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A practical 4-stage-3-model framework is introduced that models and maps pollutant concentrations in, and potential hazards of, municipal stormwater point-source releases to surface water bodies. The framework consists of a stormwater model, a stormwater quality model, geographic information systems (GIS) mapping models, and a hazard assessment procedure based on event mean concentrations (EMC) and fuzzy logic. This framework was applied to project both outfall concentrations and environmental hazards of a degradable point-source pollutant, monochloramine, in stormwater effluents released to the North Saskatchewan River, Alberta, Canada, under different weather conditions. Monochloramine loads were over the permissible limits under dry weather flows throughout the basin, and only a design storm of a 10-year return period produced monochloramine concentrations below regulation discharge limits. An EMC-based hazard map was developed that revealed 25% of the study area to lie within the moderate to high-risk zones. EMC-based hazards were driven primarily by proximity to the system outlet, total pollutant mass and system layout. Next, a generalized, fuzzy-based monochloramine hazard map was developed, using monochloramine decay-inducing factors such as annual rainfall, land-use type, EMC values, ground slope, decay rates, property assessment values, drainage system proximity and density of impervious areas. This map showed 54% of the basin at moderate to high risk. The maps developed using the proposed 4-stage-3-model framework can help system operators to improve management of stormwater pollutants without time- and labor-intensive, case-by-case calculations and to focus mitigation measures on releases from specific “hot spot” locations in the system. The framework can be generalized to other chemical substances that impair stormwater quality through either point or non-point source pollution.

This paper introduces a comprehensive modeling framework for Integrated Water Resources Management (IWRM). The model incorporates water demands, allocation, and uses under various climate, population, and economic scenarios as well as management strategies. Model outputs include crop yields, municipal water use, power generation, recreational reservoir uses, and environmental flows. Further, a novel indicator integrates many key model outputs for social, economic, and environmental assessment based on the basin-scale water balance, and provides a comprehensive and clear representation of basin conditions to improve the understanding of IWRM trade-offs. When applied to the Bow River Basin, Canada, as a practical example, this Bow River Integrated Model (BRIM) revealed through a set of modeling scenarios that (1) only the industrial demands exceeded the water license in the high-water demand and reference scenarios due to population growth and economic development; (2) increased cooling tower shares for thermal power plants was the most effective policy in managing industrial demand; and (3) the new indicator reflected both basin-scale conditions and sectoral water stresses. Finally, model results from three gaming scenarios showed socio-economic and environmental trade-offs clearly, providing users with guidance in developing a comprehensive view of basin-scale water security, and hands-on experience to support IWRM. Therefore, the modeling framework and novel indicator can improve an understanding of IWRM concepts and strategic trade-offs in efforts towards basin water sustainability.