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The need to develop new and computationally efficient artificial intelligence models that accurately simulate river flows in data-scarce regions, considering not only current but also projected future climate change conditions is vital. In this study, a hybrid artificial neural network (ANN) model that combines HEC-HMS and the feed-forward neural network (FFNN) was developed in the Python programm
