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为预测区外泥沙沉积量 ,应评价二维的修订通用土壤流失方程式是否适用于三维实体 ,方程的外推采用蒙特卡罗误差推断技术。这项技术得出模型输出值的真实概率分布并给出解释问题的可能性 ,即模型输出值与田间观察值之间的差异究竟是由于模型输入的随机性还是主要缘于模型本身的若干局限与随机性。业已发现修订的通用土壤流失方程式能够精确地预报研究区外水库的泥沙沉积量。泥沙观测值的置信区间在 6 8%之内 ,二者之间的差异仅 1 4%。故误差推测对差异的解释是主要缘于模型输入参数的随机性。因此 ,RUSLE模型中的地形因子也可作为观测地表径流输沙能力的手段。
To predict sediment deposition outside the area, a two-dimensional revision of the generalized soil loss equation should be evaluated for three-dimensional entities, and extrapolation of the equation using Monte-Carlo error inference techniques. This technique derives the true probability distribution of the model output and gives the possibility of explaining the question whether the difference between the model output and the field observations is due to the randomness of the model input or to some of the limitations of the model itself And randomness. The revised universal soil loss equation has been found to accurately predict the amount of sediment deposited in reservoirs outside the study area. Sediment observations have a confidence interval of 68%, with a difference of only 14%. Therefore, the interpretation of the discrepancy of error inference is mainly due to the randomness of the input parameters of the model. Therefore, the topographic factors in the RUSLE model can also be used as a means of observing surface runoff and sediment transport capabilities.