Application of Artificial Neural Network and Genetic Algorithm Based Artificial Neural Network Models for River Flow Prediction

Abstract

In hydrology and water resource engineering, water flow forecasting is of great importance for getting the information about the river engineering, dam structure design and waterrelated inflow demand management. In order to prevent flooding on the downstream side of the river during the rainy season, sufficient outflow from a barrage should be maintained. It is very difficult to predict the desired water flow using physically-based models and conventional regression-based methods due to the nonlinear and fuzzy nature of hydrological activity and scarcity of relevant data. These traditional methods are incapable to handle the complex non-linearity and non-stationarity process of water flow. Thus, the aim of this study is to develop intelligent hybrid artificial intelligence model, namely genetic algorithm based Artificial Neural Network (GA-ANN) for monthly Water Flow prediction in the Mahanadi river system. All parameters associated with the artificial neural network (ANN) model are optimized simultaneous automatically using Genetic Algorithm (GA) for prediction of the Water flow. Twenty years monthly data from Mahanadi river in India has collected for the development of this GA-ANN model. The hydro-climatical parameters like Rainfall, Water Level, Sediment yield and Temperature are used for the development of the ANN prediction model of Water Flow at Tikarapara gauging station which is extreme last downstream station in Mahanadi River basin, India. The performances of the GA-ANN model were compared with Artificial Neural Network (ANN) model for checking the estimation capability of the model. The obtained results revealed that the proposed novel GA-ANN model is capable to predict river flow with satisfactory performances and provided better results than the ANN model. This modelling approach can be potentially used for prediction of water flow discharge in the river system where measurement of water flow is unavailable.

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