Simulation Effect Analysis of RUSLE Model on Slope Soil Erosion Restored by Reclaimed Vegetation in Loess Plateau

LIAO Jun; JIAO Juying; YAN Zeng; LI Jianjun; ZHANG Shijie

doi:10.13870/j.cnki.stbcxb.2024.02.001

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Simulation Effect Analysis of RUSLE Model on Slope Soil Erosion Restored by Reclaimed Vegetation in Loess Plateau

更新时间：2025-03-12

- Simulation Effect Analysis of RUSLE Model on Slope Soil Erosion Restored by Reclaimed Vegetation in Loess Plateau
- Vol. 38, Issue 2, Pages: 97-108(2024)
- 作者机构：
  
  1. 西北农林科技大学水土保持研究所, 黄土高原土壤侵蚀与旱地农业国家重点实验室, 陕西杨凌,712100
  2. 中国科学院水利部水土保持研究所, 陕西杨凌,712100
  3. 安徽省&#,183
  4. 水利部淮河水利委员会水利科学研究院, 水利水资源安徽省重点实验室,合肥,230088
- 作者简介：
- 基金信息：
- DOI：10.13870/j.cnki.stbcxb.2024.02.001
  CLC： S157.1
- Published：2024
- 稿件说明：
移动端阅览
LIAO Jun, JIAO Juying, YAN Zeng, et al. Simulation Effect Analysis of RUSLE Model on Slope Soil Erosion Restored by Reclaimed Vegetation in Loess Plateau[J]. 2024, 38(2): 97-108.
DOI：

LIAO Jun, JIAO Juying, YAN Zeng, et al. Simulation Effect Analysis of RUSLE Model on Slope Soil Erosion Restored by Reclaimed Vegetation in Loess Plateau[J]. 2024, 38(2): 97-108. DOI： 10.13870/j.cnki.stbcxb.2024.02.001.

摘要

[目的] 为了探究RUSLE模型对黄土高原退耕植被恢复坡面土壤侵蚀模拟的效果。[方法] 基于陕北安塞区坊塌小流域内10个径流小区2016—2022年的降雨产流产沙监测资料

通过RUSLE模型中各因子在黄土高原的不同常用算法之间的变换组合

模拟144种因子组合下各退耕植被恢复坡面的土壤侵蚀量

采用纳什效率系数(NSE)和均方根误差(RMSE)评价模型模拟结果的有效性。[结果] 利用RUSLE模型144种因子组合模拟的退耕植被恢复坡面土壤侵蚀量

NSE范围为-38.47~0.19

RMSE范围为1.92~12.65 t/(hm2·a)

模拟效果较差

所选各因子算法难以适应退耕植被恢复坡面上的土壤流失量的评估

还需要对RUSLE模型各因子进一步改进。运用RUSLE模型对黄土高原退耕植被恢复坡面土壤侵蚀模拟时

建议尽可能采用时间分辨率高的数据减小对R因子的计算误差

综合考虑土壤有机质含量、土壤粒径与团粒结构组成和容重等土壤理化性质对K因子的影响

以及植被覆盖度、植被高度、枯落物、生物结皮等对C因子的影响

充分考虑10°以上的坡度

细化其LS因子的算法。[结论] RUSLE模型无法很好地适用于黄土高原退耕植被恢复坡面土壤侵蚀的模拟。研究结果为土壤侵蚀模型的研发及RUSLE模型在黄土高原植被恢复坡面的应用提供一定参考依据。

Abstract

[Objective] To explore the effectiveness of the Revised Universal Soil Loss Equation (RUSLE) model in simulating soil erosion on slope surfaces during vegetation restoration in the Loess Plateau. [Methods] This study utilized rainfall-runoff and sediment data from ten runoff plots in Ansai Fangta small watershed in northern Shaanxi Province during 2016—2022. Utilizing various commonly used algorithms for RUSLE model factors specific to the Loess Plateau

a total of 144 combinations of factors were simulated to estimate soil erosion on restored slopes. The Nash-Sutcliffe efficiency coefficient (NSE) and root mean square error (RMSE) were used to evaluate the effectiveness of the model simulations. [Results] The results indicated that the simulated soil erosion on restored slopes using the 144 factor combinations ranged from -38.47 to 0.19 for NSE and from 1.92 to 12.65 t/(hm2·a) for RMSE

suggesting limited model performance. The selected algorithms for RUSLE model factors appeared to be inadequate for assessing soil erosion on slopes undergoing vegetation restoration. Further improvements are needed for the individual factors within the RUSLE model. When applying RUSLE model to simulate soil erosion on restored slopes in the Loess Plateau

it is recommended to utilize data with high temporal resolution to reduce errors in calculating the R-factor

and comprehensively consider the effects of soil physical and chemical properties such as soil organic matter content

soil particle size and aggregate structure and bulk density on K-factor

and the the effects of vegetation coverage

vegetation height

litter

and biological crust and C-factor

full consider to slopes steeper than 10° in refining the LS-factor. [Conclusion] The RUSLE model is not well-suited for simulating soil erosion in the context of vegetation restoration on abandoned slopes in the Loess Plateau.This study provides some reference for the research and development of soil erosion model and the application of RUSLE model on the slope of vegetation restoration in the Loess Plateau.

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