Avalanche Risk Analysis by a Combined Geographic Information System and Bayesian Best-Worst Method

Zekeriya Konurhan (), Melih Yücesan () and Muhammet Gul ()
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Zekeriya Konurhan: Munzur University
Melih Yücesan: Munzur University
Muhammet Gul: Istanbul University

Chapter Chapter 11 in Advances in Best-Worst Method, 2023, pp 193-210 from Springer

Abstract: Abstract The formation of avalanches is related to the land structure, climatic conditions, and snow cover. It is usually seen in mountainous and sloping terrains without vegetation. In Turkey, especially in Eastern Anatolia and the Black Sea Region, which have high elevations, avalanche events are observed. This study aims to perform a risk analysis by integrating the Bayesian Best-Worst method (BWM) and Geographic Information System (GIS) for Tunceli province, which is the scene of significant avalanche events. Bayesian BWM is a method that improves the original BWM by effectively integrating the preferences of multiple experts. In the study, 16 sub-criteria, such as elevation, slope, and the number of snowy days, were determined, and experts evaluated these criteria through questionnaires created. The weight of each criterion were calculated using the Bayesian-BWM. By integrating the criteria weights from the Bayesian-BWM model into GIS, the risky places for natural avalanche disasters in Tunceli province were determined, according to which the risk in the northern part of the study area is identified as high.

Keywords: Avalanche risk analysis; GIS; Bayesian-BWM (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-40328-6_11

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DOI: 10.1007/978-3-031-40328-6_11

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