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.     

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.     

Predicting Daily Net Radiation Using Minimum Climatological Data

Net radiation (Rn) is a key variable for computing reference evapotranspiration and is a driving force in many other physical and biological processes. The procedures outlined in the Food and Agriculture Organization Irrigation and Drainage Paper No. 56 [FAO56 (reported by Allen et al. in 1998)] for predicting daily Rn have been widely used. However, when the paucity of detailed climatological data in the United States and around the world is considered, it appears that there is a need for methods that can predict daily Rn with fewer input and computation. The objective of this study was to develop two alternative equations to reduce the input and computation intensity of the FAO56-Rn procedures to predict daily Rn and evaluate the performance of these equations in the humid regions of the southeast and two arid regions in the United States. Two equations were developed. The first equation [measured-Rs-based (Rs-M)] requires measured maximum and minimum air temperatures (Tmax and Tmin), measured solar radiation (Rs), and inverse relative distance from Earth to sun (dr). The second equation [predicted-Rs-based (Rs-P)] requires Tmax, Tmin, mean relative humidity (RHmean), and predicted Rs. The performance of both equations was evaluated in different locations including humid and arid, and coastal and inland regions (Gainesville, Fla.; Miami, Fla.; Tampa, Fla.; Tifton, Ga.; Watkinsville, Ga.; Mobile, Ala.; Logan, Utah; and Bushland, Tex.) in the United States. The daily Rn values predicted by the Rs-M equation were in close agreement with those obtained from the FAO56-Rn in all locations and for all years evaluated. In general, the standard error of daily Rn predictions (SEP) were relatively small, ranging from 0.35 to 0.73 MJ?m?2?d?1 with coastal regions having lower SEP values. The coefficients of determination were high, ranging from 0.96 for Gainesville to 0.99 for Miami and Tampa. Similar results, with approximately 30% lower SEP values, were obtained when daily predictions were averaged over a three-day period. Comparisons of Rs-M equation and FAO56-Rn predictions with the measured Rn values showed that the Rs-M equations’ predictions were as good or better than the FAO56-Rn in most cases. The performance of the Rs-P equation was quite good when compared with the measured Rn in Gainesville, Watkinsville, Logan, and Bushland locations and provided similar or better daily Rn predictions than the FAO56-Rn procedures. The Rs-P equation was able to explain at least 79% of the variability in Rn predictions using only Tmax, Tmin, and RH data for all locations. It was concluded that both proposed equations are simple, reliable, and practical to predict daily Rn. The significant advantage of the Rs-P equation is that it can be used to predict daily Rn with a reasonable precision when measured Rs is not available. This is a significant improvement and contribution for engineers, agronomists, climatologists, and others when working with National Weather Service climatological datasets that only record Tmax and Tmin on a regular basis.     

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.     

Application of SEBAL Model for Mapping Evapotranspiration and Estimating Surface Energy Fluxes in South-Central Nebraska

Knowledge of spatiotemporal distribution of evapotranspiration (ET) on large scales, as quantified by satellite remote sensing techniques, can provide important information on a variety of water resources issues such as evaluating water distributions, water use by different land surfaces, water allocations, water rights, consumptive water use and planning, and better management of ground and surface water resources. The objective of this study was to assess the operational characteristics and performance of the surface energy balance algorithm for land (SEBAL) model for estimating crop ET (ETc) and other energy balance components, and mapping spatial distribution and seasonal variation of ETc on a large scale in south-central Nebraska climatic conditions. A total of seven cloud free Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM) satellite images (May 19, June 20, July 22, August 7, September 8, September 16, and October 18, 2005) were processed to generate ETc maps and estimate surface energy fluxes. Predictions from the SEBAL model were compared with the Bowen ratio energy balance system (BREBS)-measured fluxes on an instantaneous and daily basis. The ETc maps generated by the model for seven Landsat overpass days showed a very good progression of ETc with time during the growing season in 2005 as the surface conditions continuously changed. The predictions for some surface energy fluxes were very good. Overall, a very good correlation was found between the BREBS-measured and SEBAL-estimated ETc with a good r2 of 0.73 and a root-mean-square difference (RMSD) of 1.04?mm?day?1. The estimated ETc was within 5% of the measured ETc. The model was able to predict growing season (from emergence to physiological maturity) cumulative daily corn ET reasonable well within 5% of the BREBS-measured values. The model overestimated the surface albedo by about 26% with a RMSD of 0.05. The difference between the measured and predicted albedo was the greatest on May 19, early in the growing season before the full canopy cover. The second largest difference between the two albedo values was on October 18, a day after harvest. The model significantly under predicted soil heat flux with a large RMSD of 80?W?m?2 and most of the underestimation occurred in the late growing season. Local calibration of soil heat flux significantly improved the agreement between the measured and predicted values. Furthermore, the sensible heat flux was underestimated between September 20 (after physiological maturity) and October 18 (a day after harvest). While our results showed that SEBAL can be a viable tool for generating ETc maps to assess and quantify spatiotemporal distribution of ET on large scales as well as estimating surface energy fluxes, its operational assessment for estimating sensible heat flux and ETc, especially during the drier periods for different surfaces, needs further development.     

Statistical Analysis of Reference Evapotranspiration on the Tibetan Plateau

Net radiation is an important and site-specific component to determine reference evapotranspiration (ET0). The empirical Angstrom coefficients for radiation estimation in the FAO56 Penman–Monteith (PM) equation were calibrated using observed daily solar radiation and actual sunshine duration on the Tibetan Plateau. The calibrated Angstom coefficients included annual coefficients for nine meteorological stations separately and aggregation of nine stations. The calibrated annual coefficients for each station separately were applied to estimate net radiation and further employed to estimate ET0 using the PM and the Priestley–Taylor (PT) equations on the Tibetan Plateau. Moreover, the Hargreaves (Harg) equation that requires only air temperature was also applied to estimate ET0. Comparisons of three methods were conducted and the results showed that the PT method overestimated daily ET0 with respect to PM–ET0 and the Harg method underestimated it at all meteorological stations. The PT method was more suitable for the study area in the absence of the parameters necessary for the calculation of PM–ET0. The Harg equation provides ET0 estimates when only air temperature is available and local calibration in the study can be applied on the Tibetan Plateau.     

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.     

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.     

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.     

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.     

Estimating Daily Net Radiation over Vegetation Canopy through Remote Sensing and Climatic Data

Net radiation (Rn)=key variable in hydrological studies. Measured net radiation data are rarely available and are often subject to error due to equipment calibration or failure. In addition, point measurements of net radiation do not represent the diversity of the regional net radiation values which are needed for large scale evapotranspiration mapping. A procedure has been developed to estimate daily net radiation using canopy temperature, albedo, short wave radiation and air temperature. This procedure makes it possible to estimate Rn by combining information from satellite and local weather stations. Three different methodologies are presented to estimate net radiation. Comparisons between net radiation using the three methods resulted in average error ranging from 1 to 30% and standard error of estimate ranging from 1.06?to?5.34?MJ/m2/day.     

Relative Comparison of the Local Recalibration of the Temperature-Based Evapotranspiration Equation for the Korea Peninsula

It is well known that local calibration is subject to improving the performance of the temperature-based equation because that calibration includes the influence of the local climate characteristics. This paper evaluates different local recalibrations (the regression-based, one-parameter, and three-parameter methods) of the Hargreaves equation at 21 meteorological stations. The FAO-56 Penman-Monteith is used to describe the control condition against which each calibration method is then assessed. The one-parameter method provides the strength for inland areas, while it presents the worst performance for coastal areas. The regression-based calibration provides slightly better performance for coastal areas. It is true that the difference between the estimates of ETo using the different calibration methods is relatively small and that the difference does not provide the benchmark control that is desirable to demonstrate a significant difference. In relative terms, the regression-based and the three-parameter methods can be an alternative for both inland and coastal areas, giving similar level of accuracy. However, the one-parameter presents may be an alternative only for inland areas. This study can provide guidelines for crop production, water resources conservation, irrigation scheduling, and environmental assessment.     

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.     

Correlation for Diffuse Radiation from Global Solar Radiation and Sunshine Data at Beijing, China

Solar radiation data are essential for the work of energy planners, engineers, and agricultural scientists. However, most solar radiation recording stations measure only global radiation in China. It is, therefore, necessary to elaborate correlations between the rarely available diffuse radiation and other climatic data. In the present study, 10-year data (1995–2004) of daily global diffuse solar radiation and sunshine duration obtained at Beijing meteorological station of China was analyzed to guide future projects. Nine models correlating the diffuse fraction (Kd) with both the clearness index (Kt) and percentage possible sunshine (S/S0) and each variable separately were tested. The accuracy of the correlations is performed in terms of the two widely used statistical indicators, mean bias error, and root mean square error. The results indicate that the correlations relating Kd with both Kt and S/S0 are more reliable than using each variable separately and Model 9 is preferred for its accuracy. The recorded data of Zhengzhou meteorological station are compared with the corresponding values predicted by Model 9 of Beijing. Model 9 provides predictions very close to the measured values of Zhengzhou. Therefore, it may be concluded that Model 9 can be used for estimating diffuse solar radiation for locations of semiwet region of the north of China where only global solar radiation and sunshine duration are available.     

Correlations for Estimation of Solar Radiation on Horizontal Surfaces

In this study, variation of the solar radiation over horizontal surfaces for clear-sky atmospheres was predicted and compared with measurements carried out in Erzurum, Turkey (latitude: 39.55, longitude: 41.16, and altitude: 1869?m). Hottel’s clear-sky model was used in calculations of solar radiation on horizontal surfaces for clear-sky atmospheres. The results show that the model calculations are reasonably consistent with the measured data. It is recommended that Hottel’s clear-sky model can be used for solar radiation calculations in Erzurum. Also, correlation equations giving monthly averages of clear-sky and global solar radiation on horizontal surfaces have been developed. In order to indicate the performance of the correlation equations, the relative percentage error, correlation coefficient, mean percentage error, mean bias error, and root-mean-square-error methods were used.     

Estimating Regional Evapotranspiration Using Remote Sensing: Application to Sone Low Level Canal System, India

Remote sensing-derived spectral data have been used in the past to partition net radiation, soil heat, and sensible heat fluxes for estimating latent heat flux as a residual of surface energy balance, and thus regional evapotranspiration. Attempts to provide a simplified procedure for estimating sensible heat flux at a regional scale have not been successful because of the relatively strong dependence of the heat transfer coefficient on the land–atmosphere boundary condition. This paper presents a remote sensing-based procedure to estimate the sensible heat flux incorporating the local meteorological conditions, and in turn to determine the regional evapotranspiration. The model utilizes satellite-derived surface albedo, surface temperature, and leaf area index along with a very few agrometeorological data as inputs. The proposed procedure has been tested on a part of the Western Yamuna Canal system, India, and is found to be computationally simple as well as stable. For a well-watered wheat crop, the average evapotranspiration by the proposed model is estimated to be 2.05?mm?d?1 on January 30, 1996, whereas it is estimated to be 1.89?mm?d?1 using the Penman-Monteith equation, indicating a difference of less than 10%. The model is subjected to sensitivity analysis for uncertainties in the observed wind velocity and the computed leaf area index (by ±20%) to estimate sensible heat flux. Results reveal that the percentage change in mean sensible heat flux for the image is less than 5% in all cases, thus indicating the acceptability of the model against the uncertainties. Further, the model has been applied to three sets of Landsat-TM data covering the Sone Low Level Canal system, India, to demonstrate its usefulness in evaluating water delivery performance.     

Forecasting Weekly Evapotranspiration with ARIMA and Artificial Neural Network Models

Information about the parameters defining water resources availability is a key factor in their management. Reference evapotranspiration (ET0) prediction is fundamental in planning, design, and management of water resource systems for irrigation. The application of time series analysis methodologies, which allow evapotranspiration prediction, is of great use for the latter. The objective of the present study was the comparison of weekly evapotranspiration ARIMA and artificial neural network (ANN)-based forecasts with regard to a model based on weekly averages, in the region of álava situated in the Basque Country (northern Spain). The application of both ARIMA and ANN models improved the performance of 1?week in advance weekly evapotranspiration predictions compared to the model based on means (mean year model). The ARIMA and ANN models reduced the prediction root mean square differences with respect to the mean year model (based on historical averages) by 6–8%, and reduced the standard deviation differences by 9–16%. The variations in the performances of the prediction models evaluated depended on the weekly evapotranspiration patterns of the different months.     

Use of Alternative Temperature Expressions with Blaney-Criddle

The widely used Penman-Monteith equation to estimate crop evapotranspiration (ET) has limited utility in many areas of the world because of its requirement for full meteorological data. Legal and engineering water agencies commonly use the original Blaney-Criddle method in their efforts to manage competing water demands in mountain basins, both for its longtime familiarity and minimal data requirements. The original Blaney-Criddle equation predicts crop ET based solely on readily available mean monthly air temperature, t, and percentage of daylight hours. However, in semiarid, high-elevation environments, Blaney-Criddle underestimates crop ET. Subsequent modifications have not fully corrected this underestimation. Low nighttime temperatures at high elevations incorrectly weight the estimate, resulting in significant variation between computed crop ET and lysimeter measurements. Our objective was to evaluate three modifications of the Blaney-Criddle temperature expression against the original equation with mean t, and another temperature method, Hargreaves, using lysimeter measurements from nine irrigated grass meadow sites in the upper Gunnison River basin of Colorado (1999–2003). Two of the modified temperature expressions resulted in improved correlation of Blaney-Criddle estimated crop ET with lysimeter ET. Similar improvements were observed when estimating with Hargreaves, which incorporates an additional term, Tdiff, the difference between maximum and minimum daily temperature. Correlations of solar radiation (Rs, the primary energy input to ET) with alternative temperature expressions and Tdiff were improved over correlations of Rs with mean t, supporting the improved prediction performance of alternative temperature expressions. These modifications to the original Blaney-Criddle can be applied successfully throughout Colorado mountain basins and may be globally applicable to high-elevation areas.     

Performance Evaluation of ANN and ANFIS Models for Estimating Garlic Crop Evapotranspiration

Estimation of evapotranspiration (ET) is necessary in water resources management, farm irrigation scheduling, and environmental assessment. Hence, in practical hydrology, it is often necessary to reliably and consistently estimate evapotranspiration. In this study, two artificial intelligence (AI) techniques, including artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), were used to compute garlic crop water requirements. Various architectures and input combinations of the models were compared for modeling garlic crop evapotranspiration. A case study in a semiarid region located in Hamedan Province in Iran was conducted with lysimeter measurements and weather daily data, including maximum temperature, minimum temperature, maximum relative humidity, minimum relative humidity, wind speed, and solar radiation during 2008–2009. Both ANN and ANFIS models produced reasonable results. The ANN, with 6-6-1 architecture, presented a superior ability to estimate garlic crop evapotranspiration. The estimates of the ANN and ANFIS models were compared with the garlic crop evapotranspiration (ETc) values measured by lysimeter and those of the crop coefficient approach. Based on these comparisons, it can be concluded that the ANN and ANFIS techniques are suitable for simulation of ETc.