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<p>This study uses remote sensing, combined with meteorological and environmental data to identify drought-prone zones and assess drought severity across the Beni Mellal-Khénifra region in Morocco. This region is particularly vulnerable to drought due to rising temperatures and changing precipitation patterns. The Analytical Hierarchy Process (AHP), integrated with a Geographic Information System (GIS) and various influencing parameters, has proven to be a powerful tool for achieving the main objective. The study incorporated 10 parameters, namely: rainfall, land surface temperature (LST), soil moisture index (SMI), population density, elevation, land use/land cover (LULC), normalized difference vegetation index (NDVI), normalized difference drought index (NDDI), normalized difference water index (NDWI), and vegetation condition index (VCI), to delineate the drought in the study area. A multi-criteria analysis was conducted to determine the relative importance of parameters contributing to drought risk. The results of this study indicate that 43.98% of the area is classified as high drought, followed by medium drought at 42.78%, low drought at 6.11%, and very low drought at 0.35%. The study demonstrates that integrating various data sources enables effective management of risk areas.</p>

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Drought vulnerability assessment of the Beni Mellal-Khenifra region, Morocco

  • 期刊论文

  • 发表日期：

    2026年7月23日

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  • Rida Khellouk,
  • Ahmed Barakat

摘要

This study uses remote sensing, combined with meteorological and environmental data to identify drought-prone zones and assess drought severity across the Beni Mellal-Khénifra region in Morocco. This region is particularly vulnerable to drought due to rising temperatures and changing precipitation patterns. The Analytical Hierarchy Process (AHP), integrated with a Geographic Information System (GIS) and various influencing parameters, has proven to be a powerful tool for achieving the main objective. The study incorporated 10 parameters, namely: rainfall, land surface temperature (LST), soil moisture index (SMI), population density, elevation, land use/land cover (LULC), normalized difference vegetation index (NDVI), normalized difference drought index (NDDI), normalized difference water index (NDWI), and vegetation condition index (VCI), to delineate the drought in the study area. A multi-criteria analysis was conducted to determine the relative importance of parameters contributing to drought risk. The results of this study indicate that 43.98% of the area is classified as high drought, followed by medium drought at 42.78%, low drought at 6.11%, and very low drought at 0.35%. The study demonstrates that integrating various data sources enables effective management of risk areas.