Runoff and Sediment Yield Modeling using Artificial Neural Networks: Upper Siwane River, India

Accurate estimation of both runoff and sediment yield is required for proper watershed management. Artificial neural network (ANN) models were developed, to predict both runoff and sediment yield on a daily and weekly basis, for a small agricultural watershed. A total of five models were developed for predicting runoff and sediment yield, of which three models were based on a daily interval and the other two were based on a weekly interval. All five models were developed both with one and two hidden layers. Each model was developed with five different network architectures by selecting a different number of hidden neurons. The models were trained using monsoon season (June to October) data of five years (1991–1995) for different sizes of architecture, and then tested with respective rainfall and temperature data of monsoon season (June to October) of two years (1996–1997). Training was conducted using the Levenberg–Marquardt backpropagation where the input and output were presented to the neural network a...

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