Stormwater reuse for irrigating public lands is proposed to reduce pressures on water supplies over a long-term horizon for the City of Calgary. To investigate the quality of stormwater reused for irrigation, routine water quality monitoring was conducted in the Inverness Stormwater Pond and irrigation intake. The results indicate that stormwater in general satisfies recreational and irrigation water quality guidelines. Correlation and regression analysis between water quality parameters, such as total suspended solids (TSS) and microorganisms, and climatological variables clearly showed the potential influence of climatological conditions on stormwater quality. In particular, rain events were identified to contribute to elevated microorganism concentrations. In addition to routine weekly monitoring, 24-hour water quality monitoring was carried out to investigate the influence of thermal stratification on water quality on a diurnal time scale in the pond. It was found that diurnal rhythms of microorganisms, namely high concentrations during the day and low and constant concentrations during the night, appeared to be associated with diurnal thermal stratification.

To characterize site-specific stormwater runoff quality, discrete and continuous water quality monitoring was performed at the end of a stormwater drain leading to the pond. Stormwater runoff quality was studied in terms of Event Mean Concentration (EMC) or Event Mean Value (EMV), pollutant loading, and first flush (FF) effects, and their relationships with rainfall characteristics. Correlations between stormwater runoff characteristics and some rainfall characteristics, which suggest the potential influence of rainfall on stormwater runoff quality, were identified. The dependence on the flow magnitude of suspended solids transport in stormwater runoff was displayed;​ whereas the discharge of microorganisms and dissolved solids appears not to rely on the erosive power of the flow. Significant FF effects for TSS and microorganisms were not observed;​ while strong FF effects for conductivity were demonstrated. In addition, artificial neural networks (ANNs) using partial mutual information (PMI) based input selection successfully simulated stormwater runoff physicochemical quality (observed in continuous monitoring).

To estimate climate change impacts on water quality, both relationships based on historical data, referred to as the "past relationship" approach, and ANN s were employed. Future climatic scenarios were generated by downscaling changes in climatological variables from a General Circulation Model (GCM). In general, the projected future climate scenarios would produce higher EMV s of turbidity/TSS than current climate conditions;​ while they do not yield more significant FF effects in TSS. Moreover, results also demonstrated that climate change would cause increases in microorganism concentrations in both stormwater runoff and stormwater.

Results show that stormwater is in general applicable for irrigation under current climate conditions. However, a changing climate will likely deteriorate both pond quality and stormwater runoff quality (in particular microbiological quality). This result suggests a higher risk to public health in future climate conditions. In addition to the potential climate change impacts on stormwater quality, the diurnal characteristics of stormwater quality also should be considered in developing stormwater management strategies. In addition, the absence of significant FF effects for TSS and microorganisms under both current and future climate conditions throws doubt on adopting FF concepts in designing robust stormwater treatment facilities. l