The benefits of the Taguchi method have been demonstrated in diverse fields. However, its applicability to soil erosion experiments at the slope scale under various conditions remains unclear. Using 6 published datasets that included the dependent variables of erosion rate (D), runoff rate (R), sediment concentration (C), flow velocity (V) and transport capacity (Tc), we compared the results from the full-factorial design method with those from the Taguchi and orthogonal design methods to validate the applicability of the Taguchi method to simulated soil erosion experiments at the slope scale under different conditions. The statistical parameters of the dependent variables from the orthogonal design and Taguchi method were very close to those from the full-factorial design for all dependent variables. The trends of the main effects based on different factor levels were consistent for 35 out of 45 sets from the full-factorial design and Taguchi method and for 27 sets from the orthogonal design. The optimum conditions for 10 and 7 dependent variables (out of 14) for the Taguchi and orthogonal design methods were the same as those for the full-factorial design, respectively. In addition, 13 and 8 dependent variables (out of 14) for the Taguchi and orthogonal design methods had the same factor rank order of percentage contributions as the full-factorial design method, respectively. Based on a univariate analysis of variance, the evaluating indicators for predictive power, including the determination coefficient, Nash-Sutcliffe efficiency, relative root mean squared error, mean absolute percentage error and Thiel inequality coefficient, indicated that the Taguchi method predictions were better than the orthogonal design predictions. Overall, the Taguchi method could obtain more reliable conclusions for soil erosion than the orthogonal design method at the slope scale. These findings suggest that the Taguchi method could be successfully applied to soil erosion experiments and could better replace the full-factorial design method at the slope scale compared with the orthogonal design method.

Taguchi方法的好处已经在不同领域得到了证明。然而，其在各种条件下在坡度尺度上对土壤侵蚀实验的适用性仍不清楚。使用6个已发布的数据集，其中包括侵蚀率（D），径流率（R），沉积物浓度（C），流速（V）和输送量（Tc）的因变量，我们比较了全因子设计的结果该方法与Taguchi方法和正交设计方法相结合，验证了Taguchi方法在不同条件下在坡度规模下模拟土壤侵蚀实验的适用性。正交设计和田口方法的因变量统计参数与所有因变量的全因子设计的统计参数非常接近。基于全要素设计和田口方法的45套中的35套，以及基于正交设计的27套，基于不同因子水平的主要效应趋势保持一致。Taguchi和正交设计方法的10个和7个因变量（共14个）的最佳条件分别与全因子设计的最佳条件相同。此外，田口和正交设计方法的13个和8个因变量（在14个中）具有与全因子设计方法相同的百分比贡献因子等级顺序。在方差的单变量分析基础上，预测能力的评估指标包括确定系数，纳什-苏克利夫效率，相对均方根误差，平均绝对百分比误差和Thiel不等式系数，指出Taguchi方法的预测优于正交设计的预测。总体而言，在坡度范围内，Taguchi方法比正交设计方法可以获得更可靠的土壤侵蚀结论。这些发现表明，Taguchi方法可以成功地应用于土壤侵蚀实验，并且与正交设计方法相比，可以更好地代替边坡规模的全要素设计方法。