Xu Keke, Dai Huimin, Zhang Xujiao, Chen Chaoqun, Liu Kai, Du Guanxin, Qian Cheng
School of Earth Sciences and Resources, China University of Geosciences(Beijing), Beijng, China.
Shenyang Center of China Geological Survey, Shenyang, Liaoning, China.
PLoS One. 2025 Jun 9;20(6):e0324368. doi: 10.1371/journal.pone.0324368. eCollection 2025.
Black soil has good properties and high fertility. Understanding the spatial distribution of black soil layer thickness is of great significance in promoting regional agricultural development, ecological environmental protection, and soil erosion control. However, traditional soil investigation methods often fail to provide detailed soil thickness information. This study focuses on a small watershed in Northeast China's black soil region. By integrating topographical parameters and vegetation-climate indicators, random forest and kriging methods (classical bayesian, ordinary, and simple) were used to estimate the spatial distribution of thickness of black soil layer. An integrated evaluation framework was developed by combining RUSLE-derived erosion estimates with black soil layer thickness, systematically incorporating both external erosive forces and inherent soil erosion resistance attributes. The results show that the random forest model outperformed the kriging models, with smaller RMSE (34.05 cm) and larger R² (0.57), especially when handling nonlinear, high-dimensional data. The predicted thickness of the black soil layer ranged from 16.2 cm to 107 cm, with a mean of 48.31 cm, closely matching the measured value of 48 cm. Elevation (EL) was found to be the most significant factor affecting the thickness of black soil layer. Soil erosion risk assessment revealed that areas with no risk and low risk accounted for 21.91% and 62.21%, respectively, while medium and high-risk areas made up 15.87% and 0.01%. No-risk areas were soil accumulation zones, while low-risk areas were mainly sloped farmland, where measures like terracing, adjusting crop ridge directions, and planting pedunculated vegetation were recommended. Medium- and high-risk areas should be addressed by returning farmland to forests and implementing engineering practices. This study offers a reference for thickness of black soil layer estimation and provides valuable insights for soil erosion risk management.
黑土具有良好的性质和高肥力。了解黑土层厚度的空间分布对于促进区域农业发展、生态环境保护和土壤侵蚀控制具有重要意义。然而，传统的土壤调查方法往往无法提供详细的土壤厚度信息。本研究聚焦于中国东北黑土区的一个小流域。通过整合地形参数和植被 - 气候指标，采用随机森林和克里金方法（经典贝叶斯、普通和简单）来估计黑土层厚度的空间分布。通过将基于RUSLE的侵蚀估计与黑土层厚度相结合，开发了一个综合评价框架，系统地纳入了外部侵蚀力和土壤固有抗侵蚀属性。结果表明，随机森林模型优于克里金模型，具有更小的均方根误差（RMSE，34.05厘米）和更大的决定系数（R²，0.57），尤其是在处理非线性、高维数据时。预测的黑土层厚度范围为16.2厘米至107厘米，平均值为48.31厘米，与测量值48厘米密切匹配。发现海拔（EL）是影响黑土层厚度的最重要因素。土壤侵蚀风险评估显示，无风险和低风险区域分别占21.91%和62.21%，而中风险和高风险区域分别占15.87%和0.01%。无风险区域是土壤堆积区，而低风险区域主要是坡耕地，建议采取梯田、调整作物垄向和种植有梗植被等措施。中高风险区域应通过退耕还林和实施工程措施来解决。本研究为黑土层厚度估计提供了参考，并为土壤侵蚀风险管理提供了有价值的见解。
