The IMWEBs WebGIS platform uses data and modelling to inform decision-making for agricultural conservation management at several scales. From the farm scale to the watershed scale, the IMWEBs model uses data to suggest tailored best management practices to help farmers reduce excess nutrient runoff at the lowest cost to production.
In Lake Erie and in water bodies across Canada, fertilizer and manure applied to farm fields runs off the land and into our waterways. This agricultural runoff is a combined result of on-farm management practices and natural factors such as soil type and topography, as well as proximity to water sources. Excess nutrients in the fertilizer and manure, such as nitrogen or phosphorus, pollute the water and encourage the growth of algae harmful to water species and the surrounding ecosystems as well as to humans reliant on water sources. Addressing these issues requires a mix of management strategies implemented at multiple scales. Watershed modelling assessments are one tool that can model runoff processes, highlight priority areas and inform actionable strategies for managing agricultural runoff.
The Watershed Evaluation Group is addressing agricultural nutrient runoff in the Lake Erie Basin by developing a decision-support tool to help land managers make informed choices. Led by Dr. Wanhong Yang, the group has created a novel spatial analysis tool called IMWEBs (Integrated Modelling for Watershed Evaluation of BMPs), which simulates field runoff and reduction at various spatial scales. The tool provides stakeholders with actionable recommendations for reducing nutrient runoff by combining spatial, economic and site-specific data. It distills the results of complex models into easy-to-understand guidance, balancing impact and cost to support effective decision-making.
Yang’s development of the IMWEBs tool marks a significant advancement in watershed evaluation, building on traditional models with a more site-specific targeted approach. Traditional tools typically operate at a regional scale, which limits their ability to provide insights at finer, more localized levels like the farm or field scale. The IMWEBs overcomes this limitation by using a grid-based model, allowing it to generate highly specific outputs tailored to smaller areas, such as individual farms or fields. This shift from broad-scale mapping to precision-based modelling represents a leap forward in conservation science. By leveraging the same principles that have driven precision agriculture, Yang’s tool introduces a new concept: precision conservation. The IMWEBs tool helps conservation planners and land managers make data-driven decisions by offering detailed, location-specific recommendations for reducing nutrient runoff, particularly in agricultural watersheds. This level of precision makes the tool invaluable for identifying “hot spots” where nutrient runoff is most problematic and suggesting cost-effective strategies for mitigating its impact. The tool can also inform decision-making for conservation projects, target specific regions for outreach, and guide policy on nutrient runoff reduction strategies and economic incentives.
The IMWEBs tool is currently being implemented in the Lake Erie watershed, building on successful trials in case studies across Ontario and other parts of Canada. Through collaborations with farmer extension organizations like ALUS Canada and regional conservation authorities, Yang’s model is helping connect conservationists and farmers in southern Ontario. While agricultural runoff is a major contributor to Lake Erie’s environmental challenges, tools like the IMWEBs highlight the crucial role farmers play in improving watershed health. Linking agricultural producers with conservation managers is a step toward a more collaborative approach to watershed management across sectors.
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Liu, Y.B, Yang, W., Bass, B., and Yerubandi, R. (2025). Effectiveness of agricultural BMPs on phosphorus load reduction for the Canadian Lake Erie Basin: A literature review. Environmental Reviews 33: 1–24. https://doi.org/10.1139/er-2024-0069
Bodrud-Doza, M., Yang, W., Liu, Y.B., Yerubandi, R., DeVries, B., and Fraser, E.D.G. (2025). Evaluating best management practices for nutrient load reductions in tile-drained watersheds of the Laurentian Great Lakes Basin: A literature review. Science of the Total Environment 965, 178657.https://doi.org/10.1016/j.scitotenv.2025.178657
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Brouwer, R., Pinto, R., Garcia-Hernandez, J., Li, X., Macrae, M., Predrag, P., Yang, W., Liu, Y., Mark, A., and Heyming, L. (2023). Spatial optimization of nutrient reduction measures on agricultural land to improve water quality: A coupled modeling approach. Canadian Journal of Agricultural Economics, 1–25. https://doi.org/10.1111/cjag.12342
Bodrud-Doza, M., Yang, W., Miranda, R. Q., Martin, A., DeVries, B., and Fraser, E. D. G. (2023). Towards implementing precision conservation practices in agricultural watersheds: A review of the use and prospects of spatial decision support systems and tools. Science of the Total Environment 905, 167118. https://doi.org/10.1016/j.scitotenv.2023.167118
Asgari, M., Yang, W., Lindsay, J., Shao, H., Liu, Y., De Queiroga Miranda, R., and Dehnavi, M. M. (2023). Development of a knowledge-sharing parallel computing approach for calibrating distributed watershed hydrologic models. Environmental Modelling & Software, 164, 105708. https://doi.org/10.1016/j.envsoft.2023.105708
Asgari, M., Yang, W., Lindsay, J., Tolson, B., and Dehnavi, M. M. (2022). A review of parallel computing applications in calibrating watershed hydrologic models. Environmental Modelling & Software, 151, 105370, https://doi.org/10.1016/j.envsoft.2022.105370
Dr. Eric Nost, Dr. Diana Lewis, Dr. Hui Shao, Dr. Yongbo Liu
Md Bodruddoza, Marjan Asgari, Mckenna Thompson, Jubril Bello, Akeem Bello, Hope Jesmer, Dr. Rodrigo Miranda, Dr. Jaison Thomas , Laura Hopkins
Environment and Climate Change Canada, Ontario Agri-Food Innovation Alliance - a collaboration between the Government of Ontario and the University of Guelph, Food and Agribusiness, OSCIA, ALUS Canada, Grand River, Upper Thames River and Lower Thames Valley conservation authorities, Agri-Food Data Canada
