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

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Advances in Best-Worst Method (BWM 2023)

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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.

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Author information

Authors and Affiliations

  1. Department of Geography, Munzur University, Tunceli, Turkey

    Zekeriya Konurhan

  2. Department of Emergency Aid and Disaster Management, Munzur University, Tunceli, Turkey

    Melih YĆ¼cesan

  3. Department of Transportation and Logistics, Istanbul University, Istanbul, Turkey

    Muhammet Gul

Authors
  1. Zekeriya Konurhan
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  2. Melih YĆ¼cesan
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  3. Muhammet Gul
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Corresponding author

Correspondence to Zekeriya Konurhan .

Editor information

Editors and Affiliations

  1. Faculty of Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands

    Jafar Rezaei

  2. Department of Industrial Engineering, University of Trento, Trento, Italy

    Matteo Brunelli

  3. Vrije Universiteit Amsterdam (VU Amsterdam), Amsterdam, The Netherlands

    Majid Mohammadi

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Konurhan, Z., YĆ¼cesan, M., Gul, M. (2023). Avalanche Risk Analysis by a Combined Geographic Information System and Bayesian Best-Worst Method. In: Rezaei, J., Brunelli, M., Mohammadi, M. (eds) Advances in Best-Worst Method. BWM 2023. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-40328-6_11

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