Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet Plateau
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...
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2024-11-01
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| author | Wangping Li Yadong Liu Xiaodong Wu Lin Zhao Tonghua Wu Guojie Hu Defu Zou Yongping Qiao Xiaoying Fan Xiaoxian Wang |
| author_facet | Wangping Li Yadong Liu Xiaodong Wu Lin Zhao Tonghua Wu Guojie Hu Defu Zou Yongping Qiao Xiaoying Fan Xiaoxian Wang |
| author_sort | Wangping Li |
| collection | DOAJ |
| description | 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. |
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| issn | 2073-445X |
| language | English |
| publishDate | 2024-11-01 |
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| series | Land |
| spelling | doaj-art-e87115ae6e694cffabe4b371e6cb41292025-08-20T02:04:54ZengMDPI AGLand2073-445X2024-11-011311185510.3390/land13111855Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet PlateauWangping Li0Yadong Liu1Xiaodong Wu2Lin Zhao3Tonghua Wu4Guojie Hu5Defu Zou6Yongping Qiao7Xiaoying Fan8Xiaoxian Wang9School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, ChinaCryosphere 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, ChinaCryosphere 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, ChinaCryosphere 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, ChinaCryosphere 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, ChinaCryosphere 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, ChinaCryosphere 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, ChinaCryosphere 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, ChinaCryosphere 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, ChinaSchool of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, ChinaSoil 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.https://www.mdpi.com/2073-445X/13/11/1855permafrostmachine learningdigital soil mappingsoil particle size distribution |
| spellingShingle | Wangping Li Yadong Liu Xiaodong Wu Lin Zhao Tonghua Wu Guojie Hu Defu Zou Yongping Qiao Xiaoying Fan Xiaoxian Wang Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet Plateau Land permafrost machine learning digital soil mapping soil particle size distribution |
| title | Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet Plateau |
| title_full | Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet Plateau |
| title_fullStr | Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet Plateau |
| title_full_unstemmed | Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet Plateau |
| title_short | Soil Texture Mapping in the Permafrost Region: A Case Study on the Eastern Qinghai–Tibet Plateau |
| title_sort | soil texture mapping in the permafrost region a case study on the eastern qinghai tibet plateau |
| topic | permafrost machine learning digital soil mapping soil particle size distribution |
| url | https://www.mdpi.com/2073-445X/13/11/1855 |
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