Assessing drought dynamics in a semi-arid basin: a multi-index approach using hydrological and remote-sensing indicators

Understanding the hydrological responses of semi-arid watersheds to climatic variability is crucial for sustainable water resource management. This study demonstrates that integrating remote-sensing products with traditional hydrological indices offers a robust approach for comprehensive drought monitoring . An approach using multi-index was adopted by combining different remote-sensing products including the Automated Water Extraction Index (AWEI), the Normalized Difference Water Index (NDWI), and the Crop Water Stress Index (CWSI) computed over 10 years (2013–2022) using Google Earth Engine (GEE), with hydrological metrics such as the Standardized Runoff Index (SRI), the Streamflow Drought Index (SDI), and the Standardized Precipitation–Evapotranspiration Index (SPEI) analyzed over 44 years (1979–2022). Our findings reveal that remote-sensing products, particularly AWEI and NDWI, align most strongly with hydrological drought indices over 6 and 12 months, with AWEI–SRI/SDI correlations reaching r = 0.51/0.60 at 6 months and NDWI–SRI/SDI reaching r = 0.52/0.50 at 12 months. Although SPEI exhibits modest correlations with AWEI and NDWI (not exceeding r = 0.50), its integration with remote-sensing hydrological indices remains secondary. Trend analyses indicate significant declines in surface water extent during the study period: AWEI decreased by 1.03 km2/year and NDWI by 0.73 km2/year, underscoring intensifying drought conditions. These results highlight the indispensable role of remote sensing in delivering continuous, detailed spatio-temporal insights and supporting adaptive water governance strategies, particularly in regions facing increasing water scarcity.

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Publication Details

Journal
Environmental Sciences Europe
Published
2025-10-31
DOI
https://doi.org/10.1186/s12302-025-01240-4
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Assessing drought dynamics in a semi-arid basin: a multi-index approach using hydrological and remote-sensing indicators

Mohammed Mouad Mliyeh, Habib Kraiem, Lahcen Benaabidate, Ismail Bouizrou et al.
Environmental Sciences Europe
Hydrology and Drought Analysis
article

Assessing drought dynamics in a semi-arid basin: a multi-index approach using hydrological and remote-sensing indicators

Mohammed Mouad Mliyeh, Habib Kraiem, Lahcen Benaabidate, Ismail Bouizrou, Aqil Tariq, Marouane Laaraj, Mourad Aqnouy, Kasye Shitu
article en

Abstract

Understanding the hydrological responses of semi-arid watersheds to climatic variability is crucial for sustainable water resource management. This study demonstrates that integrating remote-sensing products with traditional hydrological indices offers a robust approach for comprehensive drought monitoring . An approach using multi-index was adopted by combining different remote-sensing products including the Automated Water Extraction Index (AWEI), the Normalized Difference Water Index (NDWI), and the Crop Water Stress Index (CWSI) computed over 10 years (2013–2022) using Google Earth Engine (GEE), with hydrological metrics such as the Standardized Runoff Index (SRI), the Streamflow Drought Index (SDI), and the Standardized Precipitation–Evapotranspiration Index (SPEI) analyzed over 44 years (1979–2022). Our findings reveal that remote-sensing products, particularly AWEI and NDWI, align most strongly with hydrological drought indices over 6 and 12 months, with AWEI–SRI/SDI correlations reaching r = 0.51/0.60 at 6 months and NDWI–SRI/SDI reaching r = 0.52/0.50 at 12 months. Although SPEI exhibits modest correlations with AWEI and NDWI (not exceeding r = 0.50), its integration with remote-sensing hydrological indices remains secondary. Trend analyses indicate significant declines in surface water extent during the study period: AWEI decreased by 1.03 km2/year and NDWI by 0.73 km2/year, underscoring intensifying drought conditions. These results highlight the indispensable role of remote sensing in delivering continuous, detailed spatio-temporal insights and supporting adaptive water governance strategies, particularly in regions facing increasing water scarcity.

Environmental Sciences EuropeVol. 37(1)
Northern Border University (SA), Weihenstephan-Triesdorf University of Applied Sciences (DE), Ambo University (ET), Université Moulay Ismail de Meknes (MA), Instituto Superior da Maia (PT), Sidi Mohamed Ben Abdellah University (MA), Mississippi State University (US)
Northern Border University
Openalex Percentile: Top 70%
Hydrology and Drought Analysis
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