Abstract:
When a dam is constructed on a river to store water, sediments transported by the water flow are also stored and reservoir capacity is gradually reduced by sediment accumulation. Prediction of sediment distribution in reservoirs is an important issue for dam designers to determine the reservoir active storage capacity, outlet sill elevation, dam stability, recreational facilities, and backwater conditions. The main objective of this study is to develop the most reliable parameters of sedimentation that are directly or indirectly influencing in the equations and measured dataset. For validation of the proposed parameters, data of 40 reservoir sets gathered from different reliable sources, rather than focusing entirely on bed-load equations. Artificial neural network (ANNs) method was used to validate this study. Several graphs and statistical analysis were presented to emphasize the influencing effect of those parameters that were detected by ANNs and are directly controlling the error in the bed-load sediment flux using measured particles datasets.
Description:
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