Estimation of monthly evaporation for Kovilar reservoir using Genetic Programming and Thornthwaite method

摘要

Evaporation is an important component of the hydrologic cycle. Accurate estimation of evaporation is necessary in many studies such as reservoir operation, agricultural water management and estimating the components of water balance, etc. Due to high variability in weather conditions both spatially and temporally, it is difficult to have one single model for predicting evaporation. As such, though there are many empirical and analytical models suggested in the literature, such models should be used with care and caution. Further, difficulties arise in obtaining all the climatological data used in a given analytical or empirical model. This study explores the utility of an evolutionary based data driven modeling approach, Genetic Programming (GP) to model the evaporation process for Kovilar reservoir in Vaipar basin in Tamil Nadu, India. A monthly averaged climatical data of temperature and rainfall was used. The performance of the GP model is compared with Thornthwaite method, and results from the study indicate that the GP performed better than the Thornthwaite method. The GPevolved equations are parsimonious and are well suited to modeling the dynamics of the evaporation process with a Correlation Coefficient of 0.73.