Urban stormwater quality control analysis

Stormwater from urbanized and urbanizing areas continues to be one of the major sources of pollution loading to surface water bodies. As conventional point sources come under control, the significance of nonpoint source pollution from stormwater and its control cost demand that stormwater management systems be planned and engineered within a quantitative framework to effect higher levels of quality control. To meet such a challenge, analytical probabilistic models have been developed for urban stormwater management planning based on concepts from statistics and probability theory. The objectives of this thesis are to develop analytical models for urban runoff quality assessment, performance models for runoff quality control systems and planning-level optimization methodologies for designing runoff control systems. Other contributions include characterization of urban runoff quality which is based on evaluating the general statistical characteristics of runoff pollutant concentrations from separated and combined sewer catchments. Emphasis is placed on the determination of complete probability distributions of pollutant concentrations.; Using a runoff coefficient based rainfall-runoff transformation and empirical pollutant buildup-washoff processes, analytical models are derived from probabilistic characteristics of long-term meteorologic records to estimate pollutant washoff loads and concentrations. The models are verified with available field data and a reasonable agreement is obtained between model results and observed data. Practical applications of the model are provided for runoff quality analysis and for regulatory purposes. Utilizing the developed probabilistic representations of pollutant concentrations, performance models are derived to assess the behaviour of quality control systems. Results from these models are compared to those from previous performance models which are based on a uniform concentration approach. Optimization methodologies are developed for designing stormwater management ponds to control both runoff quantity and quality in single catchment and multiple catchment scenarios. In the single catchment scenarios, the optimization procedure determines the least-cost values of system design parameters for specified levels of quantity and quality control. In multiple catchment systems, a dynamic programming procedure is used to determine least-cost values of the multiple pond system design, which is subjected to system performance constraints of specified levels of runoff quantity and quality control at a common discharge point. The proposed analytical models and methodologies, which are more computationally efficient than conventional numerical simulation models, contribute to the literature on addressing stormwater quality issues and the integration of urban runoff quality and quantity management.