Effects of rainfall patterns, vegetation cover types and antecedent soil moisture on run‐off and soil loss of typical Luvisol in southern China

Abstract

AbstractIdentifying the effect of precipitation, vegetation cover and underlying surface conditions on run‐off and soil loss is essential for understanding the mechanism of water erosion. The study site is located in the Shiqiaopu watershed of Hubei Province, China. The long‐term (2017–2021) monitoring data for this study included rainfall characteristics, antecedent soil moisture, run‐off and soil loss in four run‐off plots with four vegetation cover types (tea garden, soybean and rape, peanut and rape, and vetiver zizanioides). K‐means clustering and discriminant analysis were used to classify rainfall patterns. The improved redundancy analysis was used to quantitatively explore the relative importance of rainfall characteristics, vegetation cover and antecedent soil moisture to run‐off and soil loss. The results showed that the rainfall patterns were mainly divided into three categories: A (medium duration, small rainfall, medium rain intensity, high frequency), B (long duration, large rainfall, light rain intensity, low frequency) and C (short duration, medium rainfall, heavy rain intensity, medium frequency). The average run‐off coefficient, run‐off depth of different rainfall patterns were C > B > A, and the cumulative run‐off depth and soil loss under the A rainfall pattern were the largest. For the run‐off plots with four vegetation cover types, vetiver zizanioides had the best effect on run‐off and sediment reduction, while peanut and rape had the worst effect. The driving factor that contributed the most to the run‐off depth was vegetation cover (19.36%), and rainfall characteristics explained the most to the soil loss (11.65%). We also found that although antecedent soil moisture had a small explanation rate for soil loss, it was significantly correlated with the run‐off depth under the vegetation cover of the tea garden. Therefore, regional soil erosion should be combined with the importance of driving factors to take comprehensive control measures.