EventsThe 9th International Electronic Conference on Water Sciences
Published
This submission belongs to the session S5. Extreme Hydro-meteorological Events: Sources, Mitigation and Adaptation of the event The 9th International Electronic Conference on Water Sciences
Published date
06 Nov, 2025
Academic Editor
author-avatarLampros Vasiliades
Citation
Asif Sajjad, Anam Batool, Drought Vulnerability Assessment in the Sindh Province, Pakistan, using Multicriteria decision analysis (MCDA) Technique, in Proceedings of The 9th International Electronic Conference on Water Sciences, 11 November–14 November 2025, MDPI: Basel, Switzerland
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Drought Vulnerability Assessment in the Sindh Province, Pakistan, using Multicriteria decision analysis (MCDA) Technique

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1. Department of Environmental Sciences, Faculty of Biological Sciences, Quaid-i-Azam University, 45320 Islamabad, Pakistan, Pakistan
Abstract

Drought is a recurring environmental hazard that significantly impacts agricultural productivity and ecosystem stability. This study assesses drought vulnerability in Mirpurkhas Division, Sindh, Pakistan, in March 2021 using the Analytical Hierarchy Process (AHP) model. The analysis incorporates 11 parameters: rainfall, Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Land Surface Temperature (LST), Moisture Stress (I), elevation, slope, soil type, Topographic Wetness Index (TWI), Land Use/Land Cover (LULC), and population density (PD). The Standardized Precipitation Evapotranspiration Index (SPEI) was applied to climate data from 2021, revealing that March was among the months that were affected by drought conditions. Subsequently, Landsat imagery from March 2021 was integrated into a Geographic Information System (GIS)-based AHP framework to generate a drought vulnerability map. This approach enabled the spatial evaluation of drought-prone areas by combining remote sensing data with multi-criteria decision analysis. The result reveals that about 2.9% of the study area experienced no drought, 19.1% was affected by low levels of drought, 40.2% by moderate drought, 21.1% by severe drought, and 16.6% by extreme drought. These findings highlight significant drought vulnerability within the Mirpurkhas Division. The resulting model showed a high performance level, with a Kappa coefficient of 0.921. This high correlation of the predicted and observed drought vulnerability classes indicates the reliability of the model. The resulting vulnerability map can assist policymakers and administrators in the design and implementation of effective drought mitigation strategies, thus mitigating possible drought-related effects.

Keywords
Analytical Hierarchy Process
GIS
Drought
Extreme Hydro-meteorological Events
Vulnerability
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