HYDROGEOLOGY AND GROUNDWATER FLOW MODEL, CENTRAL CATCHMENT OF BRIBIE ISLAND, SOUTHEAST QUEENSLAND by Joanne M. Jackson Bachelor of Science (Honours) SUPERVISOR Assoc. Professor Malcolm Cox Queensland University of Technology A thesis submitted in partial fulfilment of the requirements for the Degree of Master of Applied Science. 2007 School of Natural Resource Sciences Queensland University of Technology Brisbane, Queensland, Australia
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HYDROGEOLOGY AND GROUNDWATER FLOW MODEL,
CENTRAL CATCHMENT OF BRIBIE ISLAND, SOUTHEAST QUEENSLAND
by
Joanne M. Jackson
Bachelor of Science (Honours)
SUPERVISOR
Assoc. Professor Malcolm Cox
Queensland University of Technology
A thesis submitted in partial fulfilment of the requirements for
the Degree of Master of Applied Science.
2007
School of Natural Resource Sciences
Queensland University of Technology
Brisbane, Queensland, Australia
STATEMENT OF ORIGINAL AUTHORSHIP
The work contained in this thesis has not been previously submitted for a degree or
diploma at any other higher education institution. To the best of my knowledge and
belief, the thesis contains no material previously published or written by another
person except where due reference is made.
Signed: ……………………………………..
Joanne Jackson
Date: ……………………………………..
i
ABSTRACT
Bribie Island is a large, heterogeneous, sand barrier island that contains
groundwater aquifers of commercial and environmental significance. Population
growth has resulted in expanding residential developments and consequently
increased demand for water. Caboolture Shire Council (CSC) has proposed to
increase groundwater extraction by a new borefield.
Two aquifers exist within the Quaternary sandmass which are separated by an
indurated sand layer that is ubiquitous in the area. A shallow aquifer occurs in the
surficial, clean sands and is perched on the indurated sands. Water levels in the
shallow water table aquifer follow the topography and groundwater occurs under
unconfined conditions in this system. A basal aquifer occurs beneath the indurated
sands, which act as a semi-confining layer in the island system. The potentiometric
surface of the basal aquifer occurs as a gentle groundwater mound.
The shallow groundwater system supports water-dependent ecosystems including
wetlands, native woodlands and commercial pine plantations. Excessive
groundwater extraction could lower the water table in the shallow aquifer to below
the root depth of vegetation on the island.
Groundwater discharge along the coastline is essential to maintain the position of
the saline water - fresh groundwater boundary in this island aquifer system. Any
activity that changes the volume of fresh water discharge or lowers the water table
or potentiometric surface below sea level will result in a consequent change in the
saline water – freshwater interface and could lead to saline water intrusion.
Groundwater level data was compared with the residual rainfall mass curve (RRMC)
on hydrographs, which revealed that the major trends in groundwater levels are
related to rainfall. Bribie Island has a sub-tropical climate, with a mean annual
rainfall of around 1358mm/year (Bongaree station). Mean annual pan evaporation
is around 1679mm/year and estimates of the potential evapotranspiration rates
range from 1003 to 1293mm/year.
Flows from creeks, the central swale and groundwater discharged from the area
have the potential to affect water quality within the tidal estuary, Pumicestone
Passage. Groundwater within the island aquifer system is fresh with electrical
conductivity ranging from 61 to 1018µS/cm while water near the coast, canals or
tidal creeks is brackish to saline (1596 to 34800µS/cm). Measurements of pH show
that all groundwater is acidic to slightly acidic (3.3-6.6), the lower values are
attributed to the breakdown of plant material into organic acids.
ii
Groundwater is dominated by Na-Cl type water, which is expected in a coastal
island environment with Na-Cl rainfall. Some groundwater samples possess higher
concentrations of calcium and bicarbonate ions, which could be due to chemical
interactions with buried shell beds while water is infiltrating to depth and due to the
longer residence times of groundwater in the basal aquifer.
A steady-state, sub-regional groundwater flow model was developed using the
Visual MODFLOW computer package. The 4 layer, flow model simulated the
existing hydrogeological system and the dominant groundwater processes
controlling groundwater flow. The numerical model was calibrated against existing
data and returned reasonable estimates of groundwater levels and hydraulic
parameters. The model illustrated that:
The primary source of groundwater recharge is infiltration of rainfall for the
upper, perched aquifer (Layer 1). Recharge for the lower sand layers is via
vertical leakage from the upper, perched aquifer, through the indurated sands
(Layers 2 and 3) to the semi-confined, basal aquifer (Layer 4).
The dominant drainage processes on Bribie Island are evapotranspiration
(15070m3/day) and groundwater seepage from the coast, canals and tidal
creeks (9512m3/day). Analytical calculations using Darcy’s Law estimated that
approximately 8000m3/day of groundwater discharges from central Bribie Island,
approximately 16% less than the model.
As groundwater flows preferentially toward the steepest hydraulic gradient, the
main direction of horizontal groundwater flow is expected to be along an east-
west axis, towards either the central swale or the coastline. The central swale
was found to act as a groundwater sink in the project area.
iii
ACKNOWLEGDEMENTS
I would like to thank everyone who helped in the completion of this research project.
The successful completion of this study has been made possible through the
practical and professional support and advice of many people, institutions and
departments, in particular:
I appreciate the support, guidance and expertise of Associate Professor
Malcolm Cox (principal supervisor), School of Natural Resource Sciences,
Queensland University of Technology.
Queensland University of Technology Staff
Dr. Micaela Preda, Dr. Deliana Gabeva, Wathsala Kumar, Bill Kwiecien and Dr.
Les Dawes.
Other Students: John Harbison, Tim Armstrong, Ken Spring, Lucy Paul and
Genevieve Larsen.
Funding for this study was provided by:
Caboolture Shire Council, QM Properties and Pacific Silica.
Table 3. Field parameters measured with a TPS meter
All samples were preserved at below 4oC by storing them with ice during the day
and in a refrigerator at night. Water quality analysis of samples for major ions and
metals was conducted in the School of Natural Resource Sciences (NRS) chemical
laboratory. Alkalinity was determined by acid titration. Cations were analysed with
the Varian Liberty 200 Inductively Coupled Plasma – Optical Emission
Spectrometer (ICP-OES) and anions were analysed with the DX300 Dionex Ion
Chromatograph. Ions and metals tested for are listed in Table 4.
29
Method Analysis
ICP – OES Na, K, Ca, Mg, Fe, Al, Mn, Zn and SiO2
Acid titration HCO3
Ion Chromatography Cl, F, Br, NO3, PO4 and SO4
Table 4. Parameters tested for during water chemistry analysis
3.2 MODELLING
3.2.1 Conceptual Model A conceptual model is built on an understanding of how an aquifer system works.
The model must simplify the real world complexity to a minimum level that is
appropriate to the scale of the project, for example regional or local. Simplification
depends on the end product required, the amount of available data and the current
level of understanding. Building a conceptual model is an iterative process that can
identify gaps in the data which you can try to improve with further data gathering.
A conceptual model provides a simplified representation of a hydrogeologic system
and the flow processes present. The model describes factors including the system
geometry, physical and hydraulic boundaries and hydraulic parameters.
A complex geological model is simplified into a hydrogeological model which
recognises hydrostratigraphic units. The aquifer units and semi-confining layers are
portrayed in three dimensional space. The geological framework for the central
catchment of Bribie Island was established from analysis of drill hole data and
downhole gamma-ray logs, utilising cross sections and 3D cross sections with the
HydroGeo Analyst computer program.
It is necessary to identifying physical boundaries including faults, impermeable
strata and permanent bodies of water such as lakes and oceans within the
boundary domain. As Bribie is an island, the sea to the east and west of the model
area was used as a natural boundary. The less permeable indurated sands are a
hydrogeologically significant layer in the Bribie model.
Hydraulic boundaries such as groundwater divides can be used to limit the extent of
the model where available. Streamlines are essentially a boundary since flow can
only occur parallel to them, i.e. no flow can enter the model domain normal to a
streamline. This artificial barrier was used to the north and south of the model of
30
the central area of Bribie Island as flow in this area is predominantly along an east-
west axis.
Results from hydraulic tests and well as monitoring of groundwater levels and
groundwater quality were taken into account when developing the conceptual
model. These factors assisted with understanding groundwater occurrence and
flow processes in the area. This helped to clarify the relationship between the upper
and lower aquifers and the impact of the indurated, sand layer, which lay between
the two aquifer systems.
3.2.2 Mathematical Modelling Models simulate groundwater occurrence and movement in the subsurface
environment. A model represents a simplified form of the real-world aquifer system
and assists with understanding and managing a groundwater resource (Bear et al,
1992). Mathematical models are based on a conceptual understanding of the
aquifer system and they depend on the solution of basic mathematical equations as
shown in Figure 9. Analytical models provide the simplest approach to modelling
while numerical modelling can represent more complex systems.
Figure 9. Mathematical models are based on a conceptual understanding of the aquifer system as expressed by mathematical equations (modified from Mercer and Faust, 1981)
31
Analytical Solution
The simplest mathematical model of groundwater flow is Darcy’s Law (equation 1)
which is an equation that describes the flow of groundwater. Groundwater flow
through a vertical section of an aquifer can be calculated using Darcy’s Law
(Driscoll, 1986):
L
hhKAQ )( 21 −= Equation 1
where:
Q = flow (m3/day)
K = hydraulic conductivity averaged over the height of the aquifer (m/day)
A = area (m2)
h1-h2 = difference in hydraulic head (m)
L = distance along the flowpath between the points where h1 and h2 are measured
(m)
An analytical solution of the aquifer system in the central catchment of Bribie Island
was used to assist with understanding the groundwater flow processes at a
rudimentary level. The results obtained by using Darcy’s Law were later compared
to the model results to verify the findings from numerical model.
Numerical Modelling
Numerical models are used to represent complex processes (Hill, 1998). Numerical
models are used when complex boundary conditions exist or where the value of
parameters varies within the model (Zheng and Bennett, 1995).
Due to the complicated subsurface environment, conditions can rarely be replicated
completely by mathematical expressions. Simplifying assumptions are usually
made to solve flow equations for appropriate boundary and initial hydrologic
conditions. Assumptions include; the aquifer being homogeneous; isotropic; and
infinite in areal extent. Simplification reduces the accuracy of the model (Driscoll,
1986).
The Visual MODFLOW (version 3.1.0) computer package was available for use to
build a groundwater flow model over the central catchment of Bribie Island. Visual
MODFLOW is a three-dimensional, finite-difference, Layer Property Flow (LPF)
32
package built on the MODFLOW-2000 module (Harbaugh et al., 2000). MODFLOW
is a computer program developed by the U.S. Geological Survey (USGS) that
simulates three-dimensional ground-water flow through a porous medium by using a
finite-difference method (McDonald and Harbaugh, 1988).
Visual MODFLOW is built on the MODFLOW-2000 module, which requires the
direct definition of the complete geometry of the each cell (including vertical cell
geometry), unlike previous MODFLOW versions (Harbaugh et al, 2000). The
available version of Visual MODFLOW did not support all of the features and
analysis capabilities of MODFLOW-2000 including the Observation Process, the
Sensitivity Process and the Parameter Estimation Process. Visual MODFLOW
does support the PEST package (Doherty, 1994) which is a powerful and robust
parameter estimation program.
PEST is an acronym for Parameter ESTimation. PEST optimises a set of user-
defined model parameters to minimize the calibration residuals from a set of user-
defined observations. PEST guides the model calibration process towards the most
reasonable set of parameter values in order to achieve a better calibration result.
Visual MODFLOW supports the optimisation of the model flow properties
conductivity, storage, and recharge (Waterloo Hydrogeologic, 1995). When
generating parameters using an inverse solution, exercise caution in order to
generate realistic values for aquifer parameters.
The average conditions within the central Bribie Island area were simulated by
Visual MODFLOW using the steady-state option. The model does not include
seasonal variability and does not attempt to model the fresh water-salt water
interface. These limitations are discussed in the sensitivity and uncertainty
assessment.
Spatial Discretisation and Boundary Conditions
Defining the physical configuration of the model involves delineating the areal extent
and thickness of the aquifers and defining the number of layers and the boundary
conditions within the aquifer systems (Fetter, 2001).
The model extends approximately 7.5km in a north-south direction and 8.5km in the
east-west direction. The co-ordinate system is MGA Zone 56 (GDA 94). The model
grid is aligned 16.9 degrees west of north to align the model grid with the dominant
direction of groundwater flow. Layers consisted of 75 rows and 85 columns of
33
model cells the size of 100m x 100m. The model configuration for the Bribie model
is shown in Figure 10.
Figure 10. Model configuration of central Bribie Island
There are three ways of representing a semi-confining layer in multi-aquifer
simulations. The first and simplest is the quasi-three-dimensional approach. In this
situation, the semi-confining layer is not explicitly represented. It is simply
incorporated as a leakage term (VCONT) between adjacent layers. This effectively
ignores storage within the semi-confining bed and assumes an instantaneous
response in the unstressed aquifer. This analysis is appropriate for steady-state
simulations or systems with very thin semi-confining beds with limited storage
properties (Anderson, 1993).
Visual MODFLOW requires the top and bottom elevations for each grid cell in the
model and it requires hydraulic conductivity values (Kx, Ky and Kz) for each grid
34
cell. Visual MODFLOW uses this information to calculate the interlayer leakage
(VCONT) values. As a result, a VCONT value could not be entered into the model
to simulate the leakance through the semi-confining layer between the two aquifers,
as Spring (2006) did in his regional model of the island.
A second approach is to discretise the semi-confining bed as a separate layer. This
considers the storage within the semi-confining layer but generally does not provide
a good approximation of the gradient within the confining bed (Anderson, 1993).
When this method was utilised for the Central Bribie Island area, the numerical
model would not converge.
The third method is to discretise several layers within the confining bed to
approximate the gradient. The modeller must weigh the benefits of including
gridding in an area where there is limited data and interest in hydraulic heads
(Anderson, 1993). The benefits for the central Bribie Island model of discretising
separate layers were convergence and stability of the model.
The model defines four layers: 1) the surficial sand; 2) and 3) the indurated sand
layer; and 4) the basal sand layer. Figure 11 shows a sample cross section through
the model of the island. The bedrock Landsborough Sandstone was not included in
the model because there was no hydrogeological information from this unit as none
of the piezometers penetrated to this depth. The bedrock contact was treated as a
no flow boundary as it is believed that no groundwater flows upward from this
stratigraphy.
The topography of the island (ground surface) was generated from topographic data
supplied by the Caboolture Shire and Caloundra City Councils combined with bore
hole elevations from DNRMW, HLA and QUT bores and is shown in Figure 12. The
surfaces representing the base of layers 1, 3 and 4 were gridded from data points
delineated by interpretation of drill log data and downhole gamma-ray logs.
Surfaces were contoured using the Surfer contouring software and imported into
Visual MODFLOW. Layer 3 was created by splitting the distance between the base
of Layer 1 and top of Layer 4 into two individual layers (Layer 2 and 3). The base of
the model represents the contact between Quaternary sediments and the
underlying Jurassic Landsborough Sandstone, which represents bedrock in the
area.
35
Figure 11. Cross section of model showing the four model layers. The base of the model is the sandstone bedrock.
All layers were assigned as confined/unconfined – variable S and T (Table 5).
Geological unit
Model layer Aquifer type Model layer
type Model layer thickness
Surficial sand Layer 1 Unconfined 4 – 10 m
Indurated sand
Layers 2 and 3
Semi-confining layer
1.5 – 7 m
Basal sand Layer 4 Semi-confined
Confined / unconfined, variable S,T
5 – 35 m
Table 5. Hydrogeological layers used in the model
There are three types of boundary conditions commonly used in groundwater
models: specified head, specified flow, and head dependent flow. In specified head
boundaries (Dirichlet Conditions), the head remains constant and water will flow into
and out of the model domain depending on the head distribution developed near the
boundary. Bodies of water, for example lakes and the ocean, are commonly
represented as constant head boundaries. Caution is to be used when applying
this type of boundary as it can act as an infinite source of water which may not
match the real world conditions. Specified flow boundaries (Neuman Conditions)
have a fixed flux of water assigned along the boundary. An example of this are no
flow boundaries, such as groundwater divides and impermeable barriers, which are
36
given a specified flux that is set to zero. In head dependent flow boundaries
(Cauchy Conditions), flow across the boundary is determined by a prescribed head
outside of the model domain, heads calculated within the model, and some form of
hydraulic resistance to flow in between.
0123456789101112
Figure 12. Topography for the whole of Bribie Island. Oblique view of elevation data created using Surfer contouring package.
The allocation of the boundary conditions attempted to correspond with natural
hydrogeologic boundaries in order to minimise the influence of model boundaries on
simulation results. The boundary conditions used in the model are displayed in
Figure 13.
m
(AHD)
37
Cells representing Pumicestone Passage and the Coral Sea were assigned as
inactive. Coastline cells, the Pacific Harbour canal system and tidal creeks were
assigned as fixed-head cells with a hydraulic head value of 0.3m (AHD), a typical
groundwater level along low-energy coasts (Harbison and Cox, 2002). Lagoons
were assigned as fixed-head cells with a hydraulic head value of 0.7m (AHD)
(Harbison, 1998).
The fixed head cells along the coast were assigned to give an approximation of the
interface between salt water and the less dense freshwater. This numerical model
was developed to simulate groundwater flow in central Bribie Island and does not
attempt to specifically map the fresh water - saltwater boundary along the coastline.
Artificial boundaries were created at the northern and southern boundaries of the
model, as there were no natural groundwater divides in the central catchment of
Bribie Island. They were assigned as general head boundaries as they were in full
hydraulic contact with the aquifer. The hydraulic head at the boundary was set at
0.3m and conductance values ranged from 0.012 to 0.5m2/day. Initial conductance
values were determined using equation 2; however, these values were too high
resulting in lowered groundwater levels. The conductance values were reduced
manually until a better calibration was achieved.
D
KWLC *)*(= Equation 2
where:
C = conductance (m2/day)
(L*W) = is the surface area of the grid cell face exchanging flow with the external
source/sink (m2)
K = average hydraulic conductivity of the aquifer material separating the external
source/sink from the model grid (m/day)
D = is the distance from the external source/sink to the model grid (m)
Drain cells were assigned along the central swale within Layer 1. Drainage was set
at 750m2/day, with a drainage depth of 1m below ground level. This was designed
to mimic loss of water from the model domain via evapotranspiration by vegetation
and evaporative processes along the swale.
38
The loss of groundwater from the model domain via direct seepage from the canals
was simulated by assigning drain cells in the canal estates within Layer 1. Drainage
of 1000m2/day was initially set, with a drainage depth of 1m below the land surface.
Initial attempts to assign these cells as fixed head cells failed due to the proposed
fixed head elevation (0.3m) lying below the bottom elevations of some cells in this
area, which the computer program would not accept.
Figure 13. Boundary conditions for a) Layer 1 and b) Layers 2, 3 and 4 for central Bribie Island using model layers shown in Figure 11.
39
Monitoring Bores
DNRMW, HLA and QUT monitoring bores are represented in the model as
observation points. The locations of the monitoring bores in the upper, perched
aquifer are shown in Figure 14 and the bores in the basal aquifer are shown in
Figure 15. Within the model, Layer 1 (the shallow, unconfined aquifer) contained 25
monitoring bores and Layer 4 (the basal, semi-confined aquifer) contained 20
monitoring bores. The bores were used as model calibration points to achieve
calibration in steady-state.
Initial Hydraulic Heads
Initial hydraulic heads for the model were subset from the whole island steady-state
model completed by Spring (2005). The head data for Layers 1 and 4 was
contoured in Surfer and then imported into Visual MODFLOW.
Figure 14. Location of 25 shallow monitoring bores used in the model (Layer 1)
40
Figure 15. Location of 20 deep monitoring bores used in the model (Layer 4)
Hydraulic Conductivities
Initial steady-state hydraulic conductivities were spatially invariant and based on
field test results conducted by Armstrong (2006) and HLA (2002). This method
resulted in a poor calibration between the field and the simulated water levels.
Zones were established as shown in Figure 16 and the parameter optimisation
software WinPEST was used to estimate the distribution of hydraulic conductivities.
Observed groundwater levels were matched to hydrologic inputs through the
process of inverse parameter estimation. Inverse modelling helps with
determination of parameter values that produce the best possible fit to the available
observations (Hill, 1998). This was a valuable time-saving tool which enhanced the
model calibration. However caution should be exercised when using inverse
problem solving otherwise the program can generate unrealistic values for aquifer
41
parameters. Therefore the calibrated hydraulic conductivity values in the model
were restricted to between 1 and 110m/day.
Figure 16. Zones of hydraulic conductivities showing observation bores
Recharge and Evapotranspiration
Recharge was applied across the model domain as a percentage of the annual
rainfall and it was assumed that it did not vary spatially within the model. The initial
aquifer recharge rate of 95mm/year (7% of the average annual rainfall) (Harbison,
1998) was applied to the model domain. Factors including evapotranspiration,
surface water runoff and interception by vegetation are expected to account for the
remainder of the rainfall (around 93%). Recharge of the aquifer was increased to
218mm/year (16% of the average annual rainfall) when potential evapotranspiration
was included into the model.
Evapotranspiration (ET) is expected to make up a large portion of the total
groundwater discharge for Bribie Island. Estimations of ET rates from water
balance models range from 60% (1003mm/year, Williams, 1998) to 77%
(1293mm/year, Bubb and Croton, 2000) of the pan evaporation (1679mm/year).
The bulk of rainfall removal occurs before recharge of the groundwater system.
42
The ET parameters were split into 3 zones which are displayed in Figure 17.
Divisions were based on the dominant vegetation types on the island: pine
plantation, swale and National Park. ET rates range from 180 to 270mm/year
depending on the vegetation type. The rooting depth of mature aged pines in
unsaturated soil profiles could range from 3 to 5 metres (K. Bubb, pers comm.,
2005), so the extinction depth in the pine plantation areas was set at 3m. Extinction
depth in the swale and National Park areas was set at 2.5m.
Figure 17. Evapotranspiration zones split according to dominant vegetation type as shown in example photographs
Model Calibration and Sensitivity Assessment
Model calibration is undertaken to refine a models representation of the
hydrogeologic framework, hydraulic properties, and boundary conditions to achieve
43
a desired degree of correspondence between the model simulations and
observations of the groundwater flow system (ASTM, 1996).
Visual MODFLOW supports the PEST package (Doherty, 1994) and can optimise
hydraulic conductivity, storage, and recharge (Waterloo Hydrogeologic, 1995).
PEST was used to optimise hydraulic conductivity in the model to minimize the
calibration residuals from the water level observations. The calibrated horizontal
hydraulic conductivity values were restricted to between 1 and 110m/day. Due to
the variability in time and period of water level records, an average water level per
monitoring bore was used for the calibration of the steady-state model.
The conductance values for the general head boundaries at the northern and
southern boundaries of the model were reduced manually until a better calibration
was achieved. The conductance values ranged from 0.012 to 0.5m2/day.
Sensitivity analysis is defined as the quantitative evaluation of the impact or
uncertainty in model inputs on the degree of calibration of a model and on its results
or conclusions (ASTM, 1994). When user-defined parameters within the model are
varied, it is possible to determine how sensitive the model is to these changes.
There are four types of sensitivity which are illustrated in Figure 18. Sensitivity type
is characterised by whether the changes to the calibration residuals and model
conclusions are significant or insignificant.
Sensitivity assessment was conducted on the following model inputs:
evapotranspiration and drain parameters and general head boundary conductance.
Figure 18. Summary of the four types of sensitivity (modified from ASTM, 1994)
44
4. RESULTS
4.1 HYDRAULIC MONITORING DATA
4.1.1 Climate Bribie Island has a sub-tropical climate and experiences a wet summer and a dry
winter. Figure 19 reveals that the maximum temperatures in the Moreton Bay area
range from 19°C in winter and 28°C in summer.
Caloundra
0
5
10
15
20
25
30
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Tem
p o C
Redcliffe
0
5
10
15
20
25
30
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Tem
p o C
Cape Moreton
0
5
10
15
20
25
30
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Tem
p o C
Mean daily maximum temperature (oC) Mean daily minimum temperature (oC)
Figure 19. Mean daily temperatures for Caloundra, Cape Moreton and Redcliffe
Rainfall records shown in Figure 20 reveal a seasonal trend in the data with a peak
period for rainfall occurring over summer and early autumn (December through
March). The mean annual rainfall from the Bongaree station, which operated for
45
nearly 59 years, is 1358mm/year. The mean monthly pan evaporation values from
the University of Queensland Bribie Island weather station (1970 – 1995) were
compared to mean monthly rainfall from the nearby Bongaree station in Figure 21.
Pan evaporation values exhibit seasonal fluctuations and usually exceed rainfall
from July through January. The mean annual pan evaporation was measured as
1679mm/year.
0
50
100
150
200
250
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Mea
n M
onth
ly R
ainf
all (
mm
)
Bore 14100090Bongaree StationUniversity of Qld
Figure 20. Average monthly rainfall on southern Bribie Island
Figure 21. Mean monthly rainfall compared to mean monthly pan evaporation
46
4.1.2 Monitoring Bore Network Data from all monitoring bores was used to develop a geological framework for the
central catchment of Bribie Island. The monitoring bores located within the central
area of Bribie Island are summarised in Appendix C and locations of all bores are
illustrated in Figure 22.
Figure 22. Location of monitoring bores used to build the geological framework
47
Lithological data from different sources (DNRMW, HLA and QUT) was collated and
interpreted to unify the data. Different naming conventions were used for lithology
in the various drilling programs conducted over many years. For example, material
in the upper profile that was described variably as sandstone, indurated sand or
“Coffee Rock” in previous drill hole logs were grouped into an indurated sand
assemblage.
Data was plotted in 3-dimensional space and interpolations of lithological data
between monitoring bores were made using the HydroGeo Analyst computer
package. Figure 23 shows the results of the process and graphically displays the
heterogeneous nature of the Bribie Island sandmass.
Standing water levels were recorded between May and November 2003 to obtain
site specific information to assist with understanding the groundwater flow
processes in the central catchment of Bribie Island (Appendix D).
Hydrograph analysis is an important method of presenting periodic measurements
(time series) of groundwater levels as the graphs display baseline trends in the
data. When recharge and discharge within an aquifer system are in balance,
hydrographs show that water level data can vary significantly from year to year, but
will remain relatively stable over the long term. When rainfall is inadequate to
compensate for discharges from the aquifer, such as during droughts or due to
excessive pumping, the water level will fall over time.
Figure 24 shows a hydrograph of water levels recorded from a selection of
representative monitoring bores with long-term data. Groundwater levels are
plotted with a residual rainfall mass curve (RRMC) calculated for the site 14100090
(automatic tipping bucket rainfall gauge). The RRMC shows the cumulative
difference between the rainfall recorded for a month and the average rainfall for
each month. This curve is used to illustrate trends in rainfall to assist with the
detection of seasonal and longer-term climatic variations. An increase in the RRMC
indicates periods of above average rainfall and decreases indicate periods of below
average rainfall. As can be seen in Figure 24, the groundwater levels, in the
shallow and basal monitoring bores, mimic the trends of the RRMC.
In Figure 25 groundwater levels recorded across the central Bribie Island transect
are overlain on the hydrogeological cross section. This figure displays the lithology
48
of the area and the two aquifers present: the shallow water table of the perched
aquifer and the deeper potentiometric surface of the basal, semi-confined aquifer.
Figure 23. Heterogeneous sandmass of Bribie Island The HydroGeo Analyst computer package was used to show a) the lithology of individual bores and b) the interpolation between bores.
Figure 24. Hydrograph of long-term groundwater levels and the RRMC
Figure 25. Cross section through central Bribie Island showing grounwater levels and piezometer locations (modified from Armstrong, 2006)
51
4.1.3 Groundwater Quality Physico-chemical parameters were recorded from a selection of monitoring bores in
central Bribie Island when measuring water levels and collecting groundwater
samples. A summary of the recorded physico-chemical parameters is listed in
Near coast, canals or tidal creeks 1596 - 34800 14748 3.3 - 6.5 5.1
Table 6. Groundwater physico-chemical measurements from monitoring bores
Groundwater samples were collected from selected monitoring bores across the
project area and analysed in the QUT laboratory (Appendix E). An ion balance was
calculated for each sample. An ion balance represents a summation of negative
and positive ions; expressed as equivalents [(sum of cations - sum of anions) / sum
of cations and anions]. An analysis returning an ion balance exceeding 5% was
regarded as poor (inaccurate). Water chemistry results completed in this study
were compared and combined with existing water chemistry records. One analysis
per bore was selected as a representative sample of that monitoring bore for
presentation in the following graphs.
The major ions of groundwater from monitoring bores within the central Bribie Island
area are plotted on a Trilinear diagram shown in Figure 26. Trilinear plots display
data based on the percentage of major cations and anions of a water sample. This
plot can reveal useful properties and relationships of different groundwater groups.
52
Trilinear diagrams can indicate samples with similar chemical compositions, via the
clustering of data points.
The Trilinear plot of groundwater samples within the central catchment of Bribie
Island shows that the dominant water type in this area is Na-Cl type water. A
number of groundwater samples, predominantly from the basal aquifer, display an
increase in calcium and bicarbonate ions.
Figure 26. Trilinear plot of groundwater chemistry samples
Ion concentrations of groundwater samples plotted on a Schoeller Plot display and
compare analyte concentrations in a graphical form that can differentiate
hydrochemical water types. Unlike trilinear diagrams, the Schoeller diagram
displays the actual concentration of chemical constituents on a single diagram.
Figure 27 shows that groundwater from the basal aquifer tends to possess higher
concentrations of calcium and bicarbonate ions.
53
Figure 27. Schoeller plot of groundwater chemistry samples
In Figure 28 groundwater analyses are displayed as Stiff Patterns plotted on the
cross section through central Bribie Island. A polygonal shape is created by plotting
ions in milliequivalents per litre on either side of a vertical zero axis; cations are
plotted on the left and anions on the right. Na-Cl water is the dominant water type
in the area. Calcium and bicarbonate ions are at higher concentrations in a couple
of samples in the coarse sands in the basal aquifer.
Figure 28. Stiff patterns overlain on the cross section through central Bribie Island (modified from Armstrong, 2006)
55
4.2 MODELLING
4.2.1 Conceptual Model Models are used to represent a simplified form of reality to assist with developing an
understanding of the groundwater resource. Mathematical models are based on a
conceptual understanding of the physical system to be modelled. A conceptual
model involves the conceptualisation of the geology and hydrology of a groundwater
system.
As discussed in Chapter 2, Bribie Island is composed of Quaternary sand deposits
that overlie bedrock of the Early Jurassic Landsborough Sandstone Formation.
Groundwater on Bribie Island occurs as a freshwater 'lens' within the intergranular
spaces of the heterogeneous, sand deposits. Two distinct groundwater bodies
occur on the island: a shallow, perched, unconfined aquifer and a deeper, semi-
confined, basal aquifer. A hydrogeologically significant layer of indurated sand,
locally known as “Coffee Rock”, separates these aquifers (Harbison, 1998; Harbison
and Cox, 1998; Spring, 2005; Armstrong, 2006). Hydraulic conductivity results from
field testing on Bribie Island range from 0.3 to 18.5m/day for the shallow, perched
aquifer and 1 to 25m/day for the basal, semi-confined aquifer.
Bribie Island’s groundwater aquifers are recharged via direct infiltration of rainwater
into the porous sands. Using the sodium accretion method, Harbison (1998)
calculated an aquifer recharge of 7% of the average annual rainfall for this part of
the island.
Evapotranspiration and groundwater discharge to the sea dominate groundwater
discharge processes on Bribie. Other drainage mechanisms include evaporation,
surface run-off and some direct drainage from tidal creeks along west coast
(Harbison, 1998; Harbison and Cox, 2000).
56
4.2.2 Mathematical Modelling
Analytical Solution
An analytical solution is the simplest approach to modelling. A preliminary estimate
of groundwater discharge at the coast was calculated using Darcy’s Law. The area
assessed covered the same area as the groundwater flow model. The input values
and results from this analysis are listed in Table 7. The estimate of groundwater
discharge from the central catchment of Bribie Island totalled approximately
8000m3/day. These results depend on evaluation of the thickness of the sand
layers on the island and representative hydraulic conductivities gained from field
testing. Discharge results were not directly verified with field data and are therefore
are unlikely to be very accurate.
L
hhKAQ
)( 21 −=
Units Shallow Sands
Indurated Sand
Basal Sands
K mean m/day 6.4# 0.4# 13*
A mean m3 193500 279500 860000
(h1-h2) mean m 4.5 2.5 1.5
L mean m 2875 2875 2875
Q = discharge m3/day 2000 100 6000 # Average from Slug Tests (QUT and HLA)
* Average from Pumping Tests (QUT)
Table 7. Estimated groundwater discharge
57
Numerical Modelling
A rudimentary steady-state groundwater flow model was developed for the central
area of Bribie Island. The model was designed to investigate recharge, hydraulic
properties, boundary conditions, discharge, flow budget and the sensitivity of model
parameters on model results.
Model Calibration
Model calibration is the process of refining selected model input parameters to
achieve an acceptable degree of correspondence between the model simulation
and observations of the groundwater flow system (ASTM, 1994). Calibrations were
based on achieving the best fit between simulated groundwater levels and water
levels recorded from field observation. Calibration simulations were performed
using inverse problem solving with the WinPEST package, which is included with
the Visual MODFLOW program.
The study included qualitative and quantitative measures of calibration. Qualitative
measures include the comparison of expected water level contours, hydraulic
gradients and flow directions with those simulated by the model. Quantitative
measures involve calculating differences in observed and predicted water levels
within the model.
Initial sensitivity analysis revealed that water levels were most sensitive to recharge
rates and hydraulic conductivity. The model calibration was found to be nonunique
in that the model could be calibrated if both the recharge rate and the hydraulic
conductivity were increased concurrently.
Subsequent calibration focused on adjustment to hydraulic conductivity values,
based on the assumption that uncertainties in the infiltration rate were small relative
to uncertainties in hydraulic conductivity. Initially hydraulic conductivity was based
on field hydraulic tests conducted in the area and was assumed to be spatially
invariant. This method resulted in a poor calibration and the model was unable to
simulate realistic water levels, especially in the upper, perched aquifer and for some
hydraulic values the model would not converge. Numerous discrete zones were
adopted for calibrating the hydraulic conductivities.
58
Calibrated horizontal hydraulic conductivities were limited between 1 and 110m/day
and vertical hydraulic conductivities between 0.0001 and 1.1m/day. Figure 29
displays the mathematically derived hydraulic conductivities.
The pattern of water level contours and groundwater flow predicted by the
calibrated model are qualitatively similar to the inferred water levels expected by the
conceptual model. Groundwater flows are parallel to the steepest gradient in the
study area. Flow direction is dominated by east–west flow from the topographically
higher beach ridges down to the low-lying swale and coastal areas.
The calibrated steady-state model for the central catchment of Bribie Island
simulates the observed groundwater levels and the groundwater flow processes in
the area (Appendix F). Water levels simulated by the steady-state model are
presented in Figure 30 and Appendix G contains the simulated and observed water
levels. A scattergram of observed heads verses modelled heads for the steady-
state calibration is included in Figure 31.
The normalised root mean square value from the optimised steady-state model was
4.5%, a value that represents the collective error in the model outputs. This value
was based on measured (actual) verses predicted water levels and should be less
than 5 percent (L. Luba, pers comm., 2005). The correlation coefficient is 0.99; this
value tends to 1 for perfect calibrations (Middlemis, 2000). The absolute residual
mean for the steady-state model is 0.21m. The maximum residual in the model
between assumed and simulated water levels is +0.94m at monitoring bore
14100135.
59
Figure 29. Hydraulic conductivities determined mathematically using WinPEST Figures show: a) Kx and Ky for Layer 1; b) Kz for Layer 1; c) Kx and Ky for Layers 2 and 3; Kz for Layers 2 and 3; e) Kx and Ky for Layer 4; and f) Kz for Layer 4.
60
Figure 30. Simulated water levels from steady-state model showing monitoring bores: a) shallow, unconfined; and b) basal, semi-confined aquifers.
b)
a)
61
Water Budget
In addition to the calculated hydraulic heads, MODFLOW uses computed heads to
develop a mass balance (volumetric balance). This provides a check on the
accuracy of the numerical solution. A good mass balance may not guarantee an
accurate solution, however a poor mass balance usually indicates problems within
the model. Although models are rarely useful for quantitative predictions of
consequences (Voss, 1998), data in the mass balance contains useful information
used to identify the relative importance of flows into and out of the system
(Anderson, 1993).
The mass balance graph shown in Figure 32 plots the volume of water entering and
leaving the system through the flow boundary conditions. The final steady-state
model produced a mass balance error of 0 %. The percent discrepancy of a model
should be less than 1 percent (Anderson, 1993).
As anticipated, the mass balance data shows that rainfall is the primary model input
with 25163m3/day. There is a relatively insignificant input from the constant head
boundaries of 5m3/day. Model outputs are dominated by evapotranspiration
(15070m3/day) and groundwater discharge from constant head boundaries
(9512m3/day). Minor losses occur via drains (397m3/day) and flow across the
northern and southern general head boundaries (189m3/day).
Harbison (1998) estimated that 7% of annual rainfall (1358mm/year) infiltrates into
the Pleistocene sands on Bribie Island. For the central catchment of the island this
equates to approximately 11215m3/day. When losses from the modelled system via
evapotranspiration and drains are subtracted from the rainfall recharge, the amount
that enters the aquifer system is around 9696m3/day, around 13.5% less than
anticipated. The modelled groundwater discharge from the constant head
boundaries was 9512m3/day, around 16% more than the preliminary estimate of
8000m3/day, determined from Darcy’s Law flow equation.
62
Figure 31. Calculated verses observed water levels, steady-state model
Figure 32. Mass balance for steady-state model
63
The flow zone budget data in Table 8 outlines the flow rates of water entering and
leaving user-defined zones through flow boundary conditions and through other
user-defined zones. This provides information related to groundwater movement in
areas outlined by the modeller. Five zones of interest were delineated: zones 1 – 3
in the upper aquifer (representing three different vegetation groups - National Park,
swale and pine plantation, respectively); zone 4 in the indurated, sand layer; and
zone 5 in the basal aquifer.
Rainfall was the dominant recharge process for Layer 1 (perched aquifer, zones 1 -
3) of the model while for the lower sands (Layers 2, 3 and 4, zones 4 and 5)
recharge was via vertical leakage of water from the overlying sand layers.
Groundwater discharge from Layer 1 of the model is dominated by
evapotranspiration (15070m3/day) followed by groundwater discharge at constant
head boundaries (2596m3/day). Evapotranspiration does not remove groundwater
from the lower layers 2, 3 and 4. Layers 2 and 3, representing the indurated sands,
have minor losses via seepage at the coast (60m3/day) and via flow across the
general head boundaries (18m3/day). The dominant process to remove
groundwater from layer 4 (the basal, semi-confined aquifer) is via groundwater
discharge to the coast (6856m3/day) plus with minor flow occurring across the
northern and southern general head boundaries (80m3/day).
Mathematical analysis estimated that groundwater discharge from the aquifer
system would be around 2000, 100 and 6000m3/day from the shallow, perched
aquifer, the indurated sands and the basal, semi-confined aquifer, respectively. The
modelled outputs are comparable to the results determined from analytical solution.
64
Layer 1
National Park &
remainder Swale
Pine Plantation
Layer 2 & 3 Layer 4
Zone 1 Zone 2 Zone 3 Zone 4 Zone 5
IN: Flow (m3/day)
Constant Head 4.8 -- -- -- --
Head Dep Bounds -- -- -- -- --
Recharge 15511.0 2215.8 7435.9 -- --
Zone 2 to 1 = 31.4
Zone 1 to 2 = 51.5
Zone 1 to 3 = 182.2
Zone 1 to 4 = 3787.7
Zone 4 to 5 = 6953.0
Zone 3 to 1 = 182.4
Zone 3 to 2 = 136.2
Zone 2 to 3 = 5.6
Zone 2 to 4 = 968.0
Zone 4 to 1 = 54.2
Zone 4 to 2 = 0.0
Zone 4 to 3 = 0.0
Zone 3 to 4 = 2308.3
Zone 5 to 4 = 21.4
Total IN 15784 2403.5 7623.7 7085.4 6953.0
OUT: Flow (m3/day)
Constant Head 2595.9 -- -- 59.6 6856.4
Drains 397.1 -- -- -- --
ET 8728.7 1386.4 4954.6 -- --
Head Dep Bounds 40.6 12.0 42.2 18.3 75.6
Zone 1 to 2 = 51.5
Zone 2 to 1 = 31.4
Zone 3 to 1 = 182.4
Zone 4 to 1 = 54.2
Zone 5 to 4 = 21.4
Zone 1 to 3 = 182.2
Zone 2 to 3 = 5.6
Zone 3 to 2 = 136.2
Zone 4 to 2 = 0.0
Zone 1 to 4 = 3787.7
Zone 2 to 4 = 968.0
Zone 3 to 4 = 2308.3
Zone 4 to 3 = 0.0
Zone 4 to 5 = 6953.0
Total OUT 15784 2404 7624 7085 6953
IN - OUT 0.033 -0.004 0.017 0.2 -0.244
% discrepancy 0.00 0.00 0.00 0.00 0.00
Table 8. Zone budget for steady-state model
65
Uncertainty and Sensitivity Assessment
Sensitivity analysis is undertaken to determine model sensitivity to factors that affect
groundwater flows and data uncertainty. In sensitivity analysis, results from the
base-case model simulation are compared with the results of other model runs after
altering various parameters. Evaluations are based on the degree to which the
model output changes for a given change in input.
Sources of uncertainty in numerical models can include geological, parameter (e.g.
hydraulic conductivity and recharge) and boundary condition uncertainty (Fabritz, et
al., 1998). Geological uncertainty relates to the degree to which the stratigraphy
assumed in the model represents the geology of the area. The southern portion of
the model contains few piezometers (3 in the upper aquifer and 3 in the lower
aquifer) and as such has higher uncertainty than the northern portion of the model.
Parameter and boundary condition uncertainty describe the uncertainty in the model
from imposed parameters and by characterisation of hydrogeologic conditions along
the boundary of the model. Recharge was one of the better-defined parameters of
the model. The recharge rate has a large affect on the total volume of water that
enters the flow field. Hydraulic conductivity was determined using a reverse,
parameter estimation technique within a restricted range of values. Altering
hydraulic conductivities in the Bribie model resulted in non-convergence.
Sensitivity analysis was conducted on five parameters within the model and the
results are displayed in Figure 33. The diagrams plot the normalised root mean
square and simulated water levels from monitoring bores MW3s (perched aquifer)
and MW3d (basal aquifer). Changes to ET rate, ET extinction depth and general
head boundary conductance cause a significant change to the models calibration,
while changes to drain conductance and elevation do not have any significant
impact on the models calibration.
66
Figure 33. Sensitivity analysis for steady-state model The figures show simulated water levels in monitoring bores MW3s and MW3d and the normalised RMS for the model.
67
5. DISCUSSION AND SUMMARY
5.1 HYDRAULIC MONITORING
5.1.1 Climate Bribie Island has a sub-tropical climate with the following features.
Temperature maximums for the area range from 19°C in winter up to 28°C
in summer.
Mean annual rainfall is around 1358mm/year at Bongaree station which is
located in the southwest of Bribie Island. Rainfall is seasonal with peak
rainfall occurring over summer and early autumn (December through
March).
Mean annual pan evaporation is around 1679mm/year. Pan evaporation
values fluctuate with the seasons and usually exceed rainfall from July
through January.
Potential evapotranspiration rates were estimated to range from 60%
(~1003mm/year) to 77% (~1293mm/year) of the pan evaporation.
5.1.2 Monitoring Bore Network Data from various sources (DNRMW, HLA and QUT) was collated and interpreted
in order to conceptualise the hydrogeological system in the central catchment of
Bribie Island.
Lithological data was interpreted and the various stratigraphic descriptions from the
different sources were standardised to allow comparison of data. The resulting
interpretation was plotted in 3-dimensional space using the HydroGeo Analyst
computer package. This process highlighted that the Quaternary sandmass in
central Bribie Island was spatially heterogeneous in both lateral and vertical extent.
The sandmass aquifer system in central Bribie Island contains fine to coarse sands,
clayey sands, clay bands and the hydrogeologically significant indurated sands.
The indurated sands affect groundwater flow on the island by impeding the
infiltration of water into the sandmass. This indurated layer separates the two
groundwater systems, causes perching of groundwater above this horizon and
results in the semi-confinement of the basal aquifer.
68
Groundwater levels recorded in the field across central Bribie Island show a distinct
separation between the shallow, perched aquifer and the basal, semi-confined
aquifer.
groundwater in the surficial, clean sands is perched on the indurated,
Quaternary sands and occurs under unconfined conditions. The water table
mirrors the topography and water levels range from around 1 to 7.3mAHD.
the indurated sands act as a semi-confining layer causing the groundwater
in the basal sands to occur under semi-confined conditions. The
potentiometric surface of the basal aquifer occurs as a gentle groundwater
mound and water levels range from around 1.3 to 2.9mAHD.
Hydrograph analysis of long-term, groundwater level data reveals baseline trends in
the data. This data was compared to the residual rainfall mass curve (RRMC) for
the station near bore 14100090 (BoM station 540055). The comparison revealed
that groundwater levels, in the shallow and basal monitoring bores, mimic trends
displayed by the RRMC. Hydrographs revealed that major trends in groundwater
levels are predominantly related to recharge by rainfall.
Groundwater flows preferentially toward the steepest hydraulic gradient. In the
upper, perched aquifer, the sides of the beach ridges offer the steepest gradient in
central Bribie Island. It is anticipated that the main horizontal direction of
groundwater flow is along an east-west axis, towards the low-lying central swale or
the coastline. The lower basal aquifer forms a gentle groundwater mound, with
water flowing east and west to the coastline to discharge via groundwater seepage
off the coast. As flow can only occur parallel to streamlines, the north-south flow
along the length of the island would be nominal compared to flow along the east-
west axis.
5.1.3 Groundwater Quality Groundwater chemistry investigates the processes that control the groundwater
quality. Physico-chemical measurements and water chemistry analyses for the
central catchment of Bribie Island revealed fresh groundwater of acidic to slightly
acidic quality.
Electrical conductivity readings of groundwater from the upper aquifer, the indurated
sand layer and the basal aquifer ranged from 61 to 1018µS/cm. This reveals that
groundwater within the island aquifer system is fresh. Groundwater from monitoring
69
bores near the coast, canals or tidal creeks was found to have an increased
electrical conductivity. Electrical conductivity readings were brackish to saline and
ranged from 1596 to 34800µS/cm. Predominantly the groundwater on Bribie is
fresh even though the island is surrounded by seawater. However the elevated
conductivity in some samples indicates the vulnerability of this type of groundwater
system to seawater encroachment.
Measurements indicate that the pH of groundwater is acidic to slightly acidic (3.3-
6.6). This has been attributed to the breakdown of plant material into organic acids
(Harbison, 1998; Armstrong, 2006). The average pH values of groundwater within
the upper aquifer (4.1) and indurated sand layer (3.7) were slightly more acidic than
the lower semi-confined aquifer (4.9).
Groundwater chemistry analysis can indicate samples with similar chemical
compositions, via the clustering of data points, and show trends occurring within
groundwater groups. Groundwater samples from aquifers in central Bribie Island
show that groundwater from both aquifers is dominated by Na-Cl type water. This is
to be anticipated in a coastal island environment where the primary mechanism of
groundwater recharge is coastal rainfall containing cyclic salt.
Quartz, the dominant mineral on the island, belongs to the silicate group of minerals
which are slow to chemically react with water. Some minerals are more soluble and
react fast upon contact with water, for example carbonate minerals (Appelo and
Postma, 2005). A number of groundwater samples from the basal aquifer possess
higher concentrations of calcium and bicarbonate ions. Enrichment of Ca and
HCO3 could be due to chemical interactions with shell material while water is
infiltrating to the lower levels. The longer residence times of groundwater in the
basal aquifer may also be a factor.
Groundwater recharge of the Bribie Island aquifers is via the infiltration of coastal
rainfall into the upper sand unit and vertical leakage of groundwater into the
underlying sand units. This common recharge source is reflected by the similarity of
the physico-chemical parameters and the water chemistry results. However, the
separation of the two aquifers by semi-confining, indurated sands enables chemical
interactions to alter the groundwater, resulting in subtle, localised differences in the
groundwater quality.
70
5.2 MODELLING
5.2.1 Analytical Solution Mathematical analysis was used to make a preliminary estimate of groundwater
discharge from the central portion of Bribie Island. Darcy’s Law is an equation that
describes the flow of groundwater in a system. This equation was used for a
rudimentary assessment of the discharge from the central area of the island.
Groundwater discharge from the aquifer system in the central catchment of the
island is approximately 8000m3/day. Discharge from the upper, perched aquifer
was in the order of 2000m3/day and 6000m3/day discharged from the basal, semi-
confined aquifer. The larger volume of groundwater discharge from the basal
aquifer is attributed to the larger volume of this aquifer and its higher hydraulic
conductivity rates.
A minor volume of groundwater discharges from the indurated sands (approximately
100m3/day). This is expected as this layer occupies a small volume in the
sandmass and has the lowest recorded hydraulic conductivity values. The process
of induration has resulted in the infilling of pore spaces between sand grains which
has reduced the hydraulic conductivity and available storage of the sand.
Darcy’s Law was used to calculate an initial estimate of discharge from the central
area of Bribie Island. The heterogeneous nature of the sand, variations in the
thickness and hydraulic conductivity of the aquifers were not taken into account.
The simplifications introduced uncertainty into the discharge calculations.
5.2.2 Numerical Modelling A steady-state groundwater flow model was developed and calibrated against
existing groundwater level data collected during field programs. The model was
developed to simulate the existing hydrological system and the dominant
Standing Water Levels and Physico-chemical Parameters
Bore Id SWL EC pH Eh D.O. Temp. Colour Odour Date (m b ToC) (µS/cm) (mV) (ppm) (oC) 088 6.30 402 5.76 161 0.96 22.0 Clear N 17/07/03 088 6.47 376 5.65 150 0.56 22.9 Crystal clear N 24/09/03 088 6.58 344 5.64 204 1.35 22.4 Crystal clear N 13/11/03 092 6.92 315 5.62 218 1.77 20.1 Medium brown N 14/05/03 092 6.58 320 5.31 234 1.24 21.4 Milky, almost clear Y 16/07/03 092 6.56 307 5.22 246 0.72 22.2 Milky clear N 15/09/03 092 6.79 307 5.28 272 1.12 22.7 Milky clear N 11/11/03 101 6.34 193 4.85 240 0.96 21.8 Almost clear Y 17/07/03 101 6.50 93 4.60 258 0.82 23.4 Weak tea Y 24/09/03 101 6.69 101.8 5.30 236 0.66 22.7 Weak tea N 13/11/03 112 4.94 331 6.55 135 3.17 21.0 Clear / slightly brown Y 15/05/03 112 4.98 287 5.02 174 0.92 21.6 Dark tea Y 16/07/03 112 5.09 264 5.25 162 0.73 22.2 Weak tea Y 15/09/03 112 5.43 262 5.14 185 1.1 22.3 Weak tea Y 11/11/03 114 0.96 216 3.77 270 1.00 21.2 Dark tea Y 17/07/03 114 1.28 178 4.23 281 0.85 20.4 Dark tea Y 15/09/03 114 1.46 180.4 4.09 284 0.97 22.4 Tea Y 11/11/03 115 0.70 362 3.62 323 3.64 21.1 Dark brown Y 14/05/03 115 0.72 335 3.71 309 2.32 21.1 Dark tea Y 16/07/03 115 1.09 319 3.67 319 0.87 21.0 Dark tea Y 15/09/03 115 1.31 319 3.74 331 1.08 22.4 Dark tea Y 11/11/03
Bore Id SWL EC pH Eh D.O. Temp. Colour Odour Date (m b ToC) (µS/cm) (mV) (ppm) (oC) 116 0.88 24300 6.52 139 1.73 21.3 Light brown N 15/05/03 116 1.35 18350 5.95 155 2.16 21.0 Milky, light brown saline 16/07/03 116 1.61 16420 5.45 176 2.34 21.1 Milky clear N 15/09/03 116 1.55 17720 5.59 187 1.98 21.5 Milky clear N 11/11/03 126 3.36 74 4.48 335 0.75 22.0 Dark tea Y 24/09/03 126 3.52 106.1 4.48 398 1.21 23.9 Tea Y 13/11/03 129 1.76 68 4.85 336 3.63 20.7 Dark murky brown Y 24/09/03 129 2.20 65.8 4.51 364 0.97 21.9 Dark murky brown Y 13/11/03
131 1.00 67 4.06 319 3.66 20.4 Dark brown N 14/05/03 131 1.08 63 4.19 320 4.35 19.8 Dark brown Y 15/07/03 131 1.38 61 4.60 323 0.89 21.2 Light murky brown Y 24/09/03 131 1.49 62.2 4.30 310 1.04 23.2 Lt murky brown Y 12/11/03 132 1.10 396 3.85 306 0.75 20.5 Dark murky brown Y 24/09/03 132 1.03 403 3.67 321 2.38 22.1 Dark brown Y 12/11/03 133 0.89 373 3.64 349 4.83 20.4 Dark murky brown Y 24/09/03 133 1.90 314 3.68 356 4.02 23.8 Dark brown Y 12/11/03 139 1.33 398 4.28 269 0.72 21.2 Dark murky brown Y 24/09/03 139 1.35 402 4.38 255 0.89 21.8 Dark murky brown Y 13/11/03 140 5.37 321 4.99 212 2.07 21.5 Clear tea N 17/07/03 140 5.55 303 4.91 250 0.60 22.7 Clear N 24/09/03 140 5.65 307 4.80 250 0.62 22.4 Clear N 13/11/03
Bore Id SWL EC pH Eh D.O. Temp. Colour Odour Date (m b ToC) (µS/cm) (mV) (ppm) (oC)
141 0.97 170 4.49 250 1.41 19.2 Dark brown, muddy Y 17/07/03 141 1.26 168 4.33 282 0.81 20.6 Dark murky brown Y 24/09/03 141 1.23 188.4 4.63 281 0.98 22.8 Dark murky brown Y 13/11/03 142 1.20 83 4.18 265 3.48 19.7 Medium brown Y 14/05/03 142 1.26 72 4.80 250 3.82 19.4 Dark brown, muddy Y 17/07/03 142 1.68 69 4.34 266 0.68 21.5 Dark murky brown Y 24/09/03 142 1.79 70.7 4.44 256 1.29 22.7 Dark murky brown Y 13/11/03 143 4.89 99 3.90 356 3.21 -19.3 Dark brown Y 14/05/03 143 5.02 105 3.89 290 0.54 22.4 Dark brown Y 17/07/03 143 5.40 121 3.72 295 0.64 22.8 Dark murky brown Y 24/09/03 143 5.60 90.2 3.80 286 0.76 22.3 Dark murky brown Y 13/11/03 144 2.12 1018 4.87 259 0.82 20.2 Dark tea Y 17/07/03 144 2.42 882 5.10 235 0.62 21.4 Dark tea N 24/09/03 144 2.70 941 5.18 266 1.03 21.1 Tea Y 13/11/03 145 1.30 154 3.70 372 3.41 18.3 Dark brown N 17/07/03 145 1.51 142 3.78 339 1.29 20.4 Light murky brown Y 24/09/03 145 1.59 146.6 3.69 344 1.96 21.8 Med murky brown Y 13/11/03 146 1.88 64 4.36 298 3.92 22.8 Dark murky brown Y 24/09/03 146 2.17 64.6 4.18 270 0.83 23.2 Dark murky brown Y 13/11/03 147 2.04 86 4.66 253 1.05 21.5 Weak tea Y 17/07/03 147 2.36 83 4.73 255 0.50 22.4 Weak tea Y 24/09/03
Bore Id SWL EC pH Eh D.O. Temp. Colour Odour Date (m b ToC) (µS/cm) (mV) (ppm) (oC)
147 2.62 78 4.46 275 1.17 22.0 Weak tea Y 13/11/03 148 4.64 76 4.38 310 0.74 22.6 Weak tea Y 24/09/03 148 4.90 78.1 4.54 334 0.68 23.2 Weak tea Y 13/11/03 149 1.19 224 3.52 310 1.14 19.3 Dark murky brown Y 24/09/03 149 1.31 214.8 3.53 332 1.4 22.2 Dark murky brown Y 13/11/03 150 1.25 294 3.56 307 5.52 19.9 Dark muddy brown Y 17/07/03 150 2.15 237 3.51 311 1.80 19.8 Dark murky brown Y 24/09/03 150 2.47 234 3.48 317 1.63 21.4 Dark murky brown Y 13/11/03 151 3.31 210 3.81 289 0.83 21.2 Dark tea Y 17/07/03 151 3.62 203 3.68 291 0.73 21.9 Dark tea Y 24/09/03 151 3.87 205.9 3.77 288 0.9 21.7 Dark tea Y 13/11/03 MW 1S 1.07 152 4.13 334 3.35 20.0 Dark brown Y 15/07/03 MW 1S 1.38 128 4.25 348 3.41 19.8 Murky choc brown Y 16/09/03 MW 1S 1.58 137.9 4.23 348 2.21 22.3 Dark murky brown Y 12/11/03 MW 3S 0.75 399 4.31 262 2.33 20.3 Dark brown, muddy Y 15/07/03 MW 3S 1.40 387 4.45 273 3.75 19.8 Murky choc brown Y 16/09/03 MW 3S 1.59 493 4.30 287 1.17 22.8 Dark murky brown Y 12/11/03 MW 4D 4.64 393 5.33 269 4.66 19.6 Clear / slightly brown N 14/05/03 MW 4D 4.67 386 4.61 304 1.40 21.2 Milky N 15/07/03 MW 4D 4.98 390 5.24 262 0.79 21.5 Milky clear N 16/09/03 MW 4D 5.12 392 4.94 294 0.97 22.4 Clear N 12/11/03
Bore Id SWL EC pH Eh D.O. Temp. Colour Odour Date (m b ToC) (µS/cm) (mV) (ppm) (oC)
MW 4S 1.89 233 4.00 410 4.34 - Dark brown N 14/05/03 MW 4S 1.87 294 3.61 443 5.50 18.3 Dark brown, muddy Y 15/07/03 MW 4S 2.50 308 3.52 423 6.77 19.1 Murky choc brown Y 16/09/03 MW 4S 2.53 353 3.45 454 1.94 22.0 Dark murky brown Y 12/11/03 MW 5D 4.17 263 4.52 296 1.36 20.4 Very clear N 15/07/03 MW 5D 4.37 258 5.06 273 0.81 21.5 Crystal clear N 16/09/03 MW 5D 4.65 254 4.51 326 1.18 22.2 Crystal clear N 12/11/03 MW 5S 1.34 277 3.95 346 5.35 20.0 Dark brown, muddy Y 15/07/03 MW 5S 1.64 263 3.73 358 4.52 19.4 Murky choc brown Y 16/09/03 MW 5S 1.75 259 3.71 397 2.48 23.2 Dark murky brown Y 12/11/03 MW 6D 5.33 364 4.88 277 1.20 20.8 Milky N 15/07/03 MW 6D 5.43 354 5.41 239 0.73 21.6 Milky clear N 16/09/03 MW 6D 5.70 361 5.39 255 0.94 22.4 Milky clear N 12/11/03 MW 6S 0.64 220 4.53 296 1.91 20.3 Dark brown, muddy Y 15/07/03 MW 6S 0.98 203 4.57 281 2.93 19.8 Murky choc brown Y 16/09/03 MW 6S 1.06 206.9 4.32 310 0.89 21.8 Dark murky brown Y 12/11/03 MW 8D 5.89 343 5.07 254 4.22 - Clear / slightly brown N 14/05/03 MW 8D 5.94 350 4.86 260 1.49 21.9 Milky Y 15/07/03 MW 8D 6.03 409 5.02 269 0.76 22.5 Milky clear N 16/09/03 MW 8D 6.22 379 4.50 292 1.05 22.7 Milky clear N 12/11/03 MW 8S 1.46 130 3.55 324 4.21 -14.3 Medium brown N 14/05/03
Bore Id SWL EC pH Eh D.O. Temp. Colour Odour Date (m b ToC) (µS/cm) (mV) (ppm) (oC)
MW 8S 1.52 120 3.85 333 3.17 21.2 Dark brown, muddy Y 15/07/03 MW 8S 1.73 111 3.85 343 3.68 21.1 Murky choc brown Y 16/09/03 MW 8S 1.88 120.2 3.77 346 1.38 23.4 Lt murky brown Y 12/11/03 MW 11-1D 4.80 34800 6.06 215 0.22 22.9 Dark brown Y 15/05/03 MW 11-1D 6.37 - - - - - - - 16/07/03 MW 11-1D 6.23 - - - - - - - 15/09/03 MW 11-1D 4.86 26400 5.19 227 2.99 23.9 Dark murky brown N 12/11/03 MW 11-1S 1.59 14400 3.55 480 3.64 21.9 Dark brown Y 15/05/03 MW 11-1S 2.60 - - - - - - - 16/07/03 MW 11-1S 2.33 - - - - - - - 15/09/03 MW 11-1S 1.99 13650 3.25 427 3.26 24.6 Dark murky brown N 12/11/03 MW 11D 4.80 248 4.78 262 0.75 20.2 Clear tea N 15/07/03 MW 11D 4.97 233 5.01 247 0.89 21.6 Tea N 16/09/03 MW 11D 5.15 238 4.83 277 0.95 22.0 Tea Y 12/11/03 MW 12S 1.38 344 3.39 348 2.81 18.7 Dark brown, muddy Y 15/07/03 MW 12S 1.72 331 3.44 347 4.58 19.8 Murky choc brown Y 16/09/03 MW 12S 1.89 304 3.47 332 0.84 22.0 Dark murky brown Y 12/11/03 MW 15S 1.59 112 3.79 325 4.59 20.6 Medium brown Y 15/07/03 MW 15S 1.91 112 3.76 330 5.51 20.0 Light murky brown Y 16/09/03 MW 15S 2.13 108.2 3.77 327 1.33 22.8 Light brown Y 12/11/03 MW 16D 0.89 268 4.10 285 1.71 20.6 Dark brown, muddy Y 15/07/03
Bore Id SWL EC pH Eh D.O. Temp. Colour Odour Date (m b ToC) (µS/cm) (mV) (ppm) (oC)
MW 16D 1.14 250 4.21 300 0.88 20.3 Murky choc brown Y 16/09/03 MW 16D 1.33 253 4.51 316 2.02 21.9 Dark murky brown Y 12/11/03 MW 22S 0.89 314 3.83 317 4.80 18.7 Dark brown, muddy Y 15/07/03 MW 22S 1.16 313 3.55 322 6.19 19.3 Light murky brown Y 16/09/03 MW 22S 1.32 310 3.58 324 2.4 23.6 Dark murky brown Y 12/11/03 QM 114 1.16 5310 4.90 222 0.29 23.6 Dark brown Y 15/05/03 QM 114 1.41 2085 5.06 204 1.59 19.9 Dark brown, muddy Y 15/07/03 QM 114 1.56 1596 4.85 237 4.30 22.3 Murky choc brown Y 15/09/03 QM 114 1.54 1950 4.79 285 3.01 25.6 Dark murky brown Y 11/11/03 Slnder Dr 5.31 308 3.64 285 0.81 22.8 Dark tea Y 16/07/03 Slnder Dr 5.44 284 3.60 326 0.71 23.5 Dark tea Y 15/09/03 Slnder Dr 5.91 330 4.01 347 1.05 23.2 Dark tea Y 11/11/03 TCLP nth 4.69 397 4.21 300 4.17 23.4 Dark brown Y 15/05/03 TCLP nth 4.90 590 4.15 274 5.33 22.7 Dark brown Y 16/07/03 TCLP nth 4.97 413 4.18 289 5.73 22.6 Murky choc brown Y 15/09/03 TCLP nth 5.09 384 4.14 305 3.08 23.7 Dark murky brown Y 11/11/03 W Patch 2.68 130 6.33 264 4.25 20.9 Dark tea N 15/05/03 W Patch 2.83 186 4.92 398 1.76 16.1 Tea Y 15/07/03 W Patch 2.93 132 4.60 377 0.93 21.5 Dark tea N 15/09/03 W Patch 2.59 152.1 4.86 386 1.41 22.0 Tea Y 11/11/03
APPENDIX E
Groundwater Chemical Analyses
Sample Id. Na K Mg Ca Sr Mn Fe Zn Cu F Cl Br SO4 NO3 NO2 HCO3mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L
0.82 deep 78 4.5 13 Nov 03 22.0 00.00 0.38 13.0 deep 65 4.5 19 Sep 01 21.20.28 0.58 14.5 deep 251 4.4 30 Jul 02 21.8 2870
0.72 near Dux Ck 6.2 15 May 03 00.51 near Dux Ck 10060 5.9 11 Nov 03 23.7 00.12 near shore 532 6.8 15 May 03 10.1 00.02 near shore 772 6.3 11 Nov 03 23.8 00.57 near canal 330 4.0 11 Nov 03 23.2 02.88 near canal 384 4.1 11 Nov 03 23.7 0
APPENDIX F
Steady-state Groundwater Flow Model
(see attached CD)
APPENDIX G
Observed and Calculated Water Levels - Steady-state Model
Layer 1 Layer 4 Bore Id. Obs. Head Calc. Head Calc.-Obs. Bore Id. Obs. Head Calc. Head Calc.-Obs.