Civil Engineering, National Institute of Technology Kurukhshetra
This paper is an attempt to assess the potential and usefulness of ANN based modeling for evaporation prediction from a reservoir, where in classical and empirical equations failed to predict the evaporation accurately. The meteorological data set of daily pan evaporation, temperature, solar radiation, relative humidity, wind speed is used in this study. The performance of feed forward back propagation neural network model is compared with the linear regression on the basis of performance parameters (correlation coefficient and rmse) having different combinations of input parameters. The comparison of results shows that there is a better agreement when large input parameters are considered for model building and testing as compared to a single parameter. The outcome of study suggests that the feed forward back propagation ANN based modeling can be applied as an alternative approach for estimation of daily evaporation from reservoirs effectively.