Soil erodibility (K-factor) is an essential factor in soil erosion prediction and conservation practises. The major obstacles to any accurate, large-scale soil erodibility estimation are the lack of necessary data on soil characteristics and the misuse of variable K-factor calculators. In this study, we assessed the performance of available erodibility estimators Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), Erosion Productivity Impact Calculator (EPIC) and the Geometric Mean Diameter based (Dg) model for different geographic regions based on the Chinese soil erodibility database (CSED). Results showed that previous estimators overestimated almost all K-values. Furthermore, only the USLE and Dg approaches could be directly and reliably applicable to black and loess soil regions. Based on the nonlinear best fitting techniques, we improved soil erodibility prediction by combining Dg and soil organic matter (SOM). The NSE, R2 and RE values were 0.94, 0.67 and 9.5% after calibrating the results independently; similar model performance was showed for the validation process. The results obtained via the proposed approach were more accurate that the former K-value predictions. Moreover, those improvements allowed us to effectively establish a regional soil erodibility map (1:250,000 scale) of water erosion areas in China. The mean K-value of Chinese water erosion regions was 0.0321(thah)·(haMJmm)−1 with a standard deviation of 0.0107(thah)·(haMJmm)−1; K-values present a decreasing trend from North to South in water erosion areas in China. The yield soil erodibility dataset also satisfactorily corresponded to former K-values from different scales (local, regional, and national)

Trends and variability of extreme precipitation events are important for water‐related disaster prevention and mitigation as well as water resource management. Using daily precipitation dataset from 143 meteorological stations in the Yangtze River Basin (YRB), a suite of heavy and extreme precipitation indices recommended by the Expert Team on Climate Change Detection and Indices, which has rarely been applied in this region, were analysed during 1960–2012. Results showed that simple daily intensity index, very wet day precipitation, extremely wet day precipitation, extremely heavy precipitation days, maximum 1‐day precipitation, maximum 5‐day precipitation and maximum consecutive dry days all increased significantly during 1960–2012. In contrast, ≥10 mm precipitation days and maximum consecutive wet days decreased significantly, implying that the precipitation processes in YRB were dominated by precipitation events with shorter durations. Geographically, a wetting tendency was observed in the eastern Tibet Plateau and the middle and lower YRB, while the other regions experienced precipitation deficits. The increasing precipitation was mainly due to the intensification of extreme precipitation events and the decreasing precipitation may be attributed to the decrease of ≥10 mm precipitation days or moderate precipitation events. In addition, the regional trends were of greater magnitudes in the middle and lower YRB, indicating more frequent extreme precipitation events in these sub‐regions. Time series analysis revealed that most precipitation indices exhibited neither a stable nor a gradual pattern during 1960–2012, but a clearly upward trend, although non‐monotonous, since the late‐1980s was evident.