Comparative Evaluation of ANNs and Hargreaves Method to Model ETo

Abstract

This review goes for creating counterfeit neural system (ANN) based reference
evapotranspiration (ETo) models comparing to Hargreaves (HG) strategy. The ANN models
were created utilizing pooled atmosphere information of various areas under four agroenvironmental
locales (semi-dry, dry, sub-damp, and muggy) in India. The inputs for the
development of ANN models include daily climate data of minimum, maximum air
temperatures and extra terrestrial radiation and the target consists of the FAO-56 PM
estimated ETo. Comparison of developed ANN models with the conventional HG method. The
performance indices used for comparison include root mean squared error (RMSE) and
coefficient of determination (R2). Based on the comparisons, it is concluded that the ANN
models performed better than conventional HG method.