Abstract

The demand for inexpensive and reliable warning systems has increased in recent years as a result of the increase in the number and severity of flood disasters. A new generation of low-cost sensors for flood monitoring and warning is being developed by the federal government and private sectors, in some cases collaboratively. We perform a benefit-cost analysis of this new product category, (i.e., low-cost flood inundation sensors), which can readily be deployed in a wireless or internet of things network. The use of these sensors can improve the coverage and lengthen the lead time of flood warning systems. The production costs of this new technology are only a fraction of those of existing sensors with similar capability and reliability, and operating costs are modest. Benefits depend on such factors as the ability to improve lead times of warnings to reduce property damage, deaths, and injuries from floods as well as the extent of adoption of the new sensors. Our analysis indicates a benefit–cost ratio of 1.4 to 1. However, our results are based on several assumptions. Hence, we have undertaken extensive sensitivity analyses to determine that our results are robust.

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Data Availability Statement

Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request including data on cost of sensors and response platform, including installation and operating and maintenance costs, from nine companies and full dataset and results of the uncertainty analysis and the sensitivity analysis.

Acknowledgments

This research was supported by the United States Department of Homeland Security through CREATE under Task order 70RSAT18FR0000175 of Basic ordering agreement HSHQDC-17-A-B004. The authors acknowledge the valuable input by Jeff Booth, David Alexander, Ian Helmuth, Jennifer Foley, Scott Farrow, and Ryan Guerrero. We also appreciate the research assistance of Konstantinos Papaefthymiou, Peter Eyre, and Shannon Prier. We further appreciate the help of CREATE staff members Jeffrey Countryman for handling contracting aspects of the project and Jen Sosenko for her help in editing and formatting the final report. Of course, any remaining errors and omissions are solely those of the authors. Moreover, the views expressed in this paper represent those of the authors and not necessarily those of any of the institutions with which they are affiliated nor the United States Department of Homeland Security that funded the research.

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Go to Natural Hazards Review
Natural Hazards Review
Volume 24Issue 1February 2023

History

Received: Feb 6, 2022
Accepted: Jul 12, 2022
Published online: Sep 30, 2022
Published in print: Feb 1, 2023
Discussion open until: Feb 28, 2023

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Adam Rose, M.ASCE [email protected]
Senior Research Fellow, Center for Risk and Economic Analysis of Threats and Emergencies, and Research Professor, Sol Price School of Public Policy, Univ. of Southern California, 650 Childs Way, RGL 230, Los Angeles, CA 90089. Email: [email protected]
Research Fellow, Center for Risk and Economic Analysis of Threats and Emergencies, and Research Associate Professor, Sol Price School of Public Policy, Univ. of Southern California, 3518 Trousdale Parkway Los Angeles, CPA 379C, Los Angeles, CA 90089 (corresponding author). Email: [email protected]
Research Associate, Center for Risk and Economic Analysis of Threats and Emergencies, Univ. of Southern California, 1150 S. Olive St., Suite 1700, Los Angeles, CA 90015. ORCID: https://orcid.org/0000-0003-2588-7296. Email: [email protected]
Kyle Spencer [email protected]
Chief Resilience Officer, City Manager’s Office of Resilience, City of Norfolk, Virginia, 810 Union St., Norfolk, VA 23510. Email: [email protected]

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  • Economic Value of Flood Forecasts and Early Warning Systems: A Review, Natural Hazards Review, 10.1061/NHREFO.NHENG-2094, 25, 4, (2024).

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