Rational Use of The FAO Blaney‐Criddle Formula

Allen, Richard G.; Pruitt, William O.

doi:10.1061/(asce)0733-9437(1986)112:2(139)

Cited by 130 publications

(55 citation statements)

References 9 publications

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“…FAO-24 Blaney and Criddle (Allen and Pruitt, 1986), Turc (1961), Hargreaves-Samani (Hargreaves and Samani, 1985), and the modified Hargreaves approach (Droogers and Allen, 2002). These are included in Sect.…”

Section: Fao-56 Reference Crop Evapotranspirationmentioning

confidence: 99%

Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis

McMahon

Peel

Lowe

et al. 2013

Hydrol. Earth Syst. Sci.

459

294

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Abstract. This guide to estimating daily and monthly actual, potential, reference crop and pan evaporation covers topics that are of interest to researchers, consulting hydrologists and practicing engineers. Topics include estimating actual evaporation from deep lakes and from farm dams and for catchment water balance studies, estimating potential evaporation as input to rainfall-runoff models, and reference crop evapotranspiration for small irrigation areas, and for irrigation within large irrigation districts. Inspiration for this guide arose in response to the authors' experiences in reviewing research papers and consulting reports where estimation of the actual evaporation component in catchment and water balance studies was often inadequately handled. Practical guides using consistent terminology that cover both theory and practice are not readily available. Here we provide such a guide, which is divided into three parts. The first part provides background theory and an outline of the conceptual models of potential evaporation of Penman, PenmanMonteith and Priestley-Taylor, as well as discussions of reference crop evapotranspiration and Class-A pan evaporation. The last two sub-sections in this first part include techniques to estimate actual evaporation from (i) open-surface water and (ii) landscapes and catchments (Morton and the advection-aridity models). The second part addresses topics confronting a practicing hydrologist, e.g. estimating actual evaporation for deep lakes, shallow lakes and farm dams, lakes covered with vegetation, catchments, irrigation areas and bare soil. The third part addresses six related issues: (i) automatic (hard wired) calculation of evaporation estimates in commercial weather stations, (ii) evaporation estimates without wind data, (iii) at-site meteorological data, (iv) dealing with evaporation in a climate change environment, (v) 24 h versus day-light hour estimation of meteorological variables, and (vi) uncertainty in evaporation estimates. This paper is supported by a Supplement that includes 21 sections enhancing the material in the text, worked examples of many procedures discussed in the paper, a program listing (Fortran 90) of Morton's WREVAP evaporation models along with tables of monthly Class-A pan coefficients for 68 locations across Australia and other information.

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Section: Fao-56 Reference Crop Evapotranspirationmentioning

confidence: 99%

Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis

McMahon

Peel

Lowe

et al. 2013

Hydrol. Earth Syst. Sci.

459

294

View full text Add to dashboard Cite

show abstract

“…where D is the mean daily percentage of total annual daytime hours for a given time period and latitude (values of D are given in Allen and Pruitt (1986) and Doorenbos and Pruitt (1975)), h is the elevation, a and b are correction factors that adjust the E e estimates based on the measured or estimated mean daily minimum relative humidity (Q m i"), the mean ratio of actual to possible sunshine hours (n/N) and the daytime wind speed at 20-m height (JJday)-The a and b factors can be interpolated from published tables (Doorenbos and Pruitt, 1975) or calculated using the following regression equations reported by Frevert et al (1983):…”

Section: B Thornthwaite Methodsmentioning

confidence: 99%

A comparison of different methods of estimating energy‐limited evapotranspiration in the peace river region of British Columbia

Abbaspour

1991

Atmosphere-Ocean

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The performances of eight methods for estimating daily energy-limited evapotranspiration (E e ) were compared with reliable values for the Peace River region of British Columbia. They included the methods of Priestley and Taylor (PT), Jensen and Haise (JH), Hargreaves (H) and Makkink (M), the first and second equations of Baier and Robertson (BR1 and BR2), and the modified methods of Blaney and Criddle (BC) and Thornthwaite (T). The reference data were obtained from previous workers, who in 1977 and 1979 et al., 1991). A simple method of estimating E e is required that can be used with limited data. The approaches for estimating E e can be divided into three main categories: (1) models based on the physics of evaporation and transpiration, (2) empirical models based on temperature, and (3) empirical correlations that use radiation as well as temperature.The work of Penman (1948Penman ( , 1956) is the best example of the first approach. Penman's combination equation accounts for the effects of temperature, solar radiation, atmospheric humidity and wind speed on evapotranspiration by considering the energy balance and aerodynamic transfer. Combination models such as those of Penman (1948) and Monteith (1965) are often not practical means of estimating E e because they require detailed information that is often not available. A regional model of E e that was proposed by Priestley and Taylor (1972) requires less input data.Under the second approach, the methods of Thornthwaite (1948) and Blaney and Criddle (1950) are foremost. Thornwaite (1948) deduced an equation relating the energy-limited evapotranspiration to air temperature and day length, based on catchment area data and controlled experiments. Blaney and Criddle (1950) developed a formula that used temperature and daylight hours.Under the third approach, the methods of Jensen and Haise (1963) and Hargreaves (1975) have been the most widely used. Jensen and Haise (1963) used observations of consumptive use from the western United States to develop a relationship for estimating E e . Hargreaves (1975) based his work on data from grass lysimeters and developed a model similar to that of Jensen and Haise (1963). Other methods in this approach include that of Baier and Robertson (1965), who developed eight regression equations that utilize three to six different meteorological variables, and the radiation method of Makkink (1957a, b) as described by Doorenbos and Pruitt (1975).On the basis of energy balance-Bowen ratio measurements of E e , the present work evaluates the performance of the following methods: Priestley and Taylor

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“…Note that this subsection includes a general description of equations used for calculations of potential evapotranspiration; it does not provide an analysis of the various advantages and disadvantages in applying these equations, which are given in other publications (for example, Allen et al, 1998;Allen & Pruitt, 1986;Batchelor, 1984;Maulé et al, 2006;Sumner & Jacobs, 2005;Walter et al, 2002). The two forms of Baier-Robertson equations (Baier, 1971;Baier & Robertson, 1965) are given by:…”

Section: Equations For Calculations Of Potential Evapotranspirationmentioning

confidence: 99%

“…Equation (1) takes into account the effect of temperature, and Equation (2) takes into account the effects of temperature and relative humidity. The Blaney-Criddle equation (Allen & Pruitt, 1986) is used to calculate evapotranspiration for a reference crop, which is assumed to be actively growing green grass of 8-15 cm height:…”

Section: Equations For Calculations Of Potential Evapotranspirationmentioning

confidence: 99%

Fuzzy-Probabilistic Calculations of Evapotranspiration

Faybishenko¹

2012

Evapotranspiration - Remote Sensing and Modeling

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Rational Use of The FAO Blaney‐Criddle Formula

Cited by 130 publications

References 9 publications

Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis

Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis

A comparison of different methods of estimating energy‐limited evapotranspiration in the peace river region of British Columbia

Fuzzy-Probabilistic Calculations of Evapotranspiration

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