Naim et al. (2025) Enhancing Drought Identification and Characterization in the Tensift River Basin (Morocco): A Comparative Analysis of Data and Tools

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Identification

• Journal: Hydrology
• Year: 2025
• Date: 2025-12-16
• Authors: Mohamed Naim, Brunella Bonaccorso, Shewandagn Tekle
• DOI: 10.3390/hydrology12120334

Research Groups

Not specified in the provided text.

Short Summary

This study evaluates satellite and reanalysis products for drought monitoring in the Tensift River Basin, identifies optimal probability distributions for SPI and SPEI, and compares their performance against reported drought events to enhance early-warning tools for water resource management.

Objective

• Evaluate satellite and reanalysis products (CHIRPS, ERA5-Land) against in situ observations for drought monitoring using statistical metrics.
• Identify the best probability distribution for calculating drought indices (SPI, SPEI) using goodness-of-fit testing.
• Compare the performances of SPI and SPEI at different aggregation timescales by comparing index-based and reported drought events using receiver operating characteristic (ROC) analysis, also exploring the impact of Thornthwaite and Hargreaves methods for SPEI computation.

Study Configuration

• Spatial Scale: Tensift River Basin, Mediterranean region.
• Temporal Scale: Multi-temporal aggregation timescales for drought indices (e.g., monthly to multi-monthly).

Methodology and Data

• Models used: Standardized Precipitation Index (SPI), Standardized Precipitation and Evapotranspiration Index (SPEI), Thornthwaite method (for potential evapotranspiration), Hargreaves method (for potential evapotranspiration).
• Data sources: Satellite products (CHIRPS), Reanalysis products (ERA5-Land), In situ observations.

Main Results

• CHIRPS and ERA5-Land datasets demonstrate good performance compared to in situ measurements for drought monitoring in the Tensift River Basin.
• Pearson Type 3 was identified as the optimal probability distribution for SPI calculation.
• Log-logistic was confirmed as the optimal probability distribution for SPEI calculation.
• The study explored the effect of using Thornthwaite and Hargreaves methods for SPEI computation.

Contributions

• Provides a basis for enhanced drought monitoring, modeling, and forecasting in the Tensift River Basin.
• Supports decision-makers in the sustainable management of water resources by improving early-warning tools.
• Offers specific recommendations for data products (CHIRPS, ERA5-Land) and probability distributions (Pearson Type 3 for SPI, log-logistic for SPEI) for drought index calculation in the region.

Funding

Not specified in the provided text.

Citation

@article{Naim2025Enhancing,
  author = {Naim, Mohamed and Bonaccorso, Brunella and Tekle, Shewandagn},
  title = {Enhancing Drought Identification and Characterization in the Tensift River Basin (Morocco): A Comparative Analysis of Data and Tools},
  journal = {Hydrology},
  year = {2025},
  doi = {10.3390/hydrology12120334},
  url = {https://doi.org/10.3390/hydrology12120334}
}