科研之友
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摘要
Soil erosion has become a great challenge to agricultural development and food security at regional, national and global scales. China is an agriculture country with large amount of population and long farming history, and intensive cultivation activities result in accelerated erosion. To reduce soil erosion and conserve soil resources, soil erosion models have been widely developed and applied worldwide. Soil erodibility is a key factor in erosion prediction models, such as USLE (Universal Soil Loss Equation) and RUSLE (Revised Universal Soil Loss Equation). However, the three commonly used existing soil erodibility estimation methods (K-noma, K-epic, K-Dg) would cause high biases for agricultural soils in China and the K-nomo method is not available in most regions of China. Therefore, this study proposed a linear combination of the revised K-epic and K-Dg methods for soil erodibility estimation based on data from the Second Nation Soil Survey. The new estimator performs well (R-2 = 0.590; RMSE = 0.0043). A soil erodibility map for China derived from this new method shows that soil erodibility decreases from the southeast to the northwest. The soil erodibility of China is bimodally distributed rather than following a Gaussian distribution, with modes of 0.012 and 0.023 t.h.MJ(-1) mm(-1). Finally, a national database of K factors for agricultural soils was developed.
