10.57647/j.ijes.2025.1701.03

Landslide Susceptibility Mapping (LSM) of the Boudinar Basin (Morocco) using the Geographic Information System (GIS) and the Analytical Hierarchy Process (AHP) method

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  • Morad Taher *1,
  • Mourabit Taoufik2,
  • Hajar El Talibi1,
  • Afaf Amine3,
  • Abdelhak Bourjila4,
  • Ali Errahmouni2,
  • Sadik Azzouzi5,
  • Issam Etebaai1,
  1. Applied Geosciences and Geological Engineering Research Team, FSTH, Abdelmalek Essaˆadi University, Tetouan, Morocco
  2. Department of Geology, Faculty of Science, Abdelmalek Essaˆadi University, Tetouan, Morocco
  3. Geosciences, water and Environment Laboratory, Department of Geology, Faculty of Sciences, Mohammed V University in Rabat, Rabat, Morocco
  4. Laboratory of Engineering Sciences and Applications (LSIA), Materials Science, Energy and Environment (SM2E), ENSAH, Abdelmalek Essaˆadi University, Tetouan, Morocco
  5. Department of Geography, The Faculty of Letters and Human Sciences of Oujda, Mohammed first University, Oujda, Morocco
Landslide Susceptibility Mapping (LSM) of the Boudinar Basin (Morocco) using the Geographic Information System (GIS) and the Analytical Hierarchy Process (AHP) method

Received: 2024-04-19

Revised: 2024-05-07

Accepted: 2024-07-15

Published 2025-01-10

Copyright (c) 2025 Taher Morad, Mourabit Taoufik, Hajar El Talibi, Afaf Amine, Abdelhak Bourjila, Ali Errahmouni, Sadik Azzouzi, Issam Etebaai (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Taher , M. ., Taoufik, M. ., El Talibi, H. ., Amine, A. ., Bourjila, A. ., Errahmouni, A. ., Azzouzi, S. ., & Etebaai, I. . (2025). Landslide Susceptibility Mapping (LSM) of the Boudinar Basin (Morocco) using the Geographic Information System (GIS) and the Analytical Hierarchy Process (AHP) method. Iranian Journal of Earth Sciences, 17(1), 1-10. https://doi.org/10.57647/j.ijes.2025.1701.03
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Abstract

Creating a landslide susceptibility map for the Boudinar basin is of paramount significance due to the region's susceptibility to landslides, which pose considerable risks to both human settlements and the environment. By integrating Geographic Information Systems (GIS) and the Analytical Hierarchy Process (AHP), our study aims to address this challenge. These methods provide distinct advantages, as they facilitate spatial analysis and enable a thorough evaluation of the various factors contributing to landslide susceptibility. Therefore, various factors were considered in the study, including rainfall, lithology, slope, aspect, NDVI, distance from the fault, distance from the river, distance from the road, and elevation. The causative factors were divided into sub-factors, and weightages were assigned based on the AHP methodology. The resulting landslide susceptibility map was classified into three categories: low (5 %, 18 km2), moderate (69 %, 242 km2), and high (25 %, 88 km2). Nevertheless, the primary sources of uncertainty of our analysis include data quality, and the absence of field landslide inventory data for the validation process. Using Google Earth pro, the landslide inventory, consisting of 100 landslides, was used to validate the landslide susceptibility map, which had a prediction rate of 65.7% using the area under curve (AUC) technique. The LSM study is a valuable tool for construction planners and decision-makers. Therefore, by identifying high-risk areas, it aids in better preparedness and risk reduction efforts. Its integration into the planning process can significantly enhance the region's resilience to landslide hazards.

Keywords

  • Geological hazard,
  • Heavy rainfall,
  • Rif,
  • Seismic activities
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