@article{VIVEKANANDAN_2011, title={Prediction of annual runoff using Artificial Neural Network and Regression approaches }, volume={62}, url={https://mausamjournal.imd.gov.in/index.php/MAUSAM/article/view/4711}, DOI={10.54302/mausam.v62i1.4711}, abstractNote={<p>Prediction of runoff is often important for optimal design of water storage and drainage works and<br>management of extreme events like floods and droughts. Rainfall-runoff (RR) models are considered to be most effective<br>and expedient tool for runoff prediction. Number of models like stochastic, conceptual, deterministic, black-box, etc. is<br>commonly available for RR modelling. This paper details a study involving the use of Artificial Neural Network (ANN)<br>and Regression (REG) approaches for prediction of runoff for Betwa and Chambal regions. Model performance<br>indicators such as model efficiency, correlation coefficient, root mean square error and root mean absolute error are used<br>to evaluate the performance of ANN and REG for runoff prediction. Statistical parameters are employed to find the<br>accuracy in prediction by ANN and REG for the data under study. The paper presents that ANN approach is found to be<br>suitable for prediction of runoff for Betwa and Chambal regions.</p>}, number={1}, journal={MAUSAM}, author={VIVEKANANDAN, N.}, year={2011}, month={Jan.}, pages={11–20} }