Comparisons of measured and estimated daily potential evapotranspiration in a humid region

Parmele, Leslie H.; McGuinness, J. L.

doi:10.1016/0022-1694(74)90079-1

Cited by 17 publications

(12 citation statements)

References 10 publications

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“…The ET 0 calculated with n e (Equation (5)) showed the best match with ET 0 computed with n. Mean monthly ET 0 values based on n e (Equation (5)) are plotted versus ET 0 based on n in Figure 3. Clearly, the relationship between ET 0 calculated using both n and n e is strong; the intercept value was close to zero (0.003), the slope value close to 1 (0.9971) and the R 2 value close to unity (0.9967) (Parmele and McGuinness, 1974). Therefore, Equation (5) also provided a reliable estimate of ET 0 in Libya.…”

Section: Resultsmentioning

confidence: 76%

“…0.13 and 0.01 mm day À1 , respectively, and the PE value is 100%. Clearly, the relationship between ET 0 calculated using both n and n e is strong; the intercept value was close to zero (0.003), the slope value close to 1 (0.9971) and the R 2 value close to unity (0.9967) (Parmele and McGuinness, 1974). Clearly, the relationship between ET 0 calculated using both n and n e is strong; the intercept value was close to zero (0.003), the slope value close to 1 (0.9971) and the R 2 value close to unity (0.9967) (Parmele and McGuinness, 1974).…”

Section: Resultsmentioning

confidence: 89%

“…The equation that has the lowest RMSE, the PE value closest to 100 and highest (R 2 ) is considered the best method (Parmele and McGuinness, 1974).…”

Section: Discussionmentioning

confidence: 99%

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Calculating Sunshine Hours and Reference Evapotranspiration in Arid Regions When Solar Radiation Data are Limited

El-Wahed

Snyder

2015

Irrigation and Drainage

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The Penman–Monteith equation is often recommended as the standard for both computing the reference evapotranspiration (ET0) and evaluating other ET0 equations. The main shortcoming of this equation is it requires weather data, e.g. solar radiation or sunshine hours (n), that are not always available. Since neither solar radiation nor n data are available in Libya, the main objective of the present study was to develop a reliable equation for estimating the sunshine hours (ne) to estimate monthly ET0 in arid regions. In this study, three equations were developed for predicting ne based on mean monthly temperature, relative humidity and wind speed. The derived equations were used for calculating the monthly ET0 based on the Penman–Monteith equation. The ET0 estimates were compared with ET0 calculated using observed n. The results indicate that the ET0 calculated using ne matched well with the ET0 calculated by n. The ET0 calculated by the three equations were tested against ET0 calculated by both the California Irrigation Management Information System (CIMIS) and Hargreaves–Samani equation. The ET0 based on estimated sunshine was closest to ET0 obtained from CIMIS compared to the Hargreaves–Samani equation. In conclusion, the equation to estimate sunshine hours should provide good estimates of the ET0 for similar desert locations that lack sunshine hours or solar radiation data. Copyright © 2015 John Wiley & Sons, Ltd.

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Section: Resultsmentioning

confidence: 76%

Section: Resultsmentioning

confidence: 89%

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Calculating Sunshine Hours and Reference Evapotranspiration in Arid Regions When Solar Radiation Data are Limited

El-Wahed

Snyder

2015

Irrigation and Drainage

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“…The RMSE parameter has been used to indicate the goodness-of-fit of ET 0 estimates. The best method is the one with the lowest absolute average deviation, mvalue closest to 1.0, the smallest RMSE, and the highest R 2 [23,24]. The difference in ET 0 rates with respect to standard ET 0 was also estimated and termed as over/under prediction rate of particular methods on both monthly and average seasonal time scale.…”

Section: Evaluation Criteriamentioning

confidence: 99%

Comparative Evaluation of Different Potential Evapotranspiration Estimation Approaches

Nikam¹,

Kumar²,

Garg³

et al. 2014

IJRET

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Accurate estimation of potential evapotranspiration is necessary step in water resources management. Recently, the FAO-56 version of Penman-Monteith equation has been established as a standard for calculating reference evapotranspiration (ET 0 ). Still there are different approaches (requiring less data) which estimate ET 0 closely to Penman-Monteith method for different climatological conditions. Performance Evaluation of all the approaches on the same basis is prerequisite for selecting an alternative approach in accordance with available data. Therefore, two most popular temperature-based approaches (Hargreaves and Thornthwaite) and two radiation based approaches (Priestley-Taylor and Turc) were used to estimate monthly potential evapotranspiration (ET 0 ) at Pantnagar (Uttarakhand), India. Further, the performance of all these methods were evaluated by regression and error analysis between standard ET 0 derived using FAO-56 Penman-Monteith method and ET 0 values estimated using all the four methods, on monthly and seasonal basis. On monthly basis Turc method performed best with lowest RMSE (0.562), ARE (0.137), AAD (0.448) and high coefficient of determination (0.792). On seasonal basis, the Priestley-Taylor methodwas found to be the best for Rabiseasonwith lowest error values and minimum seasonal over/under ET 0 predication rate with respect to standard ET 0 .Turc method holds second rank in Rabi season. However in Kharif season Truc method performed better than any other method with lowest error terms and lowest seasonal over/under predication rate. In summer season all the methods performed poorly compared to other two seasons but Hargreaves method performed better than other methods. Though the performance and accuracy of FAO-56 Penman-Monteith method can never be debated in theoretical or practical applications yet the comparative evaluation performed in this paper can be used as guideline for selection of alternative or less data dependent methods in case of non-availability of data.

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“…Bu nedenle birçok ara ştı rmac ı , hangi bölgelerde hangi tahmin yönteminin kullan ı labileceğ ini saptamak amac ı yla çal ış malar yapm ışlard ı r. örneğ in, Güney Florida'da U.S. Weather Bureau yönteminin (Stephens ve Stewart 1963), Nevada'da Oliver yönteminin (Behnke ve Maxey 1969), Ohio'da m ı s ı r için radyasyon ölçümlerine dayal ı yöntemlerin (Parmele ve McGuinnes 1974), Kuzey Tayland'da çeltik için Penman yönteminin (Christiansen 1968) ve Israirde yonca için Kap Buharla ş mas ı yönteminin (Lomas ve Schlesinger 1970), Ankara ko şulları nda yap ı lan bazı araştirmalarda ise şeker pancar ı için Jensen-Haise, Penman (FAO) ve Kap Buharla şmas ı (FAO) yöntemlerinin (Y ı ld ı rı m 1992), ayçiçe ğ i, patates, yonca, m ı s ı r, fasulye ve çilek için Penman (FAO) ve Kap Buharla şmas ı (FAO) yöntemlerinin (Hisarl ı 1988, Akgün 1989, biber için Penman (FAO) yönteminin (Orta 1997), taze fasulye için Kap Buharla ş mas ı (FAO) yönteminin (Y ı ld ı rı m 1994) ve ayçiçe ğ i için Christiansen-Hargreaves Kap Buharla şmas ı ve Jensen-Haise yöntemlerinin (Kaday ı fç ı 1996) daha sa ğ l ı kl ı sonuç verdi ğ i saptanm ıştı r.…”

Section: Giri şunclassified

Ankara Koşullarında Yoncanın Su Tüketimi

Fatih;KADAYIFCI¹

1999

Tarım Bilimleri Dergisi

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Comparisons of measured and estimated daily potential evapotranspiration in a humid region

Cited by 17 publications

References 10 publications

Calculating Sunshine Hours and Reference Evapotranspiration in Arid Regions When Solar Radiation Data are Limited

Calculating Sunshine Hours and Reference Evapotranspiration in Arid Regions When Solar Radiation Data are Limited

Comparative Evaluation of Different Potential Evapotranspiration Estimation Approaches

Ankara Koşullarında Yoncanın Su Tüketimi

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