dissertationControlling combined sewer overflows (CSOs) is one of the greatest urban drainage challenges in more than 700 communities in the United States. Traditional drainage design typically leads to centralized, costly and energy-intensive infrastructure solutions. Recently, however, application of decentralized techniques to reduce the costs and environmental impacts is gaining popularity. Rainwater harvesting (RWH) is a decentralized technique being used more often today, but its sustainability evaluation has been limited to a building scale, without considering hydrologic implications at the watershed scale. Therefore, the goal of this research is to study watershed-scale life cycle effects of RWH on controlling CSOs. To achieve this goal, (i) the life cycle costs (LCC) and long-term hydrologic performance are combined to evaluate the cost-effectiveness of control plans, (ii) the life cycle assessment (LCA) and hydrologic analysis were integrated into a framework to evaluate environmental sustainability of control plans, and (iii) the major sources of uncertainty in the integrated framework with relative impacts were identified and quantified, respectively. A case study of the City of Toledo, Ohio serves as the platform to investigate these approaches and to compare RWH with centralized infrastructure strategies. LCC evaluation shows that incorporating RWH into centralized control plans could noticeably improve the cost-effectiveness over the life cycle of drainage infrastructure. According to the results of the integrated framework, incorporating RWH could reduce Eco-toxicity Water (ETW) impacts, but caused an increase in the Global Warming Potential (GWP). In fact, incorporating RWH contributes to avoidance of untreated discharges into water bodies (thus reducing ETW) and additional combined sewage delivered to treatment facilities (thus increasing GWP). The uncertainty analysis suggests that rainfall data (as a hydrologic parameter) could be a significant source of the uncertainty in outputs of the integrated framework. Conversely, parameters of LCIA (life cycle impact assessment) could have trivial impacts on the outputs. This supports the need for robust hydrologic data and associated analyses to increase the reliability of LCA-based urban drainage design. In addition, results suggest that such an uncertainty analysis is capable of rendering optimal RWH system capacity as a function of annual rainfall depth to lead to minimized life cycle impacts. Capacities smaller than the optimal size would likely result in loss of RWH potable water savings and CSO control benefits, while capacities larger than optimal would probably incur excessive wastewater treatment burden and construction phase impacts
