黄土高原径流侵蚀功率输沙模型的改进

水土流失对流域生态危害严重，输沙量模拟和预测可以为流域水土流失防治提供依据，因此精确的输沙模型是流域水土流失治理的重要工具。为了精确模拟变化环境下黄土高原年输沙量，该研究基于黄土高原19个水文站的径流和输沙数据，通过随机森林变量重要性度量方法评估年径流侵蚀功率、淤地坝指数、淤地坝相对指数、归一化植被指数、不透水地面积等因子对流域年输沙量的影响，使用非线性最小二乘法估算年输沙模型参数，对比分析不同因子组合的年输沙模型精度，提出适用性较强的黄土高原年输沙模型，据此开展年输沙量变化贡献率分析。结果表明：1）以幂函数形式构建的仅含径流侵蚀功率单因子输沙模型精度与流域面积有显著的负相关关系，相关系数为-0.505（P<0.05），模型精度随着流域面积增大而下降,在大于7 000 km2的流域适用性较差；2）年径流侵蚀功率、淤地坝指数及不透水地面积因子组合建立的多因子年输沙模型在黄土高原适用性最佳，模型在率定期NSE平均值为0.84，RMSE平均值为0.21亿t，在验证期纳什系数平均值为0.79，均方根误差平均值为0.27亿t。3）影响研究流域年输沙量变化的因素依次是：年径流侵蚀功率、不透水地面积和淤地坝指数。研究可以为黄土高原不同区域水土流失防治和生态治理工作提供理论支撑。

Improvement of the sediment transport model based on runoff erosion power in the Loess Plateau

Soil and water loss has been one of the most serious hazards to the basin ecology in recent years. An accurate sediment transport model can greatly contribute to the control of soil and water loss in the basin. This study aims to explore the variation trend of sediment transport by Mann-Kendall. The runoff and sediment transport data was also collected from the 19 hydrological stations in the Loess Plateau. Annual sediment transport model was then established to take the runoff erosion power as the core factor in Pearson correlation analysis. Random forest variables were selected to evaluate the influence of factors (such as annual runoff erosion power, check-dam index, check-dam relative index, normalized difference vegetation index (NDVI) and impervious land area) on the annual sediment transport of the basin. The parameters were also determined in the annual sediment transport model by nonlinear least square method. The accuracy of the model was compared with different factor combinations. The annual sediment transport model was proposed with the strong applicability for the Loess Plateau. The attribution analysis was finally carried out on annual sediment transport. The results showed as follows: 1) It was reasonable to choose the runoff erosion power as the core factor in the annual sediment transport model. But there was a significant negative correlation between the area of watershed and the accuracy of the single factor annual sediment transport model with only annual runoff erosion power that built by the power function. The correlation coefficient was -0.505 (P<0.05). The accuracy of the single factor model decreased with the increase of the watershed area. As such, the applicability of the model was poor in watersheds larger than 7 000 km². 2) The best performance was achieved in the multi-factor annual sediment transport model with the combination of annual runoff erosion power, check-dam index and impervious area factors. The average NSE and RMSE values of the model were 0.84 and 0.21 108t at the calibration rate, 0.79 and 0.27 108t at the verification period. Compared with the single-factor annual sediment transport model that only considering the annual runoff erosion power, the mean NSE value increased by 339.39%, whereas, the mean RMSE value decreased by 81.88% during the verification period. The mean NSE value increased by 7.69%, while the mean RMSE value decreased by 38.64%, compared with the annual sediment transport model considering erosion power, the relative index of check-dam and NDVI combination. 3) The influencing factors on the annual sediment transport were as follows: annual runoff erosion power, impervious area and check-dam index. Their average contribution rates to the annual sediment transport were 79.52%, -38.89%, and 20.13%, respectively. The runoff of most watersheds decreased, where the inter-annual distribution of runoff tended to be uniform, which was greatly reduced the probability of large flow concentrated sediment transport. The simulation and prediction of sediment transport can provide the theoretical support for the prevention and control of soil and water loss in the ecological management of the Loess Plateau.