Economic Evaluation of Hurricane Flood Mitigation Strategies: Methodology Development and Case Study for New York City

Abstract

Flooding due to hurricane storm surge currently presents a large risk to New York City (NYC), and this risk is expected to grow in the future due to changes in climate and population growth. A number of strategies have been proposed to mitigate the impacts of flooding, and previous studies have attempted to quantify the economic risk to the city so that these strategies may be evaluated. This thesis improves on previous work by proposing a complete methodology that can fully integrate current and projected future hazard and vulnerability information to estimate the risk of losses due to hurricane storm surge and to evaluate flood mitigation strategies. The methodology is novel in two significant ways. First, a statistical analysis based on synthetic damage events is used to create a distribution of the loss that occurs at a storm arrival. To consider future changes in climate and building stock, a variety of methods is presented to manipulate this loss distribution. Second, Monte Carlo simulation is used as an alternative to analytical methods to obtain a simpler and more accurate model that is able to produce a full probability distribution. The complete methodology is demonstrated for New York City and is used to probabilistically evaluate the benefits and costs of several flood mitigation strategies using a full probability distribution, instead of just expected values per convention. Most of the contribution to the increased future risk is shown to come from sea level rise, followed by storm climatology change, with a small effect from building stock growth. Large-scale storm surge barriers are shown to be less economically attractive than building code measures that require residential structures to be elevated.