0.055 0.876 W285 7d MIN GW JFM DOY -0.117 0.688 W285 7d MIN GW AMJ 0.253 0.228 W285 7d MIN GW AMJ DOY 0.036 0.910


Table G-2: Annual analysis of Spearman’s Rank for Parkhill Creek. Correlation coefficient is above and p-values are


Blank cells indicate insufficient data for analysis.

Mean T

Tota

l P

PET

P-P

ET

Tota

l R

7d M

AX T

7d M

AX T

DO

Y

7d M

IN T

7d M

IN T

DO

Y

3d M

AX R

3d M

AX R

DO

Y

30d M

IN R

30d M

IN R

DO

Y

RBI

10:9

0 e

xceedance

Annual yie

ld

Annual BF y

ield

3d M

AX Q

3d M

AX Q

DO

Y

7d M

IN Q

7d M

IN Q

DO

Y

3d M

AX B

F

3d M

AX B

F D

OY

7d M

IN B

F

7d M

IN B

F D

OY

W285 G

W

W285 3

d M

AX G

W

W285 3

d M

AX G

W D

OY

W285 7

d M

IN G

W

W285 7

d M

IN G

W D

OY

Mean T -0.31 0.89 -0.46 -0.27 0.48 0.1 0.67 0.07 -0.35 0.05 0.56 0.22 0.19 0.3 -0.31 -0.28 -0.06 -0.29 -0.42 0.11 -0.23 -0.16 -0.42 0.11 -0.54 -0.31 0.13 -0.44 0.53

Total P 0.06 -0.35 0.96 0.95 -0.45 0.31 -0.06 -0.01 0.61 -0.13 -0.13 -0.44 -0.05 -0.28 0.83 0.51 0.47 0.24 0.61 -0.03 0.37 0.22 0.62 -0.02 0.25 0.24 0.44 0.2 -0.46

PET 0 0.04 -0.55 -0.36 0.49 0.09 0.41 0.04 -0.28 0.16 0.41 0.35 0.24 0.18 -0.4 -0.45 -0.08 -0.23 -0.52 0.21 -0.19 -0.08 -0.52 0.21 -0.64 -0.54 0.05 -0.35 0.36

P-PET 0 0 0 0.92 -0.54 0.28 -0.09 0 0.6 -0.18 -0.19 -0.47 -0.09 -0.28 0.85 0.58 0.48 0.24 0.7 -0.09 0.37 0.17 0.7 -0.08 0.32 0.25 0.41 0.27 -0.48

Total R 0.12 0 0.03 0 -0.44 0.27 0.02 -0.1 0.62 -0.16 -0.11 -0.55 -0.14 -0.24 0.89 0.57 0.58 0.17 0.64 -0.06 0.39 0.14 0.64 -0.05 0.26 0.28 0.42 0.21 -0.44

7d MAX T 0 0.01 0 0 0.01 -0.39 0.25 -0.02 -0.34 0.25 0.37 0.27 -0.01 0.22 -0.46 -0.38 -0.28 -0.1 -0.57 0.17 -0.21 0.08 -0.57 0.16 -0.55 -0.48 0.43 -0.07 -0.08

7d MAX T DOY 0.58 0.07 0.61 0.1 0.11 0.02 0 0.09 0.22 -0.03 -0.13 -0.15 0.18 0.03 0.25 0.06 0.2 -0.02 0.01 0.11 0.13 -0.01 -0.01 0.11 0.79 -0.12 -0.55 0.7 0.26

7d MIN T 0 0.71 0.01 0.62 0.92 0.15 0.99 0.14 -0.19 -0.02 0.57 0.13 0.04 0.25 0.01 0.18 -0.02 -0.11 -0.09 -0.12 -0.01 -0.08 -0.1 -0.12 -0.44 0.2 0.31 -0.49 0.08

7d MIN T DOY 0.7 0.96 0.8 0.99 0.57 0.93 0.59 0.41 0.03 0.33 0.07 0.39 0.4 -0.02 -0.17 -0.12 -0.42 0.23 0.14 0.06 -0.21 0.11 0.14 0.06 -0.13 -0.15 0.35 0.01 -0.26

3d MAX R 0.04 0 0.09 0 0 0.04 0.2 0.26 0.87 -0.08 -0.3 -0.27 -0.02 -0.5 0.51 0.17 0.56 0.01 0.45 0.23 0.01 0.49 0.46 0.24 -0.19 0.02 0.35 -0.07 -0.57

3d MAX R DOY 0.76 0.46 0.36 0.28 0.36 0.15 0.87 0.91 0.05 0.63 0.22 0.31 0.28 -0.1 -0.1 0 -0.41 0.28 -0.02 0.02 0.01 0.15 -0.01 0.03 -0.04 -0.35 0.16 0.22 0.15

30d MIN R 0 0.44 0.01 0.26 0.52 0.02 0.44 0 0.69 0.07 0.2 0.3 -0.15 0.38 0 0.13 -0.2 0.04 -0.23 0.19 0.16 -0.17 -0.22 0.19 -0.31 0.09 0.07 -0.49 0.42

30d MIN R DOY 0.2 0.01 0.03 0 0 0.11 0.39 0.46 0.02 0.11 0.07 0.07 0.19 0.15 -0.44 -0.34 -0.51 0.17 -0.35 0.07 -0.24 0.17 -0.34 0.05 -0.66 -0.38 0.22 -0.52 0.26

RBI 0.29 0.77 0.17 0.6 0.43 0.96 0.32 0.83 0.02 0.9 0.11 0.4 0.28 -0.36 -0.16 -0.37 -0.02 -0.24 -0.08 0.29 -0.34 0.13 -0.07 0.29

10:90 exceedance 0.09 0.11 0.31 0.11 0.17 0.21 0.85 0.15 0.92 0 0.59 0.03 0.41 0.04 -0.15 0.03 -0.34 -0.17 -0.2 -0.33 0.06 -0.4 -0.22 -0.34

Annual yield 0.08 0 0.02 0 0 0.01 0.16 0.95 0.35 0 0.57 0.98 0.01 0.35 0.39 0.72 0.6 0.21 0.69 -0.13 0.55 0.2 0.69 -0.12

Annual BF yield 0.11 0 0.01 0 0 0.03 0.73 0.3 0.51 0.34 0.99 0.46 0.05 0.03 0.87 0 0.24 0.37 0.54 -0.42 0.75 -0.04 0.54 -0.42

3d MAX Q 0.72 0.01 0.67 0 0 0.11 0.26 0.92 0.01 0 0.02 0.25 0 0.91 0.05 0 0.18 -0.2 0.32 0.1 0.13 0.08 0.33 0.11

3d MAX Q DOY 0.1 0.17 0.2 0.17 0.34 0.57 0.89 0.55 0.19 0.98 0.11 0.84 0.33 0.17 0.35 0.23 0.03 0.26 0.15 -0.14 0.38 0.28 0.17 -0.13

7d MIN Q 0.01 0 0 0 0 0 0.96 0.63 0.44 0.01 0.91 0.19 0.04 0.66 0.25 0 0 0.06 0.39 -0.2 0.27 0.1 1 -0.19

7d MIN Q DOY 0.54 0.86 0.23 0.62 0.72 0.34 0.55 0.48 0.73 0.2 0.9 0.29 0.68 0.09 0.06 0.45 0.01 0.58 0.42 0.26 -0.26 0.13 -0.19 1

3d MAX BF 0.19 0.03 0.29 0.03 0.02 0.24 0.45 0.97 0.22 0.94 0.96 0.37 0.18 0.05 0.73 0 0 0.46 0.03 0.13 0.14 -0.1 0.27 -0.25

3d MAX BF DOY 0.36 0.21 0.64 0.34 0.42 0.65 0.94 0.65 0.53 0 0.41 0.34 0.33 0.48 0.02 0.25 0.81 0.65 0.11 0.59 0.46 0.56 0.1 0.14

7d MIN BF 0.01 0 0 0 0 0 0.97 0.59 0.44 0.01 0.96 0.2 0.05 0.69 0.21 0 0 0.05 0.34 0 0.29 0.12 0.57 -0.17

7d MIN BF DOY 0.53 0.91 0.24 0.65 0.79 0.36 0.54 0.5 0.76 0.18 0.87 0.28 0.78 0.09 0.05 0.49 0.01 0.55 0.45 0.28 0 0.15 0.42 0.32

W285 GW 0.11 0.49 0.05 0.37 0.47 0.1 0.01 0.2 0.72 0.6 0.91 0.38 0.04 0.3 -0.59 0.71 0.11

W285 3d MAX GW 0.38 0.51 0.11 0.49 0.43 0.16 0.75 0.58 0.67 0.96 0.33 0.81 0.28 0.4 -0.2 -0.33 0.1

W285 3d MAX GW DOY 0.73 0.2 0.88 0.24 0.23 0.21 0.1 0.38 0.33 0.33 0.65 0.85 0.53 0.07 0.58 -0.18 -0.66

W285 7d MIN GW 0.2 0.58 0.33 0.45 0.56 0.85 0.03 0.15 0.99 0.85 0.53 0.15 0.13 0.02 0.35 0.63 -0.27

W285 7d MIN GW DOY 0.11 0.19 0.31 0.16 0.2 0.83 0.47 0.83 0.47 0.09 0.69 0.23 0.48 0.76 0.79 0.04 0.45


Table G-3: Winter seasonal analysis of Spearman’s Rank for the Parkhill Creek. Correlation coefficient is above and


shaded.

Tota

l R J

FM

7d M

AX T

JFM

7d M

AX T

JFM

DO

Y

7d M

IN T

JFM

7d M

IN T

JFM

DO

Y

3d M

AX R

JFM

3d M

AX R

JFM

DO

Y

30d M

IN R

JFM

30d M

IN R

JFM

DO

Y

JFM

yie

ld

JFM

BF y

ield

3d M

AX Q

JFM

3d M

AX Q

JFM

DO

Y

7d M

IN Q

JFM

7d M

IN Q

JFM

DO

Y

3d M

AX B

F J

FM

3d M

AX B

F J

FM

DO

Y

7d M

IN B

F J

FM

7d M

IN B

F J

FM

DO

Y

W285 3

d M

AX G

W J

FM

W285 3

d M

AX G

W J

FM

DO

Y

W285 7

d M

IN G

W J

FM

W285 7

d M

IN G

W J

FM

DO

Y

Total R JFM 0.12 0.29 0.17 0.02 0.46 0.06 0.1 -0.41 0.69 0.43 0.47 -0.09 0.45 -0.41 0.18 -0.08 0.46 -0.29 -0.05 0.11 -0.17 -0.56

7d MAX T JFM 0.49 0.28 0.41 0.26 -0.03 0.04 0.14 0.17 -0.26 -0.04 -0.22 -0.11 0.04 0.21 -0.42 -0.26 0 0.31 0.46 -0.32 0.48 0.38

7d MAX T JFM DOY 0.08 0.1 0.03 0 0.19 0.15 -0.06 -0.03 -0.06 -0.08 0.15 -0.13 -0.28 0.02 -0.31 -0.21 -0.21 0.12 0.39 -0.34 0.42 0.42

7d MIN T JFM 0.33 0.01 0.85 0.13 -0.02 -0.19 0.54 0.01 -0.04 0.43 -0.26 -0.29 0.54 -0.05 0.01 -0.33 0.52 0.03 -0.36 0.42 -0.29 -0.05

7d MIN T JFM DOY 0.91 0.12 0.98 0.44 0.03 0.26 -0.1 0.25 0.02 -0.18 -0.11 0.21 -0.1 0.21 -0.09 0.31 -0.09 0.29 -0.33 0.36 -0.4 -0.14

3d MAX R JFM 0.01 0.86 0.27 0.89 0.86 0.32 -0.38 -0.05 0.45 0.13 0.52 0.2 0.12 -0.21 0.03 0.27 0.16 -0.15 -0.16 0.24 -0.25 -0.22

3d MAX R JFM DOY 0.73 0.83 0.38 0.27 0.12 0.06 -0.25 0.14 0.06 -0.01 -0.03 0.36 -0.09 0.17 0.01 0.23 -0.09 0.2 0.16 -0.03 0.11 -0.47

30d MIN R JFM 0.57 0.42 0.74 0 0.56 0.02 0.14 -0.07 0.01 0.34 -0.33 -0.24 0.62 -0.01 0.07 -0.54 0.59 0.01 -0.15 0.1 -0.07 -0.17

30d MIN R JFM DOY 0.01 0.33 0.88 0.95 0.14 0.78 0.43 0.67 -0.47 -0.34 -0.25 0.03 -0.31 0.46 -0.14 -0.02 -0.29 0.36 -0.23 0.17 -0.25 -0.05

JFM yield 0 0.13 0.72 0.8 0.91 0.01 0.74 0.95 0 0.46 0.57 0.12 0.48 -0.33 0.41 0.12 0.49 -0.34 -0.19 0.21 -0.32 -0.46

JFM BF yield 0.01 0.82 0.64 0.01 0.3 0.47 0.97 0.04 0.04 0 0.01 -0.02 0.71 -0.29 0.7 -0.22 0.7 -0.25 0.28 -0.3 0.17 0.15

3d MAX Q JFM 0 0.2 0.38 0.12 0.53 0 0.87 0.05 0.14 0 0.95 0.06 -0.05 -0.09 0.14 0.15 0 -0.09 0.06 0.06 -0.03 -0.34

3d MAX Q JFM DOY 0.58 0.52 0.44 0.09 0.21 0.24 0.03 0.16 0.86 0.5 0.92 0.72 -0.1 0.08 0.21 0.2 -0.11 0.05 0.07 0.05 0 -0.09

7d MIN Q JFM 0.01 0.81 0.1 0 0.58 0.5 0.61 0 0.07 0 0 0.77 0.56 -0.15 0.35 -0.31 0.99 -0.1 -0.17 0.18 -0.21 -0.42

7d MIN Q JFM DOY 0.01 0.21 0.89 0.76 0.22 0.23 0.31 0.95 0.01 0.05 0.09 0.59 0.66 0.39 -0.1 -0.12 -0.12 0.88 0.44 -0.46 0.49 0.52

3d MAX BF JFM 0.3 0.01 0.07 0.97 0.6 0.87 0.94 0.69 0.43 0.01 0 0.43 0.22 0.03 0.55 0.14 0.37 -0.14 0.07 -0.21 -0.07 0.18

3d MAX BF JFM DOY 0.63 0.12 0.22 0.05 0.06 0.1 0.17 0 0.91 0.48 0.2 0.4 0.25 0.07 0.48 0.43 -0.31 -0.09 -0.21 -0.01 -0.32 -0.08

7d MIN BF JFM 0 0.98 0.22 0 0.58 0.34 0.58 0 0.08 0 0 0.98 0.54 0 0.5 0.03 0.06 -0.08 -0.25 0.23 -0.3 -0.4

7d MIN BF JFM DOY 0.09 0.07 0.47 0.85 0.09 0.39 0.24 0.95 0.03 0.04 0.14 0.59 0.77 0.56 0 0.42 0.6 0.64 0.44 -0.46 0.49 0.52

W285 3d MAX GW JFM 0.87 0.15 0.24 0.27 0.32 0.63 0.63 0.66 0.5 0.57 0.4 0.85 0.83 0.61 0.18 0.83 0.53 0.47 0.18 -0.91 0.97 0.58

W285 3d MAX GW JFM DOY 0.75 0.33 0.31 0.2 0.27 0.48 0.94 0.77 0.62 0.55 0.37 0.85 0.87 0.59 0.16 0.55 0.98 0.5 0.16 0 -0.9 -0.68

W285 7d MIN GW JFM 0.61 0.13 0.19 0.39 0.23 0.47 0.75 0.83 0.47 0.34 0.61 0.94 1 0.54 0.13 0.83 0.34 0.37 0.13 0 0 0.61

W285 7d MIN GW JFM DOY 0.07 0.25 0.2 0.89 0.68 0.52 0.15 0.62 0.89 0.15 0.66 0.31 0.78 0.2 0.1 0.6 0.82 0.23 0.1 0.06 0.02 0.05


Table G-4: Spring seasonal analysis of Spearman’s Rank for the Parkhill Creek. Correlation coefficient is above and p-


shaded.

Tota

l R A

MJ

7d M

AX T

AM

J

7d M

AX T

AM

J D

OY

7d M

IN T

AM

J

7d M

IN T

AM

J D

OY

3d M

AX R

AM

J

3d M

AX R

AM

J D

OY

30d M

IN R

AM

J

30d M

IN R

AM

J D

OY

AM

J yie

ld

AM

J BF y

ield

3d M

AX Q

AM

J

3d M

AX Q

AM

J D

OY

7d M

IN Q

AM

J

7d M

IN Q

AM

J D

OY

3d M

AX B

F A

MJ

3d M

AX B

F A

MJ

DO

Y

7d M

IN B

F A

MJ

7d M

IN B

F A

MJ

DO

Y

W285 3

d M

AX G

W A

MJ

W285 3

d M

AX G

W A

MJ

DO

Y

W285 7

d M

IN G

W A

MJ

W285 7

d M

IN G

W A

MJ

DO

Y

Total R AMJ -0.24 0.02 -0.34 -0.39 0.84 -0.11 0.29 -0.24 0.73 0.53 0.61 0.07 0.63 -0.33 0.34 0.2 0.7 -0.12 -0.35 0.34 -0.05 -0.51

7d MAX T AMJ 0.17 0.34 0.17 -0.13 -0.45 -0.04 -0.12 0.04 -0.19 -0.27 -0.34 0.05 -0.02 0.18 -0.32 -0.17 -0.04 0.03 -0.01 0.32 -0.6 -0.09

7d MAX T AMJ DOY 0.9 0.04 0.05 0.05 -0.18 -0.08 0.13 0.29 0.18 0.04 -0.16 -0.04 0.16 0.22 -0.17 -0.01 0.14 0.15 -0.02 0.23 -0.19 -0.26

7d MIN T AMJ 0.04 0.33 0.76 0.25 -0.27 -0.03 -0.12 0.06 -0.38 -0.56 -0.36 0.08 -0.19 -0.05 -0.46 0.03 -0.31 -0.19 0 0.22 -0.2 0.06

7d MIN T AMJ DOY 0.02 0.45 0.78 0.14 -0.25 0.09 -0.15 -0.11 -0.22 -0.16 -0.16 -0.07 -0.07 0.01 -0.09 0.21 -0.2 -0.17 0.32 -0.18 0.06 0.4

3d MAX R AMJ 0 0.01 0.28 0.11 0.14 -0.08 0.12 -0.25 0.54 0.43 0.57 0.06 0.43 -0.32 0.42 0.16 0.52 -0.15 -0.32 0.31 0.03 -0.42

3d MAX R AMJ DOY 0.52 0.82 0.65 0.86 0.6 0.64 0 -0.06 -0.01 -0.21 -0.15 0.44 -0.12 -0.05 -0.31 0.36 -0.14 -0.04 0.12 -0.32 0.18 0.07

30d MIN R AMJ 0.08 0.5 0.46 0.47 0.39 0.48 0.99 0.02 0.37 0.07 0.1 0.19 0.24 0.2 -0.16 0.33 0.21 0.22 -0.24 0.08 0 -0.25

30d MIN R AMJ DOY 0.16 0.81 0.08 0.73 0.51 0.15 0.74 0.9 -0.16 -0.06 -0.23 0.09 -0.49 0.32 -0.11 -0.2 -0.46 -0.16 0.17 0.06 0.09 -0.1

AMJ yield 0 0.27 0.29 0.02 0.2 0 0.97 0.03 0.36 0.53 0.73 0.08 0.49 -0.07 0.2 0.29 0.54 0.01 -0.3 0.31 -0.1 -0.45

AMJ BF yield 0 0.11 0.81 0 0.35 0.01 0.23 0.68 0.72 0 0.32 -0.1 0.49 -0.13 0.76 -0.04 0.57 -0.02 -0.16 0.12 0.06 -0.31

3d MAX Q AMJ 0 0.05 0.37 0.03 0.37 0 0.39 0.57 0.18 0 0.06 -0.16 0.29 -0.3 0.34 0.13 0.34 -0.12 -0.37 0.46 -0.17 -0.38

3d MAX Q AMJ DOY 0.69 0.76 0.81 0.63 0.68 0.72 0.01 0.26 0.62 0.64 0.56 0.36 0.03 -0.26 -0.35 0.04 -0.02 0.11 0.41 -0.48 0.28 0.29

7d MIN Q AMJ 0 0.91 0.37 0.27 0.69 0.01 0.49 0.17 0 0 0 0.09 0.87 -0.57 0.26 0.18 0.94 0.03 -0.1 0.23 -0.33 -0.36

7d MIN Q AMJ DOY 0.05 0.3 0.2 0.77 0.96 0.06 0.79 0.26 0.06 0.69 0.45 0.08 0.14 0 -0.21 0.12 -0.49 0.2 -0.01 -0.21 0.23 0.2

3d MAX BF AMJ 0.04 0.06 0.33 0.01 0.6 0.01 0.07 0.36 0.53 0.25 0 0.05 0.04 0.13 0.23 -0.24 0.33 -0.1 -0.31 0.35 -0.17 -0.42

3d MAX BF AMJ DOY 0.26 0.32 0.98 0.88 0.24 0.35 0.03 0.06 0.25 0.09 0.81 0.44 0.83 0.31 0.48 0.16 0.19 -0.12 -0.11 0.01 0.04 -0.2

7d MIN BF AMJ 0 0.8 0.41 0.07 0.24 0 0.43 0.24 0.01 0 0 0.05 0.89 0 0 0.05 0.26 -0.06 -0.19 0.31 -0.27 -0.51

7d MIN BF AMJ DOY 0.5 0.86 0.4 0.27 0.32 0.41 0.84 0.2 0.37 0.94 0.92 0.5 0.52 0.87 0.24 0.57 0.5 0.72 0.32 -0.58 0.38 0.67

W285 3d MAX GW AMJ 0.23 0.98 0.94 0.99 0.26 0.26 0.67 0.41 0.56 0.32 0.6 0.22 0.16 0.75 0.99 0.31 0.72 0.53 0.29 -0.83 0.74 0.83

W285 3d MAX GW AMJ DOY 0.23 0.27 0.43 0.44 0.55 0.28 0.26 0.79 0.85 0.31 0.69 0.11 0.1 0.46 0.49 0.23 0.98 0.31 0.04 0 -0.86 -0.84

W285 7d MIN GW AMJ 0.88 0.02 0.52 0.49 0.84 0.91 0.54 0.99 0.76 0.75 0.84 0.58 0.36 0.27 0.45 0.58 0.89 0.37 0.21 0 0 0.72

W285 7d MIN GW AMJ DOY 0.06 0.76 0.38 0.83 0.16 0.13 0.82 0.38 0.73 0.12 0.3 0.21 0.35 0.22 0.51 0.15 0.52 0.08 0.01 0 0 0


Table G-5: Summer seasonal analysis of Spearman’s Rank for the Parkhill Creek. Correlation coefficient is above and


shaded.

Tota

l R J

AS

7d M

AX T

JAS

7d M

AX T

JAS D

OY

7d M

IN T

JAS

7d M

IN T

JAS D

OY

3d M

AX R

JAS

3d M

AX R

JAS D

OY

30d M

IN R

JAS

30d M

IN R

JAS D

OY

JAS y

ield

JAS B

F y

ield

3d M

AX Q

JAS

3d M

AX Q

JAS D

OY

7d M

IN Q

JAS

7d M

IN Q

JAS D

OY

3d M

AX B

F J

AS

3d M

AX B

F J

AS D

OY

7d M

IN B

F J

AS

7d M

IN B

F J

AS D

OY

Total R JAS -0.33 0.12 -0.23 0.12 0.64 0.12 0.47 -0.28 0.73 0.61 0.69 0.5 0.72 -0.09 0.48 0.46 0.72 -0.08

7d MAX T JAS 0.05 -0.39 0.02 0.06 -0.23 -0.01 -0.38 -0.16 -0.56 -0.66 -0.56 -0.12 -0.52 0.1 -0.53 -0.21 -0.52 0.1

7d MAX T JAS DOY 0.49 0.02 0.02 0.22 0.08 0.04 0.28 0.09 0.21 0.3 0.18 -0.12 0.19 0.08 0.21 0.18 0.18 0.09

7d MIN T JAS 0.18 0.9 0.92 -0.17 -0.16 -0.24 0.14 0.33 -0.3 -0.21 -0.33 -0.26 -0.3 0.18 -0.17 -0.25 -0.29 0.17

7d MIN T JAS DOY 0.5 0.71 0.21 0.32 0.12 0.12 -0.13 0.1 0 0.01 -0.03 0.27 -0.08 -0.03 0.11 0.17 -0.08 -0.03

3d MAX R JAS 0 0.18 0.63 0.34 0.5 -0.04 0.06 -0.15 0.5 0.27 0.52 0.35 0.49 -0.02 0.21 0.28 0.49 0

3d MAX R JAS DOY 0.5 0.97 0.8 0.17 0.49 0.8 0.14 -0.08 0.12 0.19 0.18 0.3 0.15 -0.13 0.29 0.11 0.17 -0.13

30d MIN R JAS 0 0.02 0.09 0.41 0.43 0.74 0.43 -0.03 0.26 0.42 0.26 0.03 0.36 0 0.35 0.07 0.36 0

30d MIN R JAS DOY 0.1 0.34 0.62 0.05 0.56 0.37 0.65 0.85 -0.07 0.04 -0.08 -0.34 -0.38 0.45 0.01 -0.25 -0.37 0.45

JAS yield 0 0 0.23 0.08 0.98 0 0.5 0.14 0.7 0.89 0.96 0.21 0.72 0.15 0.7 0.43 0.72 0.17

JAS BF yield 0 0 0.09 0.24 0.94 0.12 0.29 0.01 0.81 0 0.85 0.2 0.72 0.12 0.88 0.47 0.72 0.14

3d MAX Q JAS 0 0 0.31 0.05 0.85 0 0.32 0.14 0.64 0 0 0.22 0.67 0.11 0.65 0.38 0.67 0.13

3d MAX Q JAS DOY 0 0.51 0.51 0.13 0.12 0.04 0.09 0.89 0.05 0.23 0.26 0.22 0.4 -0.32 0.22 0.35 0.4 -0.32

7d MIN Q JAS 0 0 0.28 0.09 0.64 0 0.4 0.03 0.03 0 0 0 0.02 -0.14 0.55 0.38 1 -0.13

7d MIN Q JAS DOY 0.61 0.56 0.63 0.32 0.86 0.92 0.46 0.99 0.01 0.4 0.49 0.53 0.06 0.42 0.02 -0.22 -0.13 1

3d MAX BF JAS 0 0 0.23 0.32 0.53 0.24 0.09 0.05 0.97 0 0 0 0.21 0 0.89 0.44 0.55 0.04

3d MAX BF JAS DOY 0.01 0.22 0.31 0.15 0.34 0.1 0.54 0.7 0.15 0.01 0.01 0.03 0.04 0.03 0.22 0.01 0.37 -0.21

7d MIN BF JAS 0 0 0.32 0.1 0.64 0 0.34 0.04 0.03 0 0 0 0.02 0 0.46 0 0.03 -0.12

7d MIN BF JAS DOY 0.66 0.58 0.63 0.33 0.88 0.98 0.48 1 0.01 0.35 0.44 0.47 0.07 0.46 0 0.82 0.23 0.51


Table G-6: Autumn seasonal analysis of Spearman’s Rank for the Parkhill Creek. Correlation coefficient is above and


shaded.

Tota

l R O

ND

7d M

AX T

ON

D

7d M

AX T

ON

D D

OY

7d M

IN T

ON

D

7d M

IN T

ON

D D

OY

3d M

AX R

ON

D

3d M

AX R

ON

D D

OY

30d M

IN R

ON

D

30d M

IN R

ON

D D

OY

ON

D y

ield

ON

D B

F y

ield

3d M

AX Q

ON

D

3d M

AX Q

ON

D D

OY

7d M

IN Q

ON

D

7d M

IN Q

ON

D D

OY

3d M

AX B

F O

ND

3d M

AX B

F O

ND

DO

Y

7d M

IN B

F O

ND

7d M

IN B

F O

ND

DO

Y

Total R OND -0.21 -0.1 0.34 -0.1 0.75 -0.2 0.58 -0.04 0.7 0.56 0.57 -0.21 0.24 -0.18 0.54 -0.4 0.25 0.09

7d MAX T OND 0.21 0.11 0.05 -0.13 -0.03 0.22 -0.02 -0.24 -0.16 -0.27 0.07 0.35 -0.39 -0.24 -0.12 0.05 -0.35 -0.19

7d MAX T OND DOY 0.56 0.54 -0.01 -0.12 -0.02 0.11 0.19 0.08 -0.04 -0.16 0.19 0.23 0.01 0.12 -0.11 0.04 0.01 0.12

7d MIN T OND 0.04 0.76 0.93 0.09 0.35 -0.08 0.39 -0.49 0.27 0.23 0.16 0.03 0.15 -0.04 0.15 0.03 0.19 0.12

7d MIN T OND DOY 0.56 0.45 0.48 0.62 -0.15 -0.09 0.03 -0.12 0.05 0.16 -0.15 -0.06 0.1 0.09 0.05 -0.14 0.09 0.1

3d MAX R OND 0 0.87 0.92 0.04 0.38 -0.08 0.29 -0.04 0.63 0.54 0.61 -0.18 0.24 -0.05 0.61 -0.35 0.3 0.22

3d MAX R OND DOY 0.23 0.2 0.53 0.66 0.59 0.63 -0.11 -0.19 -0.18 -0.27 -0.03 0.46 -0.19 -0.31 -0.18 0.53 -0.16 -0.07

30d MIN R OND 0 0.91 0.25 0.02 0.85 0.09 0.53 -0.26 0.45 0.28 0.42 0.01 0.19 -0.15 0.16 -0.19 0.2 0

30d MIN R OND DOY 0.81 0.16 0.64 0 0.47 0.84 0.28 0.12 0.13 0.15 0.1 -0.44 0.21 0.23 0.14 -0.26 0.17 0.01

OND yield 0 0.37 0.84 0.12 0.76 0 0.3 0.01 0.46 0.88 0.78 -0.36 0.67 0.34 0.82 -0.56 0.69 0.39

OND BF yield 0 0.12 0.38 0.19 0.36 0 0.12 0.11 0.4 0 0.62 -0.54 0.68 0.48 0.9 -0.66 0.7 0.59

3d MAX Q OND 0 0.69 0.28 0.37 0.4 0 0.88 0.01 0.58 0 0 -0.21 0.43 0.16 0.65 -0.49 0.47 0.3

3d MAX Q OND DOY 0.22 0.05 0.18 0.86 0.73 0.31 0.01 0.94 0.01 0.03 0 0.23 -0.44 -0.4 -0.37 0.6 -0.45 -0.37

7d MIN Q OND 0.17 0.02 0.96 0.4 0.57 0.17 0.28 0.27 0.22 0 0 0.01 0.01 0.73 0.41 -0.43 0.99 0.5

7d MIN Q OND DOY 0.32 0.17 0.5 0.84 0.6 0.79 0.08 0.39 0.2 0.05 0 0.38 0.02 0 0.29 -0.35 0.7 0.55

3d MAX BF OND 0 0.52 0.54 0.39 0.78 0 0.32 0.36 0.44 0 0 0 0.03 0.02 0.1 -0.57 0.44 0.45

3d MAX BF OND DOY 0.02 0.78 0.83 0.87 0.42 0.04 0 0.28 0.14 0 0 0 0 0.01 0.04 0 -0.42 -0.4

7d MIN BF OND 0.16 0.04 0.95 0.29 0.63 0.09 0.36 0.25 0.34 0 0 0.01 0.01 0 0 0.01 0.01 0.56

7d MIN BF OND DOY 0.61 0.29 0.5 0.49 0.59 0.21 0.69 0.98 0.96 0.02 0 0.08 0.03 0 0 0.01 0.02 0


Table G-7: Annual analysis of Kendall’s Rank for the Parkhill Creek. Correlation coefficient is above and p-value is


Blank cells indicate insufficient data for analysis.

Mean T

Tota

l P

PET

P-P

ET

Tota

l R

7d M

AX T

7d M

AX T

DO

Y

7d M

IN T

7d M

IN T

DO

Y

3d M

AX R

3d M

AX R

DO

Y

30d M

IN R

30d M

IN R

DO

Y

RBI

10:9

0 e

xceedance

Annual yie

ld

Annual BF y

ield

3d M

AX Q

3d M

AX Q

DO

Y

7d M

IN Q

7d M

IN Q

DO

Y

3d M

AX B

F

3d M

AX B

F D

OY

7d M

IN B

F

7d M

IN B

F D

OY

W285 G

W

W285 3

d M

AX G

W

W285 3

d M

AX G

W D

OY

W285 7

d M

IN G

W

W285 7

d M

IN G

W D

OY

Mean T -0.21 0.71 -0.33 -0.18 0.3 0.07 0.5 0.05 -0.23 0.03 0.44 0.14 0.13 0.21 -0.22 -0.18 -0.06 -0.18 -0.29 0.09 -0.13 -0.07 -0.3 0.09 -0.42 -0.2 0.07 -0.29 0.36

Total P 0.21 -0.23 0.84 0.82 -0.31 0.2 -0.03 0.01 0.43 -0.08 -0.12 -0.3 -0.03 -0.17 0.66 0.38 0.33 0.17 0.48 -0.02 0.25 0.14 0.5 -0.01 0.16 0.2 0.29 0.2 -0.27

PET 0 0 -0.39 -0.23 0.32 0.08 0.29 0.02 -0.2 0.11 0.3 0.24 0.16 0.12 -0.28 -0.32 -0.02 -0.17 -0.4 0.16 -0.12 -0.05 -0.4 0.15 -0.56 -0.42 0.11 -0.24 0.22

P-PET 0.05 0.17 0.02 0.77 -0.38 0.19 -0.07 -0.01 0.41 -0.14 -0.15 -0.32 -0.06 -0.17 0.72 0.43 0.35 0.18 0.55 -0.07 0.27 0.12 0.55 -0.06 0.2 0.24 0.24 0.24 -0.31

Total R 0.29 0 0.17 0 -0.3 0.16 0.02 -0.07 0.45 -0.1 -0.09 -0.39 -0.08 -0.17 0.71 0.4 0.42 0.13 0.5 -0.05 0.27 0.09 0.52 -0.04 0.2 0.24 0.24 0.24 -0.22

7d MAX T 0.08 0 0.06 0.02 0.07 -0.25 0.14 -0.02 -0.25 0.16 0.26 0.18 -0.01 0.13 -0.32 -0.26 -0.2 -0.09 -0.44 0.11 -0.14 0.03 -0.42 0.11 -0.42 -0.38 0.33 -0.02 0

7d MAX T DOY 0.7 0.06 0.64 0.28 0.36 0.14 0 0.07 0.15 -0.02 -0.1 -0.11 0.11 0.02 0.16 0.03 0.15 -0.03 0 0.06 0.11 0 -0.01 0.06 0.56 -0.11 -0.38 0.51 0.13

7d MIN T 0 0.24 0.09 0.69 0.93 0.42 0.98 0.11 -0.11 -0.01 0.44 0.09 0.03 0.15 0.01 0.12 -0.02 -0.08 -0.07 -0.07 -0.01 -0.03 -0.07 -0.07 -0.33 0.16 0.24 -0.38 0.18

7d MIN T DOY 0.75 0.84 0.9 0.97 0.67 0.91 0.69 0.53 0.03 0.23 0.04 0.29 0.3 0 -0.12 -0.08 -0.29 0.17 0.11 0.05 -0.16 0.06 0.11 0.04 -0.07 -0.16 0.25 -0.02 -0.18

3d MAX R 0.19 0.96 0.23 0.01 0.01 0.15 0.38 0.52 0.85 -0.06 -0.23 -0.2 -0.01 -0.37 0.36 0.11 0.39 0 0.34 0.16 0.01 0.36 0.35 0.16 0.02 -0.02 0.24 -0.11 -0.4

3d MAX R DOY 0.85 0.01 0.51 0.42 0.55 0.34 0.93 0.95 0.18 0.75 0.16 0.2 0.16 -0.07 -0.07 -0.01 -0.29 0.23 -0.02 0.03 0.01 0.08 -0.01 0.03 -0.02 -0.24 0.11 0.11 0.13

30d MIN R 0.01 0.65 0.07 0.38 0.59 0.12 0.55 0.01 0.83 0.17 0.34 0.24 -0.11 0.29 0 0.07 -0.15 0.03 -0.19 0.15 0.11 -0.11 -0.19 0.15 -0.16 0.05 0.05 -0.38 0.3

30d MIN R DOY 0.41 0.48 0.16 0.06 0.02 0.29 0.53 0.61 0.08 0.25 0.24 0.16 0.11 0.1 -0.3 -0.22 -0.35 0.15 -0.26 0.05 -0.16 0.12 -0.26 0.03 -0.47 -0.33 0.2 -0.33 0.18

RBI 0.48 0.07 0.37 0.76 0.67 0.98 0.55 0.88 0.09 0.98 0.35 0.53 0.54 -0.24 -0.12 -0.27 -0.01 -0.18 -0.05 0.21 -0.23 0.07 -0.04 0.21

10:90 exceedance 0.24 0.88 0.5 0.33 0.35 0.48 0.9 0.39 0.98 0.03 0.69 0.09 0.57 0.16 -0.1 0.02 -0.24 -0.11 -0.15 -0.22 0.04 -0.25 -0.16 -0.23

Annual yield 0.22 0.33 0.1 0 0 0.07 0.36 0.98 0.52 0.04 0.7 1 0.09 0.5 0.57 0.53 0.43 0.16 0.55 -0.12 0.39 0.13 0.55 -0.11

Annual BF yield 0.32 0 0.07 0.01 0.02 0.14 0.86 0.51 0.66 0.53 0.94 0.71 0.21 0.13 0.9 0 0.16 0.27 0.41 -0.3 0.58 -0.03 0.41 -0.29

3d MAX Q 0.76 0.03 0.9 0.04 0.01 0.25 0.41 0.91 0.1 0.02 0.1 0.4 0.04 0.96 0.17 0.01 0.37 -0.14 0.25 0.08 0.12 0.06 0.26 0.09

3d MAX Q DOY 0.3 0.06 0.35 0.32 0.47 0.61 0.86 0.64 0.33 0.99 0.18 0.85 0.39 0.31 0.55 0.38 0.12 0.44 0.11 -0.11 0.27 0.21 0.11 -0.1

7d MIN Q 0.09 0.34 0.02 0 0 0.01 0.99 0.7 0.53 0.05 0.93 0.28 0.14 0.8 0.41 0 0.01 0.16 0.54 -0.17 0.19 0.08 0.98 -0.16

7d MIN Q DOY 0.62 0 0.38 0.71 0.79 0.54 0.73 0.68 0.78 0.38 0.89 0.41 0.79 0.23 0.2 0.51 0.09 0.65 0.54 0.32 -0.18 0.1 -0.16 0.98

3d MAX BF 0.45 0.9 0.51 0.12 0.12 0.42 0.53 0.94 0.36 0.94 0.97 0.53 0.36 0.19 0.8 0.02 0 0.51 0.12 0.28 0.3 -0.07 0.2 -0.19

3d MAX BF DOY 0.68 0.15 0.77 0.5 0.61 0.88 1 0.85 0.73 0.04 0.64 0.52 0.49 0.7 0.16 0.45 0.85 0.74 0.24 0.66 0.58 0.71 0.08 0.11

7d MIN BF 0.09 0.43 0.02 0 0 0.01 0.95 0.68 0.55 0.04 0.95 0.29 0.14 0.82 0.37 0 0.02 0.14 0.53 0 0.36 0.27 0.64 -0.15

7d MIN BF DOY 0.6 0 0.41 0.73 0.84 0.55 0.72 0.69 0.82 0.36 0.88 0.4 0.87 0.22 0.19 0.55 0.09 0.63 0.56 0.37 0 0.29 0.53 0.41

W285 GW 0.22 0.94 0.1 0.58 0.58 0.22 0.1 0.35 0.85 0.95 0.95 0.65 0.17 0.16 -0.47 0.51 0.13

W285 3d MAX GW 0.58 0.67 0.22 0.5 0.5 0.28 0.76 0.67 0.66 0.95 0.5 0.88 0.35 0.67 -0.24 -0.24 0.04

W285 3d MAX GW DOY 0.85 0.58 0.76 0.5 0.5 0.35 0.28 0.5 0.49 0.5 0.76 0.88 0.58 0.17 0.5 -0.16 -0.54

W285 7d MIN GW 0.42 0.42 0.5 0.5 0.5 0.95 0.13 0.28 0.95 0.76 0.76 0.28 0.35 0.13 0.5 0.67 -0.18

W285 7d MIN GW DOY 0.31 0.45 0.53 0.38 0.53 1 0.71 0.62 0.61 0.25 0.71 0.4 0.62 0.71 0.9 0.11 0.62


Table G-8: Winter seasonal analysis of Kendall’s Rank for the Parkhill Creek. Correlation coefficient is above and p-


shaded.

Tota

l R J

FM

7d M

AX T

JFM

7d M

AX T

JFM

DO

Y

7d M

IN T

JFM

7d M

IN T

JFM

DO

Y

3d M

AX R

JFM

3d M

AX R

JFM

DO

Y

30d M

IN R

JFM

30d M

IN R

JFM

DO

Y

JFM

yie

ld

JFM

BF y

ield

3d M

AX Q

JFM

3d M

AX Q

JFM

DO

Y

7d M

IN Q

JFM

7d M

IN Q

JFM

DO

Y

3d M

AX B

F J

FM

3d M

AX B

F J

FM

DO

Y

7d M

IN B

F J

FM

7d M

IN B

F J

FM

DO

Y

W285 3

d M

AX G

W J

FM

W285 3

d M

AX G

W J

FM

DO

Y

W285 7

d M

IN G

W J

FM

W285 7

d M

IN G

W J

FM

DO

Y

Total R JFM 0.08 0.2 0.1 0.01 0.32 0.02 0.06 -0.26 0.54 0.3 0.33 -0.05 0.3 -0.28 0.13 -0.04 0.3 -0.19 -0.05 0.07 -0.16 -0.43

7d MAX T JFM 0.66 0.18 0.3 0.2 -0.01 0.03 0.1 0.11 -0.18 -0.03 -0.15 -0.07 0.04 0.16 -0.26 -0.18 0.02 0.23 0.35 -0.29 0.38 0.23

7d MAX T JFM DOY 0.23 0.29 0.01 0 0.13 0.14 -0.05 0 -0.04 -0.06 0.1 -0.1 -0.19 0.02 -0.23 -0.14 -0.14 0.09 0.29 -0.27 0.25 0.29

7d MIN T JFM 0.58 0.08 0.96 0.12 -0.02 -0.14 0.45 0.01 -0.04 0.28 -0.2 -0.21 0.37 -0.02 -0.01 -0.24 0.37 0.03 -0.27 0.4 -0.24 -0.04

7d MIN T JFM DOY 0.96 0.24 0.99 0.5 0.01 0.21 -0.09 0.2 0 -0.12 -0.08 0.18 -0.07 0.16 -0.06 0.24 -0.08 0.23 -0.28 0.26 -0.31 -0.12

3d MAX R JFM 0.05 0.96 0.44 0.9 0.95 0.23 -0.31 -0.03 0.34 0.06 0.39 0.14 0.09 -0.15 -0.01 0.21 0.1 -0.11 -0.16 0.22 -0.2 -0.16

3d MAX R JFM DOY 0.92 0.88 0.41 0.42 0.22 0.17 -0.21 0.14 0.03 0 -0.03 0.34 -0.08 0.1 0.01 0.16 -0.08 0.12 0.09 0.04 0.05 -0.31

30d MIN R JFM 0.71 0.54 0.77 0.01 0.62 0.07 0.21 -0.05 -0.01 0.26 -0.26 -0.21 0.48 -0.01 0.04 -0.41 0.45 0 -0.13 0.06 -0.04 -0.16

30d MIN R JFM DOY 0.12 0.5 0.98 0.97 0.25 0.85 0.42 0.76 -0.34 -0.23 -0.17 0.04 -0.22 0.34 -0.08 -0.02 -0.2 0.28 -0.2 0.11 -0.16 0

JFM yield 0 0.3 0.84 0.83 0.98 0.04 0.86 0.97 0.04 0.34 0.42 0.07 0.35 -0.22 0.29 0.11 0.34 -0.23 -0.13 0.15 -0.24 -0.35

JFM BF yield 0.07 0.87 0.72 0.09 0.47 0.73 0.99 0.13 0.18 0.04 -0.01 0 0.5 -0.18 0.54 -0.13 0.49 -0.15 0.2 -0.18 0.16 0.12

3d MAX Q JFM 0.05 0.4 0.58 0.25 0.66 0.02 0.86 0.13 0.33 0.01 0.97 0.02 -0.04 -0.06 0.1 0.11 -0.02 -0.05 0.05 0.07 -0.05 -0.27

3d MAX Q JFM DOY 0.75 0.68 0.57 0.22 0.29 0.41 0.04 0.23 0.79 0.68 0.99 0.91 -0.07 0.06 0.13 0.15 -0.07 0.05 0.06 0.07 0.02 -0.08

7d MIN Q JFM 0.08 0.81 0.26 0.03 0.69 0.62 0.66 0 0.2 0.04 0 0.83 0.68 -0.13 0.24 -0.21 0.92 -0.1 -0.13 0.15 -0.16 -0.27

7d MIN Q JFM DOY 0.09 0.37 0.93 0.9 0.35 0.39 0.55 0.94 0.04 0.19 0.29 0.75 0.73 0.44 -0.07 -0.07 -0.1 0.81 0.35 -0.37 0.38 0.39

3d MAX BF JFM 0.44 0.12 0.18 0.96 0.74 0.96 0.95 0.8 0.63 0.09 0 0.58 0.46 0.15 0.69 0.09 0.26 -0.1 0.02 -0.15 -0.02 0.16

3d MAX BF JFM DOY 0.81 0.29 0.42 0.16 0.16 0.22 0.35 0.01 0.92 0.51 0.44 0.53 0.38 0.23 0.69 0.59 -0.2 -0.04 -0.15 0.02 -0.26 -0.04

7d MIN BF JFM 0.07 0.9 0.43 0.03 0.65 0.54 0.64 0.01 0.23 0.04 0 0.91 0.68 0 0.56 0.13 0.24 -0.08 -0.2 0.22 -0.24 -0.23

7d MIN BF JFM DOY 0.27 0.17 0.61 0.85 0.17 0.51 0.48 0.99 0.1 0.17 0.39 0.78 0.78 0.55 0 0.56 0.83 0.66 0.35 -0.37 0.38 0.39

W285 3d MAX GW JFM 0.87 0.3 0.39 0.42 0.41 0.63 0.79 0.71 0.56 0.71 0.56 0.87 0.87 0.71 0.3 0.96 0.66 0.56 0.3 -0.81 0.89 0.35

W285 3d MAX GW JFM DOY 0.83 0.38 0.42 0.22 0.44 0.52 0.91 0.85 0.75 0.67 0.59 0.83 0.83 0.67 0.27 0.67 0.96 0.52 0.27 0 -0.77 -0.45

W285 7d MIN GW JFM 0.63 0.25 0.46 0.48 0.35 0.56 0.87 0.9 0.63 0.48 0.63 0.87 0.96 0.63 0.25 0.96 0.44 0.48 0.25 0 0.01 0.43

W285 7d MIN GW JFM DOY 0.19 0.49 0.39 0.91 0.73 0.65 0.35 0.64 1 0.29 0.73 0.42 0.82 0.42 0.24 0.65 0.91 0.49 0.24 0.29 0.16 0.19


Table G-9: Spring seasonal analysis of Kendall’s Rank for the Parkhill Creek. Correlation coefficient is above and p-


shaded.

Tota

l R A

MJ

7d M

AX T

AM

J

7d M

AX T

AM

J D

OY

7d M

IN T

AM

J

7d M

IN T

AM

J D

OY

3d M

AX R

AM

J

3d M

AX R

AM

J D

OY

30d M

IN R

AM

J

30d M

IN R

AM

J D

OY

AM

J yie

ld

AM

J BF y

ield

3d M

AX Q

AM

J

3d M

AX Q

AM

J D

OY

7d M

IN Q

AM

J

7d M

IN Q

AM

J D

OY

3d M

AX B

F A

MJ

3d M

AX B

F A

MJ

DO

Y

7d M

IN B

F A

MJ

7d M

IN B

F A

MJ

DO

Y

W285 3

d M

AX G

W A

MJ

W285 3

d M

AX G

W A

MJ

DO

Y

W285 7

d M

IN G

W A

MJ

W285 7

d M

IN G

W A

MJ

DO

Y

Total R AMJ -0.17 0.02 -0.24 -0.27 0.66 -0.12 0.24 -0.16 0.58 0.36 0.47 0.06 0.43 -0.24 0.24 0.14 0.5 -0.09 -0.25 0.28 0.01 -0.35

7d MAX T AMJ 0.34 0.24 0.13 -0.08 -0.32 -0.04 -0.06 0.06 -0.15 -0.19 -0.24 0.03 -0.02 0.12 -0.21 -0.14 -0.04 0.03 -0.01 0.23 -0.45 -0.06

7d MAX T AMJ DOY 0.89 0.16 0.05 0.04 -0.13 -0.1 0.1 0.2 0.12 0.02 -0.11 -0.05 0.08 0.17 -0.12 -0.02 0.08 0.12 -0.04 0.16 -0.13 -0.21

7d MIN T AMJ 0.16 0.46 0.77 0.18 -0.17 -0.04 -0.1 0.04 -0.28 -0.41 -0.25 0.05 -0.14 -0.04 -0.31 0.04 -0.24 -0.15 0.01 0.17 -0.08 0.06

7d MIN T AMJ DOY 0.11 0.66 0.82 0.31 -0.18 0.05 -0.1 -0.07 -0.16 -0.11 -0.11 -0.03 -0.05 0.02 -0.07 0.16 -0.15 -0.11 0.2 -0.13 0.01 0.24

3d MAX R AMJ 0 0.05 0.45 0.31 0.31 -0.07 0.09 -0.16 0.41 0.28 0.42 0.04 0.28 -0.23 0.29 0.1 0.36 -0.11 -0.23 0.28 0.03 -0.32

3d MAX R AMJ DOY 0.49 0.8 0.58 0.8 0.76 0.7 0.01 -0.02 -0.01 -0.15 -0.12 0.32 -0.09 -0.04 -0.23 0.27 -0.1 -0.02 0.09 -0.27 0.18 0.02

30d MIN R AMJ 0.16 0.73 0.56 0.56 0.56 0.61 0.95 0.04 0.29 0.07 0.08 0.15 0.16 0.14 -0.1 0.22 0.13 0.17 -0.14 0.03 -0.01 -0.2

30d MIN R AMJ DOY 0.35 0.75 0.25 0.82 0.68 0.35 0.91 0.82 -0.13 -0.03 -0.15 0.05 -0.37 0.24 -0.07 -0.15 -0.34 -0.11 0.13 0.02 0.09 -0.05

AMJ yield 0 0.38 0.51 0.11 0.37 0.01 0.95 0.09 0.47 0.39 0.59 0.05 0.32 -0.07 0.15 0.21 0.38 0.02 -0.23 0.27 -0.1 -0.4

AMJ BF yield 0.03 0.28 0.89 0.01 0.53 0.1 0.4 0.71 0.88 0.02 0.22 -0.07 0.3 -0.07 0.58 -0.03 0.35 -0.01 -0.1 0.04 -0.03 -0.23

3d MAX Q AMJ 0 0.16 0.53 0.14 0.54 0.01 0.5 0.64 0.39 0 0.21 -0.11 0.2 -0.21 0.22 0.1 0.25 -0.09 -0.33 0.4 -0.15 -0.34

3d MAX Q AMJ DOY 0.71 0.86 0.78 0.76 0.87 0.8 0.06 0.39 0.76 0.79 0.69 0.52 0.02 -0.19 -0.23 0.05 -0.01 0.09 0.27 -0.31 0.25 0.19

7d MIN Q AMJ 0.01 0.9 0.65 0.42 0.77 0.1 0.61 0.37 0.03 0.06 0.08 0.25 0.91 -0.41 0.17 0.13 0.8 0.02 -0.08 0.17 -0.31 -0.28

7d MIN Q AMJ DOY 0.17 0.5 0.33 0.81 0.91 0.19 0.83 0.44 0.16 0.67 0.67 0.22 0.28 0.01 -0.12 0.07 -0.35 0.19 -0.03 -0.17 0.19 0.15

3d MAX BF AMJ 0.17 0.23 0.49 0.07 0.68 0.09 0.19 0.57 0.68 0.39 0 0.2 0.18 0.34 0.49 -0.18 0.21 -0.07 -0.15 0.25 -0.13 -0.28

3d MAX BF AMJ DOY 0.42 0.43 0.91 0.83 0.37 0.57 0.11 0.19 0.4 0.22 0.86 0.57 0.76 0.46 0.7 0.31 0.15 -0.1 -0.08 0.01 0.03 -0.17

7d MIN BF AMJ 0 0.83 0.65 0.17 0.39 0.03 0.57 0.47 0.05 0.02 0.04 0.15 0.94 0 0.04 0.23 0.4 -0.04 -0.15 0.25 -0.23 -0.42

7d MIN BF AMJ DOY 0.59 0.87 0.48 0.4 0.51 0.53 0.93 0.34 0.53 0.93 0.94 0.59 0.59 0.93 0.27 0.69 0.58 0.8 0.23 -0.49 0.29 0.56

W285 3d MAX GW AMJ 0.38 0.97 0.88 0.97 0.5 0.43 0.76 0.63 0.65 0.45 0.74 0.27 0.37 0.8 0.93 0.62 0.78 0.62 0.44 -0.66 0.56 0.7

W285 3d MAX GW AMJ DOY 0.34 0.42 0.59 0.57 0.66 0.34 0.35 0.91 0.94 0.37 0.9 0.18 0.3 0.58 0.57 0.42 0.96 0.42 0.09 0.01 -0.66 -0.69

W285 7d MIN GW AMJ 0.97 0.11 0.65 0.79 0.97 0.91 0.55 0.97 0.76 0.74 0.93 0.62 0.42 0.31 0.54 0.68 0.93 0.45 0.33 0.04 0.01 0.59

W285 7d MIN GW AMJ DOY 0.22 0.84 0.48 0.84 0.41 0.26 0.94 0.49 0.87 0.18 0.46 0.26 0.54 0.35 0.63 0.35 0.57 0.15 0.04 0 0.01 0.03


Table G-10: Summer seasonal analysis of Kendall’s Rank for the Parkhill Creek. Correlation coefficient is above and


shaded.

Tota

l R J

AS

7d M

AX T

JAS

7d M

AX T

JAS D

OY

7d M

IN T

JAS

7d M

IN T

JAS D

OY

3d M

AX R

JAS

3d M

AX R

JAS D

OY

30d M

IN R

JAS

30d M

IN R

JAS D

OY

JAS y

ield

JAS B

F y

ield

3d M

AX Q

JAS

3d M

AX Q

JAS D

OY

7d M

IN Q

JAS

7d M

IN Q

JAS D

OY

3d M

AX B

F J

AS

3d M

AX B

F J

AS D

OY

7d M

IN B

F J

AS

7d M

IN B

F J

AS D

OY

Total R JAS -0.24 0.08 -0.16 0.08 0.48 0.08 0.32 -0.19 0.54 0.46 0.51 0.35 0.56 -0.06 0.36 0.34 0.56 -0.05

7d MAX T JAS 0.16 -0.26 0.02 0.06 -0.17 -0.01 -0.28 -0.12 -0.39 -0.48 -0.38 -0.05 -0.4 0.05 -0.36 -0.16 -0.39 0.05

7d MAX T JAS DOY 0.65 0.13 0.01 0.17 0.06 0.04 0.19 0.07 0.13 0.17 0.11 -0.09 0.15 0.06 0.09 0.13 0.14 0.05

7d MIN T JAS 0.36 0.93 0.93 -0.12 -0.12 -0.18 0.1 0.24 -0.2 -0.14 -0.22 -0.19 -0.23 0.12 -0.09 -0.19 -0.22 0.11

7d MIN T JAS DOY 0.62 0.71 0.34 0.49 0.08 0.09 -0.08 0.06 0.01 0.03 -0.02 0.2 -0.05 -0.01 0.09 0.13 -0.06 -0.01

3d MAX R JAS 0 0.32 0.72 0.48 0.65 -0.04 0.06 -0.1 0.35 0.18 0.39 0.23 0.37 -0.01 0.15 0.2 0.39 0.01

3d MAX R JAS DOY 0.63 0.94 0.8 0.31 0.62 0.81 0.1 -0.04 0.09 0.14 0.11 0.26 0.13 -0.06 0.22 0.08 0.14 -0.06

30d MIN R JAS 0.05 0.1 0.26 0.55 0.62 0.73 0.56 -0.01 0.19 0.28 0.19 0.01 0.27 0.01 0.23 0.04 0.27 0

30d MIN R JAS DOY 0.26 0.48 0.68 0.16 0.71 0.55 0.84 0.93 -0.05 0.02 -0.07 -0.22 -0.29 0.37 0.03 -0.17 -0.28 0.37

JAS yield 0 0.02 0.45 0.24 0.93 0.04 0.61 0.28 0.77 0.74 0.85 0.16 0.57 0.1 0.53 0.31 0.57 0.11

JAS BF yield 0.01 0 0.33 0.43 0.87 0.3 0.43 0.11 0.91 0 0.68 0.13 0.58 0.08 0.7 0.33 0.57 0.08

3d MAX Q JAS 0 0.03 0.54 0.21 0.9 0.02 0.52 0.27 0.7 0 0 0.15 0.51 0.07 0.5 0.28 0.52 0.08

3d MAX Q JAS DOY 0.04 0.78 0.62 0.28 0.26 0.19 0.14 0.98 0.22 0.38 0.46 0.39 0.32 -0.21 0.14 0.28 0.32 -0.21

7d MIN Q JAS 0 0.02 0.4 0.19 0.77 0.03 0.47 0.12 0.09 0 0 0 0.07 -0.13 0.42 0.31 0.98 -0.11

7d MIN Q JAS DOY 0.75 0.77 0.75 0.5 0.95 0.98 0.73 0.95 0.03 0.59 0.66 0.69 0.22 0.47 0.03 -0.15 -0.11 0.98

3d MAX BF JAS 0.04 0.04 0.62 0.61 0.63 0.4 0.22 0.19 0.86 0 0 0 0.41 0.01 0.85 0.32 0.42 0.05

3d MAX BF JAS DOY 0.05 0.38 0.48 0.28 0.48 0.25 0.65 0.81 0.35 0.07 0.06 0.11 0.11 0.08 0.39 0.07 0.3 -0.15

7d MIN BF JAS 0 0.02 0.44 0.22 0.75 0.02 0.42 0.13 0.11 0 0 0 0.06 0 0.52 0.01 0.08 -0.1

7d MIN BF JAS DOY 0.78 0.78 0.76 0.55 0.93 0.97 0.75 0.99 0.03 0.53 0.64 0.66 0.24 0.53 0 0.79 0.41 0.58


Table G-11: Autumn seasonal analysis of Kendall’s Rank for the Parkhill Creek. Correlation coefficient is above and p-


shaded.

Tota

l R O

ND

7d M

AX T

ON

D

7d M

AX T

ON

D D

OY

7d M

IN T

ON

D

7d M

IN T

ON

D D

OY

3d M

AX R

ON

D

3d M

AX R

ON

D D

OY

30d M

IN R

ON

D

30d M

IN R

ON

D D

OY

ON

D y

ield

ON

D B

F y

ield

3d M

AX Q

ON

D

3d M

AX Q

ON

D D

OY

7d M

IN Q

ON

D

7d M

IN Q

ON

D D

OY

3d M

AX B

F O

ND

3d M

AX B

F O

ND

DO

Y

7d M

IN B

F O

ND

7d M

IN B

F O

ND

DO

Y

Total R OND -0.14 -0.05 0.24 -0.08 0.56 -0.12 0.4 -0.02 0.51 0.39 0.41 -0.13 0.16 -0.12 0.38 -0.29 0.15 0.06

7d MAX T OND 0.43 0.07 0.04 -0.08 0 0.16 -0.06 -0.17 -0.11 -0.17 0.04 0.22 -0.28 -0.19 -0.07 0.06 -0.24 -0.16

7d MAX T OND DOY 0.79 0.68 -0.02 -0.08 -0.03 0.09 0.15 0.06 -0.01 -0.11 0.14 0.18 0 0.11 -0.08 0.02 0 0.08

7d MIN T OND 0.16 0.83 0.92 0.03 0.24 -0.04 0.27 -0.35 0.16 0.15 0.1 0.02 0.09 -0.04 0.11 0.02 0.11 0.06

7d MIN T OND DOY 0.63 0.66 0.63 0.84 -0.12 -0.05 0.02 -0.07 0.05 0.12 -0.15 -0.03 0.06 0.06 0.04 -0.11 0.05 0.08

3d MAX R OND 0 0.99 0.88 0.16 0.49 -0.03 0.17 -0.03 0.43 0.37 0.45 -0.11 0.18 -0.03 0.46 -0.25 0.23 0.17

3d MAX R OND DOY 0.48 0.34 0.62 0.8 0.76 0.85 -0.07 -0.12 -0.1 -0.19 0.01 0.32 -0.13 -0.23 -0.11 0.37 -0.12 -0.06

30d MIN R OND 0.02 0.73 0.38 0.12 0.9 0.31 0.67 -0.16 0.31 0.17 0.27 0.02 0.14 -0.11 0.09 -0.13 0.12 -0.01

30d MIN R OND DOY 0.91 0.31 0.74 0.04 0.68 0.87 0.49 0.36 0.1 0.11 0.05 -0.32 0.17 0.16 0.1 -0.17 0.14 0.01

OND yield 0 0.55 0.96 0.38 0.77 0.01 0.57 0.07 0.56 0.71 0.61 -0.23 0.49 0.24 0.64 -0.39 0.5 0.3

OND BF yield 0.02 0.33 0.55 0.39 0.5 0.03 0.29 0.33 0.52 0 0.47 -0.4 0.53 0.36 0.74 -0.45 0.54 0.45

3d MAX Q OND 0.02 0.8 0.41 0.58 0.41 0.01 0.98 0.12 0.8 0 0.01 -0.13 0.31 0.12 0.47 -0.35 0.33 0.23

3d MAX Q OND DOY 0.45 0.21 0.3 0.93 0.85 0.52 0.07 0.9 0.06 0.18 0.02 0.46 -0.33 -0.3 -0.23 0.43 -0.33 -0.28

7d MIN Q OND 0.37 0.11 0.98 0.63 0.75 0.31 0.47 0.45 0.33 0 0 0.07 0.06 0.54 0.3 -0.3 0.92 0.41

7d MIN Q OND DOY 0.51 0.28 0.54 0.83 0.74 0.86 0.2 0.55 0.35 0.18 0.03 0.5 0.08 0 0.2 -0.23 0.51 0.51

3d MAX BF OND 0.03 0.71 0.63 0.54 0.84 0.01 0.54 0.62 0.56 0 0 0.01 0.18 0.08 0.26 -0.39 0.32 0.33

3d MAX BF OND DOY 0.09 0.75 0.9 0.93 0.55 0.15 0.03 0.47 0.33 0.02 0.01 0.04 0.01 0.09 0.19 0.02 -0.3 -0.3

7d MIN BF OND 0.4 0.16 1 0.54 0.77 0.2 0.51 0.5 0.43 0 0 0.05 0.06 0 0 0.07 0.09 0.45

7d MIN BF OND DOY 0.72 0.38 0.64 0.73 0.65 0.34 0.73 0.94 0.97 0.09 0.01 0.18 0.1 0.02 0 0.06 0.09 0.01


Table G-12: Occurrences of probable correlation where Spearman’s Rank and Kendall’s Rank indicate parameter

correlation but linear regression does not for Parkhill Creek.

Spearman's

Rank

Kendall's


Time

Period Parameter 1 Parameter 2 ρ

p-

value τ

p-

value R²

p-

value

slope

sign

Annual P-PET 7d MIN Q 0.70 0.00 0.55 0.00 0.43 0.00 +

P-PET 7d MIN BF -0.52 0.00 0.52 0.00 0.48 0.00 +

JFM Total R JFM yield 0.69 0.00 0.54 0.00 0.45 0.00 +

AMJ BF yield 3d MAX BF 0.76 0.00 0.58 0.00 0.48 0.00 +

7d MIN BF DOY W285 7d MIN GW DOY 0.67 0.01 0.56 0.04 -0.09 0.82 +

W285 7d MIN GW W285 7d MIN GW DOY 0.72 0.00 0.59 0.03 0.44 0.01 +

JAS Total R 7d MIN Q 0.72 0.00 0.56 0.00 0.49 0.00 +

OND Total R 3d MAX R 0.75 0.00 0.56 0.00 0.48 0.00 +

BF yield 7d MIN Q 0.68 0.00 0.53 0.00 0.38 0.00 +

BF yield 7d MIN BF 0.70 0.00 0.54 0.00 0.30 0.00 +

7d MIN Q 7d MIN Q DOY 0.73 0.00 0.54 0.00 0.26 0.00 +

7d MIN Q DOY 7d MIN BF 0.70 0.00 0.51 0.00 0.34 0.00 +