Improving the economic evaluation of flood risk management studies
type: CreativeWork
description: This thesis provides recommendations for improving the economic evaluation of flood risk management (FRM) studies. The most common types of FRM infrastructure in the United States (U.S.) are dams and levees. The FRM infrastructure in the U.S. is aging with a large number of dams and levees now more than 50 years old and in need of restoration and modification. Furthermore, many of these FRM structures are vulnerable to the impacts of the changing climate. The federal guidance for the economic evaluation of FRM studies is to use expected annual damages (or life loss) as the primary decision criterion. Reliance on the expected value can lead to poor FRM investment decisions because it conceals extremes by equating flood events of different magnitudes and probabilities of occurrence. Given the importance of life safety and environmental considerations, such as climate change, the expected value no longer appears to be the most important criteria for FRM. There is a need for an improved economic framework for evaluating the design of FRM infrastructure that can also capture extreme and catastrophic flood events in a changing environment. This thesis presents a risk-based optimization framework for FRM studies, based on the Conditional Value-at-Risk (CVaR), that provides a more meaningful and encompassing representation of the trade-offs at hand. An example application of optimizing a new levee design for flood risk reduction is performed, and of the three optimization strategies evaluated, the CVaR optimization approach prevented the most damage and life loss over the 100-year planning period. These findings have major implications for the design of FRM infrastructure and flood insurance programs. Optimizing to minimize CVaR can significantly reduce the number of catastrophic flood events experienced by the population at risk in the floodplain, and, in turn, reduce the amount of property damage, life loss, and flood insurance claims.
abstract: This thesis provides recommendations for improving the economic evaluation of flood risk management (FRM) studies. The most common types of FRM infrastructure in the United States (U.S.) are dams and levees. The FRM infrastructure in the U.S. is aging with a large number of dams and levees now more than 50 years old and in need of restoration and modification. Furthermore, many of these FRM structures are vulnerable to the impacts of the changing climate. The federal guidance for the economic evaluation of FRM studies is to use expected annual damages (or life loss) as the primary decision criterion. Reliance on the expected value can lead to poor FRM investment decisions because it conceals extremes by equating flood events of different magnitudes and probabilities of occurrence. Given the importance of life safety and environmental considerations, such as climate change, the expected value no longer appears to be the most important criteria for FRM. There is a need for an improved economic framework for evaluating the design of FRM infrastructure that can also capture extreme and catastrophic flood events in a changing environment. This thesis presents a risk-based optimization framework for FRM studies, based on the Conditional Value-at-Risk (CVaR), that provides a more meaningful and encompassing representation of the trade-offs at hand. An example application of optimizing a new levee design for flood risk reduction is performed, and of the three optimization strategies evaluated, the CVaR optimization approach prevented the most damage and life loss over the 100-year planning period. These findings have major implications for the design of FRM infrastructure and flood insurance programs. Optimizing to minimize CVaR can significantly reduce the number of catastrophic flood events experienced by the population at risk in the floodplain, and, in turn, reduce the amount of property damage, life loss, and flood insurance claims.
author: Smith, C. Haden
language: eng
language: English
keywords: conditional value-at-risk, flood risk, levee safety, optimization, risk analysis, risk-based design
identifier: T 9287
date published: 2022
date modified: 2026-07-24T01:42:11Z
provider: Colorado School of Mines
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Colorado School of Mines. Arthur Lakes Library

PropertyValue
property ID: Handle
value: https://hdl.handle.net/11124/15369