Evaporation modeling using Artificial neural networks

The investigation was carried out to develop and test the daily pan evaporation prediction models using various weather parameters as input variables with artificial neural network (ANN) and validated with the independent subset of data for five different locations in India. The measured variables included daily observations of maximum and minimum temperature, maximum and minimum relative humidity, wind speed, sunshine hours, rainfall and pan evaporation. In this general model (GM) model development and evaluation has been done for the five locations viz. NRCC, Nagpur (M.S.); JNKVV, Jabalpur (M.P.); PDKV, Akola (M.S.); ICRISAT, Hyderabad (A.P.) and MPUAT, Udaipur (Raj.). The daily data of pan evaporation and other inputs for two years was considered for model development and subsequent 1-2 years data for validation. Weather data consisting of 3305 daily records from 2002 to 2006 were used to develop the GM models of daily pan evaporation. Additional weather of Nagpur station, which included 2139 daily records from 1996 - 2004, served as an independent evaluation data set for the performance of the models.