He Yanhu, Yang Yuyin, Xu Daoguo, Wang Zirui
Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China.
Sci Rep. 2025 Feb 10;15(1):4889. doi: 10.1038/s41598-025-88386-6.
Soil erosion contributes to the irreversible loss of soil organic carbon (SOC) into rivers (SOCR), posing risks to food security and carbon cycle assessments. Red soil regions, characterized by high carbon sink potential and selenium enrichment, are particularly vulnerable. However, existing studies largely rely on small-scale experiments, with limited understanding of basin-scale SOCR dynamics and their driving factors. This study integrates the Soil and Water Assessment Tool (SWAT) for sediment yield simulation and a Soil Organic Carbon Content (SOCC) model to quantify SOCR at the basin scale. A Random Forest-based prediction model was developed to explore the spatial-temporal variability and driving mechanisms of SOCR in the Dongjiang River Basin (DRB), a representative red soil region in southern China. Results indicate significant spatial-temporal heterogeneity, with higher SOCR observed in downstream, human-disturbed areas during flood seasons. The model demonstrates excellent performance (R²>0.9). Key drivers of SOCR variability include sediment yield, cultivated land area (CULT), and urban land area (TOWN), with urbanization showing stronger sensitivity than cultivation due to factors such as city size and impervious surfaces. The proposed framework reveals the dynamic change characteristics of SOCR and its driving mechanism, which has the potential to be generalized to other basins with similar studies, and provides a technical support for land resource management and carbon cycling in the erosion-prone red soil region.
土壤侵蚀导致土壤有机碳（SOC）不可逆地流失到河流中（SOCR），对粮食安全和碳循环评估构成风险。红壤地区具有高碳汇潜力和富硒特征，尤其脆弱。然而，现有研究很大程度上依赖于小规模实验，对流域尺度的SOCR动态及其驱动因素了解有限。本研究整合了用于泥沙产量模拟的土壤和水资源评估工具（SWAT）以及土壤有机碳含量（SOCC）模型，以量化流域尺度的SOCR。开发了基于随机森林的预测模型，以探索中国南方典型红壤地区东江流域（DRB）SOCR的时空变异性及其驱动机制。结果表明存在显著的时空异质性，在洪水季节下游受人类干扰的地区观察到较高的SOCR。该模型表现出优异的性能（R²>0.9）。SOCR变异性的关键驱动因素包括泥沙产量、耕地面积（CULT）和城市土地面积（TOWN），由于城市规模和不透水表面等因素，城市化表现出比耕种更强的敏感性。所提出的框架揭示了SOCR的动态变化特征及其驱动机制，有潜力推广到其他进行类似研究的流域，并为易侵蚀红壤地区的土地资源管理和碳循环提供技术支持。
