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
2
Brief Introduction
(adapted from Pierzynski et al., 1994)
www.theviewspaper.net/the-menace-of-eutrophication
3
Study Area
4
Study Area
Pike River Upstream
386km2
Forest = 54%
Grassland = 20%
Walbridge Upstream and
Downstream
Pike River Downstream
563km2
Forest 44%, Grassland 20% and
Corn 16%
Castor Watershed: 3 Subbasins
Grassland 28%, Corn 44%,
12 km2, Cereals 20%
Source: Beaudin et al 2007
5
Hydrologic Modeling: Hydrologic Cycle
Source: http://geofreekz.wordpress.com/thehydrosphere/
6
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
SWAT: Soil and Water Assessment Tool Modeling program developed
by the USDA/ARS
8
Spatial Input for Castor Watershed.
9
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.
10
11
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).
12
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
13
Research Methodology
14
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
15
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
16
Sampling Strategy
17
Sampled Soil Properties:
•
•
•
•
•
•
•
Organic Carbon
Bulk Density
Clay Content (Particle size distribution)
Soil pH
Water Soluble Phosphorus
Soil Test Phosphorus
Hydraulic Conductivity
18
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
19
Acknowledgement
•Prof. Chandra Madramootoo (Supervisor)
• Dr. Aubert Michaud (IRDA, Quebec)
•Isabelle Beaudin (IRDA, Quebec)
20
Thank you and Questions
21