Evapotranspiration Equations Research Articles

Crop coefficients for peanut evapotranspiration

Meteorological and soil moisture data were collected from field sites in Caddo County, Oklahoma, during the 1984 and 1985 irrigation seasons. Analysis of alfalfa ( Medicago sativa L.) water use data enabled calibration of the modified Penman equation for reference crop evapotranspiration ( et). A crop coefficient relationship for Spanish peanuts ( Arachis hypogaea L.) was developed from measurements at well-watered sites. This et relationship was used in a simple water balance model, and the resulting estimates of soil water status agreed well with field observations.

Hydrologic soil properties and application of a soil moisture model in a balsam fir forest

An analysis of hydrologic soil properties and the prediction of volumetric soil water content during four summers have been done for a site located in the balsam fir (Abiesbalsamea (L.) Mill.) forest of the Lac Laflamme watershed. The hydrologic properties were used to identify three different soil layers, THIRSTY, a soil moisture model using the Penman evapotranspiration formula, was applied to predict daily volumetric water content of these layers. Predictions of soil moisture with the calibrated model were close to the observed data for the median layer (20–60 cm from the soil surface) and less accurate for the surface layer (0–20 cm) where important transpiration activities take place. The model appeared unreliable for predicting soil water content of the bottom layer (60–100 cm) which was often saturated by groundwater. The calibration of the model required modifications of the observed values of the available water content at field capacity and the relative root density factor and was adjusted with the crop coefficient of the Penman evapotranspiration formula. These modifications of observed physical parameters raise the question of the feasibility of extrapolating the model to other sites without extensive calibration. The high sensitivity to variations of the crop coefficient applied to the evapotranspiration equation indicated that a more physically based transpiration model, supported by field-oriented process studies, would be required to improve the model's performance.

A Penman for All Seasons

Ten forms of the Penman combination evapotranspiration equation are reviewed and compared with lysimeter estimates at three locations. Aerodynamic and canopy resistance forms by Monteith and Thom and Oliver and an empirical form by Wright best predict daily lysimeter measurements at Kimberly, Idaho, and Coshocton, Ohio. Canopy resistances of 40–80 s/m and momentum roughness heights of 15 mm for clipped grass and 45–70 mm for tall grass and alfalfa result in best estimates by the Monteith and Thom‐Oliver methods. The original Penman and Priestley‐Taylor versions underestimated evapotranspiration in the arid Kimberly environment. Average standard errors of estimate of the best equations average about 0.8 mm/day over growing seasons.

Rational Use of The FAO Blaney‐Criddle Formula

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.

Effect of Potential Evapotranspiration Estimates on Crop Model Simulations

ABSTRACT TWO potential evapotranspiration (PET) equations were used in sorghum, wheat, and corn crop models. The models had been developed using one of these equations (Priestley-Taylor). Using the Penman in lieu of the Priestley-Taylor PET equation had a significant effect upon water-related model outputs (e.g., evapotranspiration and soil water) and yields based upon 30 years of simulations at three locations in Texas and one in Kansas. Because the Penman equation considers advected energy it may result in more accurate PET estimates and, consequently, water balance simulations. Based on Priestley-Taylor model yields, predictions using the Penman model were 42, 71, and 41% less for sorghum, wheat, on.

Evapotranspiration from a Humid-Region Developing Citrus Grove with Grass Cover

ABSTRACT EVAPOTRANSPIRATION (ET) of a developing citrus grove in a humid climate in the Flatwoods Land Resource Area was determined by water balance from measured rainfall, irrigation, subsurface drainage, surface runoff, and the change in soil moisture storage. The change in soil moisture storage was estimated from soil moisture characteristic curves and measured water table elevations. Annual ET ranges from 820 to 1280 mm and averaged 1090 mm across all treatments. When soil moisture was not seriously limited the annual ET averaged 1210 mm. Linear regression of ET vs time indicated a significant increase of 13% in ET over the 8 years of the study. This increase was attributed to increasing tree size since the grass understory was maintained to provide similar cover conditions throughout the study. Daily ET rate, averaged by months, ranged from 1.5 mm in January to 5.0 mm in June. Four predictive equations for ET gave good estimates of measured values, but require crop coefficients that are slightly modified from previously published values.

Evapotranspiration of Mature Orange Trees Under Drip Irrigation in an Arid Climate

ABSTRACT EVAPOTRANSPIRATION (ET) of mature Valencia orange trees (Citrus sinensis L.) was determined from a large field experiment in southwest Arizona. ET was calculated as the difference between accurate measure-ments of the amount of water applied (rainfall included) and drainage below the root zone. The amount of drain-age was estimated from various techniques of calculating leaching fraction based on the ratios of total salt and chloride concentrations. In a climate where the annual pan evaporation is 2520 mm, ET was 1470 mm or about 50 m3 per tree. The daily rate of ET, averaged by month, ranged from a low of 0.8 mm in December to 7.5 mm in August. Sev-eral predictive equations for ET were in close agreement with these values.

Estimating Water Used by Irrigated Corn in West Central Minnesota

AbstractIrrigation development in Minnesota is expanding rapidly on the sandy and droughty soils of which there is considerable area. Construction of suitable wells into underlying gravel aquifers has facilitated the rapid growth. The objective of this study was to measure water use by irrigated corn in west central Minnesota for comparing with current estimating methods for irrigation scheduling. Lysimeters, 1.75 m diam by 1.22 m deep, located in irrigated corn (Zea mays L.) plots were used to measure water use or evapotranspiration (ET) amounts. Four years of comparisons were made of measured ET to amounts calculated with the standard and refined Jensen‐Haise potential ET equations and corn crop coefficients from southeastern North Dakota data. Measured ET was also compared with ET estimates determined by the Lundstrom‐Stegman “checkbook method,” and by crop coefficients with pan evaporation. Crop coefficients with pan evaporation provided the better ET estimates, however, the “checkbook method” was the simplest and was about as accurate for estimating ET as the Jensen‐Haise potential ET equation with southeastern North Dakota crop coefficients.

Evaporation and transpiration

For years, the principal objective of evapotranspiration research has been to calculate the loss of water under varying conditions of climate, soil, and vegetation. The early simple empirical methods have generally been replaced by more detailed models which more closely represent the physical and biological processes involved. Monteith's modification of the original Penman evapotranspiration equation to include a term for canopy resistance signaled a shift in emphasis in evapotranspiration research from a physically controlled process to one which can be physiologically controlled. This change in direction was acknowledged by Federer [1975] in his earlier review and has continued for the past four years.

Evapotranspiration Computed to Estimate Leaching Fractions

ABSTRACT THE USDA Irrigation Scheduling Program with a Penman-type potential evapotranspiration equation was used as a simulation model to com-pute daily water use and deep percolation amounts on several sprinkler and furrow irrigated sites in the Grand Valley of Colorado. Input included daily weather data from one site and measured water applications on each site for the 1976 irrigation season. Leaching fractions of 0 to 0.1 were determined for a sprinkler irrigated field. For furrow irrigated sites average seasonal leaching fractions of 0.28 and 0.51 were computed for the low and high intake rate soils, respectively. Furrow intake mea-surements and computed deep percolation amounts indicate that about one-half of the seasonal leach-ing occurs following the first irrigation.

Development and Evaluation of Simplified Models for Simulating Canopy Photosynthesis and Transpiration

Several soil-plant-atmosphere models have been developed to simulate the energy transport and CO2 exchange of vegetation (Waggoner, Furnival & Reifsnyder 1969; Stewart & Lemon 1969; Sinclair, Allen & Stewart 1971; Murphy & Knoerr 1970, 1972; Goudriaan & Waggoner 1972). These models were designed to simulate, at a detailed and complex level, the physical processes involved. Submodels of physiological processes were included in these models so that predictions of micrometeorological conditions could be used to simulate the exchange of CO2 and water vapour by foliage. Previous models were so complex that they required considerable input data and computer time. We were therefore interested in developing and evaluating simpler models which require less input data and less computation. Such models should simulate, if possible, the canopy environment sufficiently well to predict photosynthesis and transpiration rates comparable to those of the complex models. With these objectives in mind, there are at least two reasons why all the micrometeorological processes may not need to be considered. First, the most significant resistance to CO2 and water vapour diffusion is generally at the foliage surface and bulk exchange in the atmosphere is comparatively much less important. Second, the microenvironment within many canopies usually does not deviate greatly from ambient conditions, except for radiation, and may be relatively unimportant in affecting CO2 and water vapour exchange. Two simpler models are here compared with a complex micrometeorological model to see to what extent complex models are necessary to obtain satisfactory estimates of CO2 and water vapour exchange. The micrometeorological model, SPAM, developed by Stewart & Lemon (1969) and modified by Sinclair et al. (1971), is used as the standard for evaluating the less complex models because it has been shown to produce adequate simulations of microenvironment and energy flux densities (Lemon, Stewart & Shawcroft 1971). A simplified version of SPAM was tested, which assumes the air temperature, water vapour, and CO2 within the canopy are similar to those above the canopy, i.e. the aerodynamic transfer coefficients are infinite. This model therefore tests directly the hypothesis that canopy microenvironment, except for radiation distribution, is unimportant. The second less-complex model assumes that a canopy can be mathematically condensed to a single plane and treated as a 'big leaf'. While the 'big leaf' model assumes all leaves are exposed to the same microenvironment, the leaf environment is different from ambient conditions above the canopy. The big leaf model for transpiration is essentially the Monteith (1965) evapotranspiration equation derived from the approach developed by Penman (1953). However, the evaluation of the variables in the Monteith

Relation of the consumptive use coefficient to the description of vegetation

Evapotranspiration from three reaches of the Gila River floodplain in Arizona was measured by the water budget during 1963–1971. Initially, the vegetation consisted of salt cedar and mesquite with densities of canopy ranging from 10 to 100%. The phreatophytes were removed from the study reaches in stages during 1967–1971. Perennial grass seed was applied but did not become established, and the postclearing vegetation was primarily annuals. Comparison of the evapotranspiration data from various reaches and comparison of data from before and after clearing required the application of an empirical equation. A consumptive use coefficient related to the description of vegetation was applied to an existing potential evapotranspiration equation based on macroclimatic observations. Initially, the vegetation description consisted of plant identification and canopy dimensions obtained by use of black and white aerial photography and ground measurements. In 1967, remote sensing in the form of color infrared aerial photography became available and densitometric interpretation was used to develop a spectral signature as the vegetation descriptor.

Sensitivity analyses of the combination evapotranspiration equation

Sensitivity equations were derived by differentiating the combination energy budgetaerodynamic evapotranspiration equation with respect to each variable. The sensitivity coefficients of these equations define the change in computed PET due to a change in the variable. Daily sensitivity coefficients were determined by applying two years of data, March through November, obtained in western Iowa over corn and grass. Annual graphs of the sensitivity coefficients showed their mean values, daily variation, and annual trends. The results showed computed evapotranspiration most sensitive to net radiation. During midyear, PET values usually change 50–90% of any radiation change or error, whereas only 20–30% of any change of vapor pressure deficit or wind travel transfers to the PET value. In the spring and fall months, the aerodynamic portion of the equation played a larger role; thus, the net radiation coefficients decreased and the aerodynamic variable coefficients increased. The calculated PET values were not largely sensitive to the wind profile parameters ( Z a , d, and Z 0) but experience has shown that large errors can occur in the measurement or prediction of these values; thus, their effect on PET can still be significant in many cases.

A generalised computer program for the solution of the Penman equation for evapotranspiration

A generalised computer program for the solution of the Penman equation for evapotranspiration

Analysis of Steady‐State Evapotranspiration from a Soil Column

AbstractNumerical analysis is applied to the steady‐state flow equation for evapotranspiration from a vertical soil column. The water uptake by the plant roots is incorporated into the flow equation as a (negative) source term. The evapotranspiration rate and its partitioning between plant transpiration and soil evaporation are specified as the top boundary condition. The lower boundary condition is a water table. The results of the analysis for a Pachappa sandy loam give pressure head, water content, source strength and soil water flux profiles. This study has (i) demonstrated that solutions to the flow equation with a source term can be obtained by numerical means, (ii) shown something of the theoretical influence of the parameters in the source term model on the flow in the soil, (iii) qualitatively indicated a transfer of water from wet soil via the root system, and (iv) indicated that the source term has little effect on the pressure head profile unless the evapotranspiration rate is about the same order of magnitude as the theoretical limiting value.