Uzaktan algılama teknikleri kullanarak RUSLE-C faktör haritalarının oluşturulması: Kırıkkale/Sarıkızlı havzası

Öz

Peyzaj bozulmalarına sebep olan en önemli fiziksel etkiler arasında erozyon başta gelmektedir. Toprak kayıpları sonucunda birçok habitat etkilenebilmektedir. Erozyon sonucu bozulmuş peyzajların iyileştirilmesi için toprak kayıplarının dağılımının ve miktarının bilinmesi gerekmektedir. Yenilenmiş Evrensel Toprak Kaybı Eşitliği (RUSLE) toprak kayıplarının tahmin edilmesin de kullanılan matematiksel bir modeldir. Bu çalışmada, Sarıkızlı Çayı havzasında uzaktan algılama ve Coğrafi Bilgi Sistemleri (CBS) kullanılarak RUSLE modeli parametrelerinden olan bitki yönetim faktörünün (C faktör) aylık olarak tahmin edilmesi ve haritalarının oluşturulması amaçlanmıştır. RUSLE-C faktör değerleri uydu görüntülerinden Normalize Edilmiş Fark Bitki İndeksi (NDVI) haritaları üretilerek ve sonra üstel regresyon eşitliği kullanılarak mekânsal olarak hesaplanmıştır. RUSLE-C faktörü en düşük haziran ayında 0,24±0,20, en yüksek aralık ayında 0,75±0,18 değerini almıştır. RUSLE-C faktörün en önemli özelliği değişiminin izlenmesi ile hassas alanların belirlenmesi ve de toprak koruma önlemlerinin nasıl alınması gerektiği konusunda yardımcı olmasıdır. Sonuç olarak, uzaktan algılama/CBS/erozyon model entegrasyonu ile peyzaj bozulmalarının mekânsal olarak daha hızlı sürede belirlenmesi onarımın daha hızlı, ekonomik ve doğru olarak yapılmasını sağlayacaktır.

Anahtar Kelimeler

• Peyzaj bozulması
• erozyon
• C Faktör
• NDVI
• RUSLE

Creation of RUSLE C factor maps using remote sensing techniques: Kırıkkale/Sarıkızlı basin

Abstract

Erosion is one of the most important physical mechanisms causing landscape degradation. Many habitats can be affected as a result of soil losses. It is necessary to know the distribution and amount of soil losses in order to improve landscapes degraded by erosion. The Revised Universal Soil Loss Equation (RUSLE) is a mathematical model used to estimate soil losses. In this study, it is aimed to estimate and map the cover management factor (C factor), which is one of the parameters of the RUSLE model, on a monthly by remote sensing and Geographic Information System (GIS) in the Sarıkızlı basin. For RUSLE-C factor value, Normalized Difference Vegetation Index (NDVI) map was produced from satellite images and then spatially calculated using an exponential regression equation. RUSLE-C factor has the lowest value of 0.24 ± 0.20 in June and the highest value of 0.75 ± 0.18 in December. The most important feature of the RUSLE-C factor is that it helps in determining the areas sensitive to degradation by monitoring the change and how to take soil conservation measures. As a result, the spatial determination of landscape degradation in a faster time with remote sensing/GIS /erosion model integration will enable the reclamation to be done faster, economically, and accurately.

Keywords

• Landscape degradation
• erosion
• C Factor
• NDVI
• RUSLE

Kaynakça

1. Aga, A. O., Chane, B., Melesse, A. M., 2018. Soil erosion modelling and risk assessment in data scarce rift valley lake regions, Ethiopia. Water, 10(11), 1684.
2. Almagro, A., Thomé, T. C., Colman, C. B., Pereira, R. B., Junior, J. M., Rodrigues, D. B. B., Oliveira, P.T.S., 2019. Improving cover and management factor (C-factor) estimation using remote sensing approaches for tropical regions. International Soil and Water Conservation Research, 7(4), 325-334.
3. Angima, S. D., Stott, D. E., O’Neill, M. K., Ong, C. K., Weesies, G. A., 2003. Soil erosion prediction using RUSLE for Central Kenyan Highland conditnons. Agriculture Ecosystems and Environment, 97, 295-308.
4. Benavidez, R. A., 2018. Understanding the effect of changing land use on floods and soil erosion in the Cagayan de Oro catchment, (Unpublished doctoral dissertation), Victoria University of Wellington, New Zealand.
5. Berberoglu, S., Cilek, A., Kirkby, M., Irvine, B., Donmez, C., 2020. Spatial and temporal evaluation of soil erosion in Turkey under climate change scenarios using the Pan-European Soil Erosion Risk Assessment (PESERA) model. Environmental Monitoring and Assessment, 192(8), 1-22.
6. Biddoccu, M., Ferraris, S., Opsi, F., Cavallo, E., 2016. Long-term monitoring of soil management effects on runoff and soil erosion in sloping vineyards in Alto Monferrato (North–West Italy). Soil and Tillage Research, 155, 176-189. Bogunovic, I., Pereira, P., Kisic, I., Sajko, K., & Sraka, M., 2018. Tillage management impacts on soil compaction, erosion and crop yield in Stagnosols (Croatia). Catena, 160, 376-384.
7. Carlson, T. N, Ripley, D. A., 1997. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3), 241-252. Cinnirella,, S., Iovino, F., Porto, P., Ferro, V., 1998. Anti‐erosive effectiveness of Eucalyptus coppices through the cover management factor estimate. Hydrological processes, 12(4), 635-649.
8. Demirci, A., & Karaburun, A., 2012. Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed, northwest Turkey. Environmental Earth Sciences, 66(3), 903-913.

9. Durigon, V, Carvalho, D.F, Antunes, M. A. H, Oliveira, P. T. S, Fernandes, M. M., 2014. NDVI time series for monitoring RUSLE cover management factor in a tropical watershed. International Journal of Remote Sensing, 35(2), 441-453.
10. Erdogan, E. H., Erpul, G., & Bayramin, İ., 2007. Use of USLE/GIS methodology for predicting soil loss in a semiarid agricultural watershed. Environmental Monitoring and Assessment, 131(1), 153-161.
11. Gabriels, D., Ghekiere, G., Schiettecatte, W., Rottiers, I., 2003. Assessment of USLE cover-management C-factors for 40 crop rotation systems on arable farms in the Kemmelbeek watershed, Belgium. Soil and Tillage Research, 74(1), 47-53.
12. Ganasri, B. P., & Ramesh, H., (2016). Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin. Geoscience Frontiers, 7(6), 953-961.
13. Golosov, V. N., Collins, A. L., Dobrovolskaya, N. G., Bazhenova, O. I., Ryzhov, Y. V., & Sidorchuk, A. Y., 2021. Soil loss on the arable lands of the forest-steppe and steppe zones of European Russia and Siberia during the period of intensive agriculture. Geoderma, 381, 114678.
14. Hacısalihoğlu, S., Mert, A., Negiz, M. G, Muys, B., 2010. Soil loss prediction using universal soil loss equation (USLE) simulation model in a mountainous area in Aglasun district, Turkey. African Journal of Biotechnology, 9(24), 3589.
15. Hudson, N. W., Jackson, D. C., 1959. Results achieved in the measurement of Erosion and Run-off in Southern Rhodesia. In Conférence interafricaine sur les sols. 3, 575-583.
16. Ismail, J., Ravichandran, S., 2008. RUSLE2 model application for soil erosion assessment using remote sensing and GIS. Water Resources Management, 22(1): 83-102.
17. Karaburun, A., 2010. Estimation of C factor for soil erosion modeling using NDVI in Buyukcekmece watershed. Ozean Journal of Applied Sciences, 3(1): 77–85.
18. Kirkby, M. J., Irvine, B. J., Jones, R. J., Govers, G. 2008. The PESERA coarse scale erosion model for Europe. I.–Model rationale and implementation. European Journal of Soil Science, 59(6), 1293-1306.
19. Laflen, J. M, Colvin, T. S., 1981. Effect of crop residue on soil loss from continuous row cropping. Transactions of the ASAE, 24(3), 605-609.
20. Lense, G. H. E, Moreira, R. S, Bócoli, F. A, Avanzi, J. C, Teodoro, A. E. D. M, Mincato, R. L., 2020. Estimation of sediments produced in a subbasin using the Normalized Difference Vegetation Index. Ciência e Agrotecnologia, 44.
21. Maetens, W, Vanmaercke, M, Poesen, J, Jankauskas, B, Jankauskiene, G, Ionita, I., 2012. Effects of land use on annual runoff and soil loss in Europe and the Mediterranean: A meta-analysis of plot data. Progress in Physical Geography, 36(5), 599-653.
22. Maltsev, K., & Yermolaev, O., 2020. Assessment of soil loss by water erosion in small river basins in Russia. Catena, 195, 104726.
23. Mohammed, S., Alsafadi, K., Talukdar, S., Kiwan, S., Hennawi, S., Alshihabi, O., ... & Harsanyie, E., 2020. Estimation of soil erosion risk in southern part of Syria by using RUSLE integrating geo informatics approach. Remote Sensing Applications: Society and Environment, 20, 100375.
24. Morgan, R. P. C., 2009. Soil erosion and conservation. John Wiley & Sons.
25. Mukharamova, S., Saveliev, A., Ivanov, M., Gafurov, A., & Yermolaev, O., 2021. Estimating the Soil Erosion Cover-Management Factor at the European Part of Russia. ISPRS International Journal of Geo-Information, 10(10), 645. Mutchler, C. K., McDowell, L. L., Johnson, J. R., 1985. Erosion from reduced-till cotton. In Proceedings of the 1985 Southern Region No-Till Conference, Griffin, GA pp. 156-158.
26. Oliveira, P. T. S, Nearing, M. A., Wendland, E., 2015. Orders of magnitude increase in soil erosion associated with land use change from native to cultivated vegetation in a Brazilian savannah environment. Earth Surface Processes and Landforms, 40(11), 1524-1532.
27. Ozcan, A. U., Erpul, G., Basaran, M., & Erdogan, H. E., 2008. Use of USLE/GIS technology integrated with geostatistics to assess soil erosion risk in different land uses of Indagi Mountain Pass—Cankırı, Turkey. Environmental Geology, 53(8), 1731-1741.
28. Özcan, A. U., 2016. CBS ve RUSLE teknolojisi yardımıyla Çankırı-Ekinne Göleti su toplama havzasında toprak kayıplarının tahmin edilmesi. TÜCAUM Uluslararası CoğrafyaSempozyumu, 668-674, Ankara.
29. Özcan, A. U, Aytaş, İ., 2020. Effects of soil erosion on doline lake degradation within karst landscapes: Bakkal Lake, Turkey. Environmental Monitoring and Assessment, 192(140).
30. Özcan, A. U., 2021. Sulakyurt Kalıntı Anadolu Palamut Meşesi (Quercus ithaburensis Decne subsp. macrolepis (Kotschy) Hedge & Yalt.) Ormanı, tehditler ve koruma önerileri. Turkish Journal of Forestry, 22(1), 8-16.
31. Özhan, S, Balcı, N, Özyuvacı, N, Hızal, A, Gökbulak, F. ve Serengil, Y., 2005. Cover and management factors for the universal soilloss equation for forest ecosystems in The Marmara Region, Turkey. Forest and Ecology Management, 214, 118–123.
32. Panagos, P., Borrelli, P., Meusburger, K., Alewell, C., Lugato, E., & Montanarella, L., 2015. Estimating the soil erosion cover-management factor at the European scale. Land use policy, 48, 38-50.
33. Panagos, P., Balbabio, C., Monatanarella, L., 2016. Mapping topsoil physical properties at European scale using the LUCAS database. Geoderma. 261, 110-123.
34. Panagos, P, Imeson, A, Meusburger, K, Borrelli, P, Poesen, J, Alewell, C., 2016. Soil conservation in Europe: wish or reality? Land Degradation & Development, 27(6), 1547-1551.
35. Pena, S. B, Abreu, M. M., Magalhães, M. R., Cortez, N., 2020. Water erosion aspects of land degradation neutrality to landscape planning tools at national scale. Geoderma, 363, 114093.
36. Pınar, M. Ö., Şahin, S., Madenoğlu, S., Erpul, G., 2020. Derinöz Baraj Havzası’nda şiddetli erozyon alanlarının belirlenmesi ve rezervuar sediment yükünün hesaplanmasi. Su Kaynakları, 5(2), 16-23.
37. Polykretis, C., Alexakis, D. D., Grillakis, M. G., & Manoudakis, S., 2020. Assessment of intra-annual and inter-annual variabilities of soil erosion in Crete Island (Greece) by incorporating the Dynamic “Nature” of R and C-Factors in RUSLE modeling. Remote Sensing, 12(15), 2439.
38. Purevdorj, T. S., Tateishi, R., Ishiyama, T., Honda, Y., 1998. Relationships between percent vegetation cover and vegetation indices. International Journal of Remote Sensing, 19(18), 3519-3535.
39. Renard, K. G., 1997. Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). United States Government Printing.
40. Renard, K. G., Foster, G. R., Weesies, G. A., Porter, J. P., 1991. RUSLE: Revised universal soil loss equation. Journal of Soil and Water Conservation, 46(1), 30-33.
41. Renard, K. G, Foster, G. A, Weesies, D. A., McCool, D. K, Yoder, D. C., 1997. Predicting Soil Erosion by Water: a Guide to Conservation Planning with The Revised Universal Soil Loss Equation (RUSLE), Agriculture Handbook No. 703. USDA, Washington, DC.
42. Ruhe, R. V., 1969. Quaternary landscapes in Iowa: Ames. Iowa State University Press, 2, 55.
43. Saygın, S. D, Ozcan, A. U, Basaran, M., Timur, O. B, Dolarslan, M., Yılman, F. E, Erpul, G., 2014. The combined RUSLE/SDR approach integrated with GIS and geostatistics to estimate annual sediment flux rates in the semi-arid catchment, Turkey. Environmental Earth Sciences, 71(4), 1605-1618.
44. Schmidt, S., Alewell, C., Meusburger, K., 2018. Mapping spatio-temporal dynamics of the cover and management factor (C-factor) for grasslands in Switzerland. Remote Sensing of Environment, 211, 89-104.
45. Şahin, Ş., Kurum, E., 2002. Erosion risk analysis by GIS in environmental impact assessments: a case study—Seyhan Köprü Dam construction. Journal of Environmental Management, 66(3), 239-247.
46. Tanyaş, H, Kolat, Ç, Süzen, M. L., 2015. A new approach to estimate cover-management factor of RUSLE and validation of RUSLE model in the watershed of Kartalkaya Dam. Journal of Hydrology, 528, 584-598.
47. Van der Knijff, J. M. F., Jones, R. J. A., Montanarella, L., 2000. Soil erosion risk assessment in Italy. European Soil Bureau, European Commission.
48. Vatandaşlar, C., & Yavuz, M., 2017. Modeling cover management factor of RUSLE using very high-resolution satellite imagery in a semiarid watershed. Environmental Earth Sciences, 76(2), 65.
49. Wang, G., Wente, S., Gertner, G.Z., Anderson, A., 2002. Improvement in mapping vegetation cover factor for the universal soil loss equation by geostatistical methods with Landsat Thematic Mapper images. International Journal of Remote Sensing, 23(18), 3649-3667.
50. Wischmeier, W. H., 1975. Estimating the soil loss equations cover and management factor for undisturbed areas. Present and prospective technology for predicting sediment yields and sources, 118-124.
51. Wischmeier, W. H., Smith, D. D., 1978. Predicting rainfall erosion losses: a guide to conservation planning (No. 537). Department of Agriculture, Science and Education Administration, USA.
52. Yang, X., Zhang, X., Lv, D., Yin, S., Zhang, M., Zhu. Q., ... and Liu, B., 2020. Remote sensing estimation of the soil erosion cover‐management factor for China's Loess Plateau. Land Degradation & Development, 31(15), 1942-1955.
53. Yavuz, M., Tufekcioglu, M., 2019. Estimating surface soil losses in the mountainous semi-arid watershed using RUSLE and geospatial technologies. Fresenius Environ Bull, 28(4), 2589-2598.
54. Yıldız, H., Mermer, A., Ünal, E., Akbaş, F., 2012. Türkiye bitki örtüsünün NDVI verileri ile zamansal ve mekansal analizi. Tarla Bitkileri Merkez Araştırma Enstitüsü Dergisi, 21(2), 50-56.
55. Zare, M., Samani, A. N., Mohammady, M., Salmani, H., & Bazrafshan, J., 2017. Investigating effects of land use change scenarios on soil erosion using CLUE-s and RUSLE models. International journal of environmental science and technology, 14(9), 1905-1918.
56. Zhou, P., Luukkanen, O., Tokola, T., Nieminen, J., 2008. Effect of vegetation cover on soil erosion in a mountainous watershed. Catena,75(3), 319-325.
57. Zivotic, L., Perovic, V., Jaramaz, D., Dordevic, A., Petrovic, R., Todorovic, M., 2012. Application of USLE, GIS, and remote sensing in the assessment of soil erosion rates in southeastern Serbia. Polish Journal of Environmental Studies, 21, 1929–1935.