Linking Agri-Environmental Water Quality Indicators (AEWQIs) to Policy: the Canadian Experience Trilateral Cooperation to Promote the Protection of Water.

Linking Agri-Environmental Water Quality Indicators (AEWQIs) to Policy:

the Canadian Experience

Trilateral Cooperation to Promote the Protection of Water Quality through

Sustainable AgricultureBanff, Alberta

October 7 – 10, 2003

Allan J. Cessna and Bruce Junkins

Agriculture andAgri-Food Canada

Agriculture etAgroalimentaire Canada

Why Risk Indicators?

• Monitoring for a range of contaminants (especially pesticides) for the whole country is very expensive

• Wanted contaminant information that was specific to agriculture

Why Risk Indicators? (continued)

• Can link agri-environmental indicators to economic models which allows us to build scenarios on policy and economic outcomes• Forward looking - Can assess impacts of

policies before they are put in place• Often there is a lag of several years between

when a policy is implemented and the effects of the policy can be measured

Why Risk Indicators? (continued)

• Can investigate adoption rates (eg., beneficial management practices) per dollars spent

• Get more information than just a trend• Although monitoring information is not

available on a national basis, monitoring information is available on regional basis to permit validation of the models

History of AEWQIs in Canada

• In 1993, under the Agri-Environmental Indicator Project, work was initiated on 2 AEWQIs: risk of water contamination by N and by risk of water contamination P

• In 2001, under the National Agri-Environmental Health Analysis and Reporting Program (NAHARP), work was continued on the N and P indicators, and development of a pesticides indicator and a pathogens indicator was initiated

Indicators of Risk of Water Contamination

• The main data source for inputs to the indicators is the Census of Agriculture which covers all agricultural regions of Canada (Available at 5-yr intervals).

• All four water quality indicators will be calculated at the Soil Landscapes of Canada polygon level (1: 1 000 000). Nationally, there are 3,267 agricultural polygons for which data are reported in the Census of Agriculture

Indicator of Risk of Water Contamination by Nitrogen

(IROWC-N)

Crop, Animal, Soil, Weather, N fertilizer

Inputs: Agricultural Production System,

Input:PolicyScenarios

Fig. 1. Data flow of integrated modelling

Canadian Agriculture Nitrogen Budget

CANB ModelCANB Model

Canadian RegionalCanadian RegionalAgricultural Model Agricultural Model (CRAM)(CRAM)

Data handling tools

Easy Easy GrapherGrapher

ScalingScalingUpUp

Canadian Soil InformationCanadian Soil InformationSystem System (CanSIS)(CanSIS)

ArcViewArcViewMapsMaps

Outputs:RSNIROWC-NComponents

350074

Map 1. Residual Soil Nitrogen (RSN) at the SLC scale (2008 business as usual scenario)

0

10

20

30

40

50

60

BC BP AB SK MB ON QC NB NS PE NF

RS

N (

kg N

/ha

)

1981 1991 1996 2001 2008Weighted average

0

2

4

6

8

10

IRO

WC

N (

mg

N/L

)

Fig. 2. RSN and IROWCN at the provincial scale

RSN = 7.24 + 0.4031(Year - 1950)

R2 = 0.9633

0

5

10

15

20

25

30

35

1976 1981 1986 1991 1996 2001 2006

Year

RS

N (

kg N

/ha

)Weighted average

Fig. 3. Time trend of RSN at the national scale

Indicator of Risk of Water Contamination by Phosphorus

(IROWC-P)

Some Characteristics of IROWC-P

• IROWC-P was adapted and combined with aspects

of IROWC-N and PI (Phosphorus Index) (Lemunyon

and Gilbert, 1993).

• The 3 principal components of IROWC-P are:

P transport,

P status

Annual P balance

Suggested Improvements of IROWC-P (2003-2008)

• Because sufficient soil P status data are available only for the province of Quebec, IROWC-P has thus far been calculated only for Quebec.

• The goal now is to improve the indicator by:

incorporating measured P sorption capacity values for all dominant soil series and extrapolated values for all sub-dominant soil series on a national basis

incorporating an hydrologic component

Indicators of Risk of Water Contamination by Pesticides

(IROWC-Pest) and Pathogens (IROWC-Path)

Approaches to Developing IROWC-Pest and IROWC-Path

• Initial emphasis will be to develop indicators for surface water

• Existing models, that estimate pesticide and pathogen movement in water and pesticide movement in air will be used where possible

• The feasibility of using an hydrology component common not only to IROWC-Pest and IROWC-Path but also to IROWC-N and IROWC-P will be explored

Linking Agri-Environmental Indicators to Policy Models

• Multidisciplinary approach to develop and apply integrated economic/environmental models to bring resource science to the policy table to analyze how:

Economic policies and market signals affect the environment

Environmental regulations and international agreements affect economic performance

New technologies impact both economic and environmental performance

Objective

Promote Sustainable and Profitable Resource Use

Soil Quality• erosion• soil carbon• nitrogen• salinization• compaction

Soil Quality• erosion• soil carbon• nitrogen• salinization• compaction

Water Quality• nitrogen• phosphorous• pesticides• pathogens

Water Quality• nitrogen• phosphorous• pesticides• pathogens

Air Quality• greenhouse gases(CO2, N2O, CH4)

• odours• particulates

Air Quality• greenhouse gases(CO2, N2O, CH4)

• odours• particulates

Biodiversity• habitat use• species at risk

Biodiversity• habitat use• species at risk

Nutrient Balance• carbon cycle• nitrogen cycle

Nutrient Balance• carbon cycle• nitrogen cycle

Farm Resource Management• land use • crops• livestock

Farm Resource Management• land use • crops• livestock

Farm Environmental Planning:Managing land and water, nutrients, and pests

Farm Environmental Planning:Managing land and water, nutrients, and pests

• Canadian Regional Agricultural Model (CRAM) Economic model used as policy tool at AAFC for many years Static, non-linear optimization model Integrates all sectors of primary agriculture on regional basis

• CRAM generates a significant amount of information Land use change for major activities (cropland, hayland, tame

pasture, native pasture) Area of major crops (cereals, oilseeds, specialty crops) Summerfallow and tillage practices (West) Livestock numbers (beef, pork, dairy, poultry) Economic impact on both producers and consumers

Changing activity levels in CRAM in terms of land use,land use management and animal production

will affect environmental outcomes

Changing activity levels in CRAM in terms of land use,land use management and animal production

will affect environmental outcomes

Policy Model – CRAM

Policy(economic)

Model

Policy(economic)

Model

Economic Impacts

Economic Impacts

Resource Allocations- cropping patterns- tillage practices- livestock numbers

Resource Allocations- cropping patterns- tillage practices- livestock numbers

Policy DecisionPolicy

Decision

Other Economic/Environmental

Considerations

Other Economic/Environmental

Considerations

feedback

EnvironmentalImpacts

EnvironmentalImpacts

Agri-EnvironmentalIndicator (AEI)

Models

Agri-EnvironmentalIndicator (AEI)

Models

• Economic Parameters• Technology• Farm Management Practices• Physical Resource Base

• Economic Parameters• Technology• Farm Management Practices• Physical Resource Base

Policy ScenarioPolicy Scenario• Scientific Knowledge• Environmental Data- F/P/T gov’t- Industry- Academics

• Scientific Knowledge• Environmental Data- F/P/T gov’t- Industry- Academics

Integrated Economic/Environmental Analysis

• F/P/T commitment to set specific environmental outcome targets

• Use existing economic and AEI models to quantify expected outcomes

• Select and analyze potential farm actions for improving environmental performance

• Provide scientifically based quantitative analysis to assist process of establishing provincial environmental targets under APF

Application: Agricultural Policy Framework (APF)

- Provincial Environmental Targets

• Risk of soil erosion from water (crop, tillage,soil)

• Risk of soil erosion from wind (Prairies) (crop, tillage, summerfallow, soil)

• Residual soil nitrogen (crop, N fertilizer, manure)

• Risk of water contamination from nitrogen (East) (residual N, precipitation, transpiration)

• Soil Carbon (tillage, crop, soil)

• Greenhouse gases (Sinks and emission reductions) (CO2, CH4, N2O)

• Biodiversity in terms of wildlife habitat (land use)

Suite of AEIs for APF Analysis (Key Drivers)

• Soil Management Increased use of conservation tillage (no-till) Decreased use of summerfallow Increased use of forage in rotations Conversion of marginal land to permanent cover

• Pasture Management Increased use of complimentary and rotational grazing

• Nutrient Management Better management of matching N applied to crop

requirements

• Livestock Management Improve management of protein in diets

• Shelterbelts and Plantation Forestry Increased use of forestry on marginal agricultural land

Scenarios Selected for APF Analysis(BMPs – Beneficial Management Practices)

RSN in Response to Policy Scenarios

24

26

28

30

32

Business asUsual

Increase No-till Matching NRequirements

ImproveLivestock Diets

CombinedScenario

RS

N (

kg

N/h

a)

Low adoption rate Medium adoption rate High adoption rate

Results of APF Analysis

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

GHG IROWCN(Ont)

Residual N WaterErosion

(Alta)

Biodiversity

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

GHG IROWCN(Ont)

Residual N WaterErosion

(Alta)

Biodiversity

National Summary of the Percentage Change in AEIs from 2008 BAU for Low, Medium and High Adoption Rates

• Enhancements to CRAM Add water component Update data and structure for livestock and crops Improve regional coverage (Ontario, Quebec, B.C.) Improve cost structure

• Address data gaps Data Warehouse Farm Environmental Management Survey

• Linkages to AEI models Refinement of existing AEIs Need for additional AEIs AEIs must be responsive to BMPs Feedback linkages between economic and environmental

components

Future Directions : Model Development

Future Directions : Spatial Issues

O T T A W A

T O R O N T O

O T T A W A

M O R R I S B U R G

L a n d U s e A l l o c a t i o nM o d e l ( L U A M )

O T T A W A

T O R O N T O

O T T A W A

T O R O N T O

O T T A W A

M O R R I S B U R G

O T T A W A

M O R R I S B U R G

L a n d U s e A l l o c a t i o nM o d e l ( L U A M )

CRAM REGIONS

SOIL-LANDSCAPEPOLYGONS

LUAMLUAM

CRAM crop production regions

Land Use Allocation Model

• Climate Change Domestic Emissions Trading/Offset system Mitigation Impacts and adaptation Environmental Co-benefits

• Environmental Assessments World Trade Organization negotiations Agriculture programs and policies

• APF environmental outcome targets

• Medium Term Policy Baseline

Future Directions : Policy Analysis

AEIsAEIsEconomics and

Markets

Economics and

Markets

ScienceScience Policy Scenario

Policy Scenario

Integrated ModelsIntegrated Models

Economic OutcomesEconomic Outcomes

Environmental Outcomes(air, soil, water, biodiversity)Environmental Outcomes

(air, soil, water, biodiversity)

Economic ValuationEconomic Valuation

Trade-Off

Analysis

Trade-Off

Analysis

Input to Policy Evaluation and Development ProcessInput to Policy Evaluation and Development Process

National Agri-Environmental Health Analysis and Reporting Program (NAHARP)

- Linking Science to Policy -