Mliyeh et al. (2025) Assessing drought dynamics in a semi-arid basin: a multi-index approach using hydrological and remote-sensing indicators

Identification

• Journal: Environmental Sciences Europe
• Year: 2025
• Date: 2025-10-31
• Authors: Mohammed Mouad Mliyeh, Mourad Aqnouy, Marouane Laaraj, Ismail Bouizrou, Aqil Tariq, Lahcen Benaabidate, Habib Kraiem, Kasye Shitu
• DOI: 10.1186/s12302-025-01240-4

Research Groups

• Laboratory of Geo−Resources and Environment, Faculty of Sciences and Techniques, Sidi Mohammed Ben Abdellah University, Fez, Morocco
• Geosciences and Technologies Research Team, Department of Geosciences, Faculty of Sciences and Techniques of Errachidia, Moulay Ismail University of Meknes, Meknes, Morocco
• Institute of Ecology and Landscape, Hochschule Weihenstephan-Triesdorf University (HSWT), Freising, Germany
• Department of Wildlife, Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, Mississippi State, MS, USA
• Center for Scientific Research and Entrepreneurship, Northern Border University, Arar, Saudi Arabia
• Department of Natural Resource Management, College of Agriculture and Natural Resources, Mekdela Amba University, Tulu Awlia, Ethiopia

Short Summary

This study integrates remote-sensing products with traditional hydrological indices to comprehensively monitor drought dynamics in a semi-arid basin, demonstrating that remote-sensing indicators, particularly AWEI and NDWI, strongly correlate with hydrological drought indices and reveal significant declines in surface water extent.

Objective

• To compute the Standardized Runoff Index (SRI) and the Streamflow Drought Index (SDI) at various temporal scales (1, 3, 6, and 12 months) to characterize hydrological drought dynamics.
• To integrate the Standardized Precipitation–Evapotranspiration Index (SPEI) to account for climatic drivers and atmospheric water balance.
• To assess the contribution of remote-sensing-based indices (Normalized Difference Water Index (NDWI), Automated Water Extraction Index (AWEI), and Crop Water Stress Index (CWSI)) in detecting surface water variability and vegetation stress.
• To evaluate the statistical relationships between hydrological and satellite-derived indices to identify the most responsive time scale and optimal index combinations.
• To apply the Mann–Kendall test and Sen’s slope estimator to detect and quantify long-term trends in drought indices.

Study Configuration

• Spatial Scale: Ahmed El Hansali (AEH) catchment, upper basin of the Oum Er Rabia, Morocco, covering an area of 950 square kilometers with an elevation range from 670 to 2230 meters.
• Temporal Scale: Hydrological indices (SPEI, SRI, SDI) analyzed over 44 years (1979–2022); remote-sensing indices (AWEI, NDWI, CWSI) analyzed over 10 years (2013–2022). Indices computed at 1, 3, 6, 9, and 12-month time scales.

Methodology and Data

• Models used:
  • Drought Indices: Standardized Runoff Index (SRI), Streamflow Drought Index (SDI), Standardized Precipitation–Evapotranspiration Index (SPEI), Normalized Difference Water Index (NDWI), Automated Water Extraction Index (AWEI), Crop Water Stress Index (CWSI).
  • Statistical Analysis: Mann–Kendall test, Sen’s slope estimator, Pearson correlation.
• Data sources:
  • Precipitation, streamflow: Oum Er Rabia Hydraulic Basin Agency (OERHBA) (in situ, monthly, 1979–2022).
  • Temperature, Potential Evapotranspiration (PET): ERA5 reanalysis (0.28 degrees spatial resolution, monthly, 1979–2022) via Climate Engine.
  • NDWI, AWEI: Landsat 8 surface reflectance imagery (LANDSAT/LC08/C02/T1_L2) (30 meters spatial resolution, 16-day revisit interval, 2013–2022) via Google Earth Engine (GEE).
  • CWSI: MODIS product (MODIS/006/MOD16A2) (500 meters spatial resolution, 8-day composite estimates, 2013–2022) via GEE.

Main Results

• The SPEI exhibited the highest sensitivity to drought, identifying 5–7 extreme and 17–28 severe drought months across various temporal scales (1979–2022).
• Remote-sensing products, particularly AWEI and NDWI, align most strongly with hydrological drought indices (SRI and SDI) over 6 and 12 months.
• AWEI–SRI/SDI correlations reached r = 0.51/0.60 at 6 months (p < 0.001), and NDWI–SRI/SDI correlations reached r = 0.52/0.50 at 12 months (p < 0.001).
• The SPEI showed modest correlations with AWEI and NDWI, not exceeding r = 0.50.
• CWSI showed significant correlations with SPEI (r = 0.46) and SDI (r = 0.70) at the 1-month scale, but these correlations declined significantly at longer temporal scales, becoming statistically negligible at 9 and 12 months.
• Trend analyses (2013–2022) indicated significant declining trends across all evaluated indices:
  • SDI at 6- and 12-month scales showed Sen’s slope values of –7.58 × 10⁻³ and –1.26 × 10⁻², respectively (p < 0.001).
  • SRI at 6- and 12-month scales showed Sen’s slope values of –1.38 × 10⁻² and –1.53 × 10⁻², respectively (p < 0.001).
  • AWEI decreased by 8.60 × 10⁻² square kilometers per year (p < 0.001).
  • NDWI decreased by 6.12 × 10⁻² square kilometers per year (p < 0.001).
• These results underscore intensifying drought conditions and a sharp decline in surface water extent in the Ahmed El Hansali catchment.

Contributions

• Demonstrates a robust multi-index approach integrating traditional hydrological indices with remote-sensing products for comprehensive drought monitoring in data-scarce semi-arid environments.
• Identifies optimal index combinations and responsive time scales (6-12 months) for hydrological drought assessment using remote sensing (AWEI, NDWI).
• Provides evidence of intensifying drought conditions and significant declines in surface water extent in the Ahmed El Hansali catchment, Morocco, using both in-situ and satellite data.
• Validates a scalable and transferable framework, operationalized through Google Earth Engine, for efficient processing of large spatio-temporal datasets in similar water-stressed regions.

Funding

• Drâa Oued Noun Hydraulic Basin Agency, Morocco (provided basic data).
• Deanship of Scientific Research at Northern Border University, Arar, KSA (project number NBU-FFR-2025-2484-17).

Citation

@article{Mliyeh2025Assessing,
  author = {Mliyeh, Mohammed Mouad and Aqnouy, Mourad and Laaraj, Marouane and Bouizrou, Ismail and Tariq, Aqil and Benaabidate, Lahcen and Kraiem, Habib and Shitu, Kasye},
  title = {Assessing drought dynamics in a semi-arid basin: a multi-index approach using hydrological and remote-sensing indicators},
  journal = {Environmental Sciences Europe},
  year = {2025},
  doi = {10.1186/s12302-025-01240-4},
  url = {https://doi.org/10.1186/s12302-025-01240-4}
}