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dc.contributor.authorYucesan, Melih
dc.contributor.authorGul, Muhammet
dc.contributor.authorYanilmaz, Sumeyye
dc.contributor.authorBaskak, Dilber
dc.date.accessioned2022-07-04T13:38:13Z
dc.date.available2022-07-04T13:38:13Z
dc.identifier.citationYanilmaz S., Baskak D., Yucesan M., Gul M., "Extension of FEMA and SMUG models with Bayesian best-worst method for disaster risk reduction", INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, cilt.66, 2021
dc.identifier.issn2212-4209
dc.identifier.othervv_1032021
dc.identifier.otherav_520af50c-a967-43e7-804c-ebf4ad1c7f7e
dc.identifier.urihttp://hdl.handle.net/20.500.12627/182757
dc.identifier.urihttps://doi.org/10.1016/j.ijdrr.2021.102631
dc.description.abstractTurkey 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.
dc.language.isoeng
dc.subjectMühendislik ve Teknoloji
dc.subjectWater Science and Technology
dc.subjectStratigraphy
dc.subjectAtmospheric Science
dc.subjectGeotechnical Engineering and Engineering Geology
dc.subjectEconomic Geology
dc.subjectPhysical Sciences
dc.subjectGeology
dc.subjectYER BİLİMİ, MULTİDİSİPLİNER
dc.subjectYerbilimleri
dc.subjectTemel Bilimler (SCI)
dc.subjectMETEOROLOJİ VE ATMOSFER BİLİMLERİ
dc.subjectSU KAYNAKLARI
dc.subjectÇevre / Ekoloji
dc.subjectTarım ve Çevre Bilimleri (AGE)
dc.subjectJEOLOJİ
dc.subjectTarımsal Bilimler
dc.subjectZiraat
dc.subjectToprak ve Bitki Besleme
dc.subjectToprak ve Su Muhafazası ve Amenajmanı
dc.subjectHavza Yönetimi
dc.subjectAtmosfer Bilimleri ve Meteoroloji Mühendisliği
dc.subjectJeoloji Mühendisliği
dc.titleExtension of FEMA and SMUG models with Bayesian best-worst method for disaster risk reduction
dc.typeMakale
dc.relation.journalINTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
dc.contributor.departmentMunzur Üniversitesi , ,
dc.identifier.volume66
dc.contributor.firstauthorID3407436


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