Wang Bin, Zheng Fenli, Wang Yuxi. Adaptability analysis on soil erodibility models in typical thin layer black soil area of Northeast China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(6): 126-131.
    Citation: Wang Bin, Zheng Fenli, Wang Yuxi. Adaptability analysis on soil erodibility models in typical thin layer black soil area of Northeast China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(6): 126-131.

    Adaptability analysis on soil erodibility models in typical thin layer black soil area of Northeast China

    • Soil erodibility is a crucial parameter in soil erosion prediction and evaluation on environmental effects. The typical eroded black soil area of Northeast China, the Binzhou River Basin, was taken as the research area. In order to evaluate the applicability of each K value calculating method in the typical eroded black soil area, the very fine sand content transform model (VFS model) in RUSLE2 (revised universal soil loss equation) was calibrated, and differences among K value calculating methods of EPIC (erosion productivity impact calculator), USLE (universal soil loss equation) and RUSLE2 were discussed respectively. Results showed that the VFS model in RUSLE2 underestimated 22.5% of the very fine sand content, compared to the observed value. Therefore, a revised VFS model was built based on the measured data, and the accuracy of gaccurateerved value, very fine sand content which was calculated by the model improved by 95%. Furthermore, RULSE2 was the most appropriate method for K value calculation, in the typical eroded black soil area. EPIC and USLE models overestimated the K value, but they can still be applied in the typical thin layer black soil region when they were calibrated by the revised K value estimators. The results provides scientific basis to support soil erosion quantification and soil quality risk assessment in the typical thin layer black soil region and similar areas.
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