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1·The stability of aggregates of T3, T2 was very low and multilevel pore was few, so soil splash erosion and sediment was very high.

T2团聚体发育差，缺乏多级孔隙，形成的高径流量和溅蚀率使T2、T3的产沙率在相对大的数值范围内变动。

2·However, the results of simulating splash erosion processes on slope that considered the effects of overland flow or canopy are obtained.

给出了考虑击溅产沙能力受坡面漫流或其它覆盖物影响下的击溅产沙过程的模拟结果。

3·Plant roots within soil can raise resistivity of soil. Splash erosion volume, penetration depth and breaking down condition are indexes expressing soil resistivity.

土壤中植物根系的存在可以增强土壤的抗蚀性，溅蚀量、贯入深度和被崩解的情况等都是土壤抗蚀性的反映。

4·Through rainfall simulating in laboratory, and observation on soil sample slices, this study intended to disclose crust development, and reveal the relationship between crust and splash erosion.

通过人工模拟降雨溅蚀实验，测定土壤溅蚀速率，同时采样制作土壤切片，观察分析结皮的发育特征以及与土壤溅蚀的关系。

5·The role of interception to rainfall by Canopy of vegetation decreased and weakened splash on soil erosion, and different vegetation restoration displayed differently.

植被冠层对降水的截留作用削弱了雨滴对土壤的溅蚀，不同植被恢复类型的截留作用表现各异。

6·The example calculation indicates that the rough neural network is an efficient and feasible algorithm to forecast sloping field rain drops splash-erosion.

实例计算表明，粗糙神经网络为坡面雨滴溅蚀量预测研究提供了一种有效可行的算法。

7·It is presented to predict slope splash-erosion for rain drops based on rough neural network.

提出采用粗糙神经网络预测坡面雨滴溅蚀量。