Flood Risk Reduction System Optimization: Application to the Galveston Bay Area

Erik van Berchum, William Mobley

Research output: Book/ReportReportProfessional

Abstract

The Galveston Bay Area is a densely populated area which is highly prone to flooding. In 2008, Hurricane Ike hit with a combination of storm surge, wind and rain. This led to an estimated 25 billion dollars in damage and nearly a hundred deaths. As a response to Hurricane Ike, several institutions have explored strategies that would protect the region from coastal flooding. Because of the complex situation, discussions on the issue have not yet led to clear or definitive conclusions. Few flood risk reduction strategies have been comprehensively assessed with impact analyses and cost estimates. More measures have been proposed, but their effectiveness cannot be evaluated without a costly investigation. In these analyses, it is often concluded that no single flood risk reduction measure can solve the bay-wide problems on its own. This would mean that research is needed on how flood risk reduction measures act in combination with each other. Moreover, non-structural measures (e.g. Nature-based Solutions, policy measures like land use zones) are increasingly implemented. The design process and discussions would greatly benefit from an increased understanding of the effects of all the proposed flood risk reduction strategies in terms of aspects such as risk reduction, costs and environmental impacts. This report will show and explain the development of a risk-based optimization model, aimed especially to fill that knowledge gap. The goal is to provide more insight in the Galveston Bay Area and the effects of design choices on the flood risk management system.
Original languageEnglish
PublisherDelft University of Technology
Number of pages68
Publication statusPublished - 20 Sep 2017

Keywords

  • Flood risk reduction
  • Flood protection
  • system optimization
  • flood risk modelling

Fingerprint Dive into the research topics of 'Flood Risk Reduction System Optimization: Application to the Galveston Bay Area'. Together they form a unique fingerprint.

  • Cite this