Experimental Study on the Mechanism of Artificial Runoff Generation on Typical Slopes in Farmland of North China

Runoff generation and concentration are essential processes of the hydrological cycle. Understanding runoff generation mechanisms is crucial for improving the accuracy of hydrological forecasting and regional water resource assessment. This research aims to explore runoff generation mechanisms of farmlands in the North China Plain through analysing the impact of farmland vegetation on runoff generation in typical slopes. Seven experimental scenarios were designed based on various land uses under an artificial rainfall intensity of 60 mm/h, using two soil tanks with slopes of 2° and 4°, respectively. The regional climates, cropping structures and management practices were considered for the scenario design. The experiments were conducted at the experimental plot of artificial rainfall runoff on the Linmingguan campus of Hebei University of Engineering, located in Hebei Province, China, from October 2019 to June 2021. The results indicated that the surface runoff rate varied significantly, while the interflow rate remained relatively stable. The surface runoff accounted for 64%–89.36% of the total runoff volume, and the proportion increased with the increase of slope gradient. The start time of surface runoff (T_Rs) was delayed by 7.5 min, and runoff volume (V_Rs) decreased by 42%–50% as winter wheat grew from seedling to maturity. In contrast, the start time of interflow (T_Ri) occurred 3.5 min earlier, and runoff volume (V_Ri) increased by 54%–55%. T_Rs advanced, and both V_Rs and peak flow increased with the slope increasing under the same vegetation type; however, the results of interflow showed the opposite trend. The runoff volume increased and start time of runoff advanced in the bare land, probably benefiting from the impact of the crop rotation system on soil characteristics in North China. The findings of this research provide an insight into understanding runoff mechanisms in North China, reducing the uncertainty between model parameters and watershed characteristics and offering beneficial references for research and practice in related fields.