Reservoir Sediment Management Using Artificial Neural Networks: A Case Study of the Lower Section of the Alpine Saalach River

Reservoir sedimentation is a critical issue worldwide, resulting in reduced storage volumes and, thus, reservoir efficiency. Moreover, can also increase the flood risk at related facilities. In some cases, drawdown flushing of an appropriate management tool. However, there are various options as to how and when perform such flushing, which should be optimized order maximize its efficiency effectiveness. This paper proposes innovative concept, based on artificial neural network (ANN), predict volume sediment flushed from given distinct input parameters. The results obtained real-world study area indicate that close correlation between inputs—including peak discharge duration flushing—and output (i.e., sediment). developed ANN readily applied site, decision-support system for hydropower operators.