Sedimentation in reservoirs constitutes a major issue worldwide, especially when hydropower, and hence profit, is involved. In this study, the sedimentation rates, due to soil erosion and sediment yields, are analyzed in the reservoir of the Rio di Pusteria hydropower dam, in South Tyrol (Italian Alps). The focus is on a five-year period, between two consecutive sediment flushing operations occurred in June 2014 and May 2019. Based on the difference between the pre- and post-flushing bathymetries, the five-year aggregated sediment yield was determined. The soil erosion from the basin surface and the sediment budget in the reservoir are calculated by means of a gridded Universal Soil Loss Equation (USLE), combined with a Sediment Delivery Ratio (SDR) module. The topographic factor is improved by the use of a fine-scale DEM and the slope length factor is adjusted to the Alpine terrain by means of a fitting threshold. The rainfall erosivity factor is determined in two different ways, one representing the precipitation regime of the study area and one the specific rainfall conditions of the study period. The two different applications result to calculated reservoir sedimentation rates of 439,279.2 tons and 589,520.5 tons with deviations from the measured value of 3.1% and −23.2%, respectively, while the sediment delivery ratio to the reservoir was found to be 12.5%. The calculations are also compared with results of the application of the conventional six-factor USLE. The comparison between calculations and measurements shows that the methods used can be efficiently applied in an Alpine basin for the estimation of reservoir sedimentation rates.

水库中的沉积是世界范围内的一个主要问题，尤其是当涉及水电和利润时。在这项研究中，在南蒂罗尔（意大利阿尔卑斯山）的 Rio di Pusteria 水电站大坝的水库中分析了由于土壤侵蚀和沉积物产量引起的沉积速率。重点是五年期间，在 2014 年 6 月和 2019 年 5 月发生的两次连续冲沙作业之间。根据冲刷前和冲刷后水深的差异，确定了五年累计沉积物产量。流域表面的土壤侵蚀和水库中的沉积物收支通过网格化通用土壤流失方程 (USLE) 结合沉积物输送率 (SDR) 模块进行计算。地形因子通过使用精细尺度的 DEM 得到改善，坡长因子通过拟合阈值调整到高山地形。降雨侵蚀力因子由两种不同的方式确定，一种代表研究区的降水状况，另一种代表研究时期的特定降雨条件。两种不同的应用导致计算出的水库沉积速率分别为 439,279.2 吨和 589,520.5 吨，与测量值的偏差分别为 3.1% 和 -23.2%，而到水库的泥沙输送率为 12.5%。计算结果也与应用传统六因素 USLE 的结果进行了比较。