Development of Stage Discharge Relationship at Barman Station on Narmada River

NARMADA is the largest west flowing peninsular river, ranks seventh in discharge. A number of dams have been constructed on the river and its tributaries. As such, a need arise to regulate the reservoir for releasing the adequate water in the river throughout the year. River discharge is an important hydrological parameter in any water resource management which requires collection of daily discharge data. This is mainly in the form of forecasting or estimating the magnitude of hydrological variable like rainfall or runoff. But, direct measurement of daily discharge in number of points in all the streams is not only prohibitive in cost, but also very much time consuming, which can be best achieved by developing stage discharge relationship. Prediction of stage discharge relation is of immense importance for reliable planning, design and management of most of the water resource project. The present study was carried out to develop a river stage and discharge modeling using Artificial Neural Network (ANN) . Ten ANN models were developed with two hidden layers and 10, 11, 12, 13, 14, 15, 16, 17, 18 and 19 numbers of neurons respectively. The developed models were trained, tested and validated on the data sets of Barman station on Narmada River in Madhya Pradesh.