Evaluation of Class A Pan Coefficients for Estimating Reference Evapotranspiration in Humid Location

Evaporation pans [Class A pan, U.S. Weather Bureau (USWB)] are used extensively throughout the world to measure free-water evaporation and to estimate reference evapotranspiration (ET0). However, reliable estimation of ET0 using pan evaporation (Epan) depends on the accurate determination of pan coefficients (Kpan). Two equations developed by Frevert et al. in 1983 and Snyder in 1992 to estimate daily Kpan values were evaluated using a 23-year climate dataset in a humid location (Gainesville, Florida). The ET0 data, calculated using daily Kpan values from these equations, were compared to the Food and Agricultural Organization (FAO)-Penman-Monteith (FAO56-PM) method. The two equations resulted in significantly different daily Kpan values that produced different daily, monthly, and annual total ET0 estimates. The ET0 values calculated using Frevert et al.’s 1983 Kpan coefficients were in very good agreement with the FAO56-PM method with daily, monthly, and annual mean percent errors (PE) of 5.8, 5.5, and 5.7%, respectively. The daily and annual mean-root-mean-square error (RMSE) of the estimates using this method were as low as 0.33 and 7.3 mm, respectively. Snyder’s 1992 equation overestimated FAO56-PM ET0 with daily, monthly, and annual mean PEs of 16.3, 13.8, and 13.2%, respectively. The daily and annual mean RMSEs for this method were higher (0.6 and 18 mm) than those obtained with Frevert et al.’s 1983 coefficients. The overestimations with Snyder’s 1992 method were highest in the peak ET0 month of May and in summer months. The performances of the Kpan equations were also evaluated using randomly selected individual years (1979, 1988, 1990, and 1994) of climate data that had different climate characteristics than the 23-year average dataset. Frevert et al.’s 1983 coefficients resulted in good ET0 estimates with lower annual mean PEs of 7.0, 0.1, 15.7, and 1.3% for 1979, 1988, 1990, and 1994, respectively, compared to Snyder’s 1992 equation, which resulted in considerably higher PEs of 17.6, 9.1, 26.2, and 14.3% in 1979, 1988, 1990, and 1994, respectively. It was concluded that using Frevert et al.’s 1983 equation to calculate daily Kpan provided more accurate ET0 estimates, relative to the FAO56-PM method, from Epan data compared to Snyder’s 1992 equation under the humid-region climatic conditions in this study. The method is very useful in computer calculations of ET0 since it does not require “table lookup” for Kpan values.     

Estimating Reference Evapotranspiration Using Limited Weather Data

The FAO-56 Penman-Monteith combination equation (FAO-56 PM) has been recommended by the Food and Agriculture Organization of the United Nations (FAO) as the standard equation for estimating reference evapotranspiration (ET0). The FAO-56 PM equation requires the numerous weather data that are not available in the most of the stations. This paper examines the potential of FAO-56 PM equation in estimating the ET0 under humid conditions from limited weather data. For this study, full weather data sets were collected from six humid weather stations from Serbia, South East Europe. FAO-56 reduced-set PM ET0 estimates were in closest agreement with FAO-56 full set PM ET0 estimates at the most of locations. The difference between FAO-56 full set PM ET0 estimates and FAO-56 PM reduced-set ET0 estimates generally increases by increasing the number of estimated weather parameters. Overall results indicate that FAO-56 reduced-set PM approaches mostly provided better results compared to Turc equation, adjusted Hargreaves equation and temperature-based RBF network. This fact strongly supports using the FAO-56 PM equation even in the absence of the complete weather data set. The minimum and maximum air temperature data and local default wind speed value are the minimum data requirements necessary to successfully use the FAO-56 PM equation under humid conditions.     

Pan Evaporation to Reference Evapotranspiration Conversion Methods

Reference evapotranspiration (ET0) is often estimated from evaporation pan data as they are widely available and of longer duration than more recently available micrometeorologically based ET0 estimates. Evaporation pan estimation of ET0 ( = KpEpan) relies on determination of the pan coefficient (Kp), which depends on upwind fetch distance, wind run, and relative humidity at the pan site. The Kp estimation equations have been developed using regression techniques applied either to the table presented in FAO-24 or to the original data upon which this table was based (from lysimeter studies in Davis, Calif.). Here, the relative performances of the FAO-24 table and six different Kp equations are evaluated with respect to reproducing the original data table using the FAO-24 table as a standard. Evaporation pan- and CIMIS-based estimates of ET0 are also compared for stations having ranges of mean humidities (48–66%) and mean wind runs (156–193 km/day) located in the Sacramento and San Joaquin valleys, and for a coastal station (Point Heuneme) near Ventura, Calif., having a greater mean humidity (71%). In comparing the means, standard deviations, root-mean-square errors, and linear regression coefficients, five of the six equations reproduced the original data table with approximately the same accuracy as the FAO-24 table. Use of either Kp table slightly underestimated measured ET0 at the coastal site, while the Cuenca, Allen-Pruitt, and Snyder Kp equations most closely approximated the average measured ET0 at all seven sites.     

History and Evaluation of Hargreaves Evapotranspiration Equation

A brief history of development of the 1985 Hargreaves equation and its comparison to evapotranspiration (ET) predicted by the Food and Agricultural Organization of the United Nations (FAO) Penman-Monteith method are described to provide background and information helpful in selecting an appropriate reference ET equation under various data situations. Early efforts in irrigation water requirement computations in California and other arid and semiarid regions required the development of simplified ET equations for use with limited weather data. Several initial efforts were directed towards improving the usefulness of pan evaporation for estimating irrigation water requirements. Similarity with climates of other countries allowed developments in California to be extended overseas. Criticism of empirical methods by H. L. Penman and others encouraged the search for a robust and practical method that was based on readily available climatic data for computing potential evapotranspiration or reference crop evapotranspiration (ETo). One of these efforts ultimately culminated in the 1985 Hargreaves ETo method. The 1985 Hargreaves ETo method requires only measured temperature data, is simple, and appears to be less impacted than Penman-type methods when data are collected from arid or semiarid, nonirrigated sites. For irrigated sites, the Hargreaves 1985 ETo method produces values for periods of five or more days that compare favorably with those of the FAO Penman-Monteith and California Irrigation Management Information Services (CIMIS) Penman methods. The Hargreaves ETo predicted 0.97 of lysimeter measured ETo at Kimberly, Idaho after adjustment of lysimeter data for differences in surface conductance from the FAO Penman-Monteith definition. Monthly ETo by the 1985 Hargreaves equation compares closely with ETo calculated using a simplified, “reduced-set” Penman-Monteith that requires air temperature data only.     

Daily Grass and Alfalfa-Reference Evapotranspiration Estimates and Alfalfa-to-Grass Evapotranspiration Ratios in Florida

Efficient use of natural water resources in agriculture is becoming an important issue in Florida because of the rapid depletion of freshwater resources due to the increasing trend of industrial development and population. Reliable and consistent estimates of evapotranspiration (ET) are a key element of managing water resources efficiently. Since the 1940s numerous grass- and alfalfa-reference evapotranspiration (ETo and ETr, respectively) equations have been developed and used by researchers and decision makers, resulting in confusion as to which equation to select as the most accurate reference ET estimates. Twenty-one ETo and ETr methods were evaluated based on their daily performance in a humid climate. The Food and Agriculture Organization Penman-Monteith (FAO56-PM) equation was used as the basis for comparison for the other methods. Measured and carefully screened daily climate data during a 23-year period (1978–2000) were used for method performance analyses, in which the methods were ranked based on the standard error of estimate (SEE) on a daily basis. In addition, the performance of the four alfalfa-based ET (ETr) equations and the ratio of alfalfa ET to grass ET (Kr values) were evaluated, which have not been studied before in Florida’s humid climatic conditions. The peak month ETo estimates by each method were also evaluated. All methods produced significantly different ETo estimates than the FAO56-PM method. The 1948 Penman method estimates were closest to the FAO56-PM method on a daily basis throughout the year, with the daily SEE averaging 0.11 mm?d?1; thus this method was ranked the second best overall. Although 1963 Penman (with the original wind function) slightly overestimated ET, especially at high ETo rates, it provided remarkably good estimates as well and ranked as the third best method, with a daily average SEE value of 0.14 mm?d?1. Both methods produced peak month ETo estimates closest to the FAO56-PM method among all methods evaluated, with daily peak month SEEs averaging 0.07 and 0.09 mm?d?1, respectively. Significant variations were observed in terms of the performance of the various forms of Penman’s equations. For example, the original Penman-Monteith method produced the poorest ETo estimates among the combination equations, with a daily SEE for all months and peak month averaging 0.50 and 0.35 mm?d?1, respectively and ranked 11th. An average value of 1.18 was used to convert ETr estimates to ETo values for alfalfa-reference methods. The Kr value of 1.18 resulted in reasonable estimates of ETo throughout the year by the Kimberley forms of the Penman equations. Another ETr-based equation, Jensen-Haise, gave consistently poor estimates. The Stephens-Stewart radiation method was the highest-ranked (10th) noncombination method overall. The temperature-based McCloud method (ranked 19th) produced the poorest ETo estimates among all methods with a daily SEE for all months and for the peak month averaging 1.93 and 1.22 mm?d?1, respectively. In general, the results obtained from the temperature methods suggest that all of the temperature methods, with the possible exception of the Turc method, can only be applicable for these climatic conditions after they are calibrated or modified locally or regionally. The FAO and Christiansen pan evaporation methods (ranked 17th and 18th, respectively) produced poor ETo estimates and had the largest amount of point scatter in daily ETo estimates relative to the FAO56-PM ETo. Both methods resulted in the highest daily SEE of 1.18 and 1.19 mm?d?1 for all months, after the McCloud method (1.93 mm?d?1), and with the highest SEE of 1.30 and 1.24 mm?d?1 for the peak month of all methods evaluated. The FAO56-PM method uses solar radiation, wind speed, relative humidity, and minimum and maximum air temperature to estimate ETo. It has been recommended that the FAO56-PM be used for estimating ETo when all the necessary input parameters are available. However, all these input variables may not be available, or some of them may not be reliable for a given location if the FAO56-PM equation is used, and one may need to choose other temperature, radiation, or pan evaporation methods based on the availability of data for estimating ETo. The results of this study can be used as a reference tool to provide practical information on which method to select based on the availability of data for reliable and consistent estimates of daily ETo relative to the FAO56-PM method in a humid climate.     

Solar and Net Radiation-Based Equations to Estimate Reference Evapotranspiration in Humid Climates

Two equations for estimating grass reference evapotranspiration (ET0) were derived using the Food and Agriculture Organization Penman–Monteith (FAO56-PM) method as an index. The first equation, solar radiation (Rs) based, estimates ET0 from incoming Rs and maximum and minimum air temperature, and the second equation, net radiation (Rn) based, uses Rn and maximum and minimum air temperature. The equations were derived using 15 years (1980–1994) of daily ET0 values estimated from the FAO56-PM method using the measured and carefully screened weather data from near Gainesville, Florida. The performance of the derived equations was evaluated for 6 validation years (1995–2000), including dry and wet years, for the same site and for other humid locations in the Southeast United States. Comparisons of the performance of the derived equations with the other commonly used methods indicated that they estimate ET0 as good or better than those other ET0 methods. The Rs- and Rn-based equations resulted in the lowest 6 year average standard error of estimate (SEE) of daily ET0 (0.44 and 0.41 mm?day?1, respectively). Both equations performed quite well for estimating peak month ET0 and had the lowest 6 year average daily SEE for the peak month ET0 (0.24 mm?day?1 for both equations). Estimates for annual total ET0 were very close to those obtained from the FAO56-PM method. The 6 year average ratio of ET0?method to ET0?FAO56-PM were 1.05 and 1.03 for the Rs- and Rn-based equations, respectively. The derived equations were further evaluated in other humid locations in the Southeast United States, including two locations in coastal regions in Florida, one location in Georgia, and another location in Alabama. The comparisons showed that both equations are likely to provide good estimates of ET0 in humid locations of the Southeast United States. When the required input variables are considered, the Priestley–Taylor (PT) method was the closest method to the second derived equation (Rn based). Therefore, it was necessary to evaluate how the PT method would perform compared to the Rn-based equation relative to the FAO56-PM method after it is calibrated locally. Although the performance of the PT method improved slightly after the calibration, its performances for estimating daily and peak month ET0 remained poorer than the Rn-based equation in all cases. Considering the limitations associated with the availability and reliability of the climatological data, especially in developing countries, the derived equations presented in this study are suggested as practical methods for estimating ET0 if the standard FAO56-PM equation cannot be used because of the above-mentioned limitations. These equations are recommended over the other commonly used simplified temperature and radiation-based methods evaluated in this study for humid climates in the Southeast United States.     

Testing Reference Evapotranspiration Estimation Methods Using Evaporation Pan and Modeling in Maritime Region of Canada

Four methods of estimating daily reference evapotranspiration (ETo) were evaluated with the data collected from 2004 to 2006 in a Maritime weather station, the Potato Research Centre, Fredericton, N.B., Canada. We tested two models [i.e., the FAO-56 Penman–Monteith (PM) and the Priestley–Taylor (PT) equations] and two Class A pan methods (Cuenca and Snyder equations). In order to assess the Evaporation Pan methods, an automatic Class A Pan system was installed in a grassed field surrounded by potato fields and continuously measured from 2004 to 2006. The results from three growing seasons (years 2004–2006) indicated that both evaporation pan methods generated lower estimations of ETo compared to the PM and PT methods. The PT method produced the highest ETo estimation. The Snyder method showed a better agreement with the PM (r2>0.56). However, the agreement varied from year to year with an r2 value range of 0.4–0.7. Kpan coefficients (a factor to convert pan observation to ETo) varied from 0.78 to 0.94. In general, the Cuenca generated lower Kpan values (0.83) than the Snyder method (0.87). Compared to the PM, the PT method overestimated ETo, which may be related to the absence of humidity adjustment in the model. Furthermore, the research suggested that the time step played an important role in the estimation of ETo in this region. The PM method at daily time step was simple but intended to overestimate ETo by 10% compared to the hourly time-step method. In summary, when Class A Pan data are available, the Snyder equation can be used to calculate Kpan with an acceptable accuracy. If the PM method is used to estimate ETo when pan observations are unavailable, a reduction of 10% to the calculated ETo at daily time step could be applied to improve the accuracy of ETo estimation.     

Comparison of Standardized Reference Evapotranspiration Equations in Southern Spain

ASCE and FAO-56 standardized reference evapotranspiration (ET0) equations were compared using data from 31 meteorological stations in Andalusia, Southern Spain. Comparisons were made between daily ET0 obtained by summing hourly standardized ASCE–Penman–Monteith estimations and calculated from the addition of hourly FAO56–Penman–Monteith estimations, daily ET0 estimated on a daily basis, and calculated by the Hargreaves equation. On an hourly basis, the FAO-56 version estimated lower than the ASCE version as 6% in some locations, with a difference of 4% on the average, mainly due to the higher surface resistance (70?s?m?1) used in the FAO-56 version during daytime periods, as opposed to the 50?s?m?1 rs value used by the ASCE version. Differences between both estimates were higher when evaporative demand increases. The level of agreement improved when the two computational time steps were compared, because differences were lower (2% on the average) and did not depend on the wind speed or ET0 values. The Hargreaves equation showed a higher spatial variability. At coastal areas, the equation generally underpredicted ASCE Penman–Monteith ET0 and provided good estimations for inland locations. Accuracy of the equation was affected by annual averages of evaporative demand and wind speed.     

Simple Equation to Estimate Reference Evapotranspiration from Evaporation Pans Surrounded by Fallow Soil

Reliable estimates of reference evapotranspiration (ET0) are key elements for efficient water resource management, and estimating ET0, based on “Class ‘A’ pan evaporation” data is common in arid climates. A pan coefficient (Kp), which depends on the distance (or fetch) of green vegetation or fallow soil around the pan (F), wind run (U), and relative humidity (RH), is used to convert from pan evaporation to ET0. Several researchers have developed models for estimating Kp values for pans surrounded by green vegetated fetch, but there is only one equation to estimate Kp values for dry fetch conditions. The equation is complex, so the objective of this research was to develop a new simple equation to estimate Kp under fallow soil fetch conditions. The new Kp equation and the more complex equation were compared with tabular values published by the United Nations Food and Agriculture Organization. The new equation performed slightly better at matching the tabular Kp values than the complex equation. The equation derivation and evaluation are presented.     

Performance Evaluation of Reference Evapotranspiration Equations across a Range of Indian Climates

Reference crop evapotranspiration (ET0) is a key variable in procedures established for estimation of evapotranspiration rates of agricultural crops. In recent years, there is growing evidence to show that the more physically based FAO-56 Penman–Monteith (PM) combination method yields consistently more accurate ET0 estimates across a wide range of climates and is being proposed as the sole method for ET0 computations. However, other methods continue to remain popular among Indian practitioners either because of traditional usage or because of their simpler input data requirements. In this study, we evaluated the performances of several ET0 methods in the major climate regimes of India with a view to quantify differences in ET0 estimates as influenced by climatic conditions and also to identify methods that yield results closest to the FAO-56 PM method. Performances of seven ET0 methods, representing temperature-based, radiation-based, pan evaporation-based, and combination-type equations, were compared with the FAO-56 PM method using historical climate data from four stations located one each in arid (Jodhpur), semiarid (Hyderabad), subhumid (Bangalore), and humid (Pattambi) climates of India. For each location, ET0 estimates by all the methods for assumed hypothetical grass reference crop were statistically compared using daily climate records extending over periods of 3–4 years. Comparisons were performed for daily and monthly computational time steps. Overall results while providing information on variations in FAO-56 PM ET0 values across climates also indicated climate-specific differences in ET0 estimates obtained by the various methods. Among the ET0 methods evaluated, the FAO-56 Hargreaves (temperature-based) method yielded ET0 estimates closest to the FAO-56 PM method both for daily and monthly time steps, in all climates except the humid one where the Turc (radiation-based) was best. Considering daily comparisons, the associated minimum standard errors of estimate (SEE) were 1.35, 0.78, 0.67, and 0.31 mm/day, for the arid, semiarid, subhumid, and humid locations, respectively. For monthly comparisons, minimum SEE values were smaller at 0.95, 0.59, 0.38, and 0.20 mm/day for arid, semiarid, subhumid, and humid locations, respectively. These results indicate that the choice of an alternative simpler equation in a particular climate on the basis of SEE is dictated by the time step adopted and also it appears that the simpler equations yield much smaller errors when monthly computations are made. In order to provide simple ET0 estimation tools for practitioners, linear regression equations for preferred FAO-56 PM ET0 estimates in terms of ET0 estimates by the simpler methods were developed and validated for each climate. A novel attempt was made to investigate the reasons for the climate-dependent success of the simpler alternative ET0 equations using multivariate factor analysis techniques. For each climate, datasets comprising FAO-56 PM ET0 estimates and the climatic variables were subject to factor analysis and the resulting rotated factor loadings were used to interpret the relative importance of climatic variables in explaining the observed variabilities in ET0 estimates. Results of factor analysis more or less conformed the results of the statistical comparisons and provided a statistical justification for the ranking of alternative methods based on performance indices. Factor analysis also indicated that windspeed appears to be an important variable in the arid climate, whereas sunshine hours appear to be more dominant in subhumid and humid climates. Temperature related variables appear to be the most crucial inputs required to obtain ET0 estimates comparable to those from the FAO-56 PM method across all the climates considered.     

Evapotranspiration Adjustment Factors in Florida

Actual evapotranspiration (ET) is commonly estimated at daily time intervals as the product of a crop coefficient and a reference-crop evapotranspiration (ET0) that is calculated by using a daily time step. When subdaily time steps are used, crop coefficients must be multiplied by adjustment factors to account for the discrepancy between ET0 calculated by using daily and subdaily time steps. These adjustment factors depend on the method used to calculate ET0. By using the ASCE and FAO-56 Penman-Monteith methods with data from several meteorological stations in Florida, the ASCE equation is shown to be preferable for all locations and seasons because it requires the least adjustment to the crop coefficient when 15-min and 1-h time steps are used. The required adjustment factors depend on location and season, are greatest in the summer, and are approximately the same for 15-min and 1-h time steps. A comparative evaluation between daily ET0 and values of potential evapotranspiration (PET) provided by three public databases shows that PET estimates should generally not be used as substitutes for ET0, because the relationship between PET and ET0 varies significantly with location and season. For all locations and seasons considered in this study, daily ET0 agrees most closely with the PET given by the Florida Automated Weather Network.     

Evapotranspiration Modeling Using Linear Genetic Programming Technique

The study investigates the accuracy of linear genetic programming (LGP), which is an extension to genetic programming (GP) technique, in daily reference evapotranspiration (ET0) modeling. The daily climatic data, solar radiation, air temperature, relative humidity, and wind speed from three stations, Windsor, Oakville, and Santa Rosa, in central California, are used as inputs to the LGP to estimate ET0 obtained using the FAO-56 Penman-Monteith equation. The accuracy of the LGP is compared with those of the support vector regression (SVR), artificial neural network (ANN), and those of the following empirical models: the California irrigation management system Penman, Hargreaves, Ritchie, and Turc methods. The root-mean-square errors, mean-absolute errors, and determination coefficient (R2) statistics are used for evaluating the accuracy of the models. Based on the comparison results, the LGP is found to be superior alternative to the SVR and ANN techniques.     

Comparison of Reference Evapotranspiration Calculations as Part of the ASCE Standardization Effort

Comparison among commonly used reference evapotranspiration (ET) equations in the United States and the recently recommended ASCE standardized reference ET equation was made as part of the ASCE standardization effort. Analyses used hourly and daily weather data from 49 geographically diverse sites in the United States. Calculations were performed for both grass and alfalfa reference crops in a consistent manner, using weather data that passed integrity and quality assessment checks. Comparisons were made between reference ET computed by the various methods and the ASCE Penman-Monteith (PM) equation used for a daily calculation time step. In addition, calculations using hourly time steps and summed daily were compared with daily calculations for the same method as well as against the ASCE-PM method. Results showed that the ASCE standardized equation agreed best with the full form of ASCE-PM. The results provide a basis for objectively assessing the relative performance of reference ET equations in a variety of climates and support adoption of a standardized equation as recommended by the ASCE Task Committee.     

Estimating Reference Evapotranspiration with Minimum Data in Florida

Reference evapotranspiration estimation methods that require minimal data are necessary when climatic data sets are incomplete, inaccurate, or unavailable. This study was conducted to evaluate temperature-based reference evapotranspiration methods in Florida. Using reference evapotranspiration estimates using satellite-derived radiation as the standard for comparison, the “reduced-set” Penman-Monteith, Hargreaves, and Turc equations were evaluated using monthly temperature data from 72 weather stations in Florida. The reduced-set Penman-Monteith equation requires maximum and minimum temperature only and uses recommended methods to estimate radiation, humidity, and wind speed. The reduced-set Penman-Monteith and Hargreaves equations were found to overestimate reference evapotranspiration while the Turc equation neither overestimated nor underestimated. The reduced-set Penman-Monteith equation showed greatest error in coastal stations while the Hargreaves equation showed greatest error at inland and island locations. In the absence of regionally calibrated methods the Turc equation is recommended for estimating reference evapotranspiration using measured maximum and minimum temperature and estimated radiation in Florida.     

Reference and Crop Evapotranspiration in South Central Nebraska. II: Measurement and Estimation of Actual Evapotranspiration for Corn

In planning, designing, and managing of surface and groundwater supply, it is essential to accurately quantify actual evapotranspiration (ETc) from various vegetation surfaces within the water supply areas to allow water management agencies to manipulate the land use pattern alternatives and scenarios to achieve a desired balance between water supply and demand. However, significant differences among water regulatory agencies and water users exist in terms of methods used to quantify ETc. It is essential to know the potential differences associated with using various empirical equations in quantifying ETc as compared with the measurements of this critical variable. We quantified and analyzed the differences associated with using 15 grass (ETo) and alfalfa-reference (ETr) combination, temperature and radiation-based reference ET (ETref) equations in quantifying grass-reference actual ET (ETco) and alfalfa-reference actual ET (ETcr) as compared with the Bowen ratio energy balance system (BREBS)-measured ETc (ETc-BREBS) for field corn (Zea mays L.). We analyzed the performance of the equations for their full season, irrigation season, peak ET month, and seasonal cumulative ETc estimates on a daily time step for 2005 and 2006. The step-wise Kc values instead of smoothed curves were used in the ETc calculations. The seasonal ETc-BREBS was measured as 572 and 561?mm in 2005 and 2006, respectively. The root-means-quare difference (RMSD) was higher for the full season than the irrigation season and peak ET month estimates for all equations. The standardized ASCE Penman-Monteith (PM) ETco had a RMSD of 1.37?mm?d?1 for the full growing season, 1.05?mm?d?1 for the irrigation season, and 0.76?mm?d?1 for the peak month ET. The ASCE-PM, 1963 and 1948 Penman ETc estimates were closest to the ETc-BREBS. The FAO-24 radiation and the HPRCC Penman ETc estimates also agreed well with the ETc-BREBS. Most combination equations performed best during the peak ET month except the temperature and radiation-based equations. There was an excellent correlation between the ASCE-PM ETco and ETcr with a high r2 of 0.99 and a low RMSD of 0.34?mm?d?1. The difference between the ETcr and ETco was found to be larger at the high ETc range (i.e., >8?mm), but overall, the ETcr and ETco values were within 3%. Significant differences were found between the cumulative ETco-METHOD and ETcr-METHOD versus ETc-BREBS. Most combination equations, including the standardized ASCE-PM ETco and ETcr underestimated ETc-BREBS during the early periods of the growing season where the soil evaporation was the dominant energy flux of the energy balance and in the late season near and after physiological maturity when the transpiration rates were less than the midseason. The underestimations early in the season can be attributed to the lack of ability of the physical structure of the ETref×crop coefficient approach to “fully” account for the soil surface conditions when complete canopy cover is not present. The results of this study can be used as a reference tool by the water resources regulatory agencies and water users and can provide practical information on which method to select based on the data availability for reliable estimates of daily ETc for corn.     

Regional Estimation of Reference Evapotranspiration in Arid and Semiarid Regions

Evapotranspiration is critical to many applications including water resource management, irrigation scheduling, and environmental studies. Many models based on meteorological data have already been developed to estimate reference evapotranspiration (ET0) in various climatic and geographical conditions. The main purpose of this study was to evaluate the performances of the Makkink, Priestley-Taylor, and Hargreaves models versus the Penman-Monteith FAO-56 (PMF-56) method in arid and semiarid regions of Iran during 1993–2005 and to identify the alternative ET0 model that presents results closest to the PMF-56 method. Additionally, a regional estimation of monthly ET0 with the best-performed model is presented by using the spatially distributed physical parameters and geographical information system. The results indicated that the Hargreaves model was the best model to estimate ET0 in eastern arid and semiarid regions of Iran. The spatial distribution maps of ET0 showed that ET0 values increased from north to south as the aridity increased in the study area. The estimated total monthly ET0 revealed a significant variation during the growing seasons (April–September) so that the study region experienced the highest and lowest ET0 values of 250 and 80 mm in July and April, respectively.     

Modeling Reference Evapotranspiration Using Evolutionary Neural Networks

The ability of evolutionary neural networks (ENN) to model reference evapotranspiration (ET0) was investigated in this study. The daily climatic data, solar radiation, air temperature, relative humidity, and wind speed of three stations in central California, Windsor, Oakville, and Santa Rosa, were used as inputs to the ENN models to estimate ET0 obtained using the FAO-56 Penman-Monteith equation. In the first part of the study, a comparison was made between the estimates provided by the ENN and those of the following empirical models: the California Irrigation Management System, Penman, Hargreaves, modified Hargreaves, and Ritchie methods. Root-mean-squared error, coefficient of efficiency, and correlation coefficient statistics were used as comparing criteria for the evaluation of the models’ accuracies. The ENN performed better than the empirical models. In the second part of the study, the ENN results were compared with those of the conventional artificial neural networks (ANN). The comparison results revealed that the ENN models were superior to ANN in modeling the ET0 process.     

Fuzzy Genetic Approach for Modeling Reference Evapotranspiration

This study investigates the ability of fuzzy genetic (FG) approach in modeling of reference evapotranspiration (ET0). The daily climatic data, solar radiation, air temperature, relative humidity, and wind speed from three stations, Windsor, Oakville and Santa Rosa, in central California, are used as inputs to the FG models to estimate ET0 obtained using the FAO-56 Penman-Monteith equation. A comparison is made between the estimates provided by the FG and those of the following empirical models: the California Irrigation Management System Penman, Hargreaves, Ritchie, and Turc methods. The FG results are also compared with the artificial neural networks. Root-mean-square errors (RMSE), mean-absolute errors (MAE), and correlation coefficient statistics are used as comparing criteria for the evaluation of the models’ performances. The comparison results reveal that the FG models are superior to the ANN and empirical models in modeling ET0 process. For the Windsor, Oakville, and Santa Rosa stations, it was found that the FG models with RMSEW = 0.138, MAEW = 0.098, and RW = 0.999; RMSEO = 0.144, MAEO = 0.102, and RO = 0.999; and RMSES = 0.167, MAES = 0.115, and RS = 0.998 in test period is superior in modeling daily ET0 than the other models, respectively.     

Single-Layer Evapotranspiration Model with Variable Canopy Resistance

A new approach to modeling canopy resistance is presented as an alternative to the Food and Agricultural Organization of the United Nations Penman-Monteith method with the constant canopy resistance. The evapotranspiration (ET) model is based on the “big-leaf” approach and a variable canopy resistance. The model's input requires standard meteorological data as in the Penman-Monteith combination approach. The model was validated using weather and grass lysimeter data measured on an hourly basis at Davis, Calif., and on a daily basis at Policoro, Southern Italy. ET estimates from the model were compared with the results of ET values obtained by the Food and Agricultural Organization of the United Nations Penman-Monteith approach using the constant canopy resistance rc = 70 s m?1. The results showed a very convincing performance of the model for estimating reference ET on both an hourly and daily basis. This work confirms that the canopy resistance depends on climate, and that a variable rc is recommended for ET models. The proposed model does not introduce any empirical parameter, does not require calibration for the two sites tested or for different time scales, and it is simple enough for direct practical application.     

Comparison of Priestley-Taylor and FAO-56 Penman-Monteith for Daily Reference Evapotranspiration Estimation in Georgia

The climate in Georgia and other southeastern states of the United States is considered to be humid and the annual precipitation is usually greater than the annual potential evapotranspiration (ET). However, during several months of the year, supplemental irrigation is needed to prevent yield reducing water stress due to the temporal rainfall variability and sometimes due to long-term droughts. The Priestley-Taylor (PT) equation has been used operationally in Georgia to compute ET for irrigation scheduling because of its simplicity, its general acceptable performance in humid regions, and its limited input requirements. A recent study for a site in the humid southeastern United States found that PT overestimated ET and was less accurate than the FAO-56 Penman-Monteith (PM) among some of the approaches that were evaluated. The objective of this study was to assess the potential improvement that can be achieved by replacing PT with FAO-56 PM in Georgia and other southeastern states in a humid climate. More than 70 weather stations across Georgia are available as part of the Georgia Automated Environmental Monitoring Network. Nine representative sites, including Blairsville in a mountainous area and Savannah in a coastal area, were selected to assess the potential improvements that may be achieved by replacing PT with FAO-56 PM. Each site had at least 10 years of daily records that included minimum and maximum air temperature, solar radiation, wind speed, and vapor pressure deficit. PT underestimated the daily and monthly ET during the winter months in the central and southwestern areas and overestimated the daily and monthly ET during the summer months in the coastal and mountainous areas. For the warm season, i.e., April through September, PT slightly overestimated the cumulative ET in the central and southwestern areas, moderately for the mountainous area and severely for the coastal area. Based on these results, it is anticipated that the use of FAO-56 PM for estimating ET will standardize the ET calculations and improve irrigation efficiency in Georgia, especially for the mountainous and coastal areas.