Elucidating the response mechanisms of hydrological and sediment connectivity to the river network structure, vegetation, and topographic features in the Jinghe River Basin

Abstract The management of basin water and soil resources greatly benefits from investigating the spatial changes and primary determinants of hydrological and sediment connectivity from perspectives of topographic features, vegetation characteristics, structural features of river networks. However, quantifying the effects of influencing factors and their interactions on connectivity is still a challenge in the field of studies of surface processes. To address this challenge, we applied the geographical detector model (GDM) and random forest (RF) to quantify the relative importance and explanatory power of topographic factors, vegetation features, and river network structure on the hydrological connectivity and sediment connectivity and to clarify the interaction mechanism of various factors in the Jinghe River Basin. Results indicate that from 2005 to 2020, the mean value of hydrological connectivity ( IC H ) witnessed a decreasing trend from −5.47 to −5.58. Similarly, the mean value of sediment connectivity ( IC S ) declined over the same period from −9.74 to −10.05, with high values registered in valleys and low values in plains. The river density ( D ) and hydrological weight factor (normalized SCS‐CN) exhibited a greater spatial explanatory power on IC H than other parameters, reaching 0.149 and 0.182, respectively. The vegetation factor (0.299) and sediment weight factor (0.410) manifested considerably more influence over IC S . Spatial integration between relevant elements can enhance our understanding of basin connectivity. Interactions between vegetation, topography, and river network structure provide more explanatory power compared to interactions among same‐type features. Ultimately, this study offers a theoretical template for understanding the management of soil and water resources in the Jinghe River Basin, as well as the spatial variability in soil erosion.