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Optimizing Urban Infrastructure Resilience Under Precipitation and Population Growth Uncertainties

Masoud Barah
ISE PhD Candidate
University of Tennessee
Friday, November 17, 2017   2:30-3:30pm
JDT 410



In recent years, increased urbanization, infrastructure degradation, and climate change have overwhelmed most stormwater management systems across the nation or rendered them ineffective. Green Infrastructure (GI) are low cost, low regret strategies that can dramatically contribute to stormwater management. We develop mathematical models to determine the optimal placement of GIs across a set of candidate locations in a watershed to minimize the excess runoff under short-term and medium-term precipitation uncertainties. We calibrate the models using precipitation projections as well as the stormwater system’s hydrologic responses to these projections. We obtain the optimal GI placement for an urban watershed in a mid-sized city in the U.S. and perform sensitivity analyses to provide insights. In addition, we develop another mathematical model to optimally place GI when (re-) designing an urban area, subject to uncertainties in both population growth and future precipitation. Specifically, we develop a stochastic programming model for a mid-term planning horizon to determine the location, area and type of GI practices in a given urban area under various considerations such as land use, budget, and ‘connectivity’ between GI practices to maximize their benefit.


Masoud Barah is a Ph.D. candidate in Industrial and Systems Engineering at the University of Tennessee-Knoxville. His dissertation is on the application of operations research in environmental engineering, with an emphasis on improving urban infrastructure resilience under uncertainty. His methodological interests include data analysis, graph theory, integer programming, and stochastic programming.

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