4.6 Article

Extension of FEMA and SMUG models with Bayesian best-worst method for disaster risk reduction

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ELSEVIER
DOI: 10.1016/j.ijdrr.2021.102631

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FEMA; SMUG; Bayesian best-worst method; Hazard prioritization; Disaster risk reduction

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This study conducted a comprehensive disaster hazard analysis for Tunceli province using the FEMA and SMUG models extended under the Bayesian Best-Worst Method, identifying earthquake as the top priority hazard. The results indicated that flood, mass movement, terrorism, and epidemics are also high-priority hazards to be considered for disaster risk reduction measures in the region.
Turkey is one of the countries that face many natural and man-made disasters. The entire geography of Turkey is affected by these disasters and the secondary disasters resulting from them. Tunceli is located in the Eastern Anatolia Region of Turkey and is a disaster-prone region. Therefore, it is important to carry out an adaptable hazard analysis for the region and support the national disaster risk reduction struggle. In this study, a comprehensive disaster hazard analysis was conducted for Tunceli province, and potential mitigation measures were discussed. As methodological background, FEMA (Federal Emergency Management Agency) and SMUG (Seriousness Manageability Urgency Growth) models, which are well-known methods, were extended under the Bayesian Best-Worst Method (BWM). Bayesian BWM is a pairwise comparison-based multi-criteria decisionmaking method that takes a probabilistic view of the experts' group decision without losing information, providing less pairwise comparison and higher consistency. Nine different disaster hazards for the Tunceli region are prioritized by the proposed approach. Initially, weights of the risk parameters in FEMA and SMUG and the priority values of disaster hazards based on each parameter were calculated. Then, ranking orders were determined. In addition, more precise evaluations were made for the results obtained with the credal ranking graphs. Some comparative studies were also included in the study to test the solidity of the approach. According to the results, both models showed that the top priority hazard for Tunceli is earthquake. Also, flood, mass movement, terrorism, and epidemics are hazards with higher priority to be taken into account. Considering the final preference values of disaster hazards for Tunceli province, the first three hazards for the FEMA model are earthquake with 0.192, mass movement with 0.141 and flood with 0.114, respectively. In the SMUG model, earthquake with 0.194, flood with 0.129 and epidemic disease with 0.120 are in the first three places.

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