This paper evaluates how well the FAO-56 style soil water evaporation model simulates measurements of evaporation (E) from bare soil. Seven data sets were identified from the literature and in all but one case, the individuals who took the measurements were contacted and they provided the writers with specific weather and soils data for model input. Missing weather and soils data were obtained from online sources or from the National Climatic Data Center. Simulations for three possible variations of soil data were completed and compared. The measured and the FAO-56 simulated E∕ETo and cumulative evaporation trends and values were similar. Specifically, the average evaporation weighted percent difference between the measured and the simulated cumulative evaporation was between −7.5 and −0.5% . This evaluation suggests model accuracy of about ±15% with the use of sound weather data and a fairly generalized understanding of soil properties in the location being evaluated.
The crop coefficient during the initial period (Kcini) 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 Kcini 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 Kcini . 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 Kcini are described. Comparisons with measured evaporation and Kcini in southern California indicate relatively good performance by the function without calibration.
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.
The FAO Blaney‐Criddle (FAO‐BC) evapotranspiration equation was calibrated and tested against a Penman combination equation with local wind function and daily lysimeter measurements of alfalfa evapotranspiration. Agreement between the calibrated FAO‐BC method and lysimeters was excellent for daily, weekly and monthly estimates when measured values for solar radiation, air temperature, relative humidity and wind speed were used. An elevation correction reduced scatter in estimates among Idaho locations. Statistics describing the daily Penman and FAO‐BC estimates deviated from those calculated for measured alfalfa reference evapotranspiration. Air temperature and relative humidity data for nonagricultural weather stations were adjusted according to fetch and aridity before being used to estimate consumptive use requirements throughout Idaho. Calibration of the FAO‐BC allowed use of alfalfa‐based crop coefficients.
Water management emphasis tends to shift from supply augmentation to limiting water consumption. Spatio-temporal information on actual evapotranspiration (ET) helps users to better understand evaporative depletion and to establish links between land use, water allocation, and water use. Satellite-based measurements, used in association with energy balance models, can provide the spatial distribution of ET for these linkages. This paper describes the major principles of the Surface Energy Balance Algorithm for Land (SEBAL) and summarizes its accuracy under several climatic conditions at both field and catchment scales. For a range of soil wetness and plant community conditions, the typical accuracy at field scale is 85% for 1day and it increases to 95% on a seasonal basis. The accuracy of annual ET of large watersheds was found to be 96% on average. SEBAL has been applied in more than 30 countries worldwide, and the 26 research studies that were conducted over the past 10years are now gradually being replaced by application studies (17 studies finished). A short case study in the Yakima River basin (Washington State) is presented as new material to demonstrate how ET from remote sensing can be used for evaluating water conservation projects.
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.
