Hachemi et al. (2026) Spatio-Temporal Analysis of Water Erosion in the Tafna Watershed (Algeria) Using the RUSLE Model and Bias-Corrected Rainfall Data (1983–2023)

Identification

• Journal: Land
• Year: 2026
• Date: 2026-01-27
• Authors: Soumia Manel Hachemi, Abdesselam Megnounif, Madani Bessedik, Navneet Kumar
• DOI: 10.3390/land15020217

Research Groups

• Eau et Ouvrages dans Leur Environnement (EOLE) Laboratory, University of Tlemcen, Tlemcen, Algeria
• Division of Ecology and Natural Resources Management, Center for Development Research (ZEF), University of Bonn, Bonn, Germany

Short Summary

This study quantifies the spatio-temporal dynamics of water erosion in Algeria's 7200 km² Tafna watershed from 1983 to 2023 using the RUSLE model and bias-corrected satellite rainfall data, revealing a 16% increase in average erosion rates driven by heightened rainfall aggressiveness and irregularity, particularly in mountainous regions.

Objective

• To provide a comprehensive spatio-temporal assessment of water-induced soil erosion in the Tafna watershed, overcoming data scarcity limitations.
• To develop a robust spatial mapping of erosion potential by integrating multi-source data.
• To evaluate the dynamic response of the 7200 km² basin to interannual and seasonal rainfall variability, identifying the sensitivity of soil loss to climatic shifts.
• To identify the dominant drivers of sediment yield through correlation analysis, providing a scalable methodology applicable to other data-limited semi-arid regions.

Study Configuration

• Spatial Scale: Tafna watershed, approximately 7200 km² (macro-scale).
• Temporal Scale: Four representative periods: 1983–1985, 1985–2000, 2000–2015, and 2015–2023 (40 years).

Methodology and Data

• Models used: Revised Universal Soil Loss Equation (RUSLE), Geographic Information Systems (GIS), Quantile Mapping (QM) for bias correction, Pearson correlation analysis, Random Forest (RF) regression algorithm.
• Data sources:
  • Digital Elevation Model (DEM): USGS/SRTM (30 m spatial resolution).
  • Rainfall Data: PERSIANN-CDR satellite data (daily; 0.25° grid resolution, 1983–2023), complemented by monthly rainfall series from 28 ground meteorological stations (National Agency of Hydraulic Resources - ANRH).
  • Soil Map: Harmonized World Soil Database (HWSD v1.2) (FAO, IIASA, ISRIC) (30 m; Scale 1:200,000).
  • Landsat Satellite Imagery: USGS (TM, ETM+, OLI) (30 m spatial resolution) for 1985, 2000, 2015, 2023.
  • Bathymetric Surveys: Agence Nationale des Barrages et Transferts (ANBT) services (2021).

Main Results

• Average annual soil loss in the Tafna watershed is estimated at 14.9 tonnes per hectare per year (t·ha⁻¹·yr⁻¹), corresponding to an annual degradation of approximately 10.9 million tonnes of arable soil over 1983–2023.
• Soil erosion increased by approximately 16% during the study period, with average erosion rates varying from less than 6 t·ha⁻¹·yr⁻¹ in stable areas to 23–27 t·ha⁻¹·yr⁻¹ in steep, sparsely vegetated regions.
• Rainfall erosivity (R factor) showed a progressive increase from 1983 to 2015, followed by a slight decrease in 2015–2023. The highest R values (>85 MJ·mm·ha⁻¹·h⁻¹·yr⁻¹) are concentrated in mountainous areas.
• The rainfall asymmetry coefficient (Cs) strongly correlates with the R-factor (r = 0.72), indicating that temporal clustering of rainfall significantly influences erosive power. A critical threshold at Cs ≈ 1.8 was identified, beyond which erosivity sharply increases.
• Topography (LS factor) and rainfall erosivity (R factor) are the primary controls on soil erosion (r = 0.27 and r = 0.21, respectively). Soil erodibility (K factor) and vegetation cover (C factor) exert weaker influences at the watershed scale.
• The highest erosion rates (exceeding 20 t·ha⁻¹·yr⁻¹) are concentrated in the mountainous areas of the Tlemcen and Traras ranges, which also exhibit high Cs values (>1.7) and degraded vegetation cover (C > 0.4).
• Bathymetric measurements from downstream reservoirs (Hammam Boughrara, Sidi Abdelli, Sikkak) show the highest sediment volumes, spatially coherent with the identified high R and Cs values in their draining mountainous areas, validating the model.

Contributions

• Provides a robust, transferable methodology for assessing water erosion in large, data-scarce semi-arid and Mediterranean watersheds by integrating RUSLE with GIS and bias-corrected satellite rainfall data.
• Introduces and quantifies the significant role of rainfall temporal irregularity (skewness coefficient, Cs) as a distinct climatic driver of soil erosivity, beyond annual precipitation totals, identifying a critical threshold for intensified erosion.
• Offers a comprehensive spatio-temporal analysis of erosion dynamics over four decades, revealing decadal climatic shifts and their impact on soil loss, which is crucial for long-term land management and water infrastructure protection.
• Qualitatively validates model results through spatial coherence with independent bathymetric surveys of reservoir siltation, enhancing the reliability of the RUSLE-GIS framework in such environments.

Funding

This research received no external funding.

Citation

@article{Hachemi2026SpatioTemporal,
  author = {Hachemi, Soumia Manel and Megnounif, Abdesselam and Bessedik, Madani and Kumar, Navneet},
  title = {Spatio-Temporal Analysis of Water Erosion in the Tafna Watershed (Algeria) Using the RUSLE Model and Bias-Corrected Rainfall Data (1983–2023)},
  journal = {Land},
  year = {2026},
  doi = {10.3390/land15020217},
  url = {https://doi.org/10.3390/land15020217}
}