Factors Affecting the Spatial and Temporal Variations in Soil Erodibility of China

Abstract

Soil erosion occurs extensively across China, leading to severe degradation of the land and ecosystem services. However, the spatial and temporal variations in soil erodibility (k) and the distribution of soil erosion across land use types and slopes remain unclear. We synthesized the results from 325 sites published in 152 literatures to analyze the factors affecting the k, such as land use type, climate, topography, soil, and vegetation restoration age. The results showed that areas with slopes >25° had a larger k factor (k = 0.1047) than did those with slope <6° (k = 0.0637) or 6–25° (k = 0.0832). The k from 2006 to 2011 (k = 0.0725) was higher than that from 1999 to 2005 (k = 0.058) and that from 2012 to 2016 (k = 0.0631). The k value initially increased with vegetation restoration age and then gradually decreased. Land use also had an impact on the k factor, with the k factor of cropland (k = 0.0697) being higher than that of grassland (k = 0.0663) but lower than that of forest (k = 0.0967). Across China, North Shaanxi, Heilongjiang, and South Guizhou, which are located in the Loess Plateau in Northwest China, the Black Soil region of Northeast China, and the Karst areas in Southwest China, respectively, were the three most severely eroded regions due to hydraulic erosion, frost‐thaw erosion, and high‐intensity erosion, respectively. Overall, the most important factors affecting the k were soil characteristics, followed by topography and climate. Among them, soil nitrogen and precipitation were the two most critical factors influencing the k.

Use of Visible and Near-Infrared Reflectance Spectroscopy Models to Determine Soil Erodibility Factor (K) in an Ecologically Restored Watershed

“…To accurately measure these properties, field soil samplings and laboratory analyses are necessary, which are labor intensive, time-consuming, and expensive. Furthermore, for a given soil, K factor changes with the expansion of space and variation of seasons [13], which further complicate the estimation of K factor. Thus, a reliable, fast, and economic measuring method is needed to assess K factor.…”

“…However, large bias exists when predicting heterogeneous samples because of the large differences in soil property and spectra [28]. In different land-use types, the soil parent materials, land cover, and range of the K factor values might vary [13]. If all the derived models do not contain the spectral diversity from a new certain (target) site, then it begs another question: Will a model calibrated from samples in a certain land-use type work in other landscape soils?…”

Modelling soil detachment by overland flow for the soil in the Tibet Plateau of China

“…Numerous studies have investigated the effects of soil properties on the soil detachment capacity, soil erodibility and the critical shear stress. However, the information on these parameters is seriously limited for the soil from the Tibetan Plateau 32 , where the dominant soil textures are characteristic of a low degree of development, parent materials, coarse particles, and detritus particle distribution 33 .…”

A Process‐Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services

“…The K factor is used to compute the average annual erosion (Renard, 1997), and the accuracy of the K factor determined the efficiency of the soil erosion model (Ostovari et al., 2016). Based on the K values from 325 sites published in 152 reports, we used Kriging interpolation to form a K surface (Zhu et al., 2019).…”