MANAGING STORMWATER RUNOFF WITH GREEN INFRASTRUCTURE: EXPLORING PRACTICAL STRATEGIES TO OVERCOME BARRIERS IN CITYWIDE IMPLEMENTATION

Cities in the United States are facing the challenges of protecting water resources, drinking water and public health with a rapid pace of population growth and urban sprawl. Large quantities of stormwater runoff arising from increased imperviousness on urbanizing watershed will cause municipal sewer system overflow and discharge of untreated runoff into waterways, and as a result, pollute local water bodies and affect the quality of drinking water in the long run. It has been increasingly acknowledged that Green Infrastructure (GI) and Low Impact Development (LID) can be used as an effective tool to capture and retain stormwater on site before it enters the sewer system. Many cities have started taking measures to encourage the use of GI and LID in new development and redevelopment of public and private projects. However, the process is very slow and only few cities have adopted green stormwater management approaches at a significant scale due to barriers hindering the wide implementation of GI/LID practices. Identification of the barriers encountered by municipalities in implementation of GI/LID practices and possible strategies to overcome them is one of the first steps to scale up the use of GI/LID in stormwater management. The intent of the research in this thesis is to identify the barriers and create strategies by conducting a systematic review and analysis of a variety of previous studies in the green stormwater management field. The research reveals 10 barrier types under four categories: institutional, technical, financial, and managerial, and at least 46 strategies to overcome those barriers. Based upon the barrier typology and the list of strategies, stormwater management plans and other published government documents of seven American cities were evaluated to determine whether those strategies have been adopted by each municipality in their respective stormwater management programs. Advisor: Zhenghong Tang