EGU24-6991, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-6991
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Calculation and Analysis of Soil Erodibility Factor (K) on a Global Scale

Miaomiao yang, Qinke Yang, Keli Zhang, Guowei Pang, Chunmei Wang, Lei Wang, and Yongqing Long
Miaomiao yang et al.
  • Northwest University, College of Urban and Environment, geography, China (mmyang@stumail.nwu.edu.cn)

The soil erodibility factor (K) is the main data required for regional soil erosion investigation and mapping using soil erosion models. USLE-K, RUSLE2-K, EPIC-K and Dg-K are four widely used methods for calculating soil erodibility factor (K). However, it remains to be studied which algorithm is more suitable to calculate soil erodibility factor (K) in the global scale. While, soil erodibility factor (K) is mostly calculated based on soil physical and chemical property data, which does not involve the content of rock fragments in these algorithms. However, the amount of rock fragments and thier distribution difference have a certain influence on soil physical and chemical properties, and then affect the accuracy of the estimation of soil erodibility factor (K). In this paper, USLE-K, RUSLE2-K, EPIC-K and Dg-K algorithms were used to estimate global soil erodibility factor (K), and its spatial pattern and main controlling factors were analyzed. In this paper, the measured data of soil erodibility factor (K) were retrieved by literature search, and the measured database of K factor value was established. The rationality of the results of the above four algorithms was analyzed, and the above four algorithms for calculating K factor were modified according to the measured database of K factor. At the same time, USLE-K and RUSLE2-K algorithm are taken as an example to calculate the effect of rock fragments in the soil profile and rock fragments on the soil surface. The results showed that (1) The spatial pattern of global K factors estimated by the USLE-K, RUSLE2-K, EPIC-K and Dg-K models is similar, but the values in the K surfaces are different in some extent. (2) Comparing to 106 measured values, the mean value of estimated RUSLE2-K is the closest to the measured K factor, followed by the USLE-K algorithm and the EPIC-K algorithm, while the estimated K by Dg-K algorithm is quite different from the measured K factor. (3) The presence of rock fragment in the soil profile increased the global soil erodibility factor. The rock fragment on the soil surface reduces soil erodibility. This article made the calculation of K more complete and accurate, thereby improving the accuracy of regional soil erosion estimation. And provide the necessary scientific basis for the selection of K algorithms globally.

How to cite: yang, M., Yang, Q., Zhang, K., Pang, G., Wang, C., Wang, L., and Long, Y.: Calculation and Analysis of Soil Erodibility Factor (K) on a Global Scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6991, https://doi.org/10.5194/egusphere-egu24-6991, 2024.