Quantification of Error in Estimation of Reference Crop Evapotranspiration by Class A Pan Evaporimeter and Its Correction

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Today Penman–Monteith equation is assumed to be the most appropriate model for estimation of reference crop evapotranspiration (ET0) across the globe. However, as the model requires many weather parameters, so it has not been percolated down to the stakeholder’s level. Instead pan evaporimeter is being widely used in many parts of the world for estimating approximate ET0 without considering the degree of error involved in this method. So an attempt has been made in the present study to quantify the percentage of error the stakeholders allowing in estimation of ET0 as well as crop water requirement. Weekly weather data were collected for 14 years from 2001 to 14 from the crop weather observatory of Orissa University of Agriculture and Technology and put into Penman–Monteith equation for estimation of actual ET0. Further, the weekly ET0 values recorded at the observatory from the depletion of water level in Class A pan evaporimeter for the corresponding period were compared with the actual ET0. It was found that the pan evaporimeter is underestimating the parameter to the tune of 50% of the actual ET0. A regression analysis between pan ET0 and Penman–Monteith ET0 carried out for a period of 12 years form 2001 to 12 discloses linear relationship based on highest R 2 value (0.81) among all the relation functions. Furthermore, the regression model was validated using pan ET0 data from the observatory for two years (2013–14) with the help of RMSE, percent deviation and Scatter plot. An average RMSE of 0.545 mm/week and percent deviation of −5.53 and 0.82% in 2013 and 2014, respectively, along with the depiction of Scatter plots in both the years depict close agreement of the model prediction with the actual ET0 values. It is recommended to use the developed model for estimation of actual ET0 instead of error-infested pan ET0 for estimation of crop water requirement and scheduling irrigation in regions having similar agro-climatic conditions.