Abidi et al. (2025) Sediment Assessment Using Coupled RUSLE-SDR Models of Future Mellegue2 Dam in Tunisia

Identification

• Journal: Jeoloji Mühendisliği Dergisi
• Year: 2025
• Date: 2025-12-06
• Authors: Sahar Abidi, Hammadi Achour, Fida Mouelhi, Omrana Aıdara, Mahnaz Gümrükçüoğlu Yiğit, Lamia Lajili Ghezal
• DOI: 10.24232/jmd.1667956

Research Groups

• Laboratoire Des Ressources Sylvo-Pastorales, Institut Sylvo-Pastoral de Tabarka, Université de Jendouba, Tunisia.
• Laboratoire de recherche-Systèmes de Production Agricole et Développement Durable, Université de Carthage, Tunisia.
• Department of Environmental Engineering, Sakarya University, Türkiye.
• Mauritanian Consulting Group (MCG), Mauritania.

Short Summary

This study utilizes integrated RUSLE-SDR and SWAT modeling to quantify soil erosion and sediment dynamics in the Mellegue2 Dam watershed, identifying a "drought-flush" mechanism that significantly accelerates siltation. The findings indicate that while the dam could lose 50% of its capacity in 24 years without intervention, targeted conservation strategies could extend its operational lifespan to over 75 years.

Objective

• To evaluate sediment dynamics and spatial erosion risks in the Mellegue2 Dam watershed by integrating climate-driven erosion processes with connectivity-based modeling to optimize watershed management and dam longevity.

Study Configuration

• Spatial Scale: Mellegue2 Dam watershed (Northwest Tunisia and part of Algeria), characterized by elevations from 259 m to 1,245 m and a semi-arid Mediterranean climate.
• Temporal Scale: 1993–2019 (historical analysis and model validation period).

Methodology and Data

• Models used: Revised Universal Soil Loss Equation (RUSLE) for soil loss estimation, Index of Connectivity (IC) and Sediment Delivery Ratio (SDR) for transport modeling, and Soil and Water Assessment Tool (SWAT) for cross-model validation.
• Data sources: 30 m SRTM Digital Elevation Models (DEM), Landsat 5/7/8 satellite imagery (NDVI for C-factor), 1:50,000 scale soil maps, and daily meteorological data from five regional weather stations.
• Analysis Techniques: Monte Carlo simulations (1,000 iterations) for uncertainty quantification and SedInConnect software for topographic connectivity analysis.

Main Results

• Model Accuracy: The integrated RUSLE-SDR approach achieved high predictive performance (NSE = 0.78, R² = 0.82) with an average annual prediction error of 12.3%.
• Drought-Flush Mechanism: Sediment export increases by 40–60% in years following droughts (e.g., 2001, 2007, 2013) due to reduced vegetation cover and weakened soil structure, regardless of absolute rainfall totals.
• Sedimentation Projections: Without management, the dam is expected to reach 50% siltation within 24 years. Comprehensive management could extend this to 75–100 years.
• Spatial Hotspots: Northwestern slopes were identified as the highest priority zones, with erosion rates exceeding 12 t/ha/year.
• Uncertainty: Monte Carlo analysis established confidence intervals of -18% to +22% for annual sediment forecasts.

Contributions

• Establishes a validated modeling framework for North African semi-arid watersheds that accounts for the non-linear "drought-flush" erosion response.
• Provides a spatially explicit prioritization for conservation (terracing, reforestation, and check dams) based on sediment connectivity rather than just gross erosion.
• Demonstrates the utility of combining empirical (RUSLE) and physically-based (SWAT) models with long-term (37-year) bathymetric survey data to improve dam lifespan predictions in data-scarce regions.

Funding

• Ministry of Higher Education and Scientific Research, Tunisia: Program of Encouragement of Young Researchers (PEJC), Project No. PEJC20-2017 ("Management of the phenomenon of silting and mapping of the risk of erosion of the watersheds of the large dams of the upper valley of Medjerda").

Citation

@article{Abidi2025Sediment,
  author = {Abidi, Sahar and Achour, Hammadi and Mouelhi, Fida and Aıdara, Omrana and Yiğit, Mahnaz Gümrükçüoğlu and Ghezal, Lamia Lajili},
  title = {Sediment Assessment Using Coupled RUSLE-SDR Models of Future Mellegue2 Dam in Tunisia},
  journal = {Jeoloji Mühendisliği Dergisi},
  year = {2025},
  doi = {10.24232/jmd.1667956},
  url = {https://doi.org/10.24232/jmd.1667956}
}

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