Comparison of Some Reference Evapotranspiration Equations for California

Four reference evapotranspiration (ETo) equations are compared using weather data from 37 agricultural weather stations across the state of California. The equations compared include the California Irrigation Management Information System (CIMIS) Penman equation, the Penman–Monteith equation standardized by the Food and Agriculture Organization (FAO), the Penman–Monteith equation standardized by the American Society of Civil Engineers, and the Hargreaves equation. Hourly and daily comparisons of ETo and net radiation (Rn) are made using graphics and simple linear regressions. ETo values estimated by the CIMIS Penman equation correlated very well with the corresponding values estimated by the standardized Penman–Monteith equations on both hourly and daily time steps. However, there are greater differences between the Rn values estimated by the two procedures. Although there are exceptions, the Hargreaves equation compared well to the FAO Penman–Monteith method. Spatial variability of the resulting correlations between the different equations is also assessed. Despite the wide variability of microclimates in the state, there are no visible spatial trends in correlations between the different ETo and/or Rn estimates.     

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.     

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.     

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.     

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.     

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.     

Reference and Crop Evapotranspiration in South Central Nebraska. I: Comparison and Analysis of Grass and Alfalfa-Reference Evapotranspiration

In Nebraska, historically, there have been differences among the water regulatory agencies in terms of the methods used to compute reference evapotranspiration (ETref) to determine actual crop water requirements and hydrologic balances of watersheds. Because simplified and/or empirical temperature or radiation-based methods lack some of the major weather parameters that can significantly affect grass and alfalfa-reference ET (ETo and ETr) the performance of these methods needs to be investigated to help decision makers to determine the potential differences associated with using various ETref equations relative to the standardized ASCE Penman–Monteith (ASCE-PM) equations. The performance of 12 ETo and five ETr equations were analyzed on a daily basis for south central Nebraska from 1983 to 2004. The standardized ASCE-PM ETo and ETr values were used as the basis for comparisons. The maximum ASCE-PM ETo value was estimated as 12.6?mm?d?1, and the highest ETr value was estimated as 19?mm?d?1 on June 21, 1988. On this day, the atmospheric demand for evaporation was extremely high and the vapor pressure deficit (VPD) reached a remarkably high value of 4.05?kPa. The combination-based equations exhibited significant differences in performance. The 1963 Penman method resulted in the lowest RMSD of 0.30?mm?d?1 (r2 = 0.98) and its estimates were within 2% of the ASCE-PM ETo estimates. The 1948 Penman estimates were similar to the 1963 Penman (r2 = 0.98, RMSD = 0.39?mm?d?1). Kimberly forms of alfalfa-reference Penman equations performed well with RMSD of 0.48?mm?d?1 for the 1972 Kimberly–Penman and 0.67?mm?d?1 for the 1982 Kimberly–Penman. The locally-calibrated High Plains Regional Climate Center (HPRCC) Penman method, ranked 6th, performed well and underestimated the ASCE-PM ET by 5% (RMSD = 0.56?mm?d?1). Most of the underestimations occurred at the high ET range (>11?mm) and this was attributed to the upper limits applied by the HPRCC on VPD, (2.3?kPa) and wind speed (5.1?m?s?1). The lack of ability of the radiation methods in accounting for the wind speed and relative humidity hindered the performance of these methods in the windy and rapidly changing VPD conditions of south central Nebraska. The 1977 FAO24 Blaney–Criddle method was the highest ranked (seventh) noncombination method (RMSD = 0.64?mm?d?1, r2 = 0.94). The FAO24 Penman estimates were within 4% of the ASCE-PM ETo. Overall, there were large differences between the ASCE-PM ETo and ETr versus other ETref equations that need to be considered when other forms of the combination or radiation and temperature-based equations are used to compute ETref. We recommend that the ASCE-PM ETo or ETr equations be used for estimating ETref when necessary weather variables are available and have good quality. The results of this study can be used as a reference tool to provide practical information, for Nebraska and similar climates, on the potential differences between the ASCE-PM ETo and ETr and other ETref equations. Results can aid in selection of the alternative method(s) for reasonable ETref estimations when all the necessary weather inputs are not available to solve the ASCE-PM equation.     

Estimating Actual Evapotranspiration from Limited Climatic Data Using Neural Computing Technique

This paper examines the potential of artificial neural networks (ANN) in estimating the actual crop evapotranspiration (ET) from limited climatic data. The study employed radial-basis function (RBF) type ANN for computing the daily values of ET for rice crop. Six RBF networks, each using varied input combinations of climatic variables, have been trained and tested. The model estimates are compared with measured lysimeter ET. The results of the study clearly demonstrate the proficiency of the ANN method in estimating the ET. The analyses suggest that the crop ET could be computed from air temperature using the ANN approach. However, the present study used a single crop data for a limited period, therefore further studies using more crops as well as weather conditions may be required to strengthen these conclusions.     

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.     

Evaluation of Reference Evapotranspiration Estimation Methods under Southeast Australian Conditions

Reference evapotranspiration (ETo) estimates are often required for use in water resources planning and irrigation scheduling. Ten ETo estimation methods ranging from simple temperature-based to data-extensive combination methods, including Hargreaves (HAR), improved Hargreaves (IHA), FAO-24 Radiation (RAD), Ritchi-type (RIT), FAO-24 Class-A Pan with pan coefficients of Doorenbos and Pruitt (PEV) and empirical regression coefficient (SEV), combination methods McIlroy (McI), FAO-Penman with wind functions of Watts and Hancock (W_H) and Meyer (M_PY), and the Penman-Monteith (P_M) were evaluated at three sites, namely, Aspendale, Griffith, and Tatura in the Goulburn-Murray Irrigation Area (GMIA) of southeastern Australia. At Aspendale, 4 out of 10 ETo methods (McI, M_PY, SEV, and RAD) overestimated the ETo estimates; at Griffith no method overestimated them, whereas at Tatura only the RAD method overestimated ETo. The overestimations were at Griffith, McI (1%), M_PY (10%), and SEV (4%); at Tatura, RAD (2%). At the Griffith and Tatura sites, almost all methods showed a strong tendency to underestimate daily ETo estimates throughout the entire range of evaporative demand. Overall, the underestimation ranges observed were McI (12–27%), W_H (7–22%), RIT (6–25%), PEV (19–31%), HAR (18–31%), and IHA (8–11%). The underestimation of daily ETo estimates by the P_M method ranged from 21 to 29%, raising caution about its use as a base method (without calibration against measured data under local conditions) to evaluate other ETo methods, as has been advocated in recent literature. The use of the McI method as the top-ranked method at Aspendale and Tatura, and the W_H method at Griffith, indicated that no single daily ETo estimation method using meteorological data was satisfactory for all three sites. Generally, the combination methods proved to be the most accurate ETo estimates. At Tatura, the fact that the RAD method was ahead of the W_H and M_P combination methods indicates how a less data-intensive ETo method, if calibrated, can perform even better than a physically based combination method. All ETo estimation methods required local calibration against measured lysimeter ETo data for better performance.     

Adaptive Neurofuzzy Computing Technique for Evapotranspiration Estimation

The accuracy of an adaptive neurofuzzy computing technique in estimation of reference evapotranspiration (ET0) is investigated in this paper. The daily climatic data, solar radiation, air temperature, relative humidity, and wind speed from two stations, Pomona and Santa Monica, in Los Angeles, Calif., are used as inputs to the neurofuzzy model to estimate ET0 obtained using the FAO-56 Penman–Monteith equation. In the first part of the study, a comparison is made between the estimates provided by the neurofuzzy model and those of the following empirical models: The California Irrigation Management System, Penman, Hargreaves, and Ritchie. In this part of the study, the empirical models are calibrated using the standard FAO-56 PM ET0 values. The estimates of the neurofuzzy technique are also compared with those of the calibrated empirical models and artificial neural network (ANN) technique. Mean-squared errors, mean-absolute errors, and determination coefficient statistics are used as comparing criteria for the evaluation of the models’ performances. The comparison results reveal that the neurofuzzy models could be employed successfully in modeling the ET0 process. In the second part of the study, the potential of the neurofuzzy technique, ANN and the empirical methods in estimation ET0 using nearby station data are investigated.     

Comparison of Simplified Pan-Based Equations for Estimating Reference Evapotranspiration

Accurate estimation of reference evapotranspiration (ET0) is essential for irrigation practice. Conversion from pan evaporation data to reference evapotranspiration is commonly practiced. The objective of this study was to evaluate the reliability of simplified pan-based approaches for estimating ET0 directly that do not require the data of relative humidity and wind speed. In this study, three pan-based (FAO-24 pan, Snyder ET0, and Ghare ET0) equations were compared against lysimeter measurements of grass evapotranspiration using daily data from Policoro, Italy. Based on summary statistics, the Snyder ET0 equation ranked first with the lowest RMSE value (0.449?mm?day?1). The pan-based equations were additional tested using mean daily data collected in Novi Sad, Serbia. The Snyder ET0 equation best matched ET0 estimates by Penman-Monteith equation at Novi Sad with lowest root mean square error value of 0.288?mm?day?1. The obtained results demonstrate that simplified pan-based equations can be successful alternative to FAO-56 Penman-Monteith equation for estimating reference evapotranspiration. The overall results recommended Snyder ET0 equation for pan evaporation to evapotranspiration conversions. The Snyder ET0 equation consistently provides better results compared to FAO-24 pan equation, although required measurements of only one weather parameter pan evaporation.     

Surface Energy Balance-Based Model for Estimating Evapotranspiration Taking into Account Spatial Variability in Weather

Reliable estimates of evapotranspiration (ET) from vegetation are needed for many types of water-resource investigations. How well models can estimate ET from vegetation varies, depending on the capabilities of the model as well as the nature of the targeted vegetation. Model accuracy also depends heavily on the quality and quantity of the data used. Several ET models have been developed that use an energy balance approach in which the data used by the models are derived from satellite imagery. This research introduces an enhanced surface energy balance-based model, the remote sensing of evapotranspiration or ReSET model, for estimating ET. ReSET is an ET estimation model that takes into consideration the spatial variability in weather parameters, which makes it particularly applicable for calculating regional scale ET. ReSET also has the capability of interpolating between the available weather stations in time and space. The model’s accuracy at daily and seasonal time scales is evaluated in several case studies.     

Prediction Accuracy for Projectwide Evapotranspiration Using Crop Coefficients and Reference Evapotranspiration

The Imperial Irrigation District is a large irrigation project in the western United States having a unique hydrogeologic structure such that only small amounts of deep percolation leave the project directly as subsurface flows. This structure is conducive to relatively accurate application of a surface water balance to the district, enabling the determination of crop evapotranspiration (ETc) as a residual of inflows and outflows. The ability to calculate ETc from discharge measurements provides the opportunity to assess the accuracy and consistency of an independently applied crop coefficient—reference evapotranspiration (Kc?ET0) procedure integrated over the project. The accuracy of the annual crop evapotranspiration via water balance estimates was ±6% at the 95% confidence level. Calculations using Kc and ET0 were based on the FAO-56 dual crop coefficient approach and included separate calculation of evaporation from precipitation and irrigation events. Grass reference ET0 was computed using the CIMIS Penman equation and ETc was computed for over 30 crop types. On average, Kc-based ET computations exceeded ETc determined by water balance (referred to as ETc?WB) by 8% on an annual basis over a 7 year period. The 8% overprediction was concluded to stem primarily from use of Kc that represents potential and ideal growing conditions, whereas crops in the study area were not always in full pristine condition due to various water and agronomic stresses. A 6% reduction to calculated Kc-based ET was applied to all crops, and a further 2% reduction was applied to lower value crops to bring the project-wide ET predicted by Kc-based ET into agreement with ETc?WB. The standard error of estimate (SEE) for annual ETc for the entire project based on Kc, following the reduction adjustment, was 3.4% of total annual ETc, which is considered to be quite good. The SEE for the average monthly ETc was 15% of average monthly ETc. A sensitivity analysis of the computational procedure for Kc showed that relaxation from using the FAO-56 dual Kc method to the more simple mean (i.e., single) Kc curve and relaxation of specificity of planting and harvest dates did not substantially increase the projectwide prediction error The use of the mean Kc curves, where effects of evaporation from wet soil are included as general averages, predicted 5% lower than the dual method for monthly estimates and 8% lower on an annual basis, so that no adjustment was required to match annual ET derived from water balance. About one half of the reduction in estimates when applying the single (or mean) Kc method rather than the dual Kc method was caused by the lack of accounting for evaporation from special irrigations during the off season (i.e., in between crops).     

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.     

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.     

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.     

Assessing Reference Evapotranspiration by the Hargreaves Method in Southern Spain

The Hargreaves method enables reference crop evapotranspiration (ET0) estimation in areas where meteorological information is scarce, as, for example, southern Spain. However, this method is known to produce considerable bias in this region, especially during the dry, hot summer months. An evaluation of the method is made by comparing daily estimates with those made by the more commonly recommended Penman–Monteith method at 16 meteorological stations. Computed ET0 values at the coastal stations are, on average, 0.69 mm?d?1 smaller than the Penman–Monteith estimates whereas at inland stations a small average overestimation of 0.13 mm?d?1 is shown. The adjusted Hargreaves coefficient (AHC), obtained through regression analysis, increases at the coastal stations, on average, to 0.0029, and decreases at the inland stations to 0.0022. Adjustment with the Samani method does generally not produce more accurate estimates in this region. Finally a linear relationship between the AHC and the rate of the average temperature to the average daily temperature range is proposed for the regional adjustment of the Hargreaves coefficient.     

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.     

Distribution and Trends in Reference Evapotranspiration in the North China Plain

The distribution and trends in reference evapotranspiration (ETo) are extremely important to water resources planning for agriculture, and it is widely believed that rates of ETo will increase with global warming. This is a big concern in China, where water deficits are common in the North China Plain (NCP). In this study, Penman-Monteith reference evapotranspiration at 26 meteorological stations during 1961–2006 in and around the NCP was calculated. The temporal variations and spatial distribution of ETo were analyzed and the causes for the variations were discussed. The results showed that: (1) the NCP was divided into two climatic regions based on aridity values: a semiarid region that accounts for 69% of the area and subhumid regions that made of the remaining area; (2) over the entire NCP, the highest annual ETo occurred in the central and western areas and the lowest total ETo was observed in the east. Comparing the mean monthly ETo and annual ETo distributions, the high ETo values from May through July mainly determined the annual ETo distribution; (3) for the whole NCP, annual ETo showed a statistically significant decrease of 11.92 mm/decade over the 46 years of data collection in the NCP or approximately a 5% total decrease compared to the ETo values in 1961; (4) to determine which variable has the greatest effect on the decrease in ETo, decadal changes were observed for daily values of maximum air temperature (+0.16°C), minimum air temperature (+0.35°C), net radiation (?0.13?MJ?m?2), and mean wind speed (?0.09?m?s?1). These results indicate that the decreasing net radiation and wind speed had a bigger impact on ETo rates than the increases observed by the maximum and minimum temperatures.