Reference evapotranspiration prediction using Heuristic approach with gamma test based on climate data
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Date
2021-02
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G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand)
Abstract
Accurate estimation of reference evapotranspiration (ETo) is critically significant in crop modelling, hydrological water simulation, irrigation scheduling and sustainable management because it accounts for more than two-thirds of global precipitation losses.
Therefore, ETo based estimation is a key issue in the hydrological cycle. In this study, FAO-56 based Penman-Monteith (PM) method was used to estimate daily ETo which was considered as output to calibrate the models. Different soft computing and statistical techniques such as ANN, wavelet coupled ANN (WANN), ANFIS and MNLR were used to predict daily reference
evapotranspiration in area of GKVK, Bengaluru. By using Gamma test, the best input combination of climatic variables (mean relative humidity, wind speed, sunshine hour, saturated and actual vapour pressure and solar radiation) was determined. The performance of the calibrated models was assessed qualitatively by visual interpretation and quantitatively using statistical and hydrological indicators such as coefficient of determination (R2), root mean square error (RMSE), coefficient of efficiency (CE) and Willmott index (WI). Additionally, sensitivity analysis was performed for the best developed model to see the effect of each
parameter on model performance. The WANN-11 model was found as the best model compared to ANN-10, ANFIS-06 and MNLR models for prediction of reference evapotranspiration of the study area.