基于相似性的多沙水库坝址含沙量预测

Similarity-based prediction of sediment concentrations for reservoir dam-sites in sediment-laden rivers

坝址含沙量过程是合理进行水库水沙调度的重要依据。在浑水总流模型的基础上,提出了基于洪水相似性的多沙水库坝址含沙量预测方法。通过聚类分析将洪水案例分组,并分别率定模型参数;根据洪水相似性动态选择未知洪水模型参数;进行模型计算。结果表明,分组率定参数一定程度上能够提高坝址含沙量预测精度,尤其是沙峰出现时刻。这对指导水库水沙调度具有实际意义,有助于决策者制定合理的排沙时机,提高排沙效率。

Better knowledge of sediment concentrating processes for reservoir dam sites is crucial in reservoir water and sediment operations. In this study, a flood similarity-based method is developed for predicting reservoir sediment concentrations in heavily sediment-laden rivers. The method uses the main principle of the total flow model for sandy rivers. An approach based on the cluster analysis of historical flood events is employed in the model application. The events are first grouped and then used separately in calibrating the similarity-based method. Thus, the same group flood events will always share the same set of model parameter values in the model applications, and the idea is also applicable to the future flood events. Model validation results show that the sediment concentrating process of reservoir damsites can be better predicted with the grouped parameter values. The improvement is especially significant in predicting the peak value of sediment concentrations. The similarity-based method could be potentially useful in the decision making process of reservoir sediment flushing.