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<p>Drought remains a critical challenge to water security, agricultural productivity, and socio-economic stability, particularly under intensifying climate variability. This study presents a novel integration of Geographic Information Systems (GIS) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) within a Multi-Criteria Decision-Making (MCDM) framework for spatial drought vulnerability assessment. The approach incorporates nine environmental and socio-economic indicators rainfall, soil moisture, groundwater level, temperature, land use/land cover, slope, elevation, roughness, and surface pressure across meteorological, hydrological, agricultural, and socio-economic dimensions. Fuzzy logic was employed to address uncertainty and subjectivity in expert judgment, while GIS facilitated spatial standardization, weighting, and overlay analysis. The integrated model generated a composite vulnerability index and high-resolution drought vulnerability maps, classifying regions into five risk categories. Results show that High and Very High vulnerability zones together account for 47.52% of the study area, driven primarily by low rainfall, depleted groundwater, and persistent soil moisture deficits. The proposed framework enhances the precision of vulnerability mapping, supports targeted resource allocation, and directly aligns with Sustainable Development Goals (SDG 6, SDG 11, SDG 13, and SDG 15). By coupling expert-informed fuzzy MCDM with spatial analytics, this methodology advances climate-resilient planning and sustainable water and land management strategies and is transferable to other drought-prone regions worldwide.</p>

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Developing a Comprehensive and Spatially Explicit GIS–Fuzzy TOPSIS Framework for Drought Vulnerability Assessment

  • 期刊论文

  • 发表日期：

    2026年2月4日

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  • Vijendra Kumar,
  • Akash Nandkumar Mohite,
  • Saleh Alsulamy

摘要

Drought remains a critical challenge to water security, agricultural productivity, and socio-economic stability, particularly under intensifying climate variability. This study presents a novel integration of Geographic Information Systems (GIS) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) within a Multi-Criteria Decision-Making (MCDM) framework for spatial drought vulnerability assessment. The approach incorporates nine environmental and socio-economic indicators rainfall, soil moisture, groundwater level, temperature, land use/land cover, slope, elevation, roughness, and surface pressure across meteorological, hydrological, agricultural, and socio-economic dimensions. Fuzzy logic was employed to address uncertainty and subjectivity in expert judgment, while GIS facilitated spatial standardization, weighting, and overlay analysis. The integrated model generated a composite vulnerability index and high-resolution drought vulnerability maps, classifying regions into five risk categories. Results show that High and Very High vulnerability zones together account for 47.52% of the study area, driven primarily by low rainfall, depleted groundwater, and persistent soil moisture deficits. The proposed framework enhances the precision of vulnerability mapping, supports targeted resource allocation, and directly aligns with Sustainable Development Goals (SDG 6, SDG 11, SDG 13, and SDG 15). By coupling expert-informed fuzzy MCDM with spatial analytics, this methodology advances climate-resilient planning and sustainable water and land management strategies and is transferable to other drought-prone regions worldwide.