Management of urban stormwater is becoming increasingly difficult due to an anticipated increase in precipitation and extreme storm events that are expected under climate change. The goal of this research is to develop an approach that effectively accounts for the uncertain conditions that may occur under climate change and to develop best management practices to manage stormwater in urban areas. This presentation focuses on management of stormwater and combined sewage in Worcester, MA, where approximately four square miles of the downtown area is serviced by a combined sewer system. The EPA Stormwater Management Model was used to determine the impacts of storms on the urban environment for future conditions. This model was used to simulate discharges of selected design storms associated with a range of climate change scenarios. Various design storms were simulated in SWMM for 2010, 2040, and 2070 under high, moderate, and low climate change scenarios. Alternative best management practices were assessed in terms of specific metrics that included flood volumes and combined sewer overflow volumes through the Worcester sewer system. Cost evaluations were used to identify appropriate best management strategies for managing the combined sewer system under future scenarios. A design cost approach and net benefits approach were used to analyze different options for managing stormwater under climate change. Both of these approaches utilize the concept of risk analyze to determine expected values of both costs and benefits for different options under different climate change scenarios. Results for the design cost approach indicate that providing upstream underground storage in select locations throughout the Worcester combined sewer system is the most cost-effective strategy. In addition, increased pumping capacity at the Quinsigamond Avenue Combined Sewer Overflow Storage and Treatment Facility (QCSOSTF) should be included for this option. However, it was determined that only select upstream storage is the most beneficial option under the net benefits approach as increased pumping capacity at the QCSOSTF was determined to be too costly due to the additional costs of CSO treatment required at the facility. The Worcester case study provides an ideal context for assessing the relative advantages of full treatment at the wastewater treatment facility, limited treatment at a centralized CSO treatment facility, decentralized storage options, and low impact stormwater controls. It also allows for an assessment of decision making methods for controlling flows and loads from the Worcester system. Comparisons between Worcester and other case studies provide a foundation for understanding how stormwater and combined sewer systems can be managed given climate change uncertainty.

Despite the runoff reduction efficiencies recommended by various regulatory agencies, minimal research exists regarding the ability of vegetated swales to simultaneously convey and reduce runoff. This study assessed the effect water quality swales distributed among upstream sub-watersheds had on watershed hydrology. The study was also posed to determine how certain design parameters can be dimensioned to increase runoff reduction according to the following modeling scenarios: base, base check dam height, minimum check dam height, maximum check dam height, minimum infiltration rate, maximum infiltration rate, minimum Manning's n, maximum Manning's n, minimum longitudinal slope, and maximum longitudinal slope. Peak flow rate, volume, and time to peak for each scenario were compared to the watershed's existing and predevelopment conditions. With respect to the existing condition, peak flow rate and volume decreased for all scenarios, and the time to peak decreased for most scenarios; the counterintuitive nature of this result was attributed to software error. Overall, the sensitivity analysis produced results contrary to the hypotheses in most cases. The cause of this result can likely be attributed to the vegetated swale design and modeling approaches producing an over designed, under constrained, and/or over discretized stormwater management practice. / Master of Science

Cities worldwide are facing problems to mitigate the impact of urban stormwater runoff caused by the increasing occurrence of heavy rainfall events and urban re-densification. This study presents a new approach for estimating the potential of the Management of Urban STormwater at Block-level (MUST-B) by decentralized blue-green infrastructures here called low-impact developments (LIDs) for already existing urban environments. The MUST-B method was applied to a study area in the northern part of the City of Leipzig, Germany. The Study areas was divided into blocks smallest functional units and considering two different soil permeability and three different rainfall events, seven scenarios have been developed: current situation, surface infiltration, swale infiltration, trench infiltration, trough-trench infiltration, and three different combinations of extensive roof greening, trough-trench infiltration, and shaft infiltration. The LIDs have been simulated and their maximum retention/infiltration potential and the required area have been estimated together with a cost calculation. The results showed that even stormwater of a 100 year rainfall event can be fully retained and infiltrated within the blocks on a soil with low permeability (kf = 10−6 m/s). The cost and the required area for the LIDs differed depending on the scenario and responded to the soil permeability and rainfall events. It is shown that the MUST-B method allows a simple down- and up-scaling process for different urban settings and facilitates decision making for implementing decentralized blue-green-infrastructure that retain, store, and infiltrate stormwater at block level.

Urban stormwater runoff is both an environmental threat and a valuable water resource. This dissertation explores the use of two stormwater management strategies, namely green stormwater infrastructure and stormwater real-time control (RTC), for capturing and treating urban stormwater runoff. Chapter 2 focuses on clean bed filtration theory and its application to fecal indicator bacteria removal in experimental laboratory-scale biofilters. This analysis is a significant step forward in our understanding of how physicochemical theories can be melded with hydrology, engineering design, and ecology to improve the water quality benefits of green infrastructure. Chapter 3 focuses on the novel application of unsteady transit time distribution (TTD) theory to solute transport in a field-scale biofilter. TTD theory closely reproduces experimental bromide breakthrough concentrations, provided that lateral exchange with the surrounding soil is accounted for. TTD theory also provides insight into how changing distributions of water age in biofilter storage and outflow affect key stormwater management endpoints, such as biofilter pollutant treatment credit. Chapter 4 focuses on stormwater RTC and its potential for improving runoff capture and water supply in areas with Mediterranean climates. We find that the addition of RTC increases the percent of runoff captured, but does not increase the percent of water demand satisfied. Our results suggest that stormwater RTC systems need to be implemented in conjunction with context-specific solutions (such as spreading basins for groundwater recharge) to reliably augment urban water supply in areas with uneven precipitation. Through a combination of modeling and experimental studies at a range of scales, this dissertation lays the foundation for future integration of TTD theory with RTC to improve regional stormwater management. / Doctor of Philosophy / Urban stormwater runoff contains a variety of pollutants. Conventional storm drain systems are designed to move stormwater as quickly as possible away from cities, delivering polluted runoff to local streams, rivers, and the coastal ocean – and discarding a valuable freshwater resource. By contrast, green stormwater infrastructure captures and retains stormwater as close as possible to where the rain falls. Green stormwater infrastructure can also help remove pollutants from stormwater through physical, chemical, and biological treatment processes. This dissertation describes two modeling approaches for understanding and predicting pollutant removal processes in green stormwater infrastructure (Chapters 2 and 3). Chapter 4 explores the implementation of smart stormwater systems, which use automated controllers and sensors to adaptively address stormwater management challenges. Through a combination of modeling and experimental studies at a range of scales, this dissertation lays the foundation for future improvements to regional stormwater management.