Estimation of evapotranspiration using climate based and regression methods under limited data Khedkar D D1,*, Singh P K2 1Interfaculty Department of Irrigation Water Management, Mahatma Phule Krishi Vidyapeeth, Rahuri-413722, Maharashtara 2Department of Soil Water Engineering, Maharana Pratap University of Agriculture & Technology, Udaipur-313001, Rajasthan *Corresponding author: devidaskhedkar@gmail.com
Online published on 16 September, 2020. Abstract Evapotranspiration is an important parameter for climatological and hydrological studies, as well as for irrigation planning and management. In this paper an attempt has been made to determine the best method for estimating ETo in the absence of the full weather data required for FAO-56 Penman- Monteith (PM-56) method application in a semi-arid environment of Niphad station, Nasik district, Maharashtra (India). Eight climate based methods viz., Soil Conservationist Society Blaney-Criddle, Thornthwaite, Hargreaves-Samani, Pan evaporation, Jensen-Haise, Priestly-Taylor, Turc, Radiation were compared with Penman-Monteith method for estimation of reference evapotranspiration (ETo). In addition, linear regression (LR) was applied in modeling of ETo using the PM-56 equation. The independent variables were considered as per the meteorological data requirement of climate based models and dependent variable ETo was estimated by PM-56 method. The input combinations for LR models are: (i) LR1- Epan (i) LR2- Tmax and Tmin; (iii) LR3- Tmax and Tmin and SSH; (iv) LR4- Tmax, Tmin, RHmax, RHmin and SSH. Among climate based methods, it was observed that pan evaporation (PAN) method RHmin shows better performance in case of d(IA) (0.931), RMSE(0.991) and CE (0.667); while Priestley-Taylor (P-T) method shows better performance in case of MAE (0.697) and MAPE(13.658). The ranking of methods was: Pan evaporation, Proestely-Taylor, and Hrgreaves-Samani method. All LR models showed satisfactory performance for prediction of ETo. The resulting best climate based models were compared with LR models on the basis of similar data requirement i.e PAN, P-T and H-S methods were compared with LR1, LR3 and LR2, respectively. In case of all statistical indices (R, d(IA), RMSE, MAE, MAPE and CE), it was observed that LR1, LR3 and LR2 models performed superiorly over PAN, P-T and H-S, respectively. Thus, linear regression models are alternatives to Penman-Monteith method under limited data availability for Niphad region of Maharashtra. Top Keywords Climatological data, Evapotranspiration, Penman-Monteith method, Regression, Statistical measures. Top |