Volume 15 Issue 1
Feb.  2024
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Samavia Rasool, Irfan Ahmad Rana, Hassam Bin Waseem. Assessing Multidimensional Vulnerability of Rural Areas to Flooding: An Index-Based Approach[J]. International Journal of Disaster Risk Science, 2024, 15(1): 88-106. doi: 10.1007/s13753-024-00547-9
Citation: Samavia Rasool, Irfan Ahmad Rana, Hassam Bin Waseem. Assessing Multidimensional Vulnerability of Rural Areas to Flooding: An Index-Based Approach[J]. International Journal of Disaster Risk Science, 2024, 15(1): 88-106. doi: 10.1007/s13753-024-00547-9

Assessing Multidimensional Vulnerability of Rural Areas to Flooding: An Index-Based Approach

doi: 10.1007/s13753-024-00547-9
  • Accepted Date: 2024-02-06
  • Available Online: 2024-03-14
  • Publish Date: 2024-02-26
  • Vulnerability assessment is essential for understanding and launching effective flood risk reduction strategies. This study aimed to examine the vulnerability of flood-prone rural communities in southern Punjab, Pakistan to external shocks. The concept of vulnerability encompasses a range of dimensions, including physical, social, institutional, environmental, economic, and attitudinal. Using a composite index method, indices were developed for each dimension and combined to create a multidimensional measure of vulnerability. A sample of 365 communities was selected using the Yamane sampling technique, and data were collected through a questionnaire containing 65 indicators across all dimensions. Descriptive statistics and ANOVA tests were used to analyze the data. The results show that communities near the Chenab River had higher attitudinal and institutional vulnerability compared to other communities. High attitudinal vulnerabilities were associated with poorly perceived flood risks and low preparedness measures, whereas institutional vulnerabilities were driven by conventional flood protection strategies, lack of institutional trust, and lack of flood risk awareness. This research provides insights into the various components of vulnerability in flood-prone rural communities in Pakistan and demonstrates a useful methodology that can be applied to other disasters at different spatial scales.
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