Abstract:
The spatiotemporal differentiation of quick-flow and slow-flow in karst regions is central to understanding the hydrological functions of the critical zone. Although previous studies have explored the potential impacts of vegetation restoration on hydrological processes, the coupling mechanisms between vegetation and runoff remain unclear. This study, based on runoff monitoring data from 12 representative slope catchments with different vegetation types (economic forest and fruit trees, shrubland, grassland, and maize), applied a recession curve analysis at the event scale to quantify the effects of vegetation changes on both quick-flow and slow-flow components. The results demonstrated that the runoff recession processes on karst slopes conformed to a double-exponential model (
R² = 0.78), with recession coefficients generally high, ranging from 0.003 to 0.02 min
−1. Specifically, the recession coefficient during the quick-flow stage (0.06 min
−1) was significantly greater than that of the slow-flow stage (0.007 min
−1). Compared with maize plots, grassland and shrubland restoration areas showed higher initial runoff but shorter durations of quick-flow and lower slow-flow recession coefficients, leading to a 17% reduction in the proportion of quick-flow. In contrast, economic forest and fruit tree plots, characterized by sparse canopy cover, exhibited a high quick-flow contribution of up to 45%. Factor analysis revealed that soil bulk density was the primary factor regulating quick-flow (
r = −0.597,
P < 0.01), followed by bedrock curvature (
r = −0.407,
P < 0.01), surface curvature (r = −0.284,
P < 0.05), and soil depth (
r = 0.327,
P < 0.05). These findings indicate that vegetation restoration can effectively slow down hydrological processes and enhance water retention through the synergistic effects of canopy structure, root systems, and soil-rock interactions. This study provides a scientific foundation for assessing the hydrological benefits of rocky desertification control projects in karst regions.