Measuring household resilience to floods: A case study in the Vietnamese Mekong River Delta

By Kien V Nguyen, H. James. 2013

143 citations recorded by the source corpus.

The flood is a well-known phenomenon in the Vietnamese Mekong River Delta (MRD). Although people have experienced the impact of floods for years, some adapt well, but others are vulnerable to floods. Resilience to floods is a useful concept to study the capacity of rural households to cope with, adapt to, and benefit from floods. Knowledge of the resilience of households to floods can help disaster risk managers to design policies for living with floods. Most researchers attempt to define the concept of resilience; very little research operationalizes it in the real context of "living with floods". We employ a subjective well-being approach to measure households' resilience to floods. Items that related to households' capacity to cope with, adapt to, and benefit from floods were developed using both a five-point Likert scale and dichotomous responses. A factor analysis using a standardized form of data was employed to identify underlying factors that explain different properties of households' resilience to floods. Three properties of households' resilience to floods were found: (1) households' confidence in securing food, income, health, and evacuation during floods and recovery after floods; (2) households' confidence in securing their homes not being affected by a large flood event such as the 2000 flood; (3) households' interests in learning and practicing new flood-based farming practices that are fully adapted to floods for improving household income during the flood season. The findings assist in designing adaptive measures to cope with future flooding in the MRD.

Subfields: Ecology, Evolution, Behavior and Systematics, Sociology and Political Science, Soil Science

View Paper: https://www.semanticscholar.org/paper/ef4617e4f7f84701eee94ea4b34ecfb460f29672

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In Ecology, Evolution, Behavior and Systematics

  1. Christophe Béné
  2. T. Tanner
  3. Lindsey Jones

In Sociology and Political Science

  1. Lindsey Jones
  2. T. Tanner
  3. Christophe Béné

In Soil Science

  1. Lindsey Jones
  2. T. Tanner
  3. Christophe Béné

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