Pedosphere 30(4): 443--456, 2020
ISSN 1002-0160/CN 32-1315/P
©2020 Soil Science Society of China
Published by Elsevier B.V. and Science Press
| Modelling soil erodibility in mountain rangelands of southern Kyrgyzstan |
Maksim KULIKOV1 , Udo SCHICKHOFF1, Alexander GRÖNGRÖFT2, Peter BORCHARDT1 |
1Centrum für Erdsystemforschung und Nachhaltigkeit(CEN), Center for Earth System Research and Sustainability, Institute of Geography, University of Hamburg, Hamburg D-20146(Germany)
2Centrum für Erdsystemforschung und Nachhaltigkeit(CEN), Center for Earth System Research and Sustainability, Institute of Soil Science, University of Hamburg, Hamburg D-20146(Germany) |
| Corresponding Author:Maksim KULIKOV |
| ABSTRACT |
| Soil erosion in mountain rangelands in Kyrgyzstan is an emerging problem due to vegetation loss caused by overgrazing. It is further exacerbated by mountain terrain and high precipitation values in Fergana range in the south of Kyrgyzstan. The main objective of this study was to map soil erodibility in the mountainous rangelands of Kyrgyzstan. The results of this effort are expected to contribute to the development of soil erodibility modelling approaches for mountainous areas. In this study, we mapped soil erodibility at two sites, both representing grazing rangelands in the mountains of Kyrgyzstan and having potentially different levels of grazing pressure. We collected a total of 232 soil samples evenly distributed in geographical space and feature space. Then we analyzed the samples in laboratory for grain size distribution and calculated soil erodibility values from these data using the Revised Universal Soil Loss Equation (RUSLE) K-factor formula. After that, we derived different terrain indices and ratios of frequency bands from ASTER GDEM and LANDSAT images to use as auxiliary data because they are among the main soil forming factors and widely used for prediction of various soil properties. Soil erodibility was significantly correlated with channel network base level (geographically extrapolated altitude of water channels), remotely sensed indices of short-wave infrared spectral bands, exposition, and slope degree. We applied multiple regression analysis to predict soil erodibility from spatially explicit terrain and remotely sensed indices. The final soil erodibility model was developed using the spatially explicit predictors and the regression equation and then improved by adding the residuals. The spatial resolution of the model was 30 m, and the estimated mean adjusted coefficient of determination was 0.47. The two sites indicated different estimated and predicted means of soil erodibility values (0.035 and 0.039) with a 0.05 significance level, which is attributed mainly to the considerable difference in elevation. |
| Key Words: channel network base level,K-factor,LANDSAT,RUSLE,soil enhancement ratio,soil mapping,slope,terrain |
| Citation: Kulikov M, Schickhoff U, Gröngröft A, Borchardt P. 2020. Modelling soil erodibility in mountain rangelands of southern Kyrgyzstan. Pedosphere. 30(4): 443–456. |
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