WEG Research Projects
Ongoing Research Projects
1. Evaluating Cost Effectiveness of Agricultural Beneficial Management Practices (BMPs) in priority subwatersheds of the Great Lakes Great Lakes Agricultural Stewardship Initiative (GLASI)
This project develops farm economic and watershed hydrologic modelling to estimate economic costs and water quality benefits (such as phosphor reduction) of agricultural BMPs in priority subwatersheds of the Great Lakes Agricultural Stewardship Initiative (https://www.ontariosoilcrop.org/oscia-programs/glasi/, https://www.ontariosoilcrop.org/oscia-programs/glasi/priority-subwatershed-project/). The representative BMPs include conservation tillage, nutrient management, cover crop, and water and sediment control basins. The modelling results can be used to evaluate performance of GLASI in terms of cost to reduce phosphorus loss from agricultural watersheds ($/kg of phosphorus reduction).
2. Evaluating Water Quality Effects of Livestock Beneficial Management Practices (BMPs) in a representative watershed in southern Alberta
This project develops BMP modules in a cell-based, fully-distributed hydrologic modelling system to estimate water quality effects of livestock BMPs at site, field, farm, and watershed scales. The representative livestock BMPs include 1) Manure and nutrient management such as manure application based on soil phosphors limit, manure catch basin/impoundment, and manure storage management; 2) Riparian and surface water management such as fencing, off-stream watering, and buffer strip; 3) Wintering site management such as alternating wintering site annually and vegetation buffer adjacent to wintering site; 4) Pasture management such as rotational grazing and sustainable use of natural areas; and 5) Marginal cropland management such as conversion to tame perennials. The livestock BMP model is being applied to a representative agricultural watershed in southern Alberta to evaluate water quality benefits of livestock BMPs at site and watershed scales.
3. Evaluate Water Quantity and Quality Effects of Wetland Loss and Restoration Scenarios in a representative Prairie watershed
This project develops a wetland module in a cell-based, fully-distributed hydrologic modelling system to estimate water quantity and quality effects of wetland loss and restoration scenarios at site, field, farm, and watershed scales. The wetland model is setup for a representative prairie watershed based on existing wetland distribution and calibrated based on observed hydrologic data. The wetland model is then applied to estimate water quantity effects such as flow intensification/attenuation and water quality effects such as phosphorus loss/retention from wetland loss/restoration scenarios. The modelling results can be used to understand environmental degradation of wetland loss and justify the retention effects of existing wetlands. Furthermore, the modelling results can be used to prioritize locations in the study watershed for targeting wetland conservation and restoration.
4. Developing a WebGIS Based Modelling Tool for Examining Cost Effectiveness of Beneficial Management Practices (BMPs) in a Representative Agricultural Watershed
Extended from a desktop based BMP assessment tool developed in our research group, this project will develop a WebGIS based modelling tool enabling agricultural producers and conservation practitioners to examine BMP cost effectiveness through Web browsers. The project will develop user friendly options using WebGIS interface which links to farm economic, watershed hydrologic, and integrated modelling in the background. The deployment of the WebGIS interface will allow agricultural producers to evaluate economic costs, water quality benefits and cost effectiveness of individual and multiple BMPs in their farms and view BMP effects at field, farm, and watershed scales. The WebGIS interface can be also used by conservation practitioners to examine spatial variations of BMP cost effectiveness measured by the ratios of economic costs and water quantity and quality benefits, and prioritize spatial locations for BMP implementation.