Predicting the impact of vegetations in open channels with different distributaries’ operations on water surface profile using artificial neural networks |
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Authors: | Mostafa A M Abdeen |
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Affiliation: | (1) Dept. of Engineering Math. & Physics, Faculty of Engineering-Cairo University, Cairo, Egypt |
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Abstract: | Most of the open water irrigation channels in Egypt suffer from the infestation of aquatic weeds, especially the submerged
ones that cause numerous hydraulic problems for the open channels themselves and their water distributaries such as increasing
water losses, obstructing water flow, and reducing channels’ water distribution efficiencies. Accurate simulation and prediction
of flow behavior in such channels is very essential for water distribution decision makers. Artificial neural networks (ANN)
have proven to be very successful in the simulation of several physical phenomena, in general, and in the water research field
in particular. Therefore, the current study aims towards introducing the utilization of ANN in simulating the impact of vegetation
in main open channel, which supplies water to different distributaries, on the water surface profile in this main channel.
Specifically, the study, presented in the current paper utilizes ANN technique for the development of various models to simulate
the impact of different submerged weeds’densities, different flow discharges, and different distributaries operation scheduling
on the water surface profile in an experimental main open channel that supplies water to different distributaries. In the
investigated experiment, the submerged weeds were simulated as branched flexible elements. The investigated experiment was
considered as an example for implementing the same methodology and technique in a real open channel system. The results showed
that the ANN technique is very successful in simulating the flow behavior of the pre-mentioned open channel experiment with
the existence of the submerged weeds. In addition, the developed ANN models were capable of predicting the open channel flow
behavior in all the submerged weeds’cases that were considered in the ANN development process |
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Keywords: | Artificial neural network Open channel hydraulics modeling Open channel infested by submerged weeds |
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