Abstract

AbstractStudying the distribution patterns and controlling mechanisms of soil organic carbon (SOC) based on the comprehensive performance of vegetation restoration and check dams at the watershed scale is important for understanding carbon cycling processes in nature. Two typical watersheds (Xinshui River and Zhujiachuan watershed) of the Loess Plateau were selected to evaluate the factors affecting the change in SOC content, and then the key factors were considered in the genetic algorithm‐support vector regression (GA‐SVR) model to predict SOC content. The results showed that the topography, vegetation, and soil characteristics had significant effects on the SOC content in the upland hillslopes, while the SOC content in the check dams was significantly affected by depth and soil characteristics. The soil organic carbon storage (TSOC) in the check dams could be evaluated and predicted by the vegetation index (NGRDI) and area of the subwatershed. The GA‐SVR model had good prediction accuracy and stable performance in predicting SOC content. According to the model simulation results, bulk density (BD), mean weight diameter (MWD), elevation, NGRDI, clay ratio (CR), and slope could be used to predict the surface SOC content of the Loess Plateau. Furthermore, depth, CR, MWD, BD, and median particle size (D50) could be applied in the model to predict the SOC content at different depths in the check dams. This study explored the potential control factors of SOC content and predicted SOC content from multiple angles, which can provide basic support for the study of the carbon sequestration on the Loess Plateau.

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