Optimizing Green Infrastructure Investment to Improve Urban Storm Water System Resilience under Environmental Uncertainty

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This research will develop an approach to optimize investment decisions to improve urban storm water system resilience to forecasted extreme weather events. Many cities already struggle with storm water pipes that are in poor condition and are undersized relative to changing weather patterns. Green infrastructure is recommended as a "low regret" strategy to reduce flooding while also providing co-benefits to freshwater provision, ecological processes, and freshwater fish populations. The question remains, however, as to how to allocate investments under environmental uncertainty. This research will formulate approaches that allow decision-makers to evaluate trade-offs in storm water infrastructure investment. The research team aims to increase gender and ethnic diversity in STEM by collaborating with various campus-wide student chapters of minority organizations, such as the Tennessee Louis Stokes Alliance for Minority Participation, to recruit underrepresented students to pursue degrees in engineering. Although more frequent and intense weather events are projected for many locations, the exact timing and effects of such events are uncertain. This research will provide a scientifically informed approach to evaluate the consequences of making infrastructure planning decisions under this uncertainty, and showcases the power of this approach to obtain and evaluate optimal green infrastructure placement. Here, the team will: (1) develop a novel framework that can incorporate predictions from a variety of weather prediction models, (2) use a semi-distributed, well calibrated, hydrologic model to evaluate the response of a storm water system to these scenarios by identifying the vulnerability of the system to flooding, (3) adopt sophisticated mathematical methodologies, including stochastic programming and robust optimization, to account for the uncertainties in weather patterns over a long planning horizon, and (4) optimize green infrastructure placement within the storm water system to maximize flood resiliency under climate uncertainties, subject to various economic, physical, and social constraints.