Abstract:
A study on ‘Estimation of pan evaporation using Artificial Neural Network’ was
carried out in K. C. A. E. T, campus, Tavanur. The meteorological parameters
considered were monthly data of wind speed, dry bulb temperature, wet bulb
temperature, maximum temperature, minimum temperature and evaporation for six years
(February 2003 to January 2009) for the model development. The entire data was
divided in to three based on the season, as pre- monsoon, monsoon and post monsoon.
The five different strategies were considered for the study viz. M-1, M-2, M-3, M-4, and
M-5. Strategy M-1 included all the input parameters. M-2 included all the input
parameters except wind speed and M-3 included wind speed, dry bulb temperature and
wet bulb temperature. Dry bulb temperature and wet bulb temperature were only
considered in strategy M-4 where as strategy M-5 included only maximum temperature
and minimum temperature. From the available data 70% data were taken for training and
15% each for testing and validation. From the results of the study, it can be seen that the
strategy M- 3, combination of wind speed, dry bulb and wet bulb temperature has
greater influence on evaporation rate the least MSE value and high R 2 value.
