Identifying the drivers of private flood precautionary measures in Ho Chi Minh City, Vietnam

Author:

Vishwanath Harish ThulasiORCID,Sairam NiveditaORCID,Yang Liang Emlyn,Garschagen Matthias,Kreibich HeidiORCID

Abstract

Abstract. Private flood precautionary measures have proven to reduce flood damage effectively. Integration of these measures into flood response systems can improve flood risk management in high-risk areas such as Ho Chi Minh City (HCMC). Since uptake of such measures is voluntary, it is important to know what drives householders to implement precautionary measures. In this study, we developed a framework representing the uptake of private precautionary measures based on protection motivation theory and the transtheoretical model. Using empirical survey data collected from 1000 flood-prone households in HCMC, we implemented lasso and elastic-net regression to identify the drivers of private precaution. The measures were classified into structural measures and non-structural measures based on whether structural changes to the building were required. The households were classified into proactive and reactive households based on whether their decision to reduce risk (i.e. uptake of precautionary measures) was preceded by experiencing a flood. The data-driven model revealed that the household's level of education, the degree of belief in the government to implement regional flood protection measures and the degree of belief that in case of flooding one has to deal with the consequences of flooding by themselves positively influence the proactive uptake of non-structural measures. Among the households that experienced flooding before implementing the measures, the uptake was found to be driven by the severity of the experienced damage. For the same group of households, perceiving a high severity of future flood impacts was found to negatively influence the uptake of structural flood precautionary measures. These results highlight that efforts to improve the implementation of private precautionary measures should consider the socio-economic characteristics of the members of the household, their past flood experience and their perception of flood risk management for communicating flood risk and incentivizing private precautionary measures.

Funder

Berlin Center for Machine Learning

Publisher

Copernicus GmbH

Subject

General Earth and Planetary Sciences

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