# Spatiotemporal characteristics and driving factors of soil erosion in the Kangding River Basin (Southwest China) based on the RUSLE model

**Authors:** Yuqi Guan, Xiong Duan, Qinglian Deng, Bin Chen, Bingrui Su, Kun Zeng

PMC · DOI: 10.1371/journal.pone.0344489 · PLOS One · 2026-03-16

## TL;DR

This study analyzes soil erosion patterns and their drivers in the Kangding River Basin in China from 2000 to 2020 using GIS and machine learning models.

## Contribution

The novel use of the RUSLE model with Geographical Detector and SHAP algorithm to assess soil erosion drivers in the Kangding River Basin.

## Key findings

- Soil erosion modulus increased from 16.32 to 21.85 t·hm-2·a-1 between 2000 and 2005, then decreased to 11.16 t·hm-2·a-1 by 2020.
- Slope, land use, and vegetation coverage were identified as the top three factors influencing soil erosion.
- Slight and very slight erosion intensity dominated, with severity peaking in 2005 before declining.

## Abstract

Soil erosion is one of the most widespread environmental issues globally, posing serious threats to ecosystems and land resources. This study employs precipitation, soil, digital elevation model, and land-use data from 2000 to 2020 to quantitatively analyze the spatiotemporal patterns of land-use change and soil erosion in the Kangding River Basin through GIS-based spatial analysis and the RUSLE (Revised Universal Soil Loss Equation) model, and to evaluate soil stability across the watershed. Furthermore, using Geographical Detector (including single-factor detection and dual-factor interaction detection) and the SHAP (SHapley Additive exPlanations) algorithm to analyze the optimal machine learning model enables the assessment of the contribution of each driving factor to soil erosion. The results revealed that: (1) From 2000 to 2020, the areas of woodland and water body exhibited a decreasing trend, while cropland and construction land expanded steadily.(2) The soil erosion modulus in the Kangding River Basin first increased and then declined during the study period, rising from 16.32 t·hm-2·a-1 in 2000 to a peak of 21.85 t·hm-2·a-1 in 2005, and subsequently decreasing to 11.16 t·hm-2·a-1 by 2020.(3) The predominant erosion intensity was slight and very slight, with an increase in erosion severity between 2000 and 2005, followed by a gradual decrease thereafter.(4) The results of the geographical detector and SHAP analysis indicate that slope, land use, and vegetation coverage were the three most influential driving factors affecting soil erosion in the basin. These findings provide a scientific basis for comprehensive watershed management and land use planning in the Kangding River Basin, offering important theoretical support for soil and water conservation in the region.

## Full-text entities

- **Genes:** SHROOM4 (shroom family member 4) [NCBI Gene 57477] {aka MRXSSDS, SHAP, shrm4}
- **Diseases:** soil loss (MESH:D005242), erosion (MESH:D014077), water loss (MESH:D000069578), loss (MESH:D016388)
- **Chemicals:** organic carbon (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

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## Figures

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## References

69 references — full list in the complete paper: https://tomesphere.com/paper/PMC12991269/full.md

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Source: https://tomesphere.com/paper/PMC12991269