Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet Plateau

Wangping Li, Yadong Liu (), Xiaodong Wu, Lin Zhao, Tonghua Wu, Guojie Hu, Defu Zou, Yongping Qiao, Xiaoying Fan and Xiaoxian Wang
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Wangping Li: School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China
Yadong Liu: Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou 730000, China
Xiaodong Wu: Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou 730000, China
Lin Zhao: Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou 730000, China
Tonghua Wu: Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou 730000, China
Guojie Hu: Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou 730000, China
Defu Zou: Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou 730000, China
Yongping Qiao: Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou 730000, China
Xiaoying Fan: Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resource, Chinese Academy of Sciences, Lanzhou 730000, China
Xiaoxian Wang: School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China

Land, 2024, vol. 13, issue 11, 1-15

Abstract: Soil particle distribution is one of the basic parameters for many Earth system models, while the soil texture data are largely not available. This is especially true for complex terrains due to the difficulties in data acquisition. Here, we selected an area, Wenquan area, with rolling mountains and valleys, in the eastern Qinghai–Tibet Plateau (QTP) as the study area. Using the random forest model, we established quantitative models of silt, clay, and sand content, and environmental variables, including elevation, slope, aspect, plane curvature, slope curvature, topographic wetness index, NDVI, EVI, MAT, and MAP at different depths based on the survey data of 58 soil sample points. The results showed that sand content was the highest, accounting for more than 75% of the soil particles. Overall, the average values of clay and silt gradually decreased with increasing soil profile depth, while sand showed the opposite pattern. In terms of spatial distribution, clay and silt are higher in the southeast and lower in the northwest in each standard layer, while sand is just the opposite. The random forest regression model showed that vegetation condition was a controlling factor of soil particle size. These results showed that random forest applies to predicting the spatial distribution of soil particle sizes for areas with complex terrains.

Keywords: permafrost; machine learning; digital soil mapping; soil particle size distribution (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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