Soil Texture and Its Relationship with Environmental Factors on the Qinghai–Tibet Plateau

Abstract

Soil texture data are the basic input parameters for many Earth System Models. As the largest middle–low altitude permafrost regions on the planet, the land surface processes on the Qinghai–Tibet Plateau can affect regional and even global water and energy cycles. However, the spatial distribution of soil texture data on the plateau is largely unavailable due to the difficulty of obtaining field data. Based on collection data from field surveys and environmental factors, we predicted the spatial distribution of clay, silt, and sand contents at a 1 km resolution, from 0–5, 5–15, 15–30, 30–60, 60–100, and 100–200 cm soil depth layers. The random forest models were constructed to predict the soil texture according to the relationships between environmental factors and soil texture data. The results showed that the soil particles of the QTP are dominated by sand, which accounts for more than 70% of the total particles. As for the spatial distribution, silt and clay contents are high in the southeast plateau, and low values of silt and clay mainly appeared in the northwest plateau. Climate and NDVI values are the most important factors that affect the spatial distribution of soil texture on the QTP. The results of this study provide the soil texture data at different depths for the whole plateau at a spatial resolution of 1 km, and the dataset can be used as an input parameter for many Earth System Models.

Keywords

• digital soil mapping
• machine learning
• soil particle size
• random forest
• soil pits