FAO-56 Dual Crop Coefficient Method for Estimating Evaporation from Soil and Application Extensions

Crop coefficient curves provide simple, reproducible means to estimate crop evapotranspiration (ET) from weather-based reference ET values. The dual crop coefficient (Kc) method of the Food and Agricultural Organization of the United States (FAO) Irrigation and Drainage Paper No. 56 (FAO-56) is intended to improve daily simulation of crop ET by considering separately the contribution of evaporation from soil. The dual method utilizes “basal” crop coefficients representing ET from crops having a dry soil surface and separately predicts evaporation from bare soil based on a water balance of the soil surface layer. Three extensions to the evaporation calculation procedure are described here that are intended to improve accuracy when applications warrant the extra complexity. The first extension uses parallel water balances representing the portion of the soil surface wetted by irrigation and precipitation together and the portion wetted by precipitation alone. The second extension uses three “stages” for surface drying and provides for application to deep cracking soils. The third extension predicts the extraction of the transpiration component from the soil surface layer. Sensitivity and analyses and illustrations indicate moderate sensitivity of daily calculated ET to application of the extensions. The dual Kc procedure, although relatively simple computationally and structurally, estimates daily ET as measured by lysimeter relatively well for periods of bare soil and partial and full vegetation cover.     

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.     

Estimation of Evapotranspiration of Different-Sized Navel-Orange Tree Orchards Using Energy Balance

Crop evapotranspiration (ETc) and crop coefficient (Kco) values of four clean-cultivated navel-orange orchards that were irrigated with microsprinklers, having different canopy features (e.g., age, height, and canopy cover) were evaluated. Half-hourly values of latent heat flux density were estimated as the residual of the energy balance equation using measured net radiation (Rn), soil heat flux density (G), and sensible heat flux density (H) estimated using the surface renewal method. Hourly means of latent heat flux density (LE) were calculated and were divided by the latent heat of vaporization (L) to obtain ETc. Crop coefficients were determined by calculating the ratio Kco = ETc/ETo, with reference evapotranspiration (ETo) determined using the hourly Penman–Monteith equation for short canopies. The estimated Kco values ranged from 0.45 to 0.93 for canopy covers having between 3.5 and 70% ground shading. The Kco values were compared with Kc values from FAO 24 (reported by Doorenbos and Pruitt in 1975) and FAO 56 (reported by Allen et al. in 1998) and with Kc values from research papers that estimated reference ET from pan evaporation data using the FAO 24 method. The observed Kco values were slightly higher than Kc values for clean-cultivated orchards with high-frequency drip irrigation in Arizona and were slightly lower than for nontilled orchards in Florida. The Kco values were considerably higher than Kc values from FAO 24 and FAO 56 and were higher than Kc values from border-irrigated orchards near Valencia, Spain.     

Estimation of Crop Coefficients Using Satellite Remote Sensing

Crop coefficient (Kc) based estimation of crop evapotranspiration (ETc) is one of the most commonly used methods for irrigation water management. The standardized FAO56 Penman-Monteith approach for estimating ETc from reference evapotranspiration and tabulated generalized Kc values has been widely adopted worldwide to estimate ETc. In this study, we presented a modified approach toward estimating Kc values from remotely sensed data. The surface energy balance algorithm for land model was used for estimating the spatial distribution of ETc for major agronomic crops during the 2005 growing season in southcentral Nebraska. The alfalfa-based reference evapotranspiration (ETr) was calculated using data from multiple automatic weather stations with geostatistical analysis. The Kc values were estimated based on ETc and ETr (i.e., Kc = ETc/ETr). A land use map was used for sampling and profiling the Kc values from the satellite overpass for the major crops grown in southcentral Nebraska. Finally, a regression model was developed to establish the relationship between the normalized difference vegetation index (NDVI) and the ETr-based crop coefficients (Kcr) for corn, soybeans, sorghum, and alfalfa. We found that the coefficients of variation (CV) for NDVI, as well as for Kcr of crops were lower during the midseason as compared to the early and late growing seasons. High CV values during the early growing season can be attributed to differences in planting dates between the fields, whereas high CVs during the late season can be attributed to differences in maturity dates of the crops, variety, and management practices. There was a good relationship between Kcr and NDVI for all the crops except alfalfa. Validation of the developed model for irrigated corn showed very promising results. There was a good correlation between the NDVI-estimated Kcr and the Bowen ratio energy balance system based Kcr with a R2 of 0.74 and a low root mean square difference of 0.21. This approach can be a very useful tool for a large (watershed or regional) scale estimation of evapotranspiration using the crop coefficient and reference evapotranspiration approach.     

Surface Renewal Estimation of Pasture Evapotranspiration

Experiments to measure the evapotranspiration of an improved, irrigated pasture were conducted at the University of California, Davis, CA field station and over a commercial irrigated pasture on Twitchell Island in the Sacramento-San Joaquin River Delta using the surface renewal (SR) method. In Davis, the SR method was used to determine well-watered crop evapotranspiration (ETc) over short grass, and the results were compared with the ASCE-EWRI standardized reference evapotranspiration (ET0) for a short canopy to establish that a crop coefficient Kc = 1.00 is appropriate for estimating well-watered pasture ETc. In the Twitchell Island study, surface renewal was used to determine the actual evapotranspiration (ETa) from a commercial pasture. A stress coefficient of Ks = ETa/ET0 ≈ 0.90 was observed during the high ET period (ET0>7?mm?day?1) from about mid-June through mid-July for the Twitchell Island pasture. Otherwise, the pasture was mainly unstressed, so the Ks = 1.0. Thus, assuming no future changes in irrigation management, using ET0 from Twitchell Island, a Kc = 1.00, and Ks = 1.00 will provide good estimates of ETa during low to moderate ET periods and Ks ≈ 0.90 should be used when ET0>7.0?mm?day?1. In general, a thermocouple for SR measurements costs about $100, whereas the price for a sonic anemometer varies between $3,000 and $20,000, so the SR method provides a low-cost method to measure ETa.     

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.     

Model for Estimating Evaporation and Transpiration from Row Crops

Accurate estimates of crop evapotranspiration ETc, that quantify the total water used by a crop, are needed to optimize irrigation scheduling for horticultural crops and to minimize water degradation. During early growth, accurate assessments of ETc are difficult in vegetable crops because of high soil evaporation due to frequent irrigation. A model to estimate ETc for vegetable crops, using only daily reference evapotranspiration data as an input parameter, was developed. It calculates crop transpiration and soil evaporation based on ground cover and daily radiation intercepted by the canopy. The model uses a two-stage soil evaporation method adapted to conditions of variable reference evapotranspiration. The model was evaluated against data using measurements from two seasons of lettuce crop, two tomato fields in the same season, and one season of broccoli crop production. Using all of the crop data, the root-mean-square error for measured versus modeled daily ETc was 0.72 mm day?1, indicating that the model works well.     

Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Applications

Recent satellite image processing developments have provided the means to calculate evapotranspiration (ET) as a residual of the surface energy balance to produce ET “maps.” These ET maps (i.e., images) provide the means to quantify ET on a field by field basis in terms of both the rate and spatial distribution. The ET images show a progression of ET during the year or growing season as well as its spatial distribution. The mapping evapotranspiration at high resolution with internalized calibration (METRIC) is a satellite-based image-processing procedure for calculating ET. METRIC has been applied with high resolution Landsat images in southern Idaho, southern California, and New Mexico to quantify monthly and seasonal ET for water rights accounting, operation of ground water models, and determination of crop coefficient populations and mean curves for common crops. Comparisons between ET by METRIC, ET measured by lysimeter, and ET predicted using traditional methods have been made on a daily and monthly basis for a variety of crop types and land uses. Error in estimated growing season ET was 4% for irrigated meadow in the Bear River basin of Idaho and 1% for an irrigated sugar beet crop near Kimberly, Id. Standard deviation of error for time periods represented by each satellite image averaged about 13 to 20% in both applications. The results indicate that METRIC and similar methods such as SEBAL hold substantial promise as efficient, accurate, and inexpensive procedures to estimate actual evaporation fluxes from irrigated lands throughout growing seasons.     

Evapotranspiration: Concepts and Future Trends

Past research on evapotranspiration has provided sound theoretical knowledge and practical applications that have been validated through field measurements. Many different approaches have been used; however, when primary concepts and standard definitions are accepted, it is possible to find reasonable agreement among methods. This paper reviews such approaches, from Penman to Penman-Monteith. The standard concepts of potential evaporation (EP) and equilibrium evaporation (Ee), and the introduction of the climatic resistance (re), provide a better understanding of the role of the climate together with surface and aerodynamic resistances (rs and ra). Therefore, the concept of reference evapotranspiration (ETo), particularly the new one adopted by the Food and Agricultural Organization of the United Nations, can be better understood, as well as its limitations. Crop evapotranspiration (ETc) is related to both ETo and Ee. Crop coefficients (Kc) can be shown to have two components, αo and αc, with Kc = αoαc. The αo is a function of the climatic resistance and of the aerodynamic resistances of the crop and of the reference crop. The αc is a function of both surface and aerodynamic resistances of the crop and of the reference crop. From this analysis some ideas on future developments result that are directed toward providing compatibility between the one- and two-step calculation of ETc.     

Estimating Evaporation from Bare Soil and the Crop Coefficient for the Initial Period Using Common Soils Information

The crop coefficient during the initial period (Kc?ini) varies with wetting frequency, evaporative demand, and water-holding capacity of the upper soil layer. It is possible to develop a semitheoretical integrated function to predict the average Kc?ini representing the initial period of a growing season when the soil is mostly bare and that incorporates these three factors. The function is based on a two-stage evaporation function as used in the Food and Agriculture Organization Irrigation and Drainage Paper No. 56 (FAO-56) dual crop coefficient method. Parameters in the integrated equation are soil based and can be calculated a priori without field measurements. The procedure can be used to produce graphical figures similar to that introduced in FAO-24 for Kc?ini. Similar to FAO-24, the function utilizes the mean time between wetting events and reference evapotranspiration. In this paper, the development of the procedure and figures for Kc?ini are described. Comparisons with measured evaporation and Kc?ini in southern California indicate relatively good performance by the function without calibration.     

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.     

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.     

Satellite-Based Energy Balance to Assess Within-Population Variance of Crop Coefficient Curves

Quantifying evapotranspiration (ET) from agricultural fields is important for field water management, water resources planning, and water regulation. Traditionally, ET from agricultural fields has been estimated by multiplying the weather-based reference ET by crop coefficients (Kc) determined according to the crop type and the crop growth stage. Recent development of satellite remote sensing ET models has enabled us to estimate ET and Kc for large populations of fields. This study evaluated the distribution of Kc over space and time for a large number of individual fields by crop type using ET maps created by a satellite based energy balance (EB) model. Variation of Kc curves was found to be substantially larger than that for the normalized difference vegetation index because of the impacts of random wetting events on Kc, especially during initial and development growth stages. Two traditional Kc curves that are widely used in Idaho for crop management and water rights regulation were compared against the satellite-derived Kc curves. Simple adjustment of the traditional Kc curves by shifting dates for emergence, effective full cover, and termination enabled the traditional curves to better fit Kc curves as determined by the EB model. Applicability of the presented techniques in humid regions having higher chances of cloudy dates was discussed.     

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.     

Evapotranspiration of Full-, Deficit-Irrigated, and Dryland Cotton on the Northern Texas High Plains

Cotton (Gossypium hirsutum L.) is beginning to be produced on the Northern Texas High Plains as a lower water-requiring crop while producing an acceptable profit. Cotton is a warm season, perennial species produced like an annual yet it requires a delicate balance of water and water deficit controls to most effectively produce high yields in this thermally limited environment. This study measured the water use of cotton in fully irrigated, deficiently irrigated, and dryland regimes in a Northern Texas High Plains environment using precision weighing lysimeters in 2000 and 2001. A lateral-move sprinkler system was used to irrigate the fields. The water use data were used to develop crop coefficient data and compared with the FAO-56 method for estimating crop water use. Cotton yield, water use, and water use efficiency was found to be as good in this region as other more noted cotton regions. FAO-56 evapotranspiration prediction procedures performed better for the more fully irrigated treatments in this environment.     

Actual and Reference Evaporative Losses and Surface Coefficients of a Maize Field during Nongrowing (Dormant) Periods

Effective water resources planning, allocation, management, and use in agroecosystems require accurate quantification of actual evapotranspiration (ETc) during growing and nongrowing (dormant) periods. Prediction of ETc for a variety of vegetation surfaces during the growing season has been researched extensively, but relatively little information exists on evaporative losses during nongrowing periods for different surfaces. The objectives of this research were to evaluate ETc in relation to available energy, precipitation, and grass and alfalfa-reference ET (ETo and ETr) for a maize (Zea mays. L) field and to analyze the dynamics of surface coefficients (Kc) during the nongrowing period (October 15–April 30). The evaporative losses were measured using a Bowen ratio energy balance system (BREBS) on an hourly basis and averaged over 24?h for three consecutive nongrowing periods: 2004–2005 (Season I), 2005–2006 (Season II), and 2006–2007 (Season III). BREBS-measured ETc was approximately 50% of available energy (Rn?G; Rn is net radiation and G is soil heat flux density) during normal and wet seasons (Seasons I and III) and 41% of available energy during a dry season (Season II). Cumulative ETc ranged from 133?mm in Season II to 167?mm in Season III and exceeded precipitation by 21% during the dry season. The ratio of ETc to precipitation was 0.85 in Season I, 1.21 in Season II, and 0.41 in Season III. ETc was approximately 50% of ETo and 36% of ETr in both Seasons I and III, whereas in Season II, ETc was 32% of ETo and 23% of ETr. Overall, measured ETc during the dormant season was generally most strongly correlated with radiation terms, particularly Rn, albedo, incoming shortwave radiation, and outgoing longwave radiation. Average surface coefficients over the three seasons were 0.44 and 0.33 for grass and alfalfa-reference surfaces, respectively. Using geometric mean Kc values to calculate ETc using a KcETref approach over the entire nongrowing season yielded adequate predictions with overall root mean square deviations of 0.64 and 0.67?mm?day?1 for ETo and ETr, respectively. Estimates of ETc using a dual crop coefficient approach were good on a seasonal basis, but performed less well on a daily basis. Regression equations that were developed (accounting for serial autocorrelation in the ETc and ETref time series) yielded good estimates of ETc. Considering nongrowing period evaporative losses in water budget calculations would enable water regulatory agencies to better account for water use in hydrologic balance calculations over the entire year rather than only for the growing season and to better assess the progression and availability of water resources for the next growing season.     

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.     

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.     

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.     

Potential Evapotranspiration for the Distributed Modeling of Belgian Catchments

To support a sensitivity analysis in the framework of catchment modeling, three potential evapotranspiration (ETp) scenarios were generated by means of two Food and Agriculture Organization (FAO) approaches, namely, the FAO-24 and the FAO-56 approaches. The crop ETp was estimated as a function of the reference evapotranspiration (ETo) by means of the kc-ETo approach. Scenario A was generated with the standard FAO-24 approach; Scenario B considered also the FAO-24 approach, but with some nonstandard parameters. Scenario C considered the standard FAO-56 approach. The ETo data were compared to point-scale ETo constraints. The annual cumulative value of ETo from Scenario A was on average approximately 200 mm larger than the values from Scenarios B and C. The research revealed similar ETo estimates for Scenarios B and C. The research also assessed the performance of the angstrom approach for estimating incoming solar radiation (Rs). In this context, a set of angstrom coefficients was derived by means of an optimization process that considered available Rs data.