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Using Geospatial Tools to Identify Critical Nutrient Source Areas and Agricultural BMP Implementation

Priorities

Presentation by: Louise HeymingGrand River Conservation Authority

Cambridge, Ontario, Canada

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Project Objectives

1) Demonstrate how a high resolution digital elevation model (DEM) and advanced GIS techniques can be used to determine nutrient source areas

2) Demonstrate how the identified nutrient source areas can be used to target agricultural best management practices (BMPs)

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The Grand River Watershed

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80 year history of water management planning

Shared responsibility

Successful collaboration

Building on existing data,knowledge and accomplishments

Finding practical ‘best value’ solutions

A long history of water management

2014

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Water Management Plan GoalsEnsure sustainable water supplies

for communities, economiesand ecosystems

Improve water quality to improve river health and reduce the river’s impact on Lake Erie

Reduce flood damage potential

Increase resiliencyto deal with climate change

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Phosphorus Loads

Priority watersheds were identified through the Water Management Plan

Highest P concentrations occur during spring from non-point sources

Point sources dominate in summer

(Adapted from GRCA 2006)

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Identifying Nutrient Source Areas

Terrain Analysis Approach

Gully Erosion

RUSLE-FAC Approach

Sheet Erosion

Identify Priority Areas Identify Priority Areas

High Priority Areas for BMPs

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Pilot Study Area – Firella Creek

The Upper Nith River Sub-basin was identified as a significant contributor of nutrients and sediment in the Water Management Plan

Firella Creek study area covers approximately 32 km2 and is located within the Upper Nith Sub-basin

Lake Erie

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DEM DevelopmentStereo Project Creation:Aerial Data

Scans Camera Files Orientation Files Control Files

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DEM Development

Source: www.planar3d.com

Large Scale 3D Vector Hydrology Creation:

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DEM DevelopmentPixel-Auto Correlation (PAC) Point Collection:

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Final Firella Creek DEM

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Terrain Analysis Approach

Digital Elevation Model

Slope Raster

Stream Power Index Raster

Flow Accumulation Raster

Stream Power Index measures the erosive power of flowing water, identifies areas of potential gully erosion

Approach adapted from (Galzki, Birr and Mulla 2011)

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Terrain Analysis Approach

Stream Power Index (SPI)

High SPI values represent the likely overland flow paths during a storm event

– the potential gullies

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Stream Power Index (SPI) Signatures

Terrain Analysis Approach

SPI Value Percentile

-0.540 75.00%

-0.079 80.00%

0.460 85.00%

1.135 90.00%

2.214 95.00%

A path of high SPI values that flow into

observed surface hydrology

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Terrain Analysis Approach

Field VerificationSPI Signatures - 95th Percentile

Correctly Identified

Incorrect IdentificationFalse Positive Thick Vegetation Other

9/10 (90%) 0/10 (0%) 1/10 (10%) 0/10 (0%)

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Terrain Analysis ApproachStream Power Index

Signatures

Stream Power Index Signature Catchment Areas

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Priority Areas using Terrain Analysis

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RUSLE - FAC Approach

A = R * K * L * S * C * P

Average annual soil loss – Potential sheet erosion (tonnes/hectare/year)

RUSLE–FAC = Revised Universal Soil Loss Equation – For Application in Canada

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Priority Areas using RUSLE - FAC

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Priority Nutrient Source Areas

Priority Nutrient Source Areas - High Values

SPI – High Catchments

RUSLE-FAC -High Values

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Current Extension Program Approach

Technical assistance and financial incentives to all farmers

Work with those farmers who come forward (i.e. they know they have an erosion issue)

Financial incentives are offered for both structures and conservation practices

All erosion control projects are offered the same incentive structure

Photo: C. Heibert

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Mapping Objectives

Identify most vulnerable areas

Apply BMPs best suited to issue (gully and/or sheet erosion)

Target outreach and financial incentives (location, incentive level)

Photo: A. Loeffler

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At the Farm Scale

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At the Farm Scale

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At the Farm Scale

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Early Results

Increase in requests for technical assistance to design erosion control system

Requests for mapping outside our pilot study area

Photo: A. Loeffler

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Future Applications

Internal CA use: Identify priority subwatersheds (best value

solutions) Connect issues to BMPs (structures vs

cropping practices) Identify potential water quality monitoring

sites.

Communication tool: Engage landowners to raise awareness.

Program delivery level: Tailor financial incentives to improve chances

of target farms participating.Erosion control structure design

DEM will help facilitate design work

Photo: L Heyming

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Thank you

Ontario Ministry of the Environment & Climate Change

Grand River Conservation Authority

Ontario Ministry of Agriculture, Food & Rural Affairs

Regional Municipality of Waterloo

Agriculture & Agri-Food Canada

Environment Canada

This Project has received funding support from the Government of Ontario. Such support does not indicate endorsement by the Government of Ontario of the contents of this material.

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ReferencesGalzki, J. C., et al. "Identifying critical agricultural areas with three-meter LiDAR elevation data for precision conservation." Journal of Soil and Water Conservation 66.6 (2011): 423-430.