Journals / Türk Bilim ve Mühendislik Dergisi / 2023 / Cilt: 5 Sayı: 2

Soil Loss Models for Somalia

Toprak Kayıp Modellerinin Somali İçin Değerlendirilmesi

Abdinasir Abdullahi Mohamed(ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ, ZİRAAT FAKÜLTESİ)0000-0001-9183-5369
Levent Başayiğit(ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ, ZİRAAT FAKÜLTESİ)0000-0003-2431-5763
Pages
146–151
Publication Date
2023-12-29
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Continuous monitoring of sensitive areas over the years is recommended, considering the role of human activities such as ongoing deforestation, poor agricultural practices, and excessive grazing, which contribute to escalating erosion risks on Somali lands.

📌 3 Key Takeaways

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Objective & Hypothesis:Soil erosion stands as a significant environmental concern impacting both agricultural productivity and natural ecosystems across various regions worldwide.
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Key Findings & Data:The soil losses attributed to erosion exacerbate concerns about food security and land degradation in Somalia, a country already grappling with numerous socio-economic challenges.
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Conclusion & Impact:Continuous monitoring of sensitive areas over the years is recommended, considering the role of human activities such as ongoing deforestation, poor agricultural practices, and excessive grazing, which contribute to escalating erosion risks on Somali lands.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:CORINE · Erozyon · RUSLE

Abstract

Soil erosion stands as a significant environmental concern impacting both agricultural productivity and natural ecosystems across various regions worldwide. The soil losses attributed to erosion exacerbate concerns about food security and land degradation in Somalia, a country already grappling with numerous socio-economic challenges. This study aims to evaluate the erosion risk in Somalia by examining potential techniques that offer valuable insights for sustainable land management and resource planning. Emphasizing the utilization of remote sensing data, geographic information system (GIS) techniques, and hydrological modeling, the research highlights the exploration of erosion risk factors and their spatial distribution nationwide. Topographic data, soil properties, land use and land cover data, precipitation models, and vegetation indices could be employed to identify erosion-prone areas and sensitive points in Somalia. Furthermore, analyzing historical erosion data can aid in calibrating and validating predictive models. Continuous monitoring of sensitive areas over the years is recommended, considering the role of human activities such as ongoing deforestation, poor agricultural practices, and excessive grazing, which contribute to escalating erosion risks on Somali lands. Decision-makers should focus on methodologies that can be utilized to implement efficient erosion management techniques ensuring environmental sustainability across Somalia.

Özet

Toprak erozyonu, dünyanın birçok yerinde hem tarımsal üretkenliği hem de doğal ekosistemleri etkileyen önemli bir çevre sorunudur. Erozyon kaynaklı toprak kayıpları, zaten birçok sosyoekonomik sorunla boğuşan bir ülke olan Somali'de gıda güvensizliği ve arazi bozulması endişelerini şiddetlendiriyor. Bu araştırmanın amacı, sürdürülebilir arazi yönetimi ve kaynak planlaması için değerli bilgiler sağlayarak, Somali'deki erozyon riskini değerlendirmek ve toprak kayıplarını tahmin etmektir. Çalışma, uzaktan algılama verileri, coğrafi bilgi sistemi (GIS) teknikleri ve hidrolojik modelleme kullanarak erozyon risk faktörlerini ve ülke genelindeki mekansal dağılımını incelemektedir. Topografik veriler, toprak özellikleri, arazi kullanımı ve arazi örtüsü verileri, yağış modelleri ve bitki örtüsü indekslerinin tümü erozyona eğilimli alanları ve sıcak noktaları belirlemek için kullanılır. Ayrıca, tahmine dayalı modelleri kalibre etmek ve doğrulamak için tarihsel erozyon verileri analiz edilir, böylece doğruluk ve güvenilirlikleri artırılır. Bu çalışmanın bulgularına göre, Somali'nin önemli bir bölümü erozyon kaynaklı toprak kayıplarına karşı savunmasızdır. En savunmasız alanlar belirlenerek, paydaşların erozyon kontrolü ve toprak koruma çabaları için kaynakları önceliklendirmesine ve tahsis etmesine izin verilir. Ayrıca çalışma, ormansızlaşma, kötü tarım uygulamaları ve aşırı otlatma gibi insan faaliyetlerinin erozyon riskini artırmadaki rolünü vurgulamaktadır. Bu çalışmada oluşturulan tahmin modelleri, iklim değişkenliğini, arazi kullanımındaki değişiklikleri ve azaltma stratejilerini dikkate alarak çeşitli senaryolar altında toprak kayıplarını tahmin etmek için yararlı kaynaklar sunmaktadır. Bu tür tahmin yetenekleri, politika seçimlerine rehberlik etmek ve tarımsal üretkenliği iyileştirebilen, ekosistemleri koruyabilen ve Somali genelinde çevresel sürdürülebilirliği teşvik edebilen verimli erozyon yönetimi tekniklerini uygulamaya koymak için çok önemlidir.

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Cite This Article

Mohamed, A. A., Başayiğit, L. (2023). Soil Loss Models for Somalia. Türk Bilim ve Mühendislik Dergisi, Cilt: 5 Sayı: 2, 146–151. https://doi.org/10.55979/tjse.1336047

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References (36)

  1. Busacca, A. J., Cook, C., & Mulla, D. J. (1993). Comparing landscape-scale estimation of soil erosion in the palouse using Cs-137 and RUSLE. Journal of Soil and Water Conservation, 48(4), 361–367.
  2. Cohen, M. J., Shepherd, K. D., & Walsh, M. (2005). Empirical reformulation of the universal soil loss equation for erosion risk assessment in a tropical watershed. Geoderma, 124(3–4), 235–252. https://doi.org/10.1016/j.geoderma.2004.05.003
  3. ISRIC (1995). Water erosion assessment using reference soils of the ISIS database. National Soil Reference Collections and Database Workshop. Wageningen, Netherlands. Retrieved January 1, 2023, from https://www.isric.org/documents/document-type/isric-report-199514-water-erosion-assessment-using-reference-soils-isis
  4. Ding, J., & Richards, K. (2009). Preliminary modelling of sediment production and delivery in the Xihanshui River basin, Gansu, China. CATENA, 79(3), 277–287. https://doi.org/10.1016/j.catena.2009.05.014
  5. Elwell, H. A. (1996). Environmental monitoring of land degradation and soil erosion methods and techniques. Guidelines for the SADC region. Compiled for SADC-ELMS, Maseru.
  6. Elwell, H., & Stocking, M. (1982). Developing a simple yet practical method of soil-loss estimation. Tropical Agriculture, 59(1), 43–48. FAO 2003. Data Sets, Indicators and Methods to Assess Land Degradation in Drylands. FAO, Rome.
  7. Feddema, J. J. (1998). Estimated impacts of soil degradation on the African water balance and climate. Climate Research, 10(2), 127-141.
  8. Flacke, W., Auerswald, K., & Neufang, L. (1990). Combining a modified Universal Soil Loss Equation with a digital terrain model for computing high resolution maps of soil loss resulting from rain wash. Catena, 17(4-5), 383-397. https://doi.org/10.1016/0341-8162(90)90040-K
  9. Fullen, M. A. (2003). Soil erosion and conservation in northern Europe. Progress in physical geography, 27(3), 331-358. https://doi.org/10.1191/0309133303pp385ra
  10. Gisladottir, G., & Stocking, M. (2005). Land degradation control and its global environmental benefits. Land Degradation & Development, 16(2), 99-112. https://doi.org/10.1002/ldr.687
  11. Gao, P. (2008). Understanding watershed suspended sediment transport. Progress in Physical Geography, 32(3), 243-263. https://doi.org/10.1177/0309133308094849
  12. Gobin, A., Govers, G., Jones, R., Kirkby, M., Kosmas, C., & Gentile, A. R. (2003). Assessment and reporting on soil erosion. European Environment Agency, 94, 103.
  13. Hudson, C. A. (1987). A Regional Application of the SLEMSA in the Cathedral Peak Area of the Drakensberg (Doctoral dissertation, University of Cape Town).
  14. İrvem, A., Topaloğlu, F., & Uygur, V. (2007). Estimating spatial distribution of soil loss over Seyhan River Basin in Turkey. Journal of Hydrology, 336(1–2), 30–37. https://doi.org/10.1016/j.jhydrol.2006.12.009
  15. Jha, M. K., & Paudel, R. C. (2010). Erosion Predictions by Empirical Models in a Mountainous Watershed in Nepal. Journal of Spatial Hydrology, 10(1).
  16. Karabulut, M., & Küçükönder, M. (2008). Kahramanmaraş ovası ve çevresinde CBS kullanılarak erozyon alanlarının tespiti. KSÜ Fen ve Mühendislik Dergisi, 11(2), 14-22.
  17. Lakew, D., & Belayneh, A. (2012). A field guide on gully prevention and control. ENWM Project. Addis Ababa.
  18. Lal, R. (2001). Soil degradation by erosion. Land Degradation & Development, 12(6), 519–539. https://doi.org/10.1002/ldr.472
  19. Lal, R., Valentin, C., Blum, W. E. H., & Stewart, B. (2020). Methods for assessment of soil degradation. In CRC Press eBooks. https://doi.org/10.1201/9781003068716
  20. Lim, K. J., Sagong, M., Engel, B. A., Tang, Z., Choi, J., & Kim, K. (2005). GIS-based sediment assessment tool. CATENA, 64(1), 61–80. https://doi.org/10.1016/j.catena.2005.06.013
  21. Merritt, W., Letcher, R., & Jakeman, A. J. (2003). A review of erosion and sediment transport models. Environmental Modelling and Software, 18(8–9), 761–799. https://doi.org/10.1016/s1364-8152(03)00078-1
  22. Mitášová, H., & Iverson, L. R. (1996). Modelling topographic potential for erosion and deposition using GIS. International Journal of Geographical Information Systems, 10(5), 629–641. https://doi.org/10.1080/02693799608902101
  23. Morgan, R. P. C. (2005). Soil erosion and conservation: Third edition. Victoria: Blackwell Publishing.
  24. Okatan, A., Aydın, M. ve Urhan O. Ş. (2007). Coğrafi Bilgi Sistemlerinin Havza Amenajmanında Kullanımı ve Önemi, TMMOB Harita ve Kadastro Mühendisleri Odası Ulusal Coğrafi Bilgi Sistemleri Kongresi. 30 Ekim- 02 Kasım, Trabzon.
  25. Oldeman, L. R., Hakkeling, R. T. A., & Sombroek, W. G. (1991). World Map of the status of human-induced soil degradation: An Explanatory Note.
  26. Pimentel, D. (2006). Soil erosion: a food and environmental threat. Environment, Development and Sustainability, 8(1), 119–137. https://doi.org/10.1007/s10668-005-1262-8
  27. Pretorius, D. J. (1998). The development of land degradation monitoring and auditing techniques with the aid of remote sensing and GIS technology (Report No. GW/A/98/27).
  28. Renard, K. G. (1997). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). US Department of Agriculture, Agricultural Research Service.
  29. Renard, K. G., & Ferreira, V. (1993). RUSLE model description and database sensitivity. Journal of Environmental Quality, 22(3), 458–466. https://doi.org/10.2134/jeq1993.00472425002200030009x
  30. Sheikh¹, A. H., Palria, S., & Alam, A. (2011). Integration of GIS and universal soil loss equation (USLE) for soil loss estimation in a Himalayan watershed. Recent Research in Science and Technology, 3(3), 51-57.
  31. Shi, Z., Cai, C., Ding, S. W., Wang, T., & Chow, T. L. (2004). Soil conservation planning at the small watershed level using RUSLE with GIS: a case study in the Three Gorge Area of China. CATENA, 55(1), 33–48. https://doi.org/10.1016/s0341-8162(03)00088-2
  32. Teng, H., Liang, Z., Chen, S., Liu, Y., Rossel, R. a. V., Chappell, A., Wu, Y., & Shi, Z. (2018). Current and future assessments of soil erosion by water on the Tibetan Plateau based on RUSLE and CMIP5 climate models. Science of the Total Environment, 635, 673–686. https://doi.org/10.1016/j.scitotenv.2018.04.146
  33. Wynants, M., Kelly, C., Mtei, K., Munishi, L. K., Patrick, A., Rabinovich, A., Nasseri, M., Gilvear, D., Roberts, N., Boeckx, P., Wilson, G. A., Blake, W., & Ndakidemi, P. A. (2019). Drivers of increased soil erosion in East Africa’s agro-pastoral systems: changing interactions between the social, economic and natural domains. Regional Environmental Change, 19(7), 1909–1921. https://doi.org/10.1007/s10113-019-01520-9
  34. Yılmaz, E. (2006), Çamlıdere Baraj Havzasında Erozyon Problemi ve Risk Analizi, (Yüksek Lisans Tezi, Ankara Üniversitesi Sosyal Bilimler Enstitüsü)
  35. Zhou, P. (2008) Landscape-Scale Soil Erosion Modelling and Ecological Restoration For A Mountainous Watershed In Sichuan, China. Tropical Forestry Reports 35, University of Helsinki.
  36. Zhu, M. (2011). Soil erosion risk assessment with CORINE model: case study in the Danjiangkou Reservoir region, China. Stochastic Environmental Research and Risk Assessment, 26(6), 813–822. https://doi.org/10.1007/s00477-011-0511-7