Gully erosion susceptibility maps and influence factor analysis in the Lhasa River Basin on the Tibetan Plateau, based on machine learning algorithms

CATENA(2024)

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摘要
The environment of the Tibetan Plateau is under stress due to the warming climate and increased human activity, which also increases the risk of soil erosion. Gully erosion is one of the main environmental problems in the Tibetan Plateau. Taking Lhasa River Basin as a representative, investigating the spatial variation and influencing factors in this area will help to understand the current status and mechanism of gully erosion. However, gully erosion factor analysis has not been carried out at the regional scale. Therefore, three machine learning algorithms, including Random Forest (RF), Support Vector Machine, and Logistic Regression, were used to analyze 2224 samples and 18 influencing factors and detect the gully erosion susceptibility in the Lhasa River Basin. Seventy percent of the samples were used to train the model and rank the influencing factors by importance, and 30% were used to assess the prediction ability of the model. Approximately 15%-20% of the study area has a high or very high gully erosion susceptibility. The slopes of the lower Lhasa River and the Nyenchen Tanglha valleys were identified as areas with a high gully erosion susceptibility. The RF model exhibits the best performance, with area under the curve (AUC) values of 0.969 and 0.894 for the training and testing datasets, respectively. The main factors affecting the occurrence of gully erosion were determined to be the elevation, normalized difference vegetation index, relief, human footprint, mean annual temperature, and distance to the residential area. Elevation has the greatest effect on gully erosion, which can be explained as elevation indirectly controls gully erosion by affecting human activities and rainfall. The findings of this study provide insights into the effects of human activities, climate and permafrost on soil erosion and can serve as a basis for regional land use planning and gully erosion prevention and control in the Tibetan Plateau.
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关键词
Gully erosion,Machine learning,Random Forest,Tibetan Plateau,Factor importance
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