A comprehensive assessment model for livelihood vulnerability using fuzzy TOPSIS technique: A case of 2022 flood in Pakistan

Abstract

One of the most significant natural disasters that results in significant economic losses and human misery is flooding. Flooding can threaten people’s livelihoods because it damages homes, infrastructure, and other essential assets. This study’s objective is to evaluate the livelihood vulnerability (LHV) of those who have been relocated and displaced as a result of the recent flood in Pakistan’s Khyber Pakhtunkhwa (KP) province. The study was conducted in three districts of KP province, which are Charsadda, Nowshera, and Dera Ismail Khan (D.I. Khan). First, a comprehensive literature review was conducted to identify relevant criteria for LHV assessment. As a result, fourteen criteria were selected to measure LHV in the selected regions. Then, a group of experts was invited to prioritize the criteria and provide linguistic ratings for the alternatives in terms of the selected criteria. Finally, the fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) method was used to classify the targeted districts on the basis of their closeness coefficient (CC) values. To assess the robustness of the proposed model, a sensitivity analysis was also provided. The findings of the study revealed that communities residing in D.I. Khan district have the highest LHV compared to Charsadda and Nowshera districts. Besides, loss of harvested or stored crops, total workability, arable landholding, and medical and living expenditures were found to be the most dominant criteria for LHV evaluation. The study concluded that greater efforts are needed during the transition period to improve migrant workers’ employment skills and help them reestablish sustainable sources of income.