Comparison of Methods for Estimating Reference Evapotranspiration: An Approach to the Management of Water Resources Within an Experimental Basin in the Brazilian Cerrado

Gotardo, Jackeline Tatiane; Gomes, Benedito Martins

doi:10.1590/1809-4430-eng.agric.v36n6p1016-1026/2016

Cited by 8 publications

(3 citation statements)

References 12 publications

(9 reference statements)

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“…Ranking of different ET 0 estimation methods for years 2016 and 2017 of Sultanpur district (Uttar Pradesh, India) was carried out with respect to the estimated value by FAO-PM model on the basis of their prediction error statistics [viz.coefficient of determination (R 2 ), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Modified Nash-Sutcliffe Coefficient (E MNS ), Percent Bias (PBIAS)].The result of such comparison is presented in Table 2. It can be observed from (Table 2) that the ranks are in line with the ranks as reported by Gotardo et al (2016). Moreover, the deviation of results as compared to FAO-PM can be attributable to the fact that the FAO-PM uses additional weather parameters, viz.…”

Section: Fao-penman Monteith Methods (Fao-pm)supporting

confidence: 75%

Performance evaluation of evapotranspiration estimation methods in Sultanpur, Uttar Pradesh, India

et al. 2022

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Accurate estimation of evapotranspiration plays a vital role in judicious irrigation scheduling. Keeping this in view, a study was undertaken to compare the performance of five methods, viz. Penman method (PM), FAO Penman Monteith (FAO-PM), Priestley-Taylor (PT), FAO Radiation method (FAO-RM) and Hargreaves methods (HM) for Sultanpur District of Uttar Pradesh, India using the daily weather data acquired from automatic weather station during 2016-17. The performance evaluation of selected methods was carried out using linear regression and simple statistical analysis to suggest a substitute of FAO-PM for estimation of reference evapotranspiration using minimal climatic parameters available at regional scales. It was observed that the PM method performed the best and was in line with estimated ET0 by FAO-PM method with coefficient of determination (R2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Modified Nash-Sutcliffe Coefficient (EMNS), Percent Bias (PBIAS) estimated as 0.94, 0.54, 0.40, 0.73, 3.74 for the year 2016 and 0.95, 0.44, 0.36, 0.73, 6.01 in 2017, respectively. Nonetheless, it was observed form this study that the PM method which requires four parameters, viz. daily solar radiation, maximum and minimum air temperature, and wind speed can be a substitute to FAO-PM that require more parameters for ET0 estimation in data scarce situations.

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Section: Fao-penman Monteith Methods (Fao-pm)supporting

confidence: 75%

Performance evaluation of evapotranspiration estimation methods in Sultanpur, Uttar Pradesh, India

et al. 2022

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“…The same point was verified for the region of Minas Gerais, in central Brazil (SILVA et al, 2018). Penman, Priestley & Taylor, and Hargreaves & Samani were better adjusted (R²) in these conditions than in the Brazilian Cerrado (GOTARDO et al, 2016). Different results were obtained in Baixada Cuiabana, MT, where Hargreaves & Samani and Linacre models presented the best performances and the Penmann model showed lower performance (SOUZA; JUNIOR, 2017).…”

Section: Eto Empirical Models Estimatessupporting

confidence: 55%

Reference crop evapotranspiration in distinct agricultural regions of Southern Brazil: a comparison of improved empirical models

Santos

Castro

Oro

et al. 2021

Reveng

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The FAO56 Penman-Monteith model is globally accepted for the accurate determination of reference evapotranspiration (ETo). However, a lack of appropriate data encouraged the improved model’s approach to estimate ETo. This study compared the performance of 10 empirical models of ETo estimation (Penman, Priestley & Taylor, Tanner & Pelton, Makkink, Jensen & Haise, Hargreaves & Samani, Camargo, Benevides & Lopes, Turc, and Linacre) contrasted with the FAO56 model in two regions in Southern Brazil. Data were collected from automatic stations of the Brazilian National Institute of Meteorology (INMET) from December 21, 2019, to February 28, 2021. The determination coefficient (R²), mean square error (nRMSE), mean bias error (MBE), Willmott index (d), and Pearson’s correlation coefficient (r), clustering, and Principal Component Analysis (PCA) were performed. For the different regions, the radiation-based model proposed by Penman was the best alternative for estimating ETo. The model showed the most appropriated values for R2 (0.9015) and r (0.9494). The clustering and PCA analyses indicated the interrelations of the meteorological data and the combination of the models according to the parameters used for the determination of ETo.

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“…The first category uses the evaporation measured with Class A pan [15] [16] [17]. Other studies employ the ET 0 of FAO-Penman Monteith for validation [7] [10] [11] [18] [19] [20] [21].…”

Section: Introductionmentioning

confidence: 99%

Predicting Reference Evaporation for the Ethiopian Highlands

Adem¹,

Aynalem²,

Tilahun³

et al. 2017

JWARP

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Water is likely the most limiting factor in increasing agricultural production in large parts of Africa. Reference evaporation (ET 0 ) is a key hydrological parameter to use efficiently the scarce supply. Several methods are available for predicting reference evaporation, but the accuracy of any of the methods has not been established for the Ethiopian highlands. The objective of this study is, therefore, to select the best methods for calculating the reference evaporation ET 0 . For the section, meteorological data of the Bahir Dar station were used, because all data needed for this study including the Class A pan Evaporation were recorded on a daily basis. Pan evaporation was considered as the best estimator of the reference evaporation. The results showed that the FAOPenman Monteith (using solar radiation, wind speed, temperature and relative humidity) and Enku method (using only maximum daily temperatures) have acceptable daily ET 0 ranges and predicted to Class A pan evaporation with correlation coefficients greater than 90% in a monthly basis. Next best was the Thornthwaite's method with correlation coefficient of 89% with pan evaporation. Piche methods performed relatively well with correlation coefficient of greater than 70%. Blaney-Criddle, Priestley & Taylor, and Hargreaves performed the poorest in predicting pan evaporation. These methods should be recalibrated for local condition and therefore not recommended for use in the Ethiopian highlands. In summary, the FAO-Penman Monteith is recommended for locations where the input data are available; otherwise, the Enku method using maximum daily temperature is best for estimating the reference evaporation.

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Comparison of Methods for Estimating Reference Evapotranspiration: An Approach to the Management of Water Resources Within an Experimental Basin in the Brazilian Cerrado

Cited by 8 publications

References 12 publications

Performance evaluation of evapotranspiration estimation methods in Sultanpur, Uttar Pradesh, India

Performance evaluation of evapotranspiration estimation methods in Sultanpur, Uttar Pradesh, India

Reference crop evapotranspiration in distinct agricultural regions of Southern Brazil: a comparison of improved empirical models

Predicting Reference Evaporation for the Ethiopian Highlands

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