Spatial Modeling of Soil Heterogeneities and their Impacts on Soil-Phosphorus Losses in a Quebec

Watershed

By

Alaba Boluwade

Department of Bioresource Engineering, McGill University, QC, Canada

Supervisor: Prof. C. A. Madramootoo

Dean, Faculty of Agric. And Environmental Science, McGill University, Quebec, Canada.

Presentation Outline

Brief Introduction

Study Area

Hydrologic Modeling

Problem Statement

Research Objectives

Research Methodology

Field Sampling

Acknowledgement

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Brief Introduction

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www.theviewspaper.net/the-menace-of-eutrophication

(adapted from Pierzynski et al., 1994)

Study Area

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Study Area

Pike River Upstream

386km2

Forest = 54%

Grassland = 20%

Walbridge Upstream and Downstream

Pike River Downstream563km2

Forest 44%, Grassland 20% and Corn 16%

Castor Watershed: 3 Subbasins

Grassland 28%, Corn 44%,

12 km2, Cereals 20%

Source: Beaudin et al 2007

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Hydrologic Modeling: Hydrologic Cycle

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Source: http://geofreekz.wordpress.com/the-hydrosphere/

Hydrologic Modeling

• This is the mathematical representation of the flow of water and its constituents on the land surface or subsurface environment

• There is a tight relationship between GIS and hydrologic models

Hydrologic Modeling:SWAT

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SWAT: Soil and Water Assessment Tool Modeling program developed by the USDA/ARS

Spatial Input for Castor Watershed.

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Problem Statement

The major challenge with this distributed model and others is that there is no clear and specific procedures on what level of details

are needed (in this spatial input) for representing the spatial heterogeneities of the soil properties.

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Research Objectives:

Overall Objective:

Quantification and evaluation of the impacts of actual-field observed spatial soil heterogeneities and dynamics on prediction of phosphorus loss in a watershed in Southern Quebec, Canada

using a 2-dimensional, physically based model(SWAT).

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Specific Objectives:

•Develop a stochastic Markov Chain Monte Carlo (MCMC) method to represent the spatial variation of soil properties for a physically based model

•Geospatial quantification of the soil-test phosphorus using various Geostatistical techniques

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Research Methodology

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Defining a sampling strategy

• Sampling strategies:greater sampling density = greater accuracy of the data

• Sampling density vs. accuracy gains: storage and processing power with spatio-temporal variation

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Stratified Sampling in MATLAB using “fmincon” function

• Minimization function for cost and sample size

• Based on proportions of the strata

• Weights for the strata = 0.5500, 0.2400, 0.2100

• Cost per sample is 4.5 dollars

• Sample Size= 264+115+101=480

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Sampling Strategy

Sampled Soil Properties:

• Organic Carbon

• Bulk Density

• Clay Content (Particle size distribution)

• Soil pH

• Water Soluble Phosphorus

• Soil Test Phosphorus

• Hydraulic Conductivity

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Finally, the research should recommend

Nutrient use efficiency Net returns to farmers Reduction in overall nutrient loss from agricultural field Classification of management zones in form of polygon Adaptive agricultural management practices Optimization of the soil Phosphorus-Index for land-use and

ecosystem management

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Acknowledgement

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•Prof. Chandra Madramootoo (Supervisor)

• Dr. Aubert Michaud (IRDA, Quebec)

•Isabelle Beaudin (IRDA, Quebec)

Thank you and Questions

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