Flood Forecasting Using Neural Networks

This paper deals with flood routing in rivers using neural networks. The unsteady river flow may be formulated in terms of two one-dimensional partial differential equations. These are the Saint Venant flow continuity and dynamic equations. Several methods of solution of these equations are known. These methods are based upon characteristics of equations, finite difference, finite element and finite volume. All of these methods have some limitations regarding data requirements and complications involved in solution of equations. Neural network techniques have been developed recently. These are easy to use and need comparatively less data and less labor for solution of the problem. One of these techniques is used in this research work. The model was applied for flood routing in River Chenab in Pakistan. Its reach from Marala to Khanki was selected. Date for various flood events was collected from Meteorological Department, Lahore and Flood Commission Islamabad. The error between the observed and simulated values of flood hydrograph ordinates was found to be in acceptable range.