WRDS Library [Home]
Digital Library Publications Videos Card Catalog

Chapter 4
Procedures for Estimating Evapotranspiration

Among the most widely used methods for estimating evapotranspiration rates are the methods based on climatological data. The models range from those using only temperature data to those that require temperature, wind, humidity, and radiation data. Methods of estimating ET from climatic data may be classified in various ways with Hill, et al., (1983) stating that there are as many as 50 methods or variations for the estimation of ET. Three general classes will be considered in this report. These include (a) temperature, (b) radiation, and (c) combination methods. Some of the methods have been modified to include crop and soil parameters as well as climatological parameters. Although improving the theoretical basis of the models, the crop and soil parameters are usually fairly difficult to define. An application which often leads to some modification of the methods is that of estimating wide area or regional ET. These applications, however, are usually more the modification of the methodology of application of the models than modification of the actual models.

Selection of the appropriate ET model for a specific situation is difficult. Estimates can vary widely among the various methods and, unfortunately, no definite guidelines are available for defining the model or method of application most likely to give the best estimates. A recent study by Hill, et al., (1983) clearly depicts the difficulty in defining the accuracy and/or representativeness of the various ET models. This can lead to at least two possibilities. One is that, due to the lack of necessary climatological data, a simple technique might be used when a more complex model may provide more accurate estimates. Another is that the more complex models may be used even when the simpler models are adequate, due to the mistaken impression that the more complex models are always the best.

It does appear that as the time period of interest becomes shorter the complex data-intensive models generally provide the better estimates. Thus, these methods are probably preferred for applications such as irrigation scheduling. On the other hand, the temperature-based models may be entirely satisfactory for monthly or annual ET estimates, especially if locally calibrated. Another advantage of the data- intensive models are their apparent ability to better define the variation of ET rates (Allen and Wright, 1983). Therefore, another consideration in selecting the ET model to use is whether the main interest is in ET averages or in both the average and variations. Finally, a major consideration is that of acceptability and precedence. It is well-known that the Blaney-Criddle method has generally been the accepted procedure in legal negotiation's. However, even with the Blaney-Criddle model there are a number of versions and the exact model being considered must be clearly specified.

Three evapotranspiration rates are usually of interest. These include reference crop evapotranspiration (ETo), maximum evapotranspiration (ETm), and actual evapotranspiration (ETa). Reference crop evapotranspiration normally has been defined based either upon well-watered alfalfa or grass as being the reference crop. Maximum evapotranspiration refers to conditions when water is adequate for unrestricted growth and development of a specific crop and represents the rate of Et of a healthy crop, grown in large fields under optimum agronomic and irrigation management. Actual evapotranspiration is the rate of ET that occurs in the field under limited soil moisture conditions and other factors.

Calculations of water use rates are normally obtained from estimates based on climatological and field data. The first step is to determine reference crop ET from either field measurements or equations requiring climatological data. Field measurements at selected locations are required to calibrate the equations which may then be used to estimate ETo at other locations using climatological data. Maximum evapotranspiration rates for specific crops are then determined by application of appropriate crop coefficients (kc). The crop coefficients represent the effect of the crop characteristics on crop water requirements and are empirically determined values relating ETo to ETm. Calculation of actual evapotranspiration is very complex when soil moisture is limited. ETa values are estimated from ETm based upon soil moisture, overall climatic conditions, soil salinity, depth of ground water table, and agronomic and irrigation practices.

Reference crop ET must be compatible with the crop coefficients that are to be used. In the Western United States alfalfa has normally been used as the reference crop. However, alfalfa is a crop which is harvested and major adjustments must be made for the periods immediately prior to and following harvest. Also, the natural growth cycle gives a reference crop for which the height is not constant. Generally when alfalfa is used as a reference crop, it is assumed that the crop is at a growth stage that it occupies an extensive surface, is actively growing, and is approximately 7 to 8 inches in height or taller.

Clipped grass is often used as a reference crop. Grass, such as alta fescue, may be maintained at a near constant height throughout the growing season. A disadvantage often attributed to clipped grass is that under the dry windy conditions typical of arid regions, the clipped grass is not capable of ET rates as high as those reached by alfalfa and many other crops. This may result in the clipped grasses being somewhat insensitive to the increased evaporative potential caused by advection of energy from dry to irrigated areas.

Other approaches to the reference crop concept include (a) the use of the empirical formulas, without local calibration, as a reference and (b) the use of pan evaporation. Neither of these actually use a crop as a reference but do provide reference ET to which crop coefficients may be applied to estimate and/or ETa. A major disadvantage in using either alfalfa or grass as a reference for Estimating ET rates of mountain meadows is that climatic conditions usually limit and/or prohibit the growth of alfalfa and reference grasses in areas where mountain meadows are located. Thus, pan data and/or estimates from evaporation formulas may provide the best reference for mountain meadows.

Evapotranspiration Formulas

Because of the large number of ET formulas and modifications which exist, any attempt to analyze the most suitable for a particular use requires some selection to limit the cases considered. This selection process is, admittedly, rather arbitrary and may be dependent as much upon personal experience as scientific criteria. The formulas considered herein include those ranging from temperature based methods to the more data intensive combination methods. In general, those which appear to be most popular in the Western United States are emphasized. Those described herein include the original Blaney-Criddle, the SCS Blaney-Criddle, the original Jensen-Haise, the modified Jensen-Haise, the ASCE Penman modification, the FAO Blaney-Criddle, the FAO Radiation, the FAO Penman, and the Kohler-Nordenson-Fox formulas. The formulas are presented as they were taken from the original references which in many cases include metric units for the various parameters. No attempt has been made to convert these units for this presentation. Rather, it is recommended that, if the equations are used, conversion of input and output data be performed to achieve desired units. The presentation which follows includes a definition of each parameter, however, more complete details for calculating the various parameters are given in Appendix G.

The original Blaney-Criddle formula (Blaney and Criddle, 1950) is of the form:

U = KF

where:
U = consumptive use over the period, inches
K = an empirical coefficient for the period, usually the growing season
F = the sum of monthly consumptive use factors f
f = monthly consumptive use factor, tP/100
t = mean monthly temperature, °F
P = percentage of the daylight hours of the year occurring during a given month.

The SCS (SCS, 1970) modified the original Blaney-Criddle formula so that:

U = kt kc (tP/100)

where:
kc = a monthly crop growth stage coefficient
kt = a climatic coefficient related to the mean air temperature.
The SCS gave a relationship for kt = 0.0173t - 0.314, with a minimum value of 0.300.
Doorenbos and Pruitt (1977) provided another modification of the BlaneyCriddle, which is generally referred to as the FAO Blaney-Criddle:

ETo = AB + BB (p(0.46T + 8))

where:
ETo = reference crop, clipped grass, evapotranspiration in mm/day
T = mean temperature over the period in degrees C
p = mean daily percentage of total annual daylight hours for the period
AB,BB = adjustment factors based on minimum relative humidity, sunshine and daytime windspeed estimates. Exact values of the input parameters are not required. Frevert et al. (1983) have given an equation to calculate BB while Doorenbos and Pruitt (1977) gave an equation for AB.

The Jensen-Haise (Jensen and Haise, 1963) formula is considered to be a radiation formula. It was derived from data collected in the western United States and is commonly considered to calculate reference crop ET for alfalfa. It takes the form:

ETr = CT (T - Tx) RS

where:
ETr = reference evapotranspiration in langleys per day (multiply by 0.000673 to convert to inches per day)
RS = solar radiation in units of langleys per day
T = mean air temperature in degrees F
Tx = a temperature axis intercept with a value of 26.4
CT = an empirical coefficient with a value of 0.014.

The formula was later modified (Jensen, 1966 and Jensen et.al., 1970) through defining the coefficients CT and Tx as:

CT = 1/(C1 + C2 CH)
and
Tx = 27.5 - 0.25 (e2 - e1) - (elev/1000)
where:
C1 = 68 - (3.6)(elev/1000) where elevation is in feet
C2 = 13
CH = 50/(e2 - e1) where e2 and e1 are the saturation vapor pressures at the mean maximum and mean minimum temperatures, respectively, for the warmest month of the year

The FAO radiation method (Doorenbos and Pruitt, 1977) is basically a modification of the Makkink formula (1957):

ETo = AR + BR (W Rse)

where:
ETo = reference crop, clipped grass, evapotranspiration in mmlday
Rse = solar radiation in equivalent evaporation in mm/day
W = a weighting factor dependent on temperature and altitude and equal to the slope of , the saturation vapor pressure-temperature curve at the air temperature in mb/degree C divided by the sum of the slope and the psychrometer constant also in mb/degree C
AR, BR = adjustment factors based on mean humidity and daytime windspeed. Frevert et al. (1983) have given equations to calculate BR while Doorenbos and Pruitt (1977) recommend -0.3 for AR.

Many modifications of the original Penman (1948) formula have been proposed. Most are adjustments of the coefficients in the wind term, although more extensive modifications have also been presented (e.g. Wright, 1982). The version used herein is that listed by Jensen et al. (1973) and which is sometimes referred to as the ASCE Penman:

ETr = (D/(D+g)) (Rn + G) + (g/(D+g)) (15.36)(1.0 + 0.0062u2)(eso - ea)

where:
ETr = reference evapotranspiration in langleys per day.
D = slope of the saturation vapor pressure-temperature curve at the air temperature in mb per degree C
g = psychrometer constant in mb per degree C
Rn = net radiation in langleys per day
G = soil heat flux in langleys per day
u2 = wind speed at 2 meters height in km per day
eso = the saturation vapor pressure obtained as the average of the saturation vapor pressures at the mean maximum and mean minimum
ea = mean actual vapor pressure obtained as the saturation vapor pressure at the daily average dewpoint, in mb

The FAO Penman (Doorenbos and Pruitt, 1977) utilizes the same general format as given above with the addition of an adjustment factor and different wind coefficients. Also, the soil heat flux term is dropped giving:

ETo = Cp (W Rn + (1 - W)(0.27)(1 + U/100)(es - ea)

where:
ETo = reference crop, clipped grass, evapotranspiration in mm/day
Rne = net radiation in equivalent evaporation in mm/day
W = the same factor as given previously in the FAO Radiation method
U = the 24 hour wind run at 2 meters height in km/day
es = the saturation vapor pressure obtained at the mean temperature, in mb
ea = the same as in the previous equation above
Cp = an adjustment factor dependent on maximum relative humidity, solar radiation, daytime windspeed, and the ratio of daytime to nighttime windspeed. Frevert etal. (1983) have given an equation to calculate Cp.

A commonly used equation for prediction of evaporation from lakes and reservoirs is the Kohler-Nordenson-Fox formula (Kohler et.al., 1955):

E = 0.70(RneD + g ((es - ea).88)(0.37 + 0.0041Up))/(D + g)

where:
E = lake evaporation in inches per day
0.70 = a coefficient adjusting pan evaporation to lake evaporation
D = slope of the saturation vapor pressure-temperature curve at the air temperature in inches of mercury per degree F
g = psychrometric constant in inches of mercury per degree F
es = saturated vapor pressure evaluated at the mean air temperature, in inches of mercury
ea = actual vapor pressure evaluated at the mean dewpoint, in inches of mercury
Up = the wind speed 6 inches above the rim of a Class A evaporation pan in miles per day
Rne = exp((Ta - 212)(0.1024 - 0.0166 ln(Rs))) - 0.0001
Rs = solar Radiation in langleys per day
Ta = the mean air temperature in degrees F.

Uncalibrated Equation Estimates vs Measurements

The need for calibrating the various evapotranspiration formulas can be shown by comparing estimates obtained from the uncalibrated equations to measured ET rates. For the Green River Basin, four types of water use rates were available during the study period. These include alta fescue and alfalfa water use measurements at Daniel, Farson, and Seedskadee; mountain meadow water use measurements in eight lysimeters along Horse Creek from just above Merna to Daniel; and evaporation pan measurements at Merna, Daniel, and Seedskadee. The formulas which will be considered in this section include the original Blaney-Criddle, the SCS Blaney-Criddle, the original Jensen- Haise, the modified Jensen-Haise, a modified Penman, the Kohler-Nordenson-Fox, the FAO Blaney-Criddle, the FAO Radiation, and the FAO Penman methods.

All water use estimates from the equations will be compared with 80% of the measured alfalfa water use rates and 100% of the measured mountain meadow and alta fescue water use rates. The reason for this is, as mentioned in the last chapter, water use rates for alfalfa when surface irrigated appear to be greater in the presence of a water table (Tovey, 1963). All measurements, except those taken to measure actual water use, were taken from lysimeters which were surface irrigated and had water tables. It is not completely clear in the literature but it appears that previous applications of the various formulas for predicting alfalfa water use were to cases which were well-watered but did not include a water table. Thus, for comparison of measured versus estimated alfalfa water use rates, values of 80% of measured appear to be reasonable for use in the analyses. In the case of mountain meadows and alta fescue, 100% of the measured values will be used. Mountain meadows are, usually grown in the presence of a water table. Also, the vegetation has not been used as a reference for the formulas as has alfalfa, thus maximum water use rates, with a water table will be used for comparison. The effect of the presence of a water table with surface irrigation for alta fescue seems to be unknown, however, a water table of 2 ft depth or more is beyond the major influence of the roots for alta fescue.

SCS TR-21 (1967) gives crop growth stage coefficients for alfalfa and pasture grass. Pasture grass is not expected to apply directly to mountain meadows, but a comparison of the relative water use rates estimated for pasture grass versus those measured for mountain meadows is still given. Values given in Table 15, show that average seasonal estimated water use rates were 56% and 49% of measured rates for alfalfa and mountain meadows, respectively, when using the SCS Blaney-Criddle formula and crop growth stage coefficients and the temperature coefficient given in TR-21.

Trelease, et al. (1970) published water use estimates for several Wyoming stations including Farson and Pinedale. Estimates were calculated using the original Blaney-Criddle formula (1962). Comparison of the published estimates with measured water use rates for alfalfa at Farson and alfalfa and mountain meadows measured at Daniel compared with estimates at Pinedale are given in Table 16. Pinedale estimates are used to compare with Daniel measurements since Pinedale is the closest station for which published estimates are given. The comparisons show that the published estimates are slightly closer to the measured values than estimates obtained using the SCS Blaney- Criddle modification as given in Table 15. However, the estimates are still lower than measured values and range from 72% to 79% of the measured ET values for alfalfa.

The radiation based Jensen-Haise model and the modified Penman being considered herein use alfalfa as a reference crop. In the case of the Penman, at least, the reference is for a well-watered, actively growing alfalfa of minimum height, usually about 8 inches (Burman, et al., 1980). After planting, early in the growing season, and after cutting, alfalfa does not match the above definition. Thus, it is necessary to apply crop coefficients to the calculated reference ET rates to estimate alfalfa water use at times when the above conditions do not exist. The results shown in Table 17 indicate that estimated values using the original Jensen-Haise are lower than measured alfalfa water use while those using the modified Jensen-Haise are very nearly the same as the measured alfalfa water use rates. Estimated values using the ASCE Penman range from greater than measured alfalfa values early and late in the growing season to less than measured values during the mid- portion of the growing season (Table 18). The June and July values would be nearest the definition of an actively growing well-developed alfalfa crop. Application of crop coefficients early in the season and following cutting is necessary to compare estimated and measured values at those times. No effort is made here to apply proper crop coefficients since the intent of this section is simply to give a general comparison of measured vs estimated ET rates without local calibration of the various equations. The modified Jensen-Haise, however, predicts measured alfalfa water use rather well throughout the entire growing season, with the exception of May, without application of crop coefficients.

The FAO methods present a slightly different approach to the concept of a reference crop (Doorenbos and Pruitt, 1977). FAD uses four methods to obtain reference crop evapotranspiration, which is defined as the rate of evapotranspiration from a well-watered clipped grass. Three of the methods, the FAD Blaney-Criddle, the FAO Radiation, and the FAO Penman are considered here with estimates from each compared with measured ET rates of alta fescue (Table 19). The FAO Radiation and FAO Penman give similar results with seasonal estimates of 127% and 133%, respectively, of measured alta fescue ET. The FAO BlaneyCriddle estimates are consistently closer with seasonal values averaging 112% of the measured alta fescue ET. An advantage of using clipped grass as opposed to alfalfa is that it is not necessary to apply crop coefficients to the reference crop to indicate its growth stage. A disadvantage often cited for clipped grass is that in windy arid areas the water use rate of the grass is limited by its reduced canopy and thus the crop is not as capable of responding to the effects of advection. Finally, the results presented in Table 19 indicate that the presence of a water table for the alta fescue may not have increased water use rates above normally expected values. In nearly all cases the measured water use rates were lower than the estimated FAO reference crop values.


TABLE 15.  UNCALIBRATED SCS BLANEY-CRIDDLE ESTIMATES VS MEASUREMENTS
=======================================================================================
		      ALFALFA VS ALFALFA              PASTURE VS MOUNTAIN MEADOWS
		-------------------------------     ----------------------------------
	TR-21  ESTIMATED  MEASURED*   % OF       TR-21  ESTIMATED  MEASURED*  % OF
MONTH    KC    (INCHES)   (INCHES)   MEASURED      KC   (INCHES)  (INCHES)   MEASURED 
---------------------------------------------------------------------------------------
MAY	1.08	1.63	  2.62	     62	         0.90	 0.83	   1.76	     47
JUN	1.13	3.98	  7.69	     52	         0.92	 2.54	   5.95	     43
JUL	1.11	5.71	  8.86	     64	         0.92	 3.95	   6.73	     59
AUG	1.06	4.45	  8.51	     52	         0.91	 3.06	   5.27	     58
SEP	0.99	2.01	  3.97	     51	         0.79	 1.26	   2.89	     44
OCT	0.91	0.66	  1.47	     45	         0.79	 0.46	   2.05	     22
--------------------------------------------------------------------------------------
SEASON         18.44     33.12       56                 12.10     24.65      49

======================================================================================
* ALFALFA VALUES ARE AVERAGES OF THE YEARS 1984 & 1985 AT DANIEL, FARSON, AND 
SEEDSKADEE.  PASTURE AND MOUNTAIN MEADOW VALUES ARE AVERAGES OF THE YEARS 1984 
& 1985 AT DANIEL AND MERNA.  MAY AND OCTOBER ARE PARTIAL MONTHS.  MEASURED VALUES 
SHOWN FOR ALFALFA ARE 80% OF THOSE ACTUALLY RECORDED DUE TO ADJUSTMENT FOR A 
WATER TABLE.



TABLE 16.  MEASURED ET VS PREVIOUSLY PUBLISHED ESTIMATES*
======================================================================================
		ALFALFA VS ALFALFA	         PASTURE VS MOUNTAIN MEADOWS
      	      ----------------------------	------------------------------
		PUBLISHED			PUBLISHED
		ESTIMATES  MEASURED  % OF       ESTIMATES  MEASURED  % OF
LOCATION MONTH  (INCHES)  (INCHES)   MEASURED   (INCHES)   (INCHES)  MEASURED 
-------------------------------------------------------------------------------------
FARSON	  JUN	5.17	   7.22	     72	           -	     -	       -
	  JUL	6.45	   7.51	     86	           -	     -	       -
	  AUG	5.12	   8.53	     60	           -	     -	       -
	  SEP	2.94	   4.20	     70	           -	     -	       -
      -----------------------------------------------------------------------------
      4 MONTHS 19.68      27.46      72 
      -----------------------------------------------------------------------------

PINEDALE  JUN   4.92	   6.23	     79	         4.48	   7.34	     61
  VS	  JUL	6.00	   8.32	     72	         5.56	   7.86	     74
DANIEL	  AUG	4.74	   4.90	     97	         4.52	   5.49	     82
	  SEP	2.64	   3.66	     72	         2.52	   3.69	     68
      ----------------------------------------------------------------------------
      4 MONTHS 18.30      23.11      79         17.08     24.38      70

======================================================================================
* ESTIMATES ARE FROM TRELEASE ET AL. (1970).  FOR PINEDALE VS DANIEL.  THE VALUES ARE 
ESTIMATED AT PINEDALE AND MEASURED AT DANIEL.  MEASURED ALFALFA VALUES SHOWN 
ARE 80% OF THOSE ACTUALLY RECORDED DUE TO ADJUSTMENT FOR A WATER TABLE.



TABLE 17.  UNCALIBRATED JENSEN-HAISE ESTIMATES VS ALFALFA MEASUREMENTS*
=========================================================================
	   ESTIMATED ET
	-------------------	MEASURED	% OF MEASURED
	ORIGINAL    MODIFIED	ALFALFA       --------------------	
	  J-H	      J-H	   ET	      ORIGINAL	MODIFIED
MONTH	(INCHES)    (INCHES)	(INCHES)	J-H	  J-H
--------------------------------------------------------------------------
MAY	 2.10	     3.57	2.62	        80	 136
JUN	 4.77	     7.53	7.69	        62	  98
JUL	 5.81	     8.98	8.86	        66	 101
AUG	 5.34	     7.88	8.51	        63	  93
SEP	 2.47	     4.27	3.97	        62	 108
OCT	 0.75	     1.56	1.47	        51	 106
--------------------------------------------------------------------------
SEASON  21.24       33.69      33.12            64       102

=========================================================================
* VALUES ARE AVERAGES OF THE YEARS 1984 & 1985 AT DANIEL, FARSON, AND 
SEEDSKADEE.  NO CROP COEFFICIENTS HAVE BEEN APPLIED FOR PERIODS OF LESS 
THAN 100% EFFECTIVE COVER.  MAY AND OCTOBER ARE PARTIAL MONTHS.  MEASURED 
ALFALFA VALUES SHOWN ARE 80% OF THOSE ACTUALLY RECORDED DUE TO ADJUSTMENT 
FOR A WATER TABLE.


TABLE 18.  UNCALIBRATED MODIFIED PENMAN ESTIMATES VS ALFALFA MEASUREMENTS*
===========================================================================
		ESTIMATED ET	MEASURED ET	% OF
MONTH		(INCHES)	(INCHES)	MEASURED
--------------------------------------------------------------------------
MAY		4.18		2.62		160
JUN		7.68		7.69		100
JUL		8.05		8.86		 91
AUG		8.27		8.51		 97
SEP	  	5.64		3.97		142
OCT		2.50		1.47		170
--------------------------------------------------------------------------
SEASON         36.32           33.12            110 

===========================================================================
* VALUES ARE AVERAGES OF THE YEARS 1984 AND 1985 AT DANIEL, FARSON AND 
SEEDSKADEE.  NO CROP COEFFICIENTS HAVE BEEN APPLIED FOR PERIODS OF LESS 
THAN 100% EFFECTIVE COVER.  MAY AND OCTOBER ARE PARTIAL MONTHS.  MEASURED 
ALFALFA VALUES SHOWN ARE 80% OF THOSE ACTUALLY RECORDED DUE TO ADJUSTMENT 
FOR A WATER TABLE.

Estimates of water losses from reservoirs, and other free water surfaces, are generally calculated using the Kohler-Nordenson-Fox equation. Warnaka (1985) has compared monthly evaporation estimates throughout Wyoming using seven climatological equations. The Kohler- Nordenson-Fox method was shown to give the overall best results in predicting pan evaporation. Measured pan evaporation rates vs Kohler-Nordenson-Fox estimates of evaporation in the Green River Basin for 1984 and 1985 are compared in Table 20. Measurements and estimates compare rather closely, with higher estimated values in the Merna and Daniel area and lower estimated values at Seedskadee. The Seedskadee values may be most representative of responses expected from the major reservoirs in the Green River Basin because of the climatic conditions being most comparable.

Model Calibrations

Results shown in the previous section indicate the need for calibration of the various evapotranspiration formulas. Calibration of the formulas usually involve either or both of two steps. The method of calculating reference crop ET may be calibrated and/or the crop coefficients may be calibrated. In most cases, the approach used herein consisted of determining new crop coefficients, except in the case of the Blaney-Criddle equation which uses crop growth stage coefficients. Only in the cases for which the estimated reference ET was considerably different than measured ET was the method of calculating reference crop ET considered for calibration. A large difference occurred for both the SCS Blaney-Criddle and original Jensen-Haise formulas, but only the SCS Blaney-Criddle has been calibrated.

The Blaney-Criddle formula does not employ a reference crop but rather crop growth stage coefficients for each type of crop. The original Blaney-Criddle uses only a crop growth stage coefficient while the SCS version of the Blaney-Criddle also includes a temperature coefficient kt. Calibrations of both the original and SCS Blaney-Criddle formulas have been performed for alfalfa and mountain meadows in the Green River Basin (Table 21). Calibration of the SCS Blaney- Criddle includes calculation of kt for each crop. The crop growth stage coefficients given in Table 21 must therefore be used only with the appropriate kt as given in the table. An advantage of the SCS Blaney-Criddle is that the alfalfa crop growth stage coefficients are more uniform for the various locations at which data was taken than they are for the original Blaney-Criddle. In each case, Daniel has the smallest coefficients and Seedskadee the largest. For the original Blaney-Criddle the values at Daniel are about 16% below and at Seedskadee about 18% above the average of the values for the three sites while for the SCS Blaney- Criddle the values are about 5% below and 7% above at Daniel and Seedskadee, respectively. Separate kt values for each crop indicate that the coefficients include crop factors as well as climatic factors.



TABLE 19.  FAO ESTIMATES VS ALTA FESCUE MEASUREMENTS*
======================================================================
		ESTIMATED ET     MEASURED ET     % OF MEASURED
	     ----------------     -----------    -------------
MONTH 	     BC   RAD    PEN     ALTA FESCUE    BC   RAD   PEN 
----------------------------------------------------------------------
MAY	    3.32  4.08	4.51	    2.41	137  170   187
JUNE	    6.70  7.83	8.25	    5.88	114  133   140
JULY	    7.92  8.19	8.37	    6.42	123  128   130
AUGUST	    7.18  7.71	7.71	    6.24	115  124   124
SEPTEMBER   3.86  4.65	4.99	    4.38	 88  106   114
OCTOBER	    1.82  2.55	2.69	    2.16	 84  119   125
---------------------------------------------------------------------
SEASON     30.80 35.01 36.25       27.49        112  127   133

=====================================================================
* VALUES ARE AVERAGES OF THE YEARS 1984 AND 1985 FOR THE LOCATIONS 
OF DANIEL, FARSON, AND SEEDSKADEE.  ET IS GIVEN IN INCHES.



TABLE 20.  KOHLER-NORDENSON-FOX ESTIMATES VS PAN EVAPORATION MEASUREMENTS*
================================================================================
	   ESTIMATED	           MEASURED PAN	           % OF MEASURED
	-------------------	-------------------	-------------------
MONTH	  MERNA DANIEL SEEDS	MERNA DANIEL SEEDS	MERNA DANIEL SEEDS
--------------------------------------------------------------------------------
MAY	  1.88   1.96   3.14	1.29   1.82   3.01	146    108    104
JUNE	  7.84   7.99  10.47	7.27   7.16  10.67	108    112     98
JULY	  8.22   8.48  10.77	7.27   7.22  11.25	113    117     96
AUGUST	  7.46   7.72  10.35	6.12   7.17  10.60	112    108     98
SEPTEMBER 4.19	 4.62	6.33	4.61   4.93   6.93	 91	94     91
OCTOBER	  1.79	 2.02	2.52	1.99   1.38   2.16	 90    146    117
-------------------------------------------------------------------------------
SEASON   31.38  32.79  43.58   28.55  29.68  44.62      110    110     98

===============================================================================
* PAN EVAPORATION ESTIMATES AND MEASUREMENTS ARE GIVEN IN INCHES.  VALUES ARE 
AVERAGES OF THE YEARS 1984 AND 1985 FOR LOCATIONS DANIEL, MERNA, AND SEEDSKADEE.  
MAY AND OCTOBER ARE PARTIAL MONTHS.

Crop coefficients for the original Jensen-Haise, the modified Jensen-Haise, and the modified Penman equations are given in Table 22 for alfalfa and mountain meadows. The results show similar types of coefficients for the modified Jensen-Haise and Penman equations while the magnitudes of the crop coefficients for the original Jensen-Haise are rather large. The coefficients for the modified Penman form a relatively smooth bell-shaped curve for the season, whereas this is not true for either of the Jensen-Haise formulas. The effects of cutting are not apparent in any of the coefficients, although seasonal cycles do exist which reflect the development of the crops during the season.

Results for the three FAO methods show that the crop coefficients for the FAO Radiation and Penman methods are of nearly the same magnitude while those for the FAO Blaney-Criddle method are somewhat larger (Table 23). The basic concept of the FAO procedures is that each of the three methods will produce the same reference crop evapotranspiration values, which is obviously not quite the case for this set of data. The crop coefficients given in Table 23, however, are of approximately the same magnitude as those given by Doorenbos and Pruitt (1977) for both alfalfa and pasture and/or grass harvested for hay. There isn't a good explanation for the differences which occur between the crop coefficients in Table 23 for the FAO Radiation and Penman methods versus the FAO Blaney-Criddle method. Note, however, that the FAO Blaney-Criddle gave reference crop ET estimates nearest to measured alta fescue ET rates (Table 19).



TABLE 21.  CROP GROWTH STAGE COEFFICIENTS FOR THE BLANEY-CRIDDLE FORMULAS
=======================================================================
	      ORIGINAL BLANEY-CRIDDLE	  SCS BLANEY-CRIDDLE
	      -----------------------	----------------------
MONTH		ALFALFA  MTN MEADOWS	ALFALFA*  MTN MEADOWS**
----------------------------------------------------------------------
MAY		1.05	   0.92		0.91	   -
JUN		1.37	   1.17		1.12	   1.19
JUL		1.34	   1.10	        0.91	   0.96
AUG	    	1.45	   1.00		1.04	   0.92
SEP	        1.01	   0.79	        0.99	   0.91

=====================================================================
* Coefficients are to be used only with kt = -0.2950 + 0.028t
** Coefficients are to be used only with kt = 0.1138 + 0.0175t



TABLE 22.  CROP COEFFICIENTS FOR THE JENSEN-HAISE AND PENMAN FORMULAS
=================================================================================
		ORIGINAL JEN-HAISE	MODIFIED JEN-HAISE	MODIFIED PENMAN
		------------------	------------------	-----------------
MONTH		ALFALFA MTN MDWS	ALFALFA MTN MDWS	ALFALFA MTN MDWS
----------------------------------------------------------------------------------
MAY		1.24	1.22		0.73	0.76		0.63	0.63
JUN		1.61	1.51		1.02	1.00		1.00	0.92
JUL		1.52	1.24		0.99	0.91		1.10	0.97
AUG		1.59	1.20		1.08	0.85		1.03	0.78
SEP		1.61	1.56		0.93	0.91		0.70	0.62
OCT		1.96	-		0.94	-		0.59	-

================================================================================



TABLE 23.  CROP COEFFICIENTS FOR THE FAO FORMULAS
=================================================================================
		FAO BLANEY-CRIDDLE	FAO RADIATION	 	FAO PENMAN
	        ------------------	-----------------     -----------------
MONTH		ALFALFA MTN MDWS	ALFALFA MTN MDWS       ALFALFA MTN MDWS
--------------------------------------------------------------------------------
MAY		0.79	0.84		0.64	0.61		0.58	0.61
JUN		1.15	1.12		0.98	0.85		0.93	0.86
JUL		1.12	1.04		1.08	0.90		1.06	0.93
AUG		1.19	0.96		1.10	0.81		1.10	0.84
SEP		1.03	0.95		0.85	0.69		0.80	0.69
OCT		0.81	-		0.58	-		0.55	-

================================================================================


87-06 Table of Contents
Water Resources Publications List
Water Resources Data System Library | Water Resources Data System Homepage