Sediment Assessment Using Coupled RUSLE-SDR Models of Future Mellegue2 Dam in Tunisia

Öz

Over the last 60 years, Mellegue1 Dam has lost approximately 80% of its original 268 million cubic meter capacity to siltation, reflecting broader Mediterranean basin patterns in which climate-driven erosion has exacerbated dam sedimentation rates. In response, the strategic building of the upstream Mellegue2 Dam is intended to address water scarcity, improve flood management, and ensure a continuous supply of water for agricultural and domestic purposes. This study fills critical knowledge gaps by integrating climate change projections with sediment modeling in Mediterranean semi-arid environments, developing spatially explicit conservation strategies using combined RUSLE-SDR and SWAT modeling, and evaluating management interventions under future scenarios using drought-flush erosion mechanisms documented across the Mediterranean basin. This study evaluates sediment dynamics in the Mellegue2 Dam watershed from 1993 to 2019 using an integrated RUSLE-IC-SDR modelling approach, with model validation performed using a three-tiered framework that included SWAT comparison, historical sedimentation records, and regional correlation analysis. The model performed well (NSE=0.78, R²=0.82), with an average annual prediction error of 12.3%, similar to verified Mediterranean erosion models. Monte Carlo simulation with 1000 iterations, accounting for parameter variability in R-factor (±15%), K-factor (±20%), and C-factor (±25%), yielded confidence intervals of -18% to +22% for annual forecasts. The temporal study demonstrates drought-flush erosion mechanisms common to Mediterranean climates, with post-drought sediment outputs increasing by 40-60% above normal years, consistent with regional research from Spain, Italy, and Greece. According to the management scenario study, Mellegue2 Dam will lose 50% of its capacity within 24 years if no intervention is implemented. However, comprehensive watershed management based on proven Mediterranean basin conservation practices has the potential to increase operational lifespan to 75 years while also delivering broader environmental benefits. The study finds three priority management zones that require distinct conservation approaches, with the largest return on investment found on northwestern slopes with erosion rates of more than 12 t/ha/year. These findings contribute to better knowledge of climate-driven erosion processes across the Mediterranean and offer management solutions that can be applied to similar semi-arid watersheds.

Anahtar Kelimeler

• Sediment Export
• Soil Erosion
• RUSLE
• SDR
• SWAT
• Index of Connectivity
• Watershed Management
• Tunisia

Tunus'ta Gelecekteki Mellegue2 Barajının Birleştirilmiş RUSLE-SDR Modelleri Kullanılarak Sediman Değerlendirmesi

Öz

Son 60 yılda, Mellegue1 Barajı, iklim kaynaklı erozyonun baraj sedimantasyon oranlarını artırdığı Akdeniz havzasındaki genel eğilimi yansıtarak, orijinal 268 milyon metreküp kapasitesinin yaklaşık %80'ini siltasyon nedeniyle kaybetmiştir. Buna yanıt olarak, yukarı akışta stratejik olarak inşa edilen Mellegue2 Barajı, su kıtlığını gidermeyi, sel yönetimini iyileştirmeyi ve tarımsal ve evsel amaçlar için sürekli su teminini sağlamayı amaçlamaktadır. Bu çalışma, iklim değişikliği tahminlerini Akdeniz yarı kurak ortamlarındaki sediman modellemesiyle entegre ederek, RUSLE-SDR ve SWAT modellemesini birleştirerek mekansal olarak açık koruma stratejileri geliştirerek ve Akdeniz havzasında belgelenen kuraklık-akış erozyon mekanizmalarını kullanarak gelecek senaryoları altında yönetim müdahalelerini değerlendirerek kritik bilgi boşluklarını doldurmaktadır. Bu çalışma, entegre RUSLE-IC-SDR modelleme yaklaşımı kullanılarak 1993'ten 2019'a kadar Mellegue2 Barajı havzasındaki sediman dinamiklerini değerlendirmekte ve model doğrulaması SWAT karşılaştırması, tarihsel sedimantasyon kayıtları ve bölgesel korelasyon analizini içeren üç aşamalı bir çerçeve kullanılarak gerçekleştirilmektedir. Model, doğrulanmış Akdeniz erozyon modellerine benzer şekilde, ortalama yıllık tahmin hatası %12,3 ile iyi bir performans göstermiştir (NSE=0,78, R²=0,82). R faktörü (±%15), K faktörü (±%20) ve C faktörü (±%25) parametre değişkenliğini hesaba katan 1000 yinelemeli Monte Carlo simülasyonu, yıllık tahminler için %-18 ile %+22 arasında güven aralıkları vermiştir. Zamansal çalışma, Akdeniz iklimlerinde yaygın olan kuraklık-sel erozyonu mekanizmalarını göstermektedir. Kuraklık sonrası sediment çıkışı normal yıllara göre %40-60 oranında artmaktadır. Bu sonuç, İspanya, İtalya ve Yunanistan'da yapılan bölgesel araştırmalarla tutarlıdır. Yönetim senaryosu çalışmasına göre, Mellegue2 Barajı, herhangi bir müdahale yapılmazsa 24 yıl içinde kapasitesinin %50'sini kaybedecektir. Ancak, Akdeniz havzasında kanıtlanmış koruma uygulamalarına dayanan kapsamlı havza yönetimi, operasyonel ömrü 75 yıla çıkarırken, daha geniş çevresel faydalar da sağlayabilir. Çalışma, farklı koruma yaklaşımları gerektiren üç öncelikli yönetim bölgesi belirlemektedir. En yüksek yatırım getirisi, erozyon oranının 12 t/ha/yıl'ın üzerinde olduğu kuzeybatı yamaçlarda görülmektedir. Bu bulgular, Akdeniz'deki iklim kaynaklı erozyon süreçleri hakkında daha iyi bilgi edinilmesine katkıda bulunmakta ve benzer yarı kurak havzalara uygulanabilecek yönetim çözümleri sunmaktadır.

Anahtar Kelimeler

• Sediment İhracı
• Toprak Erozyonu
• RUSLE
• SDR
• SWAT
• Bağlantılılık İndeksi
• Havza Yönetimi
• Tunus

Kaynakça

1. Abidi, S., Trabelsi, H., Toujeni, A., Oueslati, A., Aidara, O., & Jarray, B. (2024). Effects of wildfire on runoff and sediment production in Mellegue Watershed (Tunisia). In Advances in Science, Technology and Innovation (pp. 809–815). Springer. https://doi.org/10.1007/978-3-031-43922-3_181
2. Aneseyee, A. B., Noszczyk, T., Soromessa, T. & Elias, E. (2020). The impact of land use/land cover change on ecosystem services in the central highlands of Ethiopia. Ecosystem Services, 41, Article 101042. https://doi.org/10.1016/j.ecoser.2019.101042
3. Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M. J., Srinivasan, R., Santhi, C., Harmel, R. D., Van Griensven, A., Van Liew, M. W. & Kannan, N. (2012). SWAT: Model use, calibration, and validation. Transactions of the ASABE, 55(4), 1491-1508.
4. Ben Nsir, S., Jomaa, S., Yıldırım, Ü., Zhou, X., D’Oria, M., Rode, M., & Khlifi, S. (2022). Assessment of climate change impact on discharge of the Lakhmass catchment (Northwest Tunisia). Water, 14(4), 655. https://doi.org/10.3390/w14040655
5. Bols, P. L. (1978). The iso-erodent map of Java and Madura. Belgian Technical Assistance Project ATA 105, Soil Research Institute, Bogor, Indonesia.
6. Borrelli, P., Robinson, D. A., Fleischer, L. R., Lugato, E., Ballabio, C., Alewell, C., ... & Panagos, P. (2017). An assessment of the global impact of 21st century land use change on soil erosion. Nature Communications, 8(1), 2013.
7. Borselli, L., Cassi, P. & Torri, D. (2008). Prolegomena to sediment and flow connectivity in the landscape: A GIS and field numerical assessment. Catena, 75(3), 268-277.
8. Bouaziz, L., Boussema, M. R. & Louati, M. (2020). Modeling soil erosion in a semi-arid watershed using integrated approaches: A case study from Tunisia. Environmental Earth Sciences, 79(3), 90.

9. Crema, S. & Cavalli, M. (2018). SedInConnect: a stand-alone, free and open-source tool for the assessment of sediment connectivity. Computers & Geosciences, 111, 39-45.
10. Desmet, P. J. J. & Govers, G. (1996). A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units. Journal of Soil and Water Conservation, 51(5), 427-433.
11. Djuma, H., Bruggeman, A., Camera, C., Zoumides, C. & Eliades, M. (2015). The effect of land use change on soil erosion in Mediterranean watersheds. Land Degradation & Development, 26(6), 561-572.
12. FAOSTAT, (2014, January 01). Food and Agriculture Organization of the United Nations. FAOSTAT database. http://www.fao.org/faostat/en/
13. García-Ruiz, J. M., Nadal-Romero, E., Lana-Renault, N. & Beguería, S. (2010). Erosion in Mediterranean environments: Changes and future challenges. Geomorphology, 123(1-2), 1-2.
14. García-Ruiz, J. M., Beguería, S., Nadal-Romero, E., González-Hidalgo, J. C., Lana-Renault, N., & Sanjuán, Y. (2013). A meta-analysis of soil erosion rates across the world. Geomorphology, 239, 160-173.
15. Glade, T. (2003). Landslide occurrence as a response to land use change: a review of evidence from New Zealand. Catena, 51(3-4), 297-314.
16. Issaoui, H., Tounsi, K., Aloui, H., Hammami, A. & Dridi, M. A. (2020, March 12). Synthèse sur la désertification en Tunisie. https://scid.tn
17. Jamshidi, R., Feiznia, S., Ahmadi, H. & Keesstra, S. D. (2014). Assessing sediment yield using SDR and IC models in a Mediterranean environment. Geomorphology, 217, 84–95. https://doi.org/10.1016/j.geomorph.2014.04.022
18. Keesstra, S. D., Nunes, J. P., Saco, P., Parsons, A. J., Poeppl, R. E. & Masselink, R. (2018). The way forward: Can connectivity be useful to design better measuring and modeling schemes for water and sediment dynamics? Science of the Total Environment, 644, 1557–1572. https://doi.org/10.1016/j.scitotenv.2018.06.342
19. Kosmas, C., Danalatos, N., Cammeraat, L. H., Chabart, M., Diamantopoulos, J., Farand, R., ... & Vacca, A. (2014). The effect of land use on runoff and soil erosion rates under Mediterranean conditions. Catena, 29(1), 45-59.
20. Lahlaoi, H., Rhinane, H., Hilali, A., & Lahssini, S. (2015). Potential erosion risk calculation using remote sensing and GIS in Oued El Maleh watershed, Morocco. Journal of Geographic Information System, 7(2), 128-139.
21. Lionello, P., & Scarascia, L. (2018). The relation between climate change in the Mediterranean region and global warming. Regional Environmental Change, 18(5), 1481-1493.
22. Luetzenburg, G., Wang, H., Zou, X., Fan, Y., Liu, J., Zhang, Z. & Zeng, C. (2020). Quantifying the impact of land cover changes on ecosystem service values in a rapidly urbanizing area: A case study of the central Guanzhong region, China. Environmental Monitoring and Assessment, 192(11), 682. https://doi.org/10.1007/s10661-020-08587-6
23. Maitra, S. & Pramanick, B. (2020, June 15). Causes and effect of soil erosion and its preventive measures. https://researchgate.net
24. Michalek, A., Zarnaghsh, A. & Husic, A. (2021). Modeling linkages between erosion and connectivity in an urbanizing watershed. Science of the Total Environment, 764, Article 144255.
25. Moisa, M. B., Asfaw, A., Tegegne, Y. & Abate, S. (2021). Impact of land-use and land-cover change on soil erosion using the RUSLE model and the geographic information system: A case of Temeji watershed, Western Ethiopia. Journal of Water and Climate Change, 12(7), 3404–3420. https://doi.org/10.2166/wcc.2021.025
26. Nadal-Romero, E., Revuelto, J., Errea, P., & López-Moreno, J. I. (2018). The application of terrestrial laser scanner and SfM photogrammetry in measuring erosion and deposition processes in two opposite slopes in a humid badlands area (central Spanish Pyrenees). Soil, 4(2), 167-188.
27. Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva, S., ... & Alewell, C. (2015). Rainfall erosivity in Europe. Science of the Total Environment, 511, 801-814.
28. Poesen, J., & Hooke, J. M. (1997). Erosion, flooding and channel management in Mediterranean environments of southern Europe. Progress in Physical Geography, 21(2), 157-199.
29. Remini, B., Achour, B. & Albergel, J. (2016). The impacts of human activities on sediment yield in Algeria. Hydrological Sciences Journal, 61(9), 1707-1715.
30. Renard, K. G., Foster, G. R., Weesies, G. A., McDool, D. K. & Yoder, D. C. (1997). Predicting soil erosion by water: A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). United States Department of Agriculture.
31. Vanmaercke, M., Ardizzone, F., Rossi, M., & Guzzetti, F. (2021). Exploring the effects of seismicity on landslides and catchment sediment yield: An Italian case study. Geomorphology, 384, 107710.
32. Van der Knijff, J. M., Jones, R. J. A., & Montanarella, L. (2000). Soil erosion risk assessment in Europe. EUR 19044 EN, Office for Official Publications of the European Communities, Luxembourg.
33. Vigiak, O., Borselli, L., Newham, L. T. H., McInnes, J. & Roberts, A. M. (2012). A tool for prioritising sediment management in large river basins. Journal of Hydrology, 468, 1-12.
34. Walling, D. E. (1983). The sediment delivery problem. Journal of Hydrology, 65(1-3), 209-237. https://doi.org/10.1016/0022-1694(83)90217-8
35. Wischmeier, W. H. & Smith, D. D. (1978). Predicting rainfall erosion losses - A guide to conservation planning. United States Department of Agriculture, Agriculture Handbook No. 537.
36. Yıldırım, Ü., Güler, C., Önol, B., Rode, M., & Jomaa, S. (2022). Modelling of the discharge response to climate change under RCP8.5 scenario in the Alata River Basin (Mersin, SE Turkey). Water, 14(3), 311. https://doi.org/10.3390/w14030311.
37. Zhang, H., Wei, J., Yang, Q., Baartman, J. E., Gai, L., Yang, X., Li, S., Yu, J., Ritsema, C. J. & Geissen, V. (2021). An improved USLE-C factor for estimating vegetation cover effects on soil erosion. Catena, 207, Article 105669.
38. Zhao, G., Mu, X., Wen, Z., Wang, F. & Gao, P. (2020). Assessing sediment connectivity and soil erosion by water in a representative catchment on the Loess Plateau, China. Catena, 199, 105100.