SIMULATION OF ECONOMIC FRAMEWORKS FOR AN URBAN STORMWATER PROGRAM USING AN AGENT-BASED MODELING PLATFORM

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2019

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The U.S. Environmental Protection Agency (EPA) considers urban stormwater runoff as the only major growing source of water pollution across many parts of the United States today. The need for investments in stormwater management infrastructure is significant and growing. Pressures to drive implementation of green stormwater infrastructure (GSI) on private properties is a significant factor in the overall need for investment. This allocation of resources requires the use of incentives to motivate private property owners to consider adopting GSI. The use of incentives demands an understanding of topics such as how parcel owners gain information on incentives programs, the value of GSI, and decisions based on adopting innovative technologies, such as GSI. This study presents a methodology for a generalized approach to simulate GSI adoption across a large urban area referred to as the Green Infrastructure Social-Spatial-Adoption (G-SSA) model. The G-SSA methodology incorporates decision-making dynamics, social and spatial influencing algorithms, economic and financial considerations, and diffusion of innovation considerations. A conceptual G-SSA model is developed and explored with model output reflecting expected and observed behavior related to temporal and spatial GSI adoption patterns. Model sensitivity analysis highlights the significance of social and spatial model elements to overall GSI adoption rates and pattern. An applied G-SSA model is developed and explored to simulate the complex emergent patterns for GSI adoption across a specific cityscape (Washington, DC). The applied G-SSA model output was consistent with expected model behavior as well as observed and document GSI adoption patterns in Washington, DC. In addition, model exploration suggests that investment in public outreach/engagement throughout the duration of the program is critical; those who adopt GSI prior to the start of market-based program implementation should be leveraged for early success in GSI adoption growth, highly-innovative areas should be leveraged to ensure success in GSI adoption in early phases of a program, and single-family residential properties in areas with depressed property values is critical to long-term GSI adoption rates due to reduced opportunity costs associated with GSI implementation.

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