流入
黄土
腐蚀
水文学(农业)
地表径流
地质学
主管(地质)
冲沟侵蚀
水流动力
流域
环境科学
电流(流体)
液压头
黄土高原
构造盆地
旱地盐分
土壤科学
渗透(HVAC)
作者
Chengcheng Jiang,Zhao Jin,Wen Fan,Ningyu Yu,Enlong Liu
出处
期刊:Geoderma
[Elsevier BV]
日期:2026-01-19
卷期号:466: 117682-117682
标识
DOI:10.1016/j.geoderma.2026.117682
摘要
• The quantitative characterization identified catchment as a key driving factor of gully head erosion. • Stream power is the optimal hydrodynamic parameter for predicting gully head erosion on the Loess Plateau. • The critical thresholds under rainfall and inflow conditions were explored to predict gully head erosion on the Loess Plateau. Gully head erosion is considered a major form of soil degradation on the Loess Plateau, where distinctive topographic conditions promote runoff convergence during rainfall events and consequently intensify gully head retreat. However, systematic monitoring approaches and mitigation mechanisms under the combined effects of rainfall and inflow remain insufficiently understood. The objectives of this study are to reveal the synergistic mechanisms of rainfall and inflow driving gully head erosion through field experiments, and to establish hydrodynamic critical thresholds governing gully head erosion, thereby providing new insights for predicting erosion at the gully head by integrating topographic and hydraulic conditions. Through systematic field experiments, it was revealed that soil loss increased proportionally with both the rainfall intensity and the inflow rate. Moreover, catchment characteristics are the dominant factors influencing erosion dynamics at gully heads, with inflow playing a more significant role than rainfall in triggering gully wall expansion and collapse. Specifically, stream power is the optimal hydrodynamic parameter for predicting erosion rates, with a critical threshold of 2.33 N m −1 s −1 to distinguish stable and erosive conditions. Based on these findings, a dimensionless model was developed to predict gully head erosion under combined rainfall and inflow conditions, integrating both topographic and hydraulic parameters, and the model achieved high predictive accuracy ( R 2 = 0.843 , N SE = 0.788 ) for erosion initiation of gully head under complex rainfall-inflow interactions. This study establishes a simple and effective method for predicting erosion initiation and progression. These advances provide not only a mechanistic understanding of erosion drivers but also valuable scientific insights for rational engineering and management of the Loess Plateau.
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