Rize mikro havzasında erozyon duyarlılığının ICONA modeli ve coğrafi bilgi sistemi entegrasyonu ile mekânsal analizi

Öz

Toprak erozyonu, doğal kaynakların sürdürülebilir yönetimini tehdit eden en önemli arazi bozunumu süreçlerinden biridir. Bu çalışmada, Rize ili sınırları içerisinde yer alan bir mikro havzada erozyon riskinin mekânsal dağılımının belirlenmesi amacıyla ICONA erozyon risk modeli kullanılmıştır. Çalışma kapsamında, arazi örtüsü, arazi kullanımı-arazi örtüsü, jeoloji ve eğim gibi erozyon süreçlerini etkileyen temel çevresel faktörler Coğrafi Bilgi Sistemleri (CBS) ortamında analiz edilmiştir. Öncelikle arazi örtüsü ve arazi kullanım haritaları birleştirilerek toprak koruma haritası oluşturulmuş, ardından jeoloji ve eğim katmanlarının entegrasyonu ile potansiyel erozyon risk haritası elde edilmiştir. Son aşamada ise bu iki katmanın çakıştırılmasıyla ICONA erozyon risk haritası hazırlanmıştır. Elde edilen sonuçlar, çalışma alanının önemli bir bölümünde düşük ve orta düzeyde erozyon riskinin hâkim olduğunu göstermiştir. Bununla birlikte, özellikle havzanın güney kesimlerinde eğim değerlerinin yüksek olması, litolojik yapının ayrışmaya daha duyarlı özellikler göstermesi ve bitki örtüsünün görece zayıf olması nedeniyle yüksek ve çok yüksek erozyon riskine sahip alanların yoğunlaştığı belirlenmiştir. Çalışma sonuçları, erozyon riskinin havza ölçeğinde mekânsal olarak belirlenmesinde ICONA modelinin etkin bir araç olduğunu ortaya koymaktadır. Ayrıca elde edilen bulguların, erozyon kontrolü ve arazi yönetimi planlamalarında öncelikli alanların belirlenmesine katkı sağlayabileceği düşünülmektedir.

Anahtar Kelimeler

• Erozyon riski
• ICONA modeli
• CBS
• toprak koruma

Spatial analysis of erosion susceptibility in the Rize micro-watershed using the integration of the ICONA model and geographic information systems

Öz

Soil erosion is one of the most significant land degradation processes threatening the sustainable management of natural resources. In this study, the ICONA erosion risk model was applied to determine the spatial distribution of erosion risk within a micro-watershed located in Rize province, Türkiye. In this concept, major environmental factors influencing erosion processes, including land use-land cover, land use, geology, and slope were analyzed using Geographic Information Systems (GIS). First, a soil protection map was generated by combining land cover and land use maps. Subsequently, a potential erosion map was produced through the integration of geological and slope layers. In the final stage, the ICONA erosion risk map was created by overlaying these two layers. The results indicated that low and moderate erosion risk classes dominate a large portion of the study area. However, areas with high and very high erosion risk were mainly concentrated in the southern parts of the watershed due to higher slope values, lithological units more susceptible to weathering, and relatively sparse vegetation cover. The findings demonstrate that the ICONA model is an effective tool for identifying the spatial distribution of erosion risk at the watershed scale. Furthermore, the results may contribute to determining priority areas for erosion control and sustainable land management planning.

Anahtar Kelimeler

• Erosion risk
• ICONA model
• GIS
• soil protection

Kaynakça

1. Akay AE. 2005. The effects of forest roads on sediment production and erosion. Turkish Journal of Agriculture and Forestry, 29(2), 99–105.
2. Akay AE, Erdaş O, Reis M, Yüksel A. 2008. Estimating sediment yield from forest road surfaces in the eastern Black Sea region of Turkey. Environmental Monitoring and Assessment, 136, 95–103.
3. Arabameri A, Rezaei K, Cerda A, Lombardo L, Rodrigo-Comino J. 2019. GIS-based soil erosion susceptibility mapping using statistical and machine learning models in a semi-arid environment. Science of the Total Environment, 655, 1299–1312.
4. Bayramin İ, Dengiz O, Başkan O, Parlak M. 2003. Soil erosion risk assessment with ICONA model: Case study Beypazarı area. Turkish Journal of Agriculture and Forestry, 27, 105–116.
5. Borrelli P, Robinson DA, Fleischer LR, Lugato E, Ballabio C, Alewell C, Meusburger K, Modugno S, Schütt B, Ferro V, Bagarello V, Van Oost K, Montanarella L, Panagos P. 2020. An assessment of the global impact of 21st century land use change on soil erosion. Nature Communications, 11, 6145.
6. Bünemann EK, Bongiorno G, Bai Z, Creamer RE, De Deyn, G, De Goede R, Fleskens L, Geissen V, Kuyper TW, Mäder P, Pulleman M, Sukkel W, Van Groenigen JW, Brussaard L. 2018. Soil quality – A critical review. Soil Biology and Biochemistry, 120, 105–125.
7. Cumhurbaşkanlığı Strateji ve Bütçe Başkanlığı. 2023. On İkinci Kalkınma Planı (2024–2028). Ankara: T.C. Cumhurbaşkanlığı Strateji ve Bütçe Başkanlığı.
8. ÇMUSEP. 2019. Çölleşme ve Erozyonla Mücadele Ulusal Stratejisi ve Eylem Planı. Çölleşme ve erozyonla mücadele ulusal stratejisi ve eylem planı (2019-2030). Ankara: T.C. Tarım ve Orman Bakanlığı, Çölleşme ve Erozyonla Mücadele Genel Müdürlüğü.

9. Dengiz O, İmamoğlu A, Saygın F. 2014. Assessment of soil erosion risk using the ICONA model: A case study from the Black Sea region of Turkey. Environmental Monitoring and Assessment, 186, 6501–6518.
10. Doran JW, Parkin TB. 1994. Defining and assessing soil quality. In J. W. Doran, D. C. Coleman, D. F. Bezdicek B A. Stewart (Eds.), Defining soil quality for a sustainable environment (pp. 3–21). Soil Science Society of America. DSİ. 2010. Türkiye’de barajlarda sedimantasyon ve rezervuar kapasite kayıpları. Devlet Su İşleri Genel Müdürlüğü Yayınları, Ankara.
11. Eastman, J. R. (2012). IDRISI Selva Manual. Clark Labs-Clark University, Worcester, 45.
12. FAO. 2014. World reference base for soil resources 2014: International soil classification system for naming soils and creating legends for soil maps. Rome: Food and Agriculture Organization of the United Nations.
13. FAO ve ITPS. 2015. Status of the world’s soil resources (SWSR) – Main report. Food and Agriculture Organization of the United Nations.
14. García-Ruiz JM, Beguería S, Lana-Renault N, Nadal-Romero E, Cerdà A. 2015. Ongoing and emerging questions in water erosion studies. Land Degradation & Development, 26, 5–21.
15. Gyssels G, Poesen J, Bochet E, Li Y. 2005. Impact of plant roots on the resistance of soils to erosion by water: A review. Progress in Physical Geography, 29(2), 189–217.
16. ICONA 1988, Agresividad de la lluvia en España. Valores del factor R de la ecuación universal e pérdidas de suelo, Servicio de publicaciones del Ministerio de Agricultura, Pesca y Alimentación. Ed. Ariel, S.A, Barcelona, Madrid, pp. 292.
17. ICONA. 1991. Agresividad de la lluvia y erosión potencial en España. Instituto Nacional para la Conservación de la Naturaleza (ICONA), Ministerio de Agricultura, Pesca y Alimentación, Madrid, Spain.
18. IERE. 2025. Institute for Environmental Research and Education. How does soil erosion affect water quality?
19. Kanar E, Dengiz O. 2015. Madendere Havzasında Potansiyel Erozyon Risk Durumunun İki Farklı Parametrik Model Kullanarak Belirlenmesi ve Risk Haritalarının Oluşturulması. Türkiye Tarımsal Araştırmalar Dergisi. 2: 123-134
20. Karakoca E, Dengiz O, Özcan H. 2023. Assessment of soil erosion sensitivity using GIS-based models in watershed scale. Environmental Earth Sciences, 82, 412.
21. Kasap M. 2024. Using the ICONA model to assess the current erosion risk of the Hopa Stream catchment (Artvin, Türkiye). Forestist / Forestry related journal.
22. Lal R. 1998. Soil erosion impact on agronomic productivity and environment quality. Critical Reviews in Plant Sciences, 17(4), 319–464.
23. Lal R. 2001. Soil degradation by erosion. Land Degradation & Development, 12(6), 519–539.
24. Malczewski, J. (2004). GIS-based land-use suitability analysis: A critical overview. Progress in Planning.
25. Montgomery, D. R. (2007). Soil erosion and agricultural sustainability. Proceedings of the National Academy of Sciences, 104(33), 13268–13272.
26. Morgan RPC. 2005. Soil erosion and conservation (3rd ed.). Oxford, UK: Blackwell Publishing.
27. Pacci S Dengiz O, Alaboz P, Saygın F. 2024. Artificial neural networks in soil quality prediction: Significance for sustainable tea cultivation. Science of the Total Environment, 947, 174447.
28. Panagos P, Borrelli P, Poesen J, Ballabio C, Lugato E, Meusburger K, Alewell C. 2015. The new assessment of soil loss by water erosion in Europe. Environmental science & policy, 54, 438-447.
29. Panagos P, Borrelli P, Meusburger K. 2018. A new European slope length and steepness factor (LS-factor) for modeling soil erosion by water. Geosciences, 8(9), 1–17.
30. Panagos P, Ballabio C, Borrelli P, Meusburger K, Klik A, Rousseva S, Tadić MP, Michaelides S, Hrabalíková M, Olsen P, Aalto J, Lakatos M, Rymszewicz A, Dumitrescu A, Beguería, S, Alewell C. 2021. Rainfall erosivity in Europe. Science of the Total Environment, 769, 145252.
31. Pimentel D, Harvey C, Resosudarmo P, Sinclair K, Kurz D, McNair M, Crist S, Shpritz L, Fitton L, Saffouri R, Blair R. 1995. Environmental and economic costs of soil erosion and conservation benefits. Science, 267(5201), 1117–1123.
32. Pimentel D, Burgess M. 2013. Soil erosion threatens food production. Agriculture, 3(3), 443–463.
33. Pla I. 1997. A soil water balance model for monitoring soil erosion processes and effects on steep lands in the tropics. Soil Technology, 11(1), 17–30.
34. Poesen J. 2018. Soil erosion in the Anthropocene: Research needs. Earth Surface Processes and Landforms, 43, 64–84.
35. Saygın F, Şavşatlı Y, Dengiz O, Namlı A, Karataş A, Şenol ND, Demirkaya S. 2023. Soil quality assessment based on hybrid computational approach with spatial multi-criteria analysis and geographical information system for sustainable tea cultivation. The Journal of Agricultural Science, 161(2), 187-204.
36. Toy TJ, Foster GR, Renard KG. 2002. Soil erosion: Processes, prediction, measurement, and control. John Wiley & Sons.
37. Van Wambeke, A. 2000. The Newhall simulation model for estimating soil moisture and temperature regimes. Cornell University, Department of Crop and Soil Sciences, Ithaca, NY.
38. Verstraeten G, Poesen J, Demarée G, Salles C. 2009. Long-term (105 years) variability in rain erosivity as derived from 10-min rainfall depth data for Ukkel (Brussels, Belgium): Implications for assessing soil erosion rates. Journal of Geophysical Research, 111, F04006.
39. Yüksel A, Akay, A. E., Reis M. 2007. Estimating sediment yield from forest road surfaces in the eastern Black Sea region of Turkey. Environmental Monitoring and Assessment, 127, 347–356.
40. Zuazo VHD, Pleguezuelo CRR. 2008. Soil-erosion and runoff prevention by plant covers: A review. Agronomy for Sustainable Development, 28, 65–86.