An agent-based model for evaluating reforms of the National Flood Insurance Program: A benchmarked model applied to Jamaica Bay, NYC

Lars Tjitze de Ruig; Toon Haer; Hans de Moel; Philip Orton; W. J.Wouter Botzen; Jeroen C.J.H. Aerts

doi:10.1111/risa.13905

An agent-based model for evaluating reforms of the National Flood Insurance Program: A benchmarked model applied to Jamaica Bay, NYC

Lars Tjitze de Ruig^*, Toon Haer, Hans de Moel, Philip Orton, W. J.Wouter Botzen, Jeroen C.J.H. Aerts

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Coastal flood risk is expected to increase as a result of climate change effects, such as sea level rise, and socioeconomic growth. To support policymakers in making adaptation decisions, accurate flood risk assessments that account for the influence of complex adaptation processes on the developments of risks are essential. In this study, we integrate the dynamic adaptive behavior of homeowners within a flood risk modeling framework. Focusing on building-level adaptation and flood insurance, the agent-based model (DYNAMO) is benchmarked with empirical data for New York City, USA. The model simulates the National Flood Insurance Program (NFIP) and frequently proposed reforms to evaluate their effectiveness. The model is applied to a case study of Jamaica Bay, NY. Our results indicate that risk-based premiums can improve insurance penetration rates and the affordability of insurance compared to the baseline NFIP market structure. While a premium discount for disaster risk reduction incentivizes more homeowners to invest in dry-floodproofing measures, it does not significantly improve affordability. A low interest rate loan for financing risk-mitigation investments improves the uptake and affordability of dry-floodproofing measures. The benchmark and sensitivity analyses demonstrate how the behavioral component of our model matches empirical data and provides insights into the underlying theories and choices that autonomous agents make.

Original language	English
Pages (from-to)	405-422
Number of pages	18
Journal	Risk Analysis
Volume	43
Issue number	2
Early online date	18 Apr 2022
DOIs	https://doi.org/10.1111/risa.13905
Publication status	Published - Feb 2023

Bibliographical note

Funding Information:
The authors would like to thank Fanglin Zhang from the Stevens Institute of Technology and Anaïs Couasnon from the Institute of Environmental Studies for supplying and processing the inundation data. In addition, we would like to thank Marilyn Montgomery from the Wharton School Risk Management and Decision Processes center for sharing data. We thank the Netherlands Organization for Scientific Research (NWO; VIDI Grant 452.14.005, VICI Grant 453.13.006) for supporting this research. P.M. Orton was funded by a United States National Science Foundation Integrative and Collaborative Education and Research (ICER) Coasts and People (CoPe) award (1940273). Thanks also for Adapt2flood project support by Wolfs company.

Funding Information:
The authors would like to thank Fanglin Zhang from the Stevens Institute of Technology and Anaïs Couasnon from the Institute of Environmental Studies for supplying and processing the inundation data. In addition, we would like to thank Marilyn Montgomery from the Wharton School Risk Management and Decision Processes center for sharing data. We thank the Netherlands Organization for Scientific Research (NWO; VIDI Grant 452.14.005, VICI Grant 453.13.006) for supporting this research. P.M. Orton was funded by a United States National Science Foundation Integrative and Collaborative Education and Research (ICER) Coasts and People (CoPe) award (1940273). Thanks also for Adapt2flood project support by Wolfs company.

Publisher Copyright:
© 2022 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.

Funding

The authors would like to thank Fanglin Zhang from the Stevens Institute of Technology and Anaïs Couasnon from the Institute of Environmental Studies for supplying and processing the inundation data. In addition, we would like to thank Marilyn Montgomery from the Wharton School Risk Management and Decision Processes center for sharing data. We thank the Netherlands Organization for Scientific Research (NWO; VIDI Grant 452.14.005, VICI Grant 453.13.006) for supporting this research. P.M. Orton was funded by a United States National Science Foundation Integrative and Collaborative Education and Research (ICER) Coasts and People (CoPe) award (1940273). Thanks also for Adapt2flood project support by Wolfs company.

Keywords

affordability
agent-based model
disaster risk reduction
dynamic adaptive behavior
flood insurance

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1111/risa.13905Licence: CC BY

Risk Analysis - 2022 - RuigFinal published version, 1.82 MBLicence: CC BY

Cite this

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title = "An agent-based model for evaluating reforms of the National Flood Insurance Program: A benchmarked model applied to Jamaica Bay, NYC",

abstract = "Coastal flood risk is expected to increase as a result of climate change effects, such as sea level rise, and socioeconomic growth. To support policymakers in making adaptation decisions, accurate flood risk assessments that account for the influence of complex adaptation processes on the developments of risks are essential. In this study, we integrate the dynamic adaptive behavior of homeowners within a flood risk modeling framework. Focusing on building-level adaptation and flood insurance, the agent-based model (DYNAMO) is benchmarked with empirical data for New York City, USA. The model simulates the National Flood Insurance Program (NFIP) and frequently proposed reforms to evaluate their effectiveness. The model is applied to a case study of Jamaica Bay, NY. Our results indicate that risk-based premiums can improve insurance penetration rates and the affordability of insurance compared to the baseline NFIP market structure. While a premium discount for disaster risk reduction incentivizes more homeowners to invest in dry-floodproofing measures, it does not significantly improve affordability. A low interest rate loan for financing risk-mitigation investments improves the uptake and affordability of dry-floodproofing measures. The benchmark and sensitivity analyses demonstrate how the behavioral component of our model matches empirical data and provides insights into the underlying theories and choices that autonomous agents make.",

keywords = "affordability, agent-based model, disaster risk reduction, dynamic adaptive behavior, flood insurance",

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note = "Funding Information: The authors would like to thank Fanglin Zhang from the Stevens Institute of Technology and Ana{\"i}s Couasnon from the Institute of Environmental Studies for supplying and processing the inundation data. In addition, we would like to thank Marilyn Montgomery from the Wharton School Risk Management and Decision Processes center for sharing data. We thank the Netherlands Organization for Scientific Research (NWO; VIDI Grant 452.14.005, VICI Grant 453.13.006) for supporting this research. P.M. Orton was funded by a United States National Science Foundation Integrative and Collaborative Education and Research (ICER) Coasts and People (CoPe) award (1940273). Thanks also for Adapt2flood project support by Wolfs company. Funding Information: The authors would like to thank Fanglin Zhang from the Stevens Institute of Technology and Ana{\"i}s Couasnon from the Institute of Environmental Studies for supplying and processing the inundation data. In addition, we would like to thank Marilyn Montgomery from the Wharton School Risk Management and Decision Processes center for sharing data. We thank the Netherlands Organization for Scientific Research (NWO; VIDI Grant 452.14.005, VICI Grant 453.13.006) for supporting this research. P.M. Orton was funded by a United States National Science Foundation Integrative and Collaborative Education and Research (ICER) Coasts and People (CoPe) award (1940273). Thanks also for Adapt2flood project support by Wolfs company. Publisher Copyright: {\textcopyright} 2022 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.",

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AU - Orton, Philip

AU - Botzen, W. J.Wouter

AU - Aerts, Jeroen C.J.H.

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N2 - Coastal flood risk is expected to increase as a result of climate change effects, such as sea level rise, and socioeconomic growth. To support policymakers in making adaptation decisions, accurate flood risk assessments that account for the influence of complex adaptation processes on the developments of risks are essential. In this study, we integrate the dynamic adaptive behavior of homeowners within a flood risk modeling framework. Focusing on building-level adaptation and flood insurance, the agent-based model (DYNAMO) is benchmarked with empirical data for New York City, USA. The model simulates the National Flood Insurance Program (NFIP) and frequently proposed reforms to evaluate their effectiveness. The model is applied to a case study of Jamaica Bay, NY. Our results indicate that risk-based premiums can improve insurance penetration rates and the affordability of insurance compared to the baseline NFIP market structure. While a premium discount for disaster risk reduction incentivizes more homeowners to invest in dry-floodproofing measures, it does not significantly improve affordability. A low interest rate loan for financing risk-mitigation investments improves the uptake and affordability of dry-floodproofing measures. The benchmark and sensitivity analyses demonstrate how the behavioral component of our model matches empirical data and provides insights into the underlying theories and choices that autonomous agents make.

AB - Coastal flood risk is expected to increase as a result of climate change effects, such as sea level rise, and socioeconomic growth. To support policymakers in making adaptation decisions, accurate flood risk assessments that account for the influence of complex adaptation processes on the developments of risks are essential. In this study, we integrate the dynamic adaptive behavior of homeowners within a flood risk modeling framework. Focusing on building-level adaptation and flood insurance, the agent-based model (DYNAMO) is benchmarked with empirical data for New York City, USA. The model simulates the National Flood Insurance Program (NFIP) and frequently proposed reforms to evaluate their effectiveness. The model is applied to a case study of Jamaica Bay, NY. Our results indicate that risk-based premiums can improve insurance penetration rates and the affordability of insurance compared to the baseline NFIP market structure. While a premium discount for disaster risk reduction incentivizes more homeowners to invest in dry-floodproofing measures, it does not significantly improve affordability. A low interest rate loan for financing risk-mitigation investments improves the uptake and affordability of dry-floodproofing measures. The benchmark and sensitivity analyses demonstrate how the behavioral component of our model matches empirical data and provides insights into the underlying theories and choices that autonomous agents make.

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An agent-based model for evaluating reforms of the National Flood Insurance Program: A benchmarked model applied to Jamaica Bay, NYC

Abstract

Bibliographical note

Funding

Keywords

UN SDGs

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