Quantifying Flood Vulnerability Reduction via Private Precaution
- Private precaution is an important component in contemporary flood risk management and climate adaptation. However, quantitative knowledge about vulnerability reduction via private precautionary measures is scarce and their effects are hardly considered in loss modeling and risk assessments. However, this is a prerequisite to enable temporally dynamic flood damage and risk modeling, and thus the evaluation of risk management and adaptation strategies. To quantify the average reduction in vulnerability of residential buildings via private precaution empirical vulnerability data (n = 948) is used. Households with and without precautionary measures undertaken before the flood event are classified into treatment and nontreatment groups and matched. Postmatching regression is used to quantify the treatment effect. Additionally, we test state-of-the-art flood loss models regarding their capability to capture this difference in vulnerability. The estimated average treatment effect of implementing private precaution is between 11 and 15Private precaution is an important component in contemporary flood risk management and climate adaptation. However, quantitative knowledge about vulnerability reduction via private precautionary measures is scarce and their effects are hardly considered in loss modeling and risk assessments. However, this is a prerequisite to enable temporally dynamic flood damage and risk modeling, and thus the evaluation of risk management and adaptation strategies. To quantify the average reduction in vulnerability of residential buildings via private precaution empirical vulnerability data (n = 948) is used. Households with and without precautionary measures undertaken before the flood event are classified into treatment and nontreatment groups and matched. Postmatching regression is used to quantify the treatment effect. Additionally, we test state-of-the-art flood loss models regarding their capability to capture this difference in vulnerability. The estimated average treatment effect of implementing private precaution is between 11 and 15 thousand EUR per household, confirming the significant effectiveness of private precautionary measures in reducing flood vulnerability. From all tested flood loss models, the expert Bayesian network-based model BN-FLEMOps and the rule-based loss model FLEMOps perform best in capturing the difference in vulnerability due to private precaution. Thus, the use of such loss models is suggested for flood risk assessments to effectively support evaluations and decision making for adaptable flood risk management.…
Author details: | Nivedita SairamORCiD, Kai SchröterORCiDGND, Stefan LüdtkeORCiD, Bruno MerzORCiDGND, Heidi KreibichORCiDGND |
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DOI: | https://doi.org/10.1029/2018EF000994 |
ISSN: | 2328-4277 |
Title of parent work (English): | Earth future |
Publisher: | American Geophysical Union |
Place of publishing: | Washington |
Publication type: | Article |
Language: | English |
Date of first publication: | 2019/02/04 |
Publication year: | 2019 |
Release date: | 2021/03/23 |
Tag: | adaptation; average treatment effect; flood loss; loss models; matching methods; risk analysis |
Volume: | 7 |
Issue: | 3 |
Number of pages: | 15 |
First page: | 235 |
Last Page: | 249 |
Funding institution: | European UnionEuropean Union (EU) [676027]; reinsurance company Deutsche Ruckversicherung; German Research Network Natural Disasters (German Ministry of Education and Research (BMBF)) [01SFR9969/5]; MEDIS project (BMBF) [0330688]; project "Hochwasser 2013" (BMBF) [13N13017]; German Research Centre for Geosciences GFZ; University of Potsdam; Deutsche Ruckversicherung AG, Dusseldorf |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Umweltwissenschaften und Geographie |
DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer review: | Referiert |
Publishing method: | Open Access / Gold Open-Access |
DOAJ gelistet | |
License (German): | CC-BY-NC-ND - Namensnennung, nicht kommerziell, keine Bearbeitungen 4.0 International |