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Effects of Periglacial Landforms on Soil Erosion Sensitivity Factors and Predicted by Artificial Intelligence Approach in Mount Cin, NE Turkey

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Abstract

In this study, the differences in soil properties formed on various periglacial landforms located on slope land and high elevation so, this case create main problem against to soil erosion. The main aims of the study are to determine the physico-chemical properties and some soil erosion sensitivity parameters of the soils formed on the different periglacial landforms of Mount Cin and to predict those soil erosion sensitivity factor using artificial neural network (ANN). It was detected three different periglacial landforms on the Mount Cin. Stony earth circles spread over Cin Hill which is on the summit plain of Mount Cin, while non-sorted steps are located on the northern slopes of Cin Hill and Topkaya Hill. In addition, mud circle landforms spread to the south of Karaçakrak Hill. 25 soil samples were taken from the periglacial landforms in the study area. Afterwards, the physico-chemical properties of the samples were analysed in the laboratory. According to soil analysis from various periglacial landforms, the dominant soil texture is sandy loam: clay ranges from 5.61 to 16.79%, and sand from 48.61 to 76.72%. Also, the average soil erosion sensitivity factors, namely structure stability index (SSI), dispersion rate (DR), and crust formation (CF), were calculated at 29.65, 28.36, and 40.72%, respectively. Moreover, ANN is a model that can operate directly like the human brain. ANN uses the data of the current problem to make predictions. According to regression results of soil erosion sensitivity factors using ANN, the highest prediction rate was obtained for SSI (78%) and the lowest for DR (57%).

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Authors and Affiliations

  1. Department of Geography, Ardahan University, 75002, Ardahan, Turkey

    V. Dede

  2. Department of Geography, The Faculty of Economic, Administrative and Social Sciences, Samsun University, 55080, Samsun, Turkey

    İ. Demirağ Turan

  3. Department of Soil Science and Plant Nutrition, Faculty of Agriculture, Ondokuz Mayıs University, 55139, Samsun, Turkey

    O. Dengiz & S. Pacci

  4. Institute of Social Sciences, İstanbul University, 34119, İstanbul, Turkey

    S. Serin

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The authors declare that they have no conflict of interest related to the content of this manuscript. The authors have no relevant financial or non-financial interests to disclose.

AUTHORS’ CONTRIBUTIONS

All authors contributed to the study’s conception and design. Methodology, Conceptualization, and Resources were done by V. Dede and O. Dengiz. Supervision was performed by O. Dengiz. Material preparation, investigation, and analysis were performed by İ.D. Turan, S. Serin and S. Pacci. All maps were created by S. Serin, and V. Dede. The first draft of the manuscript was written by V. Dede, O. Dengiz and İ.D. Turan and all authors performed fieldworks and commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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The datasets generated and analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

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Dede, V., Turan, İ.D., Dengiz, O. et al. Effects of Periglacial Landforms on Soil Erosion Sensitivity Factors and Predicted by Artificial Intelligence Approach in Mount Cin, NE Turkey. Eurasian Soil Sc. 55, 1857–1870 (2022). https://doi.org/10.1134/S106422932260138X

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