Table of Contents
ISRN Civil Engineering
Volume 2011, Article ID 291370, 4 pages
http://dx.doi.org/10.5402/2011/291370
Research Article

ANN-Based Approach for Predicting Rating Curve of an Indian River

Department of Civil Engineering, National Institute of Technology, Kurukshetra, Haryana 136119, India

Received 5 April 2011; Accepted 17 May 2011

Academic Editor: I. Raftoyiannis

Copyright © 2011 Arun Goel. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Prediction of stage-discharge relation or a rating curve is of immense importance for reliable planning, design, and management of most of the water resources projects. Measurement of discharge in a river is a time-consuming, expensive, and difficult process, and the conventional approach of regression analysis of stage-discharge relation does not provide encouraging results especially during the floods. Therefore, the present study is aimed at the application of soft computing techniques such as back propagation feed forward neural network-based algorithm for modelling stage-discharge relation. A data set of discharge-measuring station located on an Indian river has been used for analysis in the present study. A multilinear regression model was also employed on the same data in order to compare the performance of the results. The performance of each model has been compared by calculating correlation coefficient and root mean square error for the used data set. The outcome of the study suggests that the back propagation feed forward ANN works quite well for the data sets and produced promising results in comparison to the linear regression technique.