Quantifying Flood Vulnerability Reduction via Private Precaution

Abstract

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 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.

Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes

“…However, the implemented measures did not completely prevent losses during extreme fluvial floods (Table 1: Median water depth for all the events was more than 1.5 m). Since most of the property-level flood barriers were overtopped during these events (Hudson et al, 2014;Sairam et al, 2019), the implemented measures could mostly reduce the…”

Reply to Anonymous Referee #2

“…Printer-friendly version Discussion paper synthetic models rely on a description of flood damage mechanisms (Gerl et al, 2016). Some empirical flood damage models include precautionary measures as explanatory variables (see for example Kreibich et al (2017)) and can be used to estimate their mean efficacy (Sairam et al, 2019). They account for the mean effect of all measures in the sample used to produce them on flood damage.…”

Needed: A systems approach to improve flood risk mitigation through private precautionary measures

“…Studies have shown that private precaution can reduce loss [37,26,53,56], but implementation/uptake levels are often low and usually only rise following a flood event [36,18,32,50]. Knowledge about private precautionary measures and how to incorporate them into a flood risk management plan is scarce [38].…”