Prepared in Cooperation with the 

New Jersey Pinelands Commission

Measurement and Simulation of Evapotranspiration at a 

Wetland Site in the New Jersey Pinelands

NEW

JERSEY

Pinelands

Weekly evapotranspiration

Daily energy fluxes

Evapotranspiration flux tower

Sensor arrays

Daily measured and simulated

evapotranspiration

Data logging

Scientific Investigations Report 2012–5118

U.S. Department of the Interior

U.S. Geological Survey

Measurement and Simulation of 

Evapotranspiration at a Wetland Site 

in the New Jersey Pinelands

By David M. Sumner, Robert S. Nicholson, and Kenneth L. Clark

Prepared in cooperation with the 

New Jersey Pinelands Commission

Scientific Investigations Report 2012–5118

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

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reproduce any copyrighted materials contained within this report.

Suggested citation:

Sumner, D.M., Nicholson, R.S., and Clark, K.L., 2012, Measurement and simulation of evapotranspiration at a wetland 

site in the New Jersey Pinelands: U.S. Geological Survey Scientific Investigations Report 2012–5118, 30 p.
iii

Acknowledgments

Access to the evapotranspiration (ET) monitoring site was arranged by Christian Bethman, 

Superintendent of Brendan T. Byrne State Forest, whose assistance in clearing the site and 

providing road improvements to this previously inaccessible area is gratefully acknowledged. 

The authors gratefully acknowledge U.S. Geological Survey (USGS) colleagues Amanda Garcia 

and Amy Swancar for providing helpful comments that greatly improved this report, and William 

Ellis, Ruth Larkins and Gregory Simpson for their assistance with report preparation and illustrations. Special thanks are extended to Richard W. Edwards, USGS Electronics Technician, whose 

technical organization, skill, and resourcefulness ensured a successful ET monitoring campaign 

at this remote location.

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Purpose and Scope ..............................................................................................................................3

Previous Investigations........................................................................................................................3

Methods for Measurement and Simulation of Evapotranspiration.......................................................4

Measurement of Evapotranspiration.................................................................................................5

Eddy-Covariance Method...........................................................................................................5

Source area of Measurements .................................................................................................6

Instrumentation............................................................................................................................7

Calculation of Turbulent Fluxes.................................................................................................7

Consistency of Measurements with Energy Budget .............................................................8

Simulation of Evapotranspiration.......................................................................................................9

Priestley-Taylor Equation .........................................................................................................10

Hargreaves Equation.................................................................................................................10

North American Regional Reanalysis ....................................................................................11

Measurement of Environmental Variables.....................................................................................11

Results of Evapotranspiration Measurement and Simulation..............................................................12

Comparison of Measured Evapotranspiration at Wetland and Upland Sites...........................18

Utility of Models to Simulate Evapotranspiration..........................................................................22

Priestley-Taylor Equation .........................................................................................................22

Hargreaves Equation.................................................................................................................24

North American Regional Reanalysis (NARR) ......................................................................25

Comparison and Limitations of Evapotranspiration Models........................................................25

Summary........................................................................................................................................................26

References Cited..........................................................................................................................................27
iv

Figures

1. Map showing location of McDonalds Branch basin, selected weather stations, 

and evapotranspiration station, Pinelands area, New Jersey..............................................2

2. Photographs showing evapotranspiration station at a pitch-pine lowland site in 

the McDonalds Branch basin, Pinelands area, New Jersey: A, tower with instrumentation and B, krypton hygrometer (foreground) and sonic anemometer (background) 

mounted at top of tower at evapotranspiration station..........................................................4

3. Graph showing radial extent of source area for daytime turbulent flux 

measurements...............................................................................................................................6

4. Graphs showing monthly values of regression coefficients used in equations 

21 and 22.......................................................................................................................................12

5. Graphs showing measured and simulated energy fluxes: A, sensible heat flux and 

B, latent heat flux at the wetland site in the Pinelands area, New Jersey, 

July 1–10, 2006.............................................................................................................................13

6. Graph showing mean diurnal pattern of energy fluxes at the wetland site in the 

Pinelands area, New Jersey, 2005–6 ......................................................................................14

7. Graph showing relative frequency of measured wind direction at the wetland site 

in the Pinelands area, New Jersey, 2005–6 ...........................................................................14

8. Graph showing mean weekly values of net radiation, turbulent fluxes, and wind 

speed at the wetland site in the Pinelands area, New Jersey, November 

2004–February 2007 ....................................................................................................................15

9. Graph showing daily evapotranspiration measured using the standard eddy-covariance method, the Bowen ratio method, and the residual energy-budget variant 

method, at the wetland site in the Pinelands area, New Jersey, November 

2004–February 2007 ....................................................................................................................15

10. Graphs showing relation of A, weekly mean air temperature and B, weekly mean 

soil moisture to evaporative fraction, at a wetland site in the Pinelands area, 

New Jersey, November 2004–February 2007.........................................................................19

11. Map showing location of the wetland and upland evapotranspiration measurement 

stations, Pinelands area, New Jersey ....................................................................................20

12. Graph showing annual evapotranspiration measured at the wetland, pine upland, 

oak upland, and mixed oak/pine upland sites in the Pinelands area, New Jersey, 

2005–9 ...........................................................................................................................................21

13. Graph showing optimized relation between Priestley-Taylor α and mean daily air 

temperature for the wetland site in the Pinelands area, New Jersey..................................22

14. Graph showing relation of residuals using the modified Priestley-Taylor model to 

daily mean wind direction, wetland site, Pinelands area, New Jersey, 2004–7 ..............22

15. Graph showing measured and modified Priestly-Taylor-simulated daily latent heat 

flux for the wetland site, Pinelands area, New Jersey, 2005–6 ..........................................23

16. Graph showing daily measured and modified Hargreaves-simulated evapotranspiration for the wetland site, Pinelands area, New Jersey, 2005–6...................................24

17. Graph showing relation of residuals using the modified Hargreaves daily 

evapotranspiration model to daily mean wind direction, wetland site, Pinelands 

area, New Jersey, 2004–7 .........................................................................................................25

18. Graph showing daily measured and modified North American Regional Reanalysis 

simulated evapotranspiration, and volumetric soil mositure for the wetland site, 

Pinelands area, 2005–6 ..............................................................................................................26
v

Tables

1. Description of study instrumentation........................................................................................5

2. Weekly measured rainfall and evapotranspiration measured using the residual 

energy-budget variant of the eddy covariance method at the wetland site, 

Pinelands area, New Jersey, November 2004–February 2007............................................16

3. Monthly and 12-month measured rainfall and evapotranspiration measured using 

the residual energy-budget variant of the eddy-covariance method at the wetland 

site, Pinelands area, New Jersey, December 2004–January 2007 ....................................17

4. Summary of selected characteristics measured or simulated annually and dates of 

spring and fall freezes at the wetland site, Pinelands area, New Jersey, 2005–6 ..........18

5. Annual evapotranspiration at the wetland site and three upland forest sites, 

Pinelands area, New Jersey, 2005–9 ......................................................................................21

6. Error statistics relating evapotranspiration measured at the wetland site to evapotranspiration simulated using alternative models, Pinelands area, New Jersey ............23

7. Parameters for the standard Hargreaves reference evapotranspiration equation 

and optimized parameters for the modified Hargreaves actual evapotranspiration 

equation for alternative sources of daily temperature data................................................24
vi

Conversion Factors and Vertical Datum 

Multiply By To obtain

Length

millimeter (mm) 0.039 inch (in.)

centimeter (cm) 0.394 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.621 mile (mi)

Area

square meter (m2) 10.76 square foot (ft2) 

square kilometer (km2) 0.386 square mile (mi2)

Volume

cubic meter (m3) 264.2 gallon (gal) 

cubic meter (m3) 35.31 cubic foot (ft3)

Flux

millimeter per day (mm/d) 0.03937 inch per day (in/d)

millimeter per year (mm/yr) 0.03937 inch per year (in/yr)

watt per square meter (W/m2) 0.0342 at 0 oC millimeter per day (mm/d)

watt per square meter (W/m2) 0.0354 at 25 oC millimeter per day (mm/d)

watt per square meter (W/m2) 0.0359 at 50 oC millimeter per day (mm/d)

Flow rate

meter per second (m/s) 3.281 foot per second (ft/s) 

cubic meter per second (m3/s) 35.31 cubic foot per second (ft3/s)

Energy

joule (J) 0.239 calorie

joule (J) 0.0000002 kilowatt-hour (kWh)

Mass

gram (g) 0.035 ounce, avoirdupois (oz)

kilogram (kg) 2.294 pound (lb)

Pressure

kilopascal (kPa) 0.010 atmosphere, standard (atm)

kilopascal (kPa) 0.296 inch of mercury at 60°F (in Hg)

kilopascal (kPa) 0.145 pound-force per inch (lbf/in) 

Density

gram per cubic centimeter (g/cm3) 62.422 pound per cubic foot (lb/ft3) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Altitude, as used in this report, refers to distance above the vertical datum.
vii

List of Symbols

a An empirical coefficient equal to a value of 0.0135

b An empirical coefficient equal to a value of 17.8

B Bowen ratio, equal to the ratio of sensible and latent heat fluxes

Cp Specific heat capacity of air, in J/(g·C)

d Momentum displacement height of vegetation, in m

e Vapor pressure, in kPa

es Saturation vapor pressure, in kPa

E Evapotranspiration rate, in g/(m2·s)

ET Evapotranspiration rate, in mm/yr

ETa Reference ET, in the same water evaporation units as Ra

F Factor used in krypton hygrometer correction that accounts for molecular 

 weights of air and atmospheric abundance of oxygen, equal to 0.229 g·oC/J

G Soil heat flux at land surface, in W/m2

h Canopy height, in m

H Sensible heat flux, in W/m2

HBREB Sensible heat flux as estimated by the Bowen ratio energy-budget variant of 

 the eddy covariance method, in W/m2

Ko Extinction coefficient of hygrometer for oxygen, in m3/(g·cm)

KRS An empirical coefficient usually estimated as 0.16 and 0.19 for inland and 

 coastal areas, respectively

Kw Extinction coefficient of hygrometer for water, in m3/(g·cm)

Pa Atmospheric pressure, in Pa
viii

q Specific humidity, in g water/g moist air

r

h Aerodynamic resistance, in seconds per meter

Ra Extraterrestrial radiation, in the same water evaporation units as ETa

Rd Gas constant for dry air, equal to 0.28704 J/oC/g

Rn Net radiation, in W/m2

Rs Incoming solar radiation on land surface, in the same water evaporation 

 units as ETa

S Change in storage of energy in the biomass, air, and any standing water, in 

 W/m2

Ta Air temperature, in oC

TC Daily air temperature, in oC

TR Daily temperature range, in oC

Ts Sonic temperature, in oC

u Lateral wind speed along coordinate x-direction, in m/s

v Lateral wind speed along coordinate y-direction, in m/s

w Wind speed along coordinate z-direction, in m/s

x One of two orthogonal coordinate directions within a plane parallel to canopy 

 surface

y One of two orthogonal coordinate directions within a plane parallel to canopy 

 surface

z Coordinate direction perpendicular to canopy surface

zs Height of sensors above land surface, in m

zm Roughness length of canopy for momentum, in m

α Priestley-Taylor coefficient, dimensionless

Δ Slope of the saturation vapor pressure curve, in kPa/oC

η Angle of rotation about the z-axis to align u into the x-direction on the x-y 

 plane, in radians

γ Psychrometric constant, in kPa/oC

λ Latent heat of vaporization, in J/g

λΕ Latent heat flux, in W/m2
ix

λΕBREB Latent heat flux as estimated by the Bowen ratio energy-budget variant of the 

 eddy covariance method, in W/m2

λΕREB Latent heat flux as estimated by the residual energy-budget variant of the 

 eddy-covariance method, in W/m2

θ Angle of rotation in the y-direction to align w along the z-direction, in radians

ρ Air density, in g/m3

ρv Vapor density, in g/m3

μ Ratio of molecular weight of air to molecular weight of water

σ Ratio of vapor density (ρv) to air density (ρ)

Measurement and Simulation of Evapotranspiration at a 

Wetland Site in the New Jersey Pinelands

By David M. Sumner1, Robert S. Nicholson1, and Kenneth L. Clark2

Abstract

Evapotranspiration (ET) was monitored above a wetland 

forest canopy dominated by pitch-pine in the New Jersey 

Pinelands during November 10, 2004–February 20, 2007, 

using an eddy-covariance method. Twelve-month ET totals 

ranged from 786 to 821 millimeters (mm). Minimum and 

maximum ET rates occurred during December–February 

and in July, respectively. Relations between ET and several 

environmental variables (incoming solar radiation, air temperature, relative humidity, soil moisture, and net radiation) 

were explored. Net radiation (r2 = 0.72) and air temperature 

(r2 = 0.73) were the dominant explanatory variables for daily 

ET. Air temperature was the dominant control on evaporative 

fraction with relatively more radiant energy used for ET at 

higher temperatures. Soil moisture was shown to limit ET during extended dry periods. With volumetric soil moisture below 

a threshold of about 0.15, the evaporative fraction decreased 

until rain ended the dry period, and the evaporative fraction 

sharply recovered. A modified Hargreaves ET model, requiring only easily obtainable daily temperature data, was shown 

to be effective at simulating measured ET values and has the 

potential for estimating historical or real-time ET at the wetland site. The average annual ET measured at the wetland site 

during 2005–06 (801 mm/yr) is about 32 percent higher than 

previously reported ET for three nearby upland sites during 

2005–09. Periodic disturbance by fire and insect defoliation at 

the upland sites reduced ET. When only undisturbed periods 

were considered, the wetland ET was 17 percent higher than 

the undisturbed upland ET. Interannual variability in wetlands 

ET may be lower than that of uplands ET because the upland 

stands are more susceptible to periodic drought conditions, 

disturbance by fire, and insect defoliation. Precipitation during 

the study period at the nearby Indian Mills weather station 

was slightly higher than the long-term (1902–2011) annual 

mean of 1,173 millimeters (mm), with 1,325 and 1,396 mm of 

precipitation in 2005 and 2006, respectively.

Introduction

Water budgets are fundamental to the understanding of 

hydrologic systems. If the various components of the water 

budget can be quantified, including inflows, outflows, and 

changes in stored water, then a more complete understanding 

and evaluation of a hydrologic system becomes possible. In 

the New Jersey Pinelands area (fig. 1), wetlands and aquatic 

habitats are supported by discharge from the KirkwoodCohansey aquifer system, and detailed water budgets of the 

area are needed in order to develop a quantitative understanding of aquifer-wetland-stream interactions at the watershed 

scale. As described by Rhodehamel (1970), groundwater flow 

in the Pinelands is initiated as aquifer recharge, primarily in 

upland areas, and follows regional and local subsurface flow 

paths, with local flow paths terminating as aquifer discharge to 

wetlands and streams. Temporal variations in recharge affect 

aquifer interactions with wetlands and streams, as demonstrated by investigations in the New Jersey Pinelands by 

Modica (1998) and Walker and others (2011). Quantification 

of aquifer recharge on a seasonal basis, therefore, is needed to 

understand the dynamics of aquifer interactions with wetlands 

and streams.

Evapotranspiration (ET) is an important component of 

the hydrologic budget in the Pinelands, and ET variability 

exerts considerable control over the amount of water available 

seasonally for aquifer recharge. On an average annual basis, 

ET from the Pinelands has been estimated to exceed recent 

Statewide public water use in New Jersey by more than a factor of two (based on data presented in Rhodehamel, 1979, and 

Hutson and others, 2004). In spite of its significance, the seasonal variability of ET and the relations between ET and other 

environmental factors in this ecologically important region 

are poorly quantified. Methods for direct measurement of ET 

have been developed (Dyer, 1961; Tanner and Greene, 1989) 

and used in a number of settings (Moore, 1976; Sumner, 1996; 

Stannard, 1993). Estimating seasonally variable ET rates for 

specific time periods at the watershed scale in the Pinelands 

requires site-specific data.

The U.S. Geological Survey (USGS) conducted a study 

of ET in the Pinelands, in cooperation with the New Jersey 

1

 U.S. Geological Survey

2

 U.S. Department of Agriculture, Forest Service, New Lisbon, New Jersey
2 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

Figure 1. Location of McDonalds Branch basin, selected weather stations, and evapotranspiration station, Pinelands area, 

New Jersey.

#

WOODLAND TOWNSHIP

£¤72

£¤563

£¤70

£¤72

£¤72

£¤563

01466500

0 0.4 0.8 MILES

0 0.4 0.8 1.2 KILOMETERS

McDonalds 

Branch 

watershed

Evapotranspiration 

 station

Pinelands 

Area

NEW JERSEY

Moorestown 

weather 

station

Indian Mills 2W

weather

station

Wetlands within McDonalds Branch 

basin

U.S. Geological Survey evapotranspiration station

EXPLANATION

Stream

Major road

Township boundary

Source area of flux measurement–

inner and outer circles delineate 

approximate source areas for 

80 percent and 90 percent, 

respectively, of daytime flux

McDonalds Branch watershed

# Streamgaging station and number 01466500

74°32' 74°30'

39°54'

39°52'

Base from U.S. Geological Survey 

digital line graph files, 1:24,000, 

Universal Transverse Mercator 

projection, Zone 18, NAD83

PEMBERTON

TOWNSHIP
Introduction 3

Pinelands Commission, to quantify the temporal variability of 

ET and to examine relations between ET and environmental 

variables as part of the Kirkwood-Cohansey Project (Pinelands 

Commission, 2003). During November 10, 2004–February 

20, 2007, ET was monitored above a wetland forest canopy 

in the McDonalds Branch basin in Burlington County, New 

Jersey (fig. 1). Meteorological and eddy-covariance sensors 

were deployed on a 24.5-meter (m) tower, and groundwater 

levels and soil moisture at the site were also monitored. Three 

models were evaluated for their utility in simulating ET, and a 

time series of weekly ET rates was developed for the measurement period. 

Purpose and Scope

This report presents the results of an ET study at the wetland forest site in the Pinelands area. It includes an explanation of the methods used, an analysis of the flux source area, 

measured ET rates, relation of these rates to environmental 

variables, a comparison of wetland ET with ET measured in 

upland areas in the Pinelands, and a comparison of ET measured during the 27-month monitoring period to ET simulated 

using selected models. The results of this study can be used 

in conjunction with information on other components of the 

water budget to develop an understanding of temporal variations in water exchange among different compartments of the 

Pinelands hydrologic system. Results can also be extended 

to formulate approaches for estimating ET in the Pinelands 

during other time periods using commonly measured environmental variables. Values for ET are shown in figures and are 

listed in tables. 

Previous Investigations

ET in the New Jersey Pinelands has been the subject of 

published investigations for more than 115 years. The following summary of previous investigations provides context for 

the present study. Determination of ET played a key role in 

early water-supply planning in the region. Vermeule (1894) 

approximated monthly and annual ET for southern New Jersey 

watersheds on the basis of calculations made using empirical 

relations between precipitation and runoff in other East Coast 

watersheds. These calculations were used to estimate the safe 

yield for Joseph Wharton’s 1891 proposal to divert flow from 

more than 1,191 square kilometers of “the great pine belt” of 

southern New Jersey and deliver it to the cities of Camden 

and Philadelphia (City of Philadelphia, 1892). Wood (1937) 

quantified interception (the amount of rain or snow stored on 

leaves and branches and eventually evaporated back to the 

atmosphere), an important component of the hydrologic cycle 

that contributes to evapotranspiration, in an oak-pine forest 

in the Pinelands. A number of studies were conducted during the 1950s and 1960s to understand the effects of forest 

management practices on water resources in the Pinelands as 

part of a research initiative referred to as the “Pine Region 

Hydrological Research Project” (Buell, 1955); related research 

continued into the 1970s. Lull and Axley (1958) studied ET 

in different upland vegetative communities in the Pinelands 

by measuring soil moisture changes, but significant differences were not found among the communities. Barksdale 

(1958) concluded that ET in the lower Delaware River Basin 

accounted for about 50 percent of precipitation. Rhodehamel 

(1970) found this 50-percent value applicable to the Pinelands 

area and estimated the mean annual ET rate in the Pinelands 

on the basis of the long-term difference between precipitation 

and runoff to be 572 millimeters per year (mm/yr), or about 50 

percent of precipitation. Rhodehamel (1979) found reasonable 

agreement between this ET rate and estimated ET rates from 

other investigations in the Pinelands and vicinity. Summer ET 

rates in hardwood-dominated and cedar-dominated wetlands 

in the Pinelands were estimated from water-table fluctuations, 

and no differences in the ET rates of these communities were 

detected (Ballard, 1971; Buell and Ballard, 1972). ET rates in 

lowland shrub communities were found to be lower than those 

of lowland tree communities (Buell and Ballard, 1972). ET 

rates were shown to be greater in lowland (wetland) areas of 

the Pinelands, where water is more available to plants, than in 

upland areas (Ballard and Buell, 1975). Ballard (1979) examined these differences in an energy flux context and concluded 

that in wetland tree areas, the net summer loss of groundwater 

discharge through ET was 250 millimeters (mm). 

ET has been estimated as part of water-supply and availability studies in the New Jersey Coastal Plain. Mean ET 

rates in the major drainage areas of the New Jersey Coastal 

Plain were estimated by Vowinkel and Foster (1981) as the 

long-term difference between mean precipitation and mean 

runoff. Estimates of ET (presented as “water loss”) for basins 

partly within the Pinelands ranged from 414 to 653 mm/yr 

(Vowinkel and Foster, 1981). More detailed examinations of 

water budgets that include ET in selected drainage areas that 

are within the New Jersey Coastal Plain and at least partly 

within the Pinelands are presented in a series of reports by 

Watt and Johnson (1992), Johnsson and Barringer (1993), Watt 

and others (1994), Johnson and Watt (1996), Watt and others 

(2003), and Gordon (2004). Although the methods used to 

estimate ET in these studies vary somewhat, the ET estimates 

were all based on the concept of water-budget closure and 

are, therefore, consistent with estimates of other water-budget 

components. The ET estimates from the previously mentioned 

series of reports range from 563 to 658 mm/yr. As part of the 

Kirkwood-Cohansey Project, the USGS assessed hydrologic 

conditions in three basins in the Pinelands during 2004–06, 

including the McDonalds Branch basin where the present ET 

study site is located (Walker and others, 2011). Results of the 

hydrologic assessment of the McDonalds Branch basin include 

estimates of water-budget components that can be used to 

evaluate the veracity of ET measurements presented in this 

report.

Other recent investigations have examined the physiological responses of a variety of Pinelands shrub and tree species to hydrologic stress, fire, and insect defoliation. As part 
4 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

of their research on carbon and fire dynamics in the Pinelands, 

Clark and others (2010, 2011) measured ET flux using an eddy 

covariance method at an oak-dominated upland site and two 

pine-dominated upland sites in the Pinelands. They observed 

that ET at the oak-dominated upland site was slightly greater 

in summer and lower in winter than ET at the pitch pinedominated upland site and that ET averaged 51 to 62 percent 

of annual precipitation at the sites when they were undisturbed. Additional flux monitoring demonstrated the effects 

of fire and insect defoliation on ET and water-use efficiency 

at the three sites; annual ET at one of the defoliated sites was 

as low as 419 mm/yr, 37 percent of incident precipitation 

(Clark and others, 2011). When all years were considered, 

maximum seasonal leaf area index at these sites explained 82 

and 80 percent of the variation in daily ET during the summer 

at the oak- and pine-dominated sites, respectively. Results of 

the study by Clark and others (2011) indicate that gypsy moth 

defoliation disturbance in 2007 may have resulted in a temporary increase in aquifer recharge of approximately 9 percent in 

upland forests throughout the Pinelands. Schafer (2011) examined changes in stomatal conductance in response to drought, 

defoliation, and mortality in an upland oak/pine forest in the 

Pinelands. Drought caused reductions in canopy-level conductance, and corresponding reductions in ET, with the magnitude 

of the effect varying by species. 

Methods for Measurement and 

Simulation of Evapotranspiration

ET was measured at a site within McDonalds Branch 

basin (fig. 1) using the eddy-covariance method (Dyer, 1961; 

Baldocchi and others, 1988; and Tanner and Greene, 1989). 

The site chosen for the ET station is within a pitch-pine 

lowland stand. Canopy vegetation at the site is dominated by 

Pinus rigida (pitch pine) that reaches a maximum height of 

about 15 m. Understory vegetation is dominated by Gaylussacia frondosa (dangleberry), Kalmia angustifolia (sheep 

laurel), Eubotrys racemosa (fetterbush), and Xerophyllum 

asphdeloides (turkeybeard). Vegetation types in nearby areas 

of cedar swamp are dominated by Chamaecyparis thyroides

(Atlantic white cedar) and Shagnum spp (shagnum moss); 

nearby areas of hardwood swamp are dominated by Acer 

rubrum (red maple) and Nyssa silvatica (blackgum). Depth 

to the water table at the site fluctuates between about 0.5 to 

1.5 meters (m) below land surface although parts of the surrounding area exhibit standing water during wet periods. The 

site of the ET station is adjacent to one of the vegetation plots 

used by Laidig and others (2010a, 2010b) to develop models 

for predicting the distribution of wetland vegetation on the 

basis of hydrologic conditions. Eddy-covariance instrumentation was deployed on a 24.5 m tall Rohn 45G communications-type tower at the site (fig. 2), and 30-minute data were 

collected for an 833-day period from November 10, 2004, 

to February 20, 2007. Other meteorological and hydrologic 

Figure 2. Evapotranspiration station at a pitch-pine lowland site 

in the McDonalds Branch basin, Pinelands area, New Jersey: 

A, tower with instrumentation (Photograph by Anthony S. Navoy, 

USGS) and B, krypton hygrometer (foreground) and sonic anemometer (background) mounted at top of tower at evapotranspiration 

station (Photograph by Robert S. Nicholson, USGS).

A

B
Methods for Measurement and Simulation of Evapotranspiration 5

instrumentation also was deployed on or around the tower to 

collect data for ET models and to provide ancillary data for 

the eddy-covariance analysis. The instrumentation used in the 

study is described in table 1. Measured values of ET were used 

to calibrate ET models or for comparison with model results.

Measurement of Evapotranspiration

Evapotranspiration can be measured above a forest 

canopy by using a variety of methods. The method selected for 

this study is the eddy-covariance method.

Eddy-Covariance Method

The eddy-covariance method (Dyer, 1961; Tanner and 

Greene, 1989) was used to measure two components of the 

energy budget of the plant canopy: latent and sensible heat 

fluxes. Latent heat flux (lE) is the energy removed from the 

canopy in the liquid-to-vapor phase change of water and is 

the product of the heat of vaporization of water (l) and the 

ET rate (E). Sensible heat flux (H) is the heat energy removed 

from/added to the canopy as a result convective transport 

along a temperature gradient between the canopy and the 

air. Both latent and sensible heat fluxes are transported by 

turbulent eddies in the air that are generated by a combination 

of frictional and convective forces. The energy available to 

generate turbulent fluxes of vapor and heat is equal to the net 

radiation (Rn) less the sum of the heat flux into the soil surface 

(G) and the change in storage (S) of energy in the biomass, air, 

and any standing water. The energy involved in fixation of carbon dioxide is usually negligible (Brutsaert, 1982, p. 144). Net 

radiation is the difference between incoming radiation (shortwave solar radiation and longwave atmospheric radiation) and 

outgoing radiation (reflected shortwave and surface-emitted 

longwave radiation). Energy is transported to and from the 

base of the canopy by conduction through the soil. Assuming 

that net horizontal advection of energy is negligible, the 

energy-budget equation, for a control volume extending from 

land surface to a height zs at which the turbulent fluxes are 

measured, takes the following form:

R G n - - S H= + λE , (1)

where

the left-hand side of equation 1 represents the available 

energy, the right-hand side represents the turbulent fluxes, and

Rn is net radiation to/from plant canopy, in watts 

per square meter;

G is soil heat flux at land surface, in watts per 

square meter;

S is change in storage of energy in the biomass, 

air, and in any standing water, in watts per 

square meter;

H is sensible heat flux at height zs above land 

surface, in watts per square meter;

Table 1. Description of study instrumentation.

[CSI, Campbell Scientific, Inc.; HS, Hydrological Services Pty Ltd; REBS, Radiation and Energy Balance Systems, Inc.; RMY, R.M. Young, Inc.; psi, pounds 

per square inch; negative height is depth below land surface; number of instruments listed in parentheses]

Characteristic Instrument Height above land surface

(meters)

Evapotranspiration CSI eddy-covariance system including Model CSAT3 three-dimensional sonic anemometer and Model KH2O krypton hygrometer (1) 22.1

Air temperature/relative humidity CSI Model HMP45 temperature and relative humidity probe (1) 22.3

Solar radiation LI-COR, Inc., Model LI200 pyranometer (1) 22

Net radiation REBS Model Q-7.1 net radiometers (2) 22

Soil moisture CSI Model CS615 Water content reflectometer (1) 0 – -0.3

Precipitation HS Model TB3 tipping bucket rain gage (1) 14.2

Water level in well In-Situ Model MiniTROLL 5 pounds per square inch pressure sensor 

and datalogger unit (1) -2

Wind speed and direction RMY Model 05305VM Wind Monitor (1) 24.7

Data logging CSI Model 10X data loggers (2), 12-volt 100 amp-hour deepcycle batteries (2), 50 watt solar panels (2) 0–1, 0–1, 10–13
6 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

	 lE is latent heat flux at height zs above land 

surface, in watts per square meter; and

the sign convention is such that Rn and G

are positive downwards and 

H and lE are positive upwards.

The eddy-covariance method is a conceptually simple, 

one-dimensional approach for measuring the turbulent fluxes 

of vapor and heat above a surface. For the case of vapor transport above a flat, level landscape, the time-averaged product of 

measured values of vertical wind speed (w) and vapor density 

(ρv) is the estimated vapor flux (ET rate) during the averaging 

period, assuming that the net lateral advection of vapor is negligible. Because of the insufficient accuracy of instrumentation 

available for measurement of actual values of wind speed and 

vapor density, this procedure generally is performed by monitoring the fluctuations of wind speed and vapor density about 

their means, rather than monitoring their actual values. This 

formulation is represented by the following equations:

E w = ρ ρ w v v ( ' + w + v = )(ρ ') , (2)

= w ρ ρw + w ' ' ρ ρ w ' v v + ' v v + , (3)

and

w c ' ' ρ ρ v = ( ovariance w v , ) , (4)

where

E is ET rate, in grams per square meter per 

second;

w is vertical wind speed, in meters per second;

ρv is vapor density, in grams per cubic meter; 

and overbars and primes indicate means 

over the averaging period and deviations 

from means, respectively.

The first term of equation 3 is approximately zero 

because mass-balance considerations dictate that mean vertical 

wind speed perpendicular to the surface is zero; this conclusion is based on an assumption of constant air density (correction for air-density fluctuations are noted later in this report). 

The second and third terms are zero based on the definition 

that the mean fluctuation of a variable is zero. Therefore, it is 

apparent from equation 4 that vertical wind speed and vapor 

density have to be correlated for a non-zero vapor flux to exist. 

The turbulent eddies that transport water vapor (and sensible 

heat) produce fluctuations in both the direction and magnitude 

of vertical wind speed. The ascending eddies must on average 

be moister than the descending eddies for ET to occur; that 

is, upward air movement has to be positively correlated with 

vapor density, and downward air movement must be negatively correlated with vapor density.

Source Area of Measurements

The source area for a turbulent flux measurement is 

defined as the area (upwind of the measurement location) contributing to the measurement. The source area can consist of 

a single vegetative cover if that cover is adequately extensive. 

This condition is met if the given cover extends sufficiently far 

upwind such that the atmospheric boundary layer has equilibrated with the cover from ground surface to at least the height 

of the instrumentation. If this condition is not met, the flux 

measurement is a composite of fluxes from two or more covers 

within the source area. 

Schuepp and others (1990) provide an estimate of the 

source area for turbulent flux measurements and the relative 

contributions within the source area on the basis of an analytical solution of a one-dimensional (upwind) diffusion equation 

for a uniform surface cover. In this approach, source area varies with instrument height (zs

), zero displacement height (d), 

roughness length for momentum (zm), and atmospheric stability. The instrument height for the turbulent flux measurements 

in this study was 22.1 m. Campbell and Norman (1998, p. 71) 

proposed empirical relations for zero displacement height 

(d~0.65h) and roughness length for momentum (zm~0.10h), 

where h is the canopy height. A uniform canopy height of 

15 m was assumed in this analysis. The source area estimates 

were made assuming mildly unstable conditions typical of 

daytime conditions when heat and vapor fluxes are highest; the 

Obukhov stability length (Businger and Yaglom, 1971) was set 

equal to -10 m. About 80 percent and 90 percent of the source 

area for the daytime turbulent flux measurements were estimated to be within upwind distances of about 205 and 435 m, 

respectively, as shown in figures 1 and 3. The source area 

during the generally more stable nighttime conditions could 

extend considerably further, but turbulent fluxes are relatively 

small in the absence of sunlight. The source area is forested 

throughout, but includes wetlands with pitch pine and cedar 

swamps and uplands covered by oak and pine (fig. 1). Because 

the measured turbulent fluxes are representative of upwind 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1 10 100 1,000 10,000

Radial distance from instrument, in meters

Cumulative fractional contribution 

to measurement

 A radial distance

of 205 meters

defines a source

area accounting

for 80 percent of

daytime flux

 A radial distance

of 435 meters

defines a source

area acounting

for 90 percent of

daytime flux

Canopy height, h = 15 meters

Observation height, z = 1.47h

Obukhov stability length L = -10

(mildly unstable conditions)

s

Figure 3. Radial extent of source area for daytime turbulent 

flux measurements. (Produced using the method of Schuepp and 

others, 1990)
Methods for Measurement and Simulation of Evapotranspiration 7

land covers, the vegetative composition of the source area 

will change with varying wind direction. For example, wind 

directions ranging clockwise from southeast to west would 

provide flux measurements almost exclusively representative 

of forested wetland; other wind directions provide flux measurements representative of varying mixtures of wetland and 

upland forests. In this study, discrepancies between measured 

ET and simulated ET from models that are invariant with wind 

direction are examined as a function of wind direction. This 

comparison will show the degree to which differences in ET 

between the two forest communities can be discerned with the 

available measurements.

Instrumentation

Instrumentation capable of high-frequency resolution is 

used in applications of the eddy-covariance method because 

of the relatively high frequency of the turbulent eddies that 

transport water vapor. Instrumentation included a three-axis 

sonic anemometer and a krypton hygrometer to measure or 

infer variations in wind speed and vapor density, respectively 

(fig. 2; table 1). The sonic anemometer relies on three pairs 

of sonic transducers to detect wind-induced changes in the 

transit time of emitted sound waves and to infer fluctuations in 

wind speed in three orthogonal directions. The measurement 

path length between transducer pairs is 10.0 centimeter (cm) 

(vertical) and 5.8 cm (horizontal); the transducer path angle 

from the horizontal is 60 degrees. In contrast to some sonic 

anemometers used previously (Sumner, 1996), the transducers 

of this improved anemometer are not permanently destroyed 

by exposure to moisture and thus are suitable for long-term 

deployment. Operation of the anemometer used in this study 

ceases when moisture on the transducer disrupts the sonic 

signal but recommences upon drying of the transducers. 

The hygrometer relies on the attenuation of ultraviolet 

radiation, emitted from a source tube, by water vapor in the 

air along the 1-cm path to the detector tube. The instrument 

pathline was laterally displaced 10 cm from the midpoint of 

the sonic-transducer pathlines (fig. 2B). Hygrometer voltage output is proportional to the attenuated radiation signal, 

and fluctuations in this signal can be related to fluctuations 

in vapor density by Beer’s Law (Weeks and others, 1987). 

Similar to the anemometer, the hygrometer ceases data collection when moisture obscures the windows on the source 

or detector tubes. Also, the tube windows become “scaled” 

with exposure to the atmosphere, resulting in a loss of signal 

strength. The hygrometer is designed such that vapor density 

fluctuations are accurately measured in spite of variable signal 

strength; however, if signal strength declines to near-zero 

values, the fluctuations cannot be discerned. Periodic cleaning of the sensor windows (performed monthly in this study) 

with a cotton swab and distilled water restores signal strength. 

Eddy-covariance instrument-sampling frequency was 8 Hertz 

(Hz) with 30-minute averaging periods. The eddy-covariance 

instrumentation was placed about 7.1 m above the tree canopy. 

The 8-Hz data were processed into 30-minute composites and 

stored in a data logger near ground level.

Flux measurements are made in the constant-flux inertial 

sublayer, in which lateral variations in vertical flux are negligible, to be representative of the surface cover. Measurements 

made in the underlying roughness sublayer can reflect individual roughness elements (for example, individual trees or gaps 

between trees) rather than the composite surface cover (Monteith and Unsworth, 1990). Garratt (1980) defines the lower 

boundary of the inertial sublayer to occur where the difference 

of the instrument height (zs) and the zero displacement height 

(d) is much greater than the roughness length for momentum (zm). Employing the empirical relations of Campbell and 

Norman (1998) for zero displacement height and roughness 

length for momentum, and assuming that “much greater than” 

implies greater by a factor of eight (8), leads to an instrument 

height requirement of zs greater than 1.45h. A factor of about 

1.47 was used in the present study.

Calculation of Turbulent Fluxes

Latent heat flux was estimated based on a modified form 

of equation 4:

(1 ) σ ρ

ρ

ρ

w' ' +

H

C T + + FK v

v 

p a

0 (

( 273.15)

)

H

K T w a ( +273.15)

μ λE = λ( + ) , (5)

where

lE is latent heat flux, in watts per square meter;

l is latent heat of vaporization of water, 

estimated as a function of temperature

 (Stull, 1988), in joules per gram;

μ is ratio of molecular weight of air to 

molecular weight of water;

ơ is ratio of vapor density (ρv) to air density (ρ);

ρ is air density, estimated as a function of air 

temperature, total air pressure, and vapor 

pressure (Monteith and Unsworth, 1990), 

in grams per cubic meter;

H is sensible heat flux, in watts per square 

meter;

Cp is specific heat capacity of air, estimated as 

a function of temperature and relative 

humidity (Stull, 1988), in joules per gram 

per degree Celsius;

Ta is air temperature, in degrees Celsius;

F is a factor that accounts for molecular weights 

of air and oxygen, and atmospheric 

abundance of oxygen, equal to 0.229 gramdegree Celsius per joule;

Ko is extinction coefficient of hygrometer for 

oxygen, estimated as -0.0045 cubic meters 

per gram per centimeter (Tanner and 

others, 1993);

Kw is extinction coefficient of hygrometer for 

water, equal to the manufacturer-calibrated 
8 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

value, in cubic meters per gram per 

centimeter; and overbars and primes 

indicate means over the averaging 

period and deviations from the means, 

respectively.

The (1 + μs) multiplier and the second term of the righthand side of equation 5 account for temperature-induced fluctuations in air density (Webb and others, 1980), and the third 

term accounts for the sensitivity of the hygrometer to oxygen 

(Tanner and Greene, 1989).

Similar to vapor transport, sensible heat can be 

estimated by:

H C = ' w T ' ρ p a . (6)

The sonic anemometer is capable of measuring “sonic” 

temperature on the basis of the dependence of the speed of 

sound on this variable (Kaimal and Businger, 1963; Kaimal 

and Gaynor, 1991). Schotanus and others (1983) related the 

sonic sensible heat, based on measurement of sonic temperature fluctuations, to the true sensible heat given in equation 6. 

Those researchers included a correction for the effect of 

wind blowing normal to the sonic acoustic path that has been 

incorporated directly into the anemometer measurement by the 

manufacturer (E. Swiatek, Campbell Scientific, Inc., written 

commun., 1998), leading to a simplified form of the Schotanus 

and others (1983) formulation given by

w Ta s w T T +a ' ' = ' ' - 0.51 ( 273.15) w'q' , (7)

where

Ts is the sonic temperature, in degrees Celsius; 

and

q is specific humidity, in grams of water vapor 

per gram of moist air.

On the basis of the relation between specific humidity 

and vapor density (Fleagle and Businger,1980),

q 

R T +

P

v d a

a

≈ ρ ( 273.15) , (8)

where

Rd, is the gas constant for dry air (0.28704 joules 

per degree Celsius per gram) and

Pa, is atmospheric pressure, in pascals (assumed 

to remain constant at 100,534 pascals at 

top of tower about 58 meters above sea 

level).

Equation 7 can be expressed in terms of fluctuations in 

the hygrometer-measured water vapor density rather than 

fluctuations in specific humidity as

w T' ' ( ' ' - + w

T +

T + a w T a

s

s = ( 273.15)

( 273.15)

 0.51 ( 273.15) ' ' / ) 2 R Td a ρv a P . (9)

Estimation of turbulent fluxes (eqs. 5 and 6) relies on an 

accurate measurement of velocity fluctuations perpendicular to 

the lateral airstream. The study area is relatively flat and level, 

indicating that the airstream is approximately perpendicular to 

gravity and the sonic anemometer was oriented with respect 

to gravity with a bubble level. Measurement of wind speed in 

three orthogonal directions with the sonic anemometer used 

in this investigation allowed for a more refined orientation of 

the collected data with the natural coordinate system through 

mathematical coordinate rotations. The magnitude of the coordinate rotations are determined by the components of the wind 

vector in each 30-minute averaging period. The wind vector is 

composed of three time-averaged components (u, v, w) in the 

three coordinate directions (x, y, z). Direction z initially was 

approximately oriented vertically (with respect to gravity) and 

the other two directions were arbitrary. Tanner and Thurtell 

(1969) and Baldocchi and others (1988) outline a procedure 

in which measurements made in the initial coordinate system are transformed into values consistent with the natural 

coordinate system. First, the coordinate system is rotated by 

an angle h about the z-axis to align u into the x-direction on 

the x-y plane. Next, rotation by an angle q is performed about 

the y-direction to align w along the z-direction. These rotations 

force v and w equal to zero; therefore, u is pointed directly into 

the airstream. A third rotation is sometimes used in complex 

situations (such as a curving airstream around a mountain) to 

force v w' ' equal to zero, although Baldocchi and others (1988) 

indicate that two rotations generally are adequate, and two 

rotations were used in the current study.

Consistency of Measurements with Energy 

Budget

Previous investigators (Moore, 1976; Lee and Black, 

1993; Bidlake and others, 1996; Goulden and others, 1996; 

Sumner, 1996; Twine and others, 2000; German, 2000; and 

Foken, 2008) have described a recurring problem with the 

eddy-covariance method: a frequent discrepancy of the measured latent and sensible heat fluxes with the energy-budget 

equation (eq. 1). The usual case is that measured turbulent 

fluxes (H + lE) are less than the measured available energy 

(Rn - G - S). Turbulent fluxes measured above a coniferous 

forest by Lee and Black (1993) accounted for only 83 percent 

of available energy. Possible explanations for the observed 

discrepancy in the measured turbulent fluxes include a sensor frequency response that is insufficient to capture highfrequency eddies; an averaging period insufficient to capture 
Methods for Measurement and Simulation of Evapotranspiration 9

low-frequency eddies; drift in the absolute values of anemometer and hygrometer measurements, resulting in statistical 

non-stationarity within the averaging period; lateral advection 

of energy; a discrepancy in the measurement points for the 

wind and vapor density sensors; and overestimation of available energy. Several researchers (Moore, 1976; Goulden and 

others, 1996; German, 2000) have shown that the eddy-covariance method obtains better energy-budget closure in windy 

conditions than during calm conditions. 

Twine and others (2000) performed an experiment using 

multiple models of eddy-covariance sensors and net radiometers to measure energy fluxes from a grassland and observed 

a systematic energy closure discrepancy (turbulent fluxes less 

than available energy) of 10 to 30 percent. Their conclusion 

was that eddy-covariance measurements should be adjusted 

for energy-budget closure. Two common alternatives to adjust 

turbulent flux measurements for energy-budget closure are 

to (1) preserve the Bowen ratio or (2) preserve the measured 

sensible heat flux. Twine and others (2000) indicate a preference for the Bowen ratio approach but state that “the method 

for obtaining closure appears to be less important than assuring that eddy-covariance measurements are consistent with 

conservation of energy.” The Bowen ratio alternative assumes 

that the ratio of turbulent fluxes is adequately measured by 

the eddy-covariance method. The energy-budget equation 

(eq. 1), along with turbulent fluxes (H and lE) measured using 

the standard eddy-covariance method are used to produce 

corrected (HBREB and lEBREB) turbulent fluxes in this “Bowen 

ratio energy-budget variant” of the eddy-covariance method as 

indicated in equations 10 to 12. On the basis of equation 12, 

this variant fails when the Bowen ratio is close to -1 and the 

denominator approaches zero.

R G n - - S = H + BREB λ λ E E BREB = ( BREB 1 ) + B , (10)

where the Bowen ratio (B) is given by

B

H

E =

λ

, (11)

Rearranging eq. 10,

λE

R G S

+ B BREB

n

= - -

1 , (12)

H R BREB = - n G S EBREB - - λ . (13)

The second alternative for adjustment of fluxes for 

energy-budget closure used in this study assumes that the 

sensible heat flux measured by the standard eddy-covariance 

method is correct but that latent heat flux is underestimated. 

Therefore, the corrected latent heat flux is computed as a 

residual of the energy budget (eq. 1). This “residual energybudget” variant of the eddy-covariance method is

λEREB = - R G n - - S H . (14)

Energy generally enters the soil surface and (or) any 

standing water and is stored in the biomass and air during the 

day and released at night. Implementation of equations 10 

to 14 was facilitated by using daily composites of terms in 

these equations and assuming that soil heat flux and changes 

in energy storage in the biomass, air, and any standing water 

were negligible at this site over a diurnal cycle. Therefore, 

although eddy-covariance flux measurements were made 

at 30-minute resolution, only daily or coarser ET estimates 

incorporate energy-budget closure considerations. Use of a 

daily compositing interval of flux values in this study allowed 

for neglect of those terms of the energy budget that were 

not measured (soil heat flux and biomass/air/standing water 

energy storage). However, during periods of rapid temperature 

changes (for example, cold front passage), the net soil heat 

flux and the net change in energy stored in the biomass/air/

standing water over a diurnal cycle may not be negligible. 

As mentioned previously, missing 30-minute turbulent 

flux data can result from scaling of hygrometer windows and 

from moisture on the anemometer or hygrometer. These data 

need to be estimated prior to construction of daily composites 

of turbulent fluxes. In the present study, regression analysis of 

measured 30-minute turbulent flux and net radiation data was 

used to estimate unmeasured values of 30-minute turbulent 

fluxes. Additionally, both H and lE were set to zero during 

periods of rainfall when rainwater on eddy-covariance and 

net radiation sensors resulted in missing or corrupted data. An 

assumption of negligible turbulent fluxes during rainfall events 

was considered reasonable because of the cloudy and, therefore, low net radiation conditions generally prevalent 

during rain.

Simulation of Evapotranspiration

Several models were evaluated for their utility in estimating ET. The eddy-covariance instrumentation can have 

extended periods of non-operation, as discussed previously. 

However, more robust meteorological and hydrologic instrumentation (sensors for measurement of net radiation, air temperature, relative humidity, solar radiation, wind speed, soil 

moisture, and water-table depth) provide nearly uninterrupted 

data. ET models, calibrated to measured turbulent flux data 

and based on continuous meteorological and hydrologic data, 

can be used to fill gaps in measured data, providing continuous 

estimates of ET. Additionally, ET models can provide insight 

into the cause-and-effect relation between the environment 

and ET— in particular, relations among water-table depth, soil 

moisture, and ET. Finally, some ET models can provide estimates of maximum (potential or reference) ET under conditions of optimal moisture availability. 

Measurement of ET using the eddy-covariance method is 

resource intensive, so it is practical to use the results of shortterm studies to develop and verify ET models that can then be 

used to estimate ET for other time periods and to understand 

the cause-and-effect nature of evaporative processes. The 
10 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

utility of different models is related to the model assumptions or the data used by the models. For example, results of 

a model that is indifferent to wind direction can be compared 

with measurements to help determine if ET is related to wind 

direction. A model that requires only temperature data can 

be used to estimate historical variability in ET using readily 

available long-term temperature records. The three ET models 

explored are described below.

Priestley-Taylor Equation

Physics-based ET models generally rely on the work of 

Penman (1948), who developed an equation for evaporation 

from wet surfaces that is based on energy budget and aerodynamic principles. That equation has been applied to estimate 

ET from well-watered, dense agricultural crops (reference or 

potential ET). In Penman’s equation, the transport of latent 

and sensible heat fluxes from a “big leaf” to the sensor height 

is subject to an aerodynamic resistance. The big leaf assumption implies that the plant canopy can be conceptualized as 

a single source of both latent and sensible heat at a given 

height and temperature. Inherent in the Penman approach is 

the assumption of a net one-dimensional, vertical transport of 

vapor and heat from the canopy. The Penman equation is

( - ( -

λ

ρ

γ

E

R S +

C e

r

+

n

p s

h =

)

e)

Δ

Δ , (15)

where

	 D	 is slope of the saturation vapor-pressure 

curve, in kilopascals per degree Celsius;

es is saturation vapor pressure, in kilopascals;

e is vapor pressure, in kilopascals;

rh is aerodynamic resistance, in seconds 

per meter;

	 g	 is the psychrometric “constant”, equal to 

approximately 0.067 kilopascals per 

degree Celsius but varying slightly with 

atmospheric pressure and temperature; and 

other terms are as previously defined.

The first term is known as the energy term; the second 

term is known as the aerodynamic term.

Priestley and Taylor (1972) proposed a simplification 

of the Penman equation for the case of saturated atmosphere 

(e = es), for which the aerodynamic term is zero, leaving

λ

γ

E

Δ+ = Δ(Rn - S) . (16)

However, Priestley and Taylor (1972) noted that empirical evidence indicates that evaporation from extensive wet 

surfaces is greater than this amount, presumably because the 

atmosphere generally does not attain saturation. Therefore, the 

Priestley-Taylor coefficient, a, was introduced as an empirical 

correction to the theoretical expression

λ

γ

E

Δ+ = Δ(Rn - S)

α . (17)

This formulation assumes that the energy and aerodynamic terms of the Penman equation are proportional to each 

other. The value of a has been estimated to be 1.26, which 

indicates that under potential ET conditions, where there is 

no moisture limitation, the aerodynamic term of the Penman equation is about 21 percent of the total latent heat flux. 

Eichinger and others (1996) have shown that the empirical 

value of a has a theoretical basis; a nearly constant value of 

a is expected under the existing range of Earth-atmospheric 

conditions.

Previous studies (Flint and Childs, 1991; Stannard, 1993; 

Sumner, 1996) have applied a modified form of the PriestleyTaylor equation. The approach in these studies relaxes the 

Penman assumption of a free-water surface or a dense, wellwatered canopy by allowing a to be less than 1.26 and to vary 

as a function of environmental factors. The Penman-Monteith 

equation (Monteith, 1965) is a more theoretically rigorous 

generalization of the Penman equation that also accounts for 

a relaxation of the Penman assumptions. However, Stannard 

(1993) noted that the modified Priestley-Taylor approach to 

simulation of observed ET rates was superior to the PenmanMonteith approach for a sparsely vegetated site in the semiarid rangeland of Colorado. Similarly, Sumner (1996) found 

the modified Priestley-Taylor approach performed better 

than the Penman-Monteith for a site of herbaceous, successional vegetation in central Florida. The modified PriestleyTaylor approach was evaluated in the present investigation 

to simulate daily ET. The selected form of a as a function of 

environmental variables was determined in this study through 

trial-and-error exploratory data analysis, and the parameterization of a particular form of a was determined using regression 

with measured daily values of ET.

Hargreaves Equation

The Hargreaves equation (Hargreaves and Allen, 2003) 

is widely used in agricultural studies in the United States and 

globally to estimate reference ET. Reference ET is defined as 

the evapotranspiration from an actively growing, well-watered 

grass or alfalfa vegetative cover of a specific height range 

(Allen and others, 2005). The Hargreaves equation is appealing because of the sparse data requirements; only minimum 

and maximum daily air temperature are required, and these are 

typically measured at most weather stations. The coefficients 

and form of the equation are empirical and were developed 

based on a comparison with ET data from precision weighing 

lysimeters used with grass land covers. The Hargreaves equation is based on an empirical relation between ET and the two 

most important explanatory variables for this term—incoming 
Methods for Measurement and Simulation of Evapotranspiration 11

solar radiation and air temperature (eq. 18). Another empirical 

relation (eq. 19) is used to relate incoming solar radiation to 

extraterrestrial radiation and a variable highly correlated with 

cloud cover (daily temperature range). Combining equations 

18 and 19 leads to the Hargreaves equation (eq. 20).

ET aR (TC +b) a s = , (18)

R K s RSR TR0. 50 = a , (19)

ETa R = ( aK S R T a C +b TR 0. 50 ) , (20)

where

ETa is reference ET, in the same water evaporation 

units as Ra (for example, millimeters 

per day);

Rs is incoming solar radiation on land surface, in 

the same water evaporation units as ETa;

Ra is extraterrestrial radiation, in the same water 

evaporation units as ETa;

TC is average daily air temperature, in degrees 

Celsius;

TR is daily temperature range, in degrees Celsius;

a is an empirical coefficient equal to a value 

of 0.0135;

b is an empirical coefficient equal to a value 

of 17.8; and 

KRS is an empirical coefficient usually estimated 

as 0.16 and 0.19 for inland and coastal 

areas, respectively.

Hargreaves and Samani (1985) suggest that the product 

aKRS be set equal to 0.0023 for reference conditions. Ra can be 

estimated using an analytical expression of latitude and day of 

year (Allen and others, 2005). TC and TR are usually estimated as the average and difference of maximum and minimum daily air temperature, respectively. 

In this study, a modified form of the Hargreaves equation was considered to allow for the non-reference conditions. 

The modification allows the empirical coefficients a and b

of eq. 18 to vary in a regression analysis to best replicate 

measured daily values of ET and incoming solar radiation. 

The necessary daily temperature data for this analysis were 

obtained from measurements at the ET station and also from 

nearby National Weather Service stations in New Jersey 

(Moorestown and Indian Mills; National Climatic Data 

Center, 2012).

North American Regional Reanalysis

The National Centers for Environmental Prediction 

(NCEP) North American Regional Reanalysis (NARR) is an 

effort to create a long-term set of consistent climate data for 

North America (Mitchell and others, 2004; North American 

Regional Reanalysis, 2012). NARR is based on a coupled 

approach to simulation of atmospheric and land-surface 

processes of energy and mass transfer that assimilates weather 

data. The period of record of NARR is from 1979 to 2012, and 

the resolution is 32 kilometers (km) and 3 hours. In the present 

study, NARR estimates of latent heat flux (at NARR grid centered at 39.75o N. and 74.5o

W.) were compared to the values 

measured at the ET station (39.89o N. and 74.52oW.).

Measurement of Environmental Variables

Meteorological, hydrologic, and vegetative data were 

collected in the study area as ancillary data required by the 

energy-budget variant of the eddy-covariance method and as 

independent variables within an ET model. Meteorological 

variables monitored included net radiation, air temperature, 

relative humidity, wind speed, and incoming solar radiation. 

These data were monitored by data loggers at 15-second 

intervals, using instrumentation summarized in table 1; the 

resulting 30-minute means were stored.

Two net radiometers, deployed at a height of 22 m, 

provided redundant measurement of net radiation at the ET 

station. Measured values of net radiation were corrected for 

wind-speed effects as instructed by the instrument manual. 

About 90 percent of the source area of the net radiation measurement is contained within a radius of three times the height 

of the sensor above the canopy (Stannard, 1994). Therefore, 

the measurement of net radiation had a much smaller source 

area (radius of about 21 m) than did the turbulent flux measurement (about 90 percent of source area within upwind 

distance of about 450 m during typical daytime conditions). 

The source area for measured net radiation is composed 

exclusively of the pitch pine lowlands/cedar swamp typical of 

forested wetlands in the Pinelands area.

Air temperature and relative humidity were monitored at 

the ET station at a height of 22.3 m. The slope of the saturation vapor pressure curve (a function of air temperature) was 

computed in the manner of Lowe (1977), using the measured 

air temperature. A propeller-type anemometer to monitor wind 

speed and direction and an upward-facing pyranometer to 

measure incoming solar radiation were deployed at heights of 

24.7 and 22 m, respectively, at the ET station (table 1). 

Hydrologic variables that were monitored include precipitation, water-table depth, stream discharge, and soil moisture. 

Precipitation records were obtained from a tipping-bucket rain 

gage deployed at a height of 14.2 m at the ET station. Soil 

moisture at a location at the ET station was monitored using a 

water content reflectometer probe installed to provide an averaged volumetric soil moisture content within the upper 30 cm 

of the soil profile. The measured soil moisture values at this 

single location are not necessarily representative of the watershed or of the source area of the turbulent flux measurements 

but are presumed to be correlated with generalized wetting and 

drying conditions. Soil-moisture measurements were made 

and recorded on the data logger every 30 minutes (table 1).
12 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

Water levels in a shallow (3-m depth) observation well at 

the ET station (USGS well number 051604) were measured at 

60-minute intervals using a pressure transducer and recorded. 

The well is situated 5 m from the ET flux tower. Stream 

discharge of the McDonalds Branch was measured at 15-minute intervals at an upstream site 1.4 km east of the ET station 

(USGS station number 01466500; fig. 1). Well-construction 

data, water-level and stream-discharge data collection methods, water-level data, and stream-discharge data are presented 

in Walker and others (2011). 

Results of Evapotranspiration 

Measurement and Simulation

Most (73 percent) of the 30-minute resolution eddy-covariance measurements made during the 833-day study period 

were acceptable and could be used to develop ET models to 

estimate missing data and discern the effect of environmental 

variables on ET. Unacceptable measurements resulted from 

failure of the krypton hygrometer or sonic anemometer and 

were most extensive (81 percent of missing data) during nighttime hours because dew formation at night is common in this 

humid climate. This diurnal pattern of missing data was less 

of a problem than it might appear initially because turbulent 

fluxes are relatively small during the evening to early-morning 

hours when solar radiation is zero or low, so errors associated with gap filling do not translate into substantial errors in 

total ET. The environmental variable that provided the best 

explanatory value for 30-minute turbulent flux values was net 

radiation; missing flux data were estimated on the basis of linear regressions between the turbulent fluxes and net radiation 

for each month of the study (eqs. 21 and 22). This approach 

reproduced measured 30-minute values of lE and H with r2

values of 0.80 and 0.84, respectively, and standard errors of 

34 and 46 watts per square meter (W/m2), respectively. The 

Rn-to-turbulent flux regression coefficients showed considerable consistency for a given month from year to year (fig. 4). 

Although 27 percent of the 30-minute turbulent flux measurements were gap filled using equations 21 and 22, the fraction 

of energy flux gap filled was small (5 and 7 percent of lE and 

H, respectively) because missing data generally occurred during periods of low energy flux.

λE a = iR +n bi , (21)

H c = in R +di , (22)

where

ai, bi, ci, and di are coefficients for a given year-month i, 

ai and ci are unitless, and 

bi and di are in watts per square meter.

Examples of measured and regression-simulated energy 

fluxes are shown for July 1–10, 2006, in figure 5. The prominence of daytime over nighttime turbulent fluxes is evident. 

Also, a strong correspondence between the diurnal and 

cloudiness-related variations in net radiation and the turbulent 

fluxes is apparent. The simple linear relations of eqs. 21 and 

22 also reproduced the variations in measured turbulent fluxes 

reasonably. The mean, diurnal pattern of turbulent fluxes and 

net radiation (fig. 6) indicates that the vast majority of ET 

occurs during daytime, driven by incoming solar radiation. 

During average daytime conditions, both latent and sensible 

heat flux are upward. At night, the surface cools below air 

temperature, producing a reversal in the direction of sensible 

heat flux. Although the average, nighttime latent heat flux was 

slightly upward, dew formation (downward latent heat flux) 

commonly occurred.

Daytime wind was predominantly from wetland source 

areas (fig. 1 and fig. 7). The two wind arcs most representative 

of uplands (350o clockwise to 20o and 90o clockwise to 120o) 

represent only 15 percent of measured wind directions; other 

wind directions were primarily representative of wetlands, 

although to varying degrees. From this analysis and the analysis of the source area (figs. 1 and 3), it is concluded that the 

source of measured evaporative flux is primarily wetlands.

Energy-budget closure of turbulent fluxes relative to net 

radiation was examined using weekly, gap-filled composites of 

the sum of lE and H. As previously discussed, for this analysis, net radiation is equivalent to available energy because it 

has been assumed that the storage and soil heat flux energybudget terms are negligible over daily or greater time scales. 

Energy-budget closure was generally better during relatively 

windy periods, as indicated in figure 8. Measured and gapfilled 30-minute turbulent fluxes accounted for 77 and 83 

percent of mean net radiation values of 101 and 100 W/m2 for 

a b

EXPLANATION

b d

EXPLANATION

1 2 3 4 5 6 7 8 9 10 11 12

Month

1 2 3 4 5 6 7 8 9 10 11 12

Month

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

-30 

-20 

-10 

0 

10 

20 

30 

b and d coefficients,

in watts per square meter 

a and c coefficients,

in watts per square meter 

Figure 4. Monthly values of regression coefficients used in 

equations 21 and 22.
Results of Evapotranspiration Measurement and Simulation 13

Figure 5. Measured and simulated energy fluxes: A, sensible heat flux and B, latent heat flux at the wetland site in the Pinelands area, 

New Jersey, July 1–10, 2006. (H, sensible heat flux; λE, latent heat flux)

July 2006

Net radiation 

Measured λE 

Simulated λE 

EXPLANATION 

Net radiation 

Measured H 

Simulated H 

EXPLANATION 

1 2 3 4 5 6 7 8 9 10 11 

-100 

0 

100 

200 

300 

400 

500 

600 

700 

800 

Energy fluxes, in 

watts per square meter 

-100 

0 

100 

200 

300 

400 

500 

600 

700 

800 

Energy fluxes, in 

watts per square meter 

2 3 4 5 6 7 8 9 10 11 

July 2006

1 

A

B
14 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

2005 and 2006, respectively. The relatively large energy-budget discrepancy from early June 2005 to mid-October 2005 led 

to an exchange of krypton hygrometers on October 19, 2005, 

and to subsequently improved energy-budget closure. The 

hygrometer used in the early part of the study was returned to 

the manufacturer for evaluation and was diagnosed as exhibiting an unstable voltage output. For this reason, daily values 

of lE computed using either the standard eddy-covariance 

method or the Bowen ratio variant are considered unreliable for the period June 1, 2005, to October 19, 2005. After 

the conclusion of the study, the hygrometer used subsequent 

to October 19, 2005, was returned to the manufacturer for 

evaluation and was deemed to be stable with a drift in calibration of less than 1 percent. Daily values of ET are shown 

in figure 9 for the standard eddy-covariance method and the 

Bowen ratio and residual variants, excluding the standard and 

Bowen ratio methods for the period in 2005 when a hygrometer readings were suspect. For 2006, average ET was 1.66, 

2.10, and 2.25 millimeters per day (mm/d) for the standard, 

Bowen ratio, and residual eddy-covariance methods, respectively; this comparison was restricted to the 343 days when the 

Bowen ratio was not close to -1 and equation 12 did not have 

a denominator near zero. As indicated by Twine and others 

(2000), energy-budget-closure methods are preferable to the 

standard eddy-covariance method. The discrepancy in estimated ET between the Bowen ratio and the residual energybudget methods averaged 7 percent in 2006 with the Bowen 

ratio variant producing consistently lower ET estimates than 

the residual variant. The residual variant was selected in this 

study as the final method to quantify ET and will be used from 

here on, primarily because of the loss of data continuity in 

the Bowen ratio method associated with the suspected failure 

of the hygrometer during June–October 2005. However, the 

7 percent overestimation of ET by the residual method relative 

to the Bowen ratio method can serve as an estimate of possible 

bias or uncertainty in estimated ET related to the method of 

energy-budget closure.

Weekly, monthly, and 12-month totals of measured 

rainfall and ET estimated with the residual energy-budget 

variant of the eddy-covariance method are summarized in 

tables 2 and 3. Annual ET was a remarkably consistent fraction of annual precipitation (0.62 and 0.58 in 2005 and 2006, 

respectively) and of net radiation (0.62 in 2005 and 2006) as 

shown in table 4. An examination of long-term (1902–2011) 

precipitation data at the nearby National Weather Service 

Indian Mills weather station indicates that the study period 

was slightly wetter than mean annual total of 1,173 mm; 

annual precipitation totals at Indian Mills were 1,325 and 

1,396 mm for 2005 and 2006, respectively. The Indian Mills 

precipitation totals are within 30 mm (about 2 percent) of the 

precipitation measured at the study site during 2005 and 2006 

(table 4). Streamflow measurements during 2005–06 indicate 

average conditions; mean annual streamflow measured at 

USGS streamgaging station 01466500 (fig. 1) during 2005–06 

was 0.0593 cubic meters per second (m3/s), which is nearly 

identical to the long-term mean annual flow of 0.0592 m3/s 

for the 1954–2011 period of record. Streamflow, water-table 

altitude, and soil moisture all fluctuated with similar responses 

to precipitation and no precipitation. Soil moisture and watertable altitude were highly correlated (r2

=0.91). Minimum and 

maximum ET occurred during December to February and 

July, respectively (table 3). Twelve-month ET totals were in 

a relatively narrow range (786 to 821 mm) over the period 

of record compared to the range in 12-month rainfall totals 

(1,124 to 1,452 mm). A first-order data analysis consisting of 

linear regressions between several environmental variables 

(incoming solar radiation, air temperature, relative humidity, 

soil moisture, and net radiation) indicated that net radiation 

(r2 = 0.72) and air temperature (r2 = 0.73) were the dominant 

explanatory variables for daily ET. Cross correlation was 

noted between net radiation and air temperature (r2 = 0.41), 

and cross correlations are expected between these variables 

and forest phenological changes, precluding a unique determination of the role of each variable in determining ET. 

Variations in the evaporative fraction (ratio of latent heat flux 

to net radiation) indicate that air temperature is the strongest 

explanatory variable in the partitioning of available energy 

for ET (fig. 10A). The evaporative fraction was seemingly 

unaffected by decreased soil moisture during the April to 

September 2005 and the July to August 2006 dry periods, 

Figure 6. Mean diurnal pattern of energy fluxes at the wetland 

site in the Pinelands area, New Jersey, 2005–06.

Latent heat flux 

EXPLANATION

Sensible heat flux 

Net radiation 

-100 

0 

100 

200 

300 

400 

500 

0 600 1200 1800 2400 

Mean energy fluxes,

in watts per square meter

Hour of day 

Figure 7. Relative frequency of measured wind direction at the 

wetland site in the Pinelands area, New Jersey, 2005–06.

0 

0.05 

0.1 

0.15 

0.2 

0.25 

0 45 90 135 180 225 270 315 360 

Frequency 

Wind direction, degrees from north 
Results of Evapotranspiration Measurement and Simulation 15

Figure 8. Mean weekly values of net radiation, turbulent fluxes, and wind speed at the wetland site in the Pinelands area, New Jersey, 

November 2004–February 2007.

Sum of latent heat flux (λE) and 

sensible heat flux (H) 

Net radiation (Rn) 

Wind speed

EXPLANATION

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

4.5 

0 

50 

100 

150 

200 

250 

Mean weekly turbulent flux or net radiation, in watts per square meter

Wind speed, in meters per second

N D

2004 2005

J F M A M J J A S O N D J F M A M J J A S O N D J F

2005 2006 2006 2007

Figure 9. Daily evapotranspiration measured using the standard eddy-covariance method, the Bowen ratio method, and the residual 

energy-budget variant method, at the wetland site in the Pinelands area, New Jersey, November 2004–February 2007.

Evapotranspiration, standard method

EXPLANATION

Evapotranspiration, residual method

Evapotranspiration, Bowen ratio method

-1 

0 

1 

2 

3 

4 

5 

6 

7 

Evapotranspiration, in millimeters per day

N D

2004 2005

J F M A M J J A S O N D J F M A M J J A S O N D J F

2005 2006 2006 2007
16 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

First day 

of week

Rainfall 

(mm)

Evapotranspiration 

(mm)

11/10/2004 37 4

11/17/2004 3 4

11/24/2004 39 3

12/1/2004 33 2

12/8/2004 19 2

12/15/2004 2 0

12/22/2004 26 0

12/29/2004 2 5

1/5/2005 38 2

1/12/2005 31 0

1/19/2005 6 2

1/26/2005 11 1

2/2/2005 9 6

2/9/2005 30 5

2/16/2005 14 3

2/23/2005 21 5

3/2/2005 14 6

3/9/2005 2 6

3/16/2005 3 6

3/23/2005 64 5

3/30/2005 44 11

4/6/2005 35 17

4/13/2005 0 17

4/20/2005 10 15

4/27/2005 30 18

5/4/2005 5 17

5/11/2005 0 23

5/18/2005 43 18

5/25/2005 17 25

6/1/2005 34 27

6/8/2005 0 35

6/15/2005 0 32

6/22/2005 51 33

6/29/2005 53 31

7/6/2005 31 31

7/13/2005 47 27

7/20/2005 1 42

7/27/2005 7 34

8/3/2005 29 30

8/10/2005 16 33

8/17/2005 1 31

8/24/2005 1 26

First day 

of week

Rainfall 

(mm)

Evapotranspiration 

(mm)

8/31/2005 0 25

9/7/2005 0 24

9/14/2005 8 21

9/21/2005 2 20

9/28/2005 3 17

10/5/2005 92 10

10/12/2005 135 13

10/19/2005 68 8

10/26/2005 1 10

11/2/2005 0 10

11/9/2005 6 7

11/16/2005 70 4

11/23/2005 26 3

11/30/2005 34 2

12/7/2005 17 2

12/14/2005 27 0

12/21/2005 16 3

12/28/2005 67 3

1/4/2006 1 4

1/11/2006 31 6

1/18/2006 52 6

1/25/2006 6 5

2/1/2006 17 4

2/8/2006 14 4

2/15/2006 1 6

2/22/2006 2 0

3/1/2006 7 1

3/8/2006 4 10

3/15/2006 0 1

3/22/2006 2 4

3/29/2006 3 13

4/5/2006 24 11

4/12/2006 0 14

4/19/2006 46 15

4/26/2006 1 16

5/3/2006 0 17

5/10/2006 66 19

5/17/2006 9 23

5/24/2006 0 28

5/31/2006 43 22

6/7/2006 26 25

6/14/2006 0 32

Table 2. Weekly measured rainfall and evapotranspiration measured using the residual energy-budget variant of the eddy covariance 

method at the wetland site, Pinelands area, New Jersey, November 2004–February 2007. 

[mm, millimeter]
Results of Evapotranspiration Measurement and Simulation 17

First day 

of week

Rainfall 

(mm)

Evapotranspiration 

(mm)

6/21/2006 82 27

6/28/2006 28 41

7/5/2006 78 32

7/12/2006 3 37

7/19/2006 13 30

7/26/2006 26 40

8/2/2006 5 37

8/9/2006 0 30

8/16/2006 0 27

8/23/2006 90 19

8/30/2006 127 16

9/6/2006 0 25

9/13/2006 68 21

9/20/2006 15 20

9/27/2006 11 20

10/4/2006 26 16

10/11/2006 76 12

10/18/2006 15 9

10/25/2006 40 8

11/1/2006 5 5

11/8/2006 117 6

11/15/2006 11 6

11/22/2006 44 7

11/29/2006 5 2

12/6/2006 0 4

12/13/2006 4 5

12/20/2006 44 4

12/27/2006 39 3

1/3/2007 51 7

1/10/2007 3 4

1/17/2007 7 0

1/24/2007 3 3

1/31/2007 5 0

2/7/2007 0 0

2/14/2007 34 3

Table 3. Monthly and 12-month measured rainfall and 

evapotranspiration measured using the residual energy-budget 

variant of the eddy-covariance method at the wetland site, 

Pinelands area, New Jersey, December 2004–January 2007. 

[mm, millimeter; -, no data]

YearMonth

Monthly 

measured 

evapotranspiration 

(mm)

12-month 

moving sum 

evapotranspiration 

(mm)

Monthly 

measured 

rainfall 

(mm)

12-month 

moving sum 

rainfall 

(mm)

04-Dec 7 - 79 -

05-Jan 7 - 88 -

05-Feb 18 - 60 -

05-Mar 27 - 97 -

05-Apr 66 - 111 -

05-May 94 - 73 -

05-June 133 - 115 -

05-July 148 - 108 -

05-Aug 134 - 48 -

05-Sep 94 - 13 -

05-Oct 49 - 296 -

05-Nov 27 804 120 1,208

05-Dec 8 805 96 1,225

06-Jan 22 821 136 1,273

06-Feb 14 816 33 1,245

06-Mar 24 814 13 1,161

06-Apr 58 806 74 1,124

06-May 94 807 76 1,127

06-June 119 794 171 1,183

06-July 157 802 125 1,201

06-Aug 124 792 99 1,252

06-Sep 88 786 213 1,452

06-Oct 55 792 163 1,319

06-Nov 26 790 176 1,375

06-Dec 15 797 53 1,332

07-Jan 14 789 104 1,299

Table 2. Weekly measured rainfall and evapotranspiration 

measured using the residual energy-budget variant of the eddy 

covariance method at the wetland site, Pinelands area, New 

Jersey, November 2004–February 2007.—Continued 

[mm, millimeter]
18 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

until soil moisture fell below a critical threshold of about 0.15, 

and evaporative fraction decreased. When rains ended the dry 

period and soil moisture rose above this threshold again, the 

evaporative fraction recovered (fig. 10B). A similar drop in 

evaporative fraction during a dry period in early July 2004 

was observed at a nearby upland oak-pine site and attributed to 

apparent stomatal closure (Kenneth Clark, U.S. Forest Service, 

written commun., 2010). Schafer (2011) measured a reduction in sap-flux scaled canopy conductance at the upland site 

during drought conditions in 2006. The observed decrease in 

the evaporative fraction during the extreme dry periods is an 

important indication that lower water availability can result in 

lower rates of ET.

Comparison of Measured Evapotranspiration at 

Wetland and Upland Sites

Basin-scale hydrologic analysis requires estimates of ET 

over large areas, and therefore, an accounting of variability in 

ET rates across the landscape is needed. Previous investigations have indicated a substantial difference in ET between 

wetlands and uplands in the Pinelands area. Plot-scale studies 

using lysimeters concluded that ET from wetland areas in the 

Pinelands is expected to be greater than ET from upland areas 

because wetland soils are wetter and water is more readily 

available for ET (Ballard and Buell, 1975; Ballard, 1979). 

Evaluation of this difference over larger areas is possible by 

comparing ET measurements collected at the wetland station 

with those collected at three nearby upland stations operated 

by the U.S. Forest Service (USFS). The locations of evapotranspiration measurement stations for the wetland stand and 

the three upland USFS stands are shown in figure 11. The 

Table 4. Summary of selected characteristics measured or simulated annually and dates of spring and fall freezes at the wetland 

site, Pinelands area, New Jersey, 2005–06.

Characteristic Year 2005 Year 2006

Measured evapotranspiration at McDonalds Branch (AETm), in millimeters 805 797

Priestley-Taylor potential evapotranspiration (PET), in millimeters 1,022 1,013

Hargreaves reference evapotranspiration (RET), in millimeters 986 1,008

North American Regional Reanalysis (NARR) actual evapotranspiration

(AETNARR), in millimeters 831 930

Rainfall (R) at McDonalds Branch, in millimeters 1,225 1,332

Snow (S) at Indian Mills, in millimeters 749 343

Estimated precipitation (P = R + 0.1S), in millimeters 1,300 1,366

Measured latent heat flux, in watts per square meter 63 62

Incoming solar radiation, in watts per square meter 159 163

Net radiation (Rn), in watts per square meter 101 100

Average daily minimum temperature, in °C 6.64 7.62

Average daily maximum temperature, in °C 16.75 17.83

Last spring freeze 17-April 24-March

First fall freeze 11-November 27-October

Priestley-Taylor vegetation factor (AETm /PET) 0.79 0.82

Hargreaves vegetation factor (AETm /RET) 0.79 0.79

Measured to NARR evapotranspiration ratio (AETm / AETNARR) 0.97 0.86

Evapotranspiration to precipitation ratio (AETm /P) 0.62 0.58

Evaporative fraction (ratio of mean latent heat flux to mean net radiation) 0.62 0.62
Results of Evapotranspiration Measurement and Simulation 19

Figure 10. Relation of A, weekly mean air temperature and B, weekly mean soil moisture to evaporative fraction, at a wetland site in 

the Pinelands area, New Jersey, November 2004–February 2007.

-0.2 

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

1.4 

1.6 

Evaporative fraction (latent heat flux/net radiation) 

-10 

-5 

0 

5 

10 

15 

20 

25 

30 

Weekly mean air temperature, in degrees Celsius 

-0.2 

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

1.4 

1.6 

Weekly mean soil moisture or evaporative fraction 

N D

2004 2005

J F M A M J J A S O N D J F M A M J J A S O N D J F

2005 2006 2006 2007

N D

2004 2005

J F M A M J J A S O N D J F M A M J J A S O N D J F

2005 2006 2006 2007

Air temperature 

EXPLANATION

A

B

EXPLANATION

Evaporative 

fraction 

Soil moisture 

Evaporative fraction 

(latent heat flux/net radiation) 
20 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

Figure 11. Location of the wetland and upland evapotranspiration measurement stations, Pinelands area, New Jersey. 

(USGS, U.S. Geological Survey; USFS, U.S. Forest Service)

WOODLAND TOWNSHIP

PEMBERTON TOWNSHIP

MANCHESTER TOWNSHIP

TABERNACLE TWP

LACEY TOWNSHIP

PLUMSTED TOWNSHIP NEW HANOVER TOWNSHIP

SOUTHAMPTON TOWNSHIP

BARNEGAT

TOWNSHIP

JACKSON TOWNSHIP

74°40' 74°35' 74°30' 74°25'

40°

39°55'

39°50'

0 1 2 MILES

0 1 2 KILOMETERS

Base from U.S. Geological Survey 

digital line graph files, 1:24,000, 

Universal Transverse Mercator 

projection, Zone 18, NAD83

Area shown

Pinelands 

Area

USGS McDonalds Branch 

Wetlands Station

USFS Fort Dix 

Mixed Oak/Pine Upland Station

USFS Silas Little

 Oak Upland Station

USFS Cedar Bridge 

Pine Upland Station

NEW JERSEY

Lake

Evapotranspiration station

EXPLANATION

Stream

Township boundary

McDonalds Branch watershed boundary
Results of Evapotranspiration Measurement and Simulation 21

three upland stations are located within 14 km of the wetland 

station, and fluxes were monitored using eddy-covariance 

techniques similar to those used at the wetland station. The 

specific ET measurement methods used at the three upland 

sites are described by Clark and others (2010, 2011, 2012). 

The three upland forest stands are dominated by oak, pine, 

and mixed oak and pine, respectively. ET was measured at the 

upland stations during 2005–09, which included periods of 

disturbance by fire and insect defoliation that had a significant 

effect in reducing ET. Annual precipitation and ET measured 

at the three upland stations and the wetland station are listed 

in table 5. Clark and others (2012) showed that, when averaged across all upland stations for all years of measurement 

(2005–09), annual ET was 606 mm/yr. The average annual ET 

measured at the wetland station during 2005–06 (801 mm/yr)

is about 32 percent higher than this upland average. When ET 

at the upland stations is averaged over years without disturbance (685 mm/yr), the average annual wetland ET is about 

17 percent higher. As a percentage of precipitation, ET at the 

wetland station was higher than that of the undisturbed oak 

and mixed oak/pine upland stations in 2005 and was similar to 

that of the undisturbed oak and pine upland stations in 2006. 

Several factors are likely contributing to differences in 

ET rates among different stations and among different years. 

These factors include water availability, dominant plant species, and leaf area. Water availability varies year to year with 

precipitation and evapotranspiration, and it also varies site to 

site with depth to the water table and other site conditions. 

Water availability is less variable in wetlands because the 

water table is close to or at land surface, whereas in uplands 

the water table is deeper. Also, upland soils are more susceptible to drought conditions. Phenological and physiological differences among plant species result in different seasonal patterns of ET and different responses to stress and disturbance 

in the Pinelands, as described by Clark and others (2012). 

Leaf area is a function of several site characteristics, including 

plant species, successional stage, and response to disturbance 

(including by fire and defoliation). The results presented in 

table 5 and figure 12 indicate that interannual variability in 

wetland ET may be less than that of upland ET because the 

Table 5. Annual evapotranspiration at the wetland site and three upland forest sites, Pinelands area, New Jersey, 2005–09. 

[Data for upland sites are from Clark and others (2012). mm, millimeters; ET, evapotranspiration]

Site Year Disturbance

(if any)

Annual 

precipitation 

(mm)

Annual ET 

(mm)

Annual ET 

as a percentage 

of precipitation

Wetland (this study) 2005 1,225 805 66

2006 1,332 797 60

Oak upland 2005 1,092 616 56

2006 1,108 677 61

2007 Complete defoliation 934 442 47

2008 Partial defoliation 936 637 68

2009 1,173 699 60

Mixed upland 2005 1,184 607 51

2006 Burn and defoliation 1,163 452 39

2007 Partial defoliation 1,135 419 37

Pine upland 2006 1,230 757 62

2007 Partial defoliation 1,052 593 56

2008 Prescribed burn 1,163 611 54

2009 1,382 759 55

Figure 12. Annual evapotranspiration measured at the wetland, 

pine upland, oak upland, and mixed oak/pine upland sites in the 

Pinelands area, New Jersey, 2005–09.

Wetland

Pine upland

Oak upland

Mixed oak/pine upland

EXPLANATION 

0 

500

400

300

200

100

600

700 

800 

900 

2005 2006 2007 2008 2009 

Annual evapotranspiration, in millimeters

Year
22 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

wetland sites are less susceptible to periodic drought conditions, disturbance by fire (Foreman and Boerner, 1981), and 

insect defoliation (Houston and Valentine, 1985; Whitmire and 

Tobin, 2006). Higher ET in wetlands is probably attributable 

to greater water availability and differences in canopy plant 

species and leaf area. 

A useful approach for validating ET measurements is to 

use them in a watershed-scale analysis of the water budget, 

along with other hydrologic measurements. A balanced water 

budget is an indication that the various measurements are 

internally consistent. Walker and others (2011) describe the 

water balance in the McDonalds Branch basin for 2005–06. 

The analysis includes an estimate of basin-wide, spatially 

weighted ET that was based on the respective ET rates for the 

wetland and upland sites described previously. The analysis included a land-surface water budget and a groundwater 

budget. Both budgets were used to estimate aquifer recharge 

independently as a residual. The comparability of the independent recharge estimates for the McDonalds Branch basin 

indicate that the ET measurements presented in this report are 

reasonably consistent with other hydrologic measurements. 

Utility of Models to Simulate Evapotranspiration

The utility of three models—Priestley-Taylor, Hargreaves, and North American Regional Reanalysis (NARR)—

were evaluated through a comparison of model-simulated 

ET with ET measured at the wetland site using the residual 

energy-budget variant method. Models that successfully replicated measured ET offer the potential to transfer the results 

of the site measurements to other locations or to other time 

periods outside the study period.

Priestley-Taylor Equation

The environmental variables considered as possible predictors of modified Priestley-Taylor a included soil moisture, 

solar radiation, air temperature, vapor-pressure deficit, and 

wind speed. Exploratory data analysis revealed that the greatest explanatory value for the Priestley-Taylor a was related 

to air temperature, followed by solar radiation, soil moisture, 

wind speed, and finally vapor-pressure deficit. A Priestley-Taylor a function composed of a second order polynomial of air 

temperature (fig. 13) was optimized to successfully reproduce 

daily values of latent heat flux measured with the energybudget residual variant (r2

 = 0.90; standard error = 0.65 mm or 

19 W/m2; and bias = 0; table 6). 

Comparison of modeled latent heat flux residuals with 

possible explanatory variables other than air temperature 

revealed little relation, supporting the use of the simple 

temperature-dependent Priestley-Taylor a function. This 

function shows an increase in a with air temperature, with 

the rate of increase decreasing with increasing air temperature. This relation for a probably represents a combination 

of direct plant stomatal response to air temperature but also 

a response to phenological changes in the forest plant species that are associated with seasonal temperature changes. A 

comparison of residuals with vector-averaged daily mean wind 

direction (fig. 14) provides a means of evaluating the effects 

of non-homogeneous surface covers (wetlands and uplands) 

within the source area of the latent heat flux measurement. No 

obvious relation was apparent between ET residuals and wind 

direction that was consistent with the patterns of wetlands and 

uplands in the source area, indicating that wind direction, a 

surrogate for source areas with different vegetation, was not 

responsible for variability in ET not already accounted for by 

the temperature relation.

Figure 15 shows a good relation between daily measured 

(energy-budget residual variant) and modified PriestleyTaylor simulated latent heat flux, without noticeable temporal 

bias. The simulated values of latent heat flux generally are 

less erratic in the winter than are the measured values; this 

phenomenon may be more a consequence of violation of one 

-0.2 

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

1.4 

-20 -15 -10 -5 0 5 10 15 20 25 30 

Priestley-Taylor alpha (α)

Mean daily air temperature, in degrees Celsius 

 = -0.00071 Ta2 α + 0.0447 Ta + 0.474 

Figure 13. Optimized relation between Priestley-Taylor α and 

mean daily air temperature for the wetland site in the Pinelands 

area, New Jersey.

Figure 14. Relation of residuals using the modified PriestleyTaylor model to daily mean wind direction, wetland site, 

Pinelands area, New Jersey, 2004–07. Residual is simulated 

evapotranspiration minus measured evapotranspiration: The 

two wind arcs most representative of uplands are 350 degrees 

clockwise to 20 degrees and 90 degrees clockwise to 120 degrees. 

The red line is mean residual for a given wind direction.

-3 

-2 

-1 

0 

1 

2 

3 

Modified Priestley-Taylor

daily evapotranspiration

model residuals,

in millimeters 

0 45 90 135 180 225 270 315 360 

Daily mean wind direction,

in degrees clockwise from north 
Results of Evapotranspiration Measurement and Simulation 23

Table 6. Error statistics relating evapotranspiration measured at the wetland site to evapotranspiration simulated using alternative 

models, Pinelands area, New Jersey. 

[mm, millimeter]

Alternative

model

Coefficient 

of determination (r2

) with 

measured actual 

evapotranspiration

Root mean 

square error

 (mm/day)

Bias relative 

to measured 

evapotranspiration 

(mm/year)

Priestley-Taylor potential evapotranspiration (PET) 0.85 1.08 +216

Hargreaves reference evapotranspiration (RET) 0.87 0.85 +196

Modified Priestley-Taylor actual evapotranspiration (AETPT) 0.9 0.65 0

Modified Hargreaves actual evapotranspiration (AETH)

McDonalds Branch wetland site 0.89 0.61 0

Indian Mills weather station 0.84 0.73 0

Moorestown weather station 0.83 0.76 0

North American Regional Reanalysis (NARR) actual 

evapotranspiration (AETNARR) 0.6 1.21 +80

EXPLANATION

Measured daily 

latent heat flux 

Modified Priestly-Taylorsimulated daily latent 

heat flux 

-50 

-5 

50 

100 

150 

200 

250 

Daaily latent heat flux, in watts per square meter

N D J F M A M J J A S O N D J F M A M J J A S O N D J F

2004 2005 2005 2006 2006 2007

Figure 15. Measured and modified Priestly-Taylor-simulated daily latent heat flux for the wetland site, Pinelands area, New Jersey, 

2005–06.
24 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

of the assumptions of latent heat flux measurement—negligible changes in canopy heat storage during rapid winter-time 

temperature changes— than an error in the model. 

The modified Priestley-Taylor model developed in this 

study is subject to several qualifications. The form of the equation developed for a was empirical rather than physics based 

and was simply designed to reproduce measured values of ET 

as accurately as possible. The covariance between environmental variables confounds a unique parameterization. The 

model was developed for a limited range of environmental 

conditions, and therefore, extrapolation of the model to conditions not encountered in this study are best done with caution. 

As noted earlier, deficit soil moisture appeared to play a role 

in restricting ET during particularly dry periods, but this effect 

was not considerable enough to be discerned clearly in the 

identification of the appropriate Priestley-Taylor a function. 

Annual measured ET at the wetland site was a relatively 

constant fraction of potential ET as estimated by the standard 

Priestley-Taylor method with an a of 1.26 (0.79 and 0.82 in 

2005 and 2006, respectively; table 4). However, potential ET 

was highly correlated with measured ET (r2 = 0.85), indicating 

that a constant vegetation factor applied to potential ET also 

can replicate actual ET rather well at this wetland site, where 

moisture availability was not often a constraint.

Hargreaves Equation

The modified Hargreaves equation performed remarkably well at reproducing measured values of daily ET 

(table 6; fig 16.) with relatively low error and little temporal 

bias. Additionally, measurements of daily incoming solar 

radiation were also well replicated (r2 = 0.70; coefficient of 

variation = 31 percent; and bias = 3 percent) using the preferred value of KRS = 0.16 for inland areas. The values of a and 

b identified by the regression analysis to most closely replicate 

measured daily ET for each source of temperature data are 

shown in table 7. As might be expected, use of temperature 

data from the ET station at the McDonalds Branch site provides better explanatory values within the modified Hargreaves equation for ET (r2

 = 0.89; standard error = 0.61 mm/d; 

and bias = 0 mm/year) than does use of remote temperature 

data from either of the National Weather Service stations 

(Indian Mills and Moorestown; table 6). However, Hargreaves models adjusted for temperature data from either of the 

remote temperature stations can be considered successful at 

Figure 16. Daily measured and modified Hargreaves-simulated evapotranspiration for the wetland site, Pinelands area, New Jersey, 

2005–06.

EXPLANATION

Measured evapotranspiration 

Modified Hargreaves-simulated

evapotranspiration

N D J F M A M J J A S O N D J F M A M J J A S O N D 

-1 

0 

1 

2 

3 

4 

5 

8 

7 

6 

Daily evapotranspiration, in millimeters

2004 2005 2005 2006

Table 7. Parameters for the standard Hargreaves reference 

evapotranspiration equation and optimized parameters for the 

modified Hargreaves actual evapotranspiration equation for 

alternative sources of daily temperature data.

[a, b, KRS, and aKRS are empirical coefficients]

Parameter Standard 

Hargreaves

McDonalds 

Branch 

wetland 

site

Moorestown

weather 

station

Indian 

Mills

weather 

station

a 0.0148 0.0198 0.0167 0.0169

b 17.8 4.1 3.1 3.2

KRS (inland) 0.16 0.16 0.16 0.16

aKRS 0.0023 0.0032 0.0027 0.0027
Results of Evapotranspiration Measurement and Simulation 25

ET estimation, although the models performed slightly better 

using values from the closer Indian Mills station (r2 = 0.84; 

standard error = 0.73 mm/d; and bias = 0 mm/year) than using 

values from the more distant Moorestown station (r2 = 0.83; 

standard error = 0.76 mm/d; and bias = 0 mm/year). The lower 

values (3.1 to 4.1) of the temperature offset parameter b in the 

optimized forms of the modified Hargreaves actual ET equation relative to the b value of 17.8 in the standard Hargreaves 

reference evapotranspiration equation imply that actual ET 

shows greater sensitivity to temperature at this site than does 

reference ET. Annual ET was a constant fraction of reference 

ET, as estimated by the standard Hargreaves method (0.79 in 

2005 and 2006; table 4). However, daily reference ET was 

highly correlated (r2 = 0.87) with measured ET, indicating 

that a constant vegetation factor applied to reference ET can 

replicate actual ET at the wetland site rather well. Again, no 

obvious relation was apparent between ET residuals and wind 

direction that was consistent with the patterns of wetlands and 

uplands in the source area (fig. 17).

of the NARR product (32-km grid) is intended for a more 

regional estimate of ET than the relatively small-scale measurement described in the present study, and this discrepancy 

in scale can be expected to account for some of the difference 

between the two ET estimates. Annual measured ET totals as 

a fraction of NARR ET were 0.97 and 0.86 in 2005 and 2006, 

respectively (table 4).

Comparison and Limitations of 

Evapotranspiration Models

Of the models investigated in the present study, the modified Hargreaves can be considered the best at replicating the 

measured daily ET values. The error statistics of the modified 

Hargreaves model were comparable to those of the modified 

Priestley-Taylor model and superior to those of the North 

American Regional Reanalysis product. Additionally, the data 

requirements of the modified Hargreaves model (minimum 

and maximum daily air temperature) are more easily met than 

those of the modified Priestley-Taylor model, which requires 

both mean daily air temperature and the more difficult to 

obtain net radiation. The data requirements of the modified 

Hargreaves equation are ideal for retrospective investigations 

of ET because they are met by standard National Weather 

Service measurements that extend back over a century in parts 

of the Nation, including at Moorestown and Indian Mills, New 

Jersey. Likewise, in the absence of continuing eddy-covariance measurements, historical or real-time estimates of ET in 

the study area can be obtained through use of air-temperature 

data (available from the National Climatic Data Center [http://

www.ncdc.noaa.gov/oa/ncdc.html] or the New Jersey Weather 

and Climate Network [http://climate.rutgers.edu/njwxnet], for 

example) and the modified Hargreaves equation. Sumner and 

Nicholson (2010) present historical and future probabilistic 

estimates of ET at the wetland site using a Hargreaves-based 

approach.

The ET models described in this report are best applied 

to estimate ET at locations or during time periods for which 

the environmental conditions are similar to those prevailing during the period of record for which these models were 

calibrated. Use of the models outside of these environmental 

conditions introduces additional uncertainty in the evapotranspiration estimates. For example, under more extreme dry 

periods than those that occurred during the study period, ET 

may be overestimated by models that do not explicitly account 

for plant moisture stress.

Figure 17. Relation of residuals using the modified Hargreaves 

daily evapotranspiration model to daily mean wind direction, 

wetland site, Pinelands area, New Jersey, 2004–07. Residual is 

simulated evapotranspiration minus measured evapotranspiration: 

The two wind arcs most representative of uplands are 350 

degrees clockwise to 20 degrees and 90 degrees clockwise to 120 

degrees. The blue line is mean residual for a given wind direction.

-3.0 

-2.0 

-2.5 

-1.0 

-1.5 

-0.5

0 

1.0 

1.5 

0.5 

2.0 

2.5 

Modified Hargreaves

daily evapotranspiration

model residuals,

in millimeters 

0 45 90 135 180 225 270 315 360 

Daily mean wind direction,

in degrees clockwise from north 

North American Regional Reanalysis (NARR)

The North American Regional Reanalysis performed 

relatively poorly (r2 = 0.60; standard error = 1.21 mm; and 

bias = 80 mm/year) at replicating measured values of daily ET 

relative to the other models considered (table 6). In particular, 

NARR showed substantial under-prediction of measured ET 

during the dry periods (fig. 18) that occurred during August–

October 2005 and in August 2006 and slight over-prediction 

during wetter periods. Apparently, the NARR algorithms 

restrict ET as a result of perceived plant moisture stress during 

dry periods to a degree that is excessive for the largely wetland 

environment of the study area. The large spatial resolution 
26 Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands

Summary

Evapotranspiration (ET) was monitored above a wetland forest canopy in the New Jersey Pinelands during 

November 10, 2004–February 20, 2007. Meteorological, 

radiation, and eddy-covariance flux measurements were made 

near the top of a 24.5-meter tower; soil moisture and watertable depth at the site also were monitored. An analysis of 

the eddy-covariance sensors’ source area and predominant 

wind directions indicated that the source of measured ET was 

primarily pitch pine/cedar wetlands.

Three methods were evaluated for their utility in estimating ET. The standard eddy-covariance method was used to 

measure the two turbulent-flux components of the plant-canopy energy budget: latent and sensible heat fluxes. Regression 

analysis of measured 30-minute turbulent flux and net radiation data was used to estimate missing values of 30-minute 

turbulent fluxes, which occurred mostly at night and accounted 

for only 5 percent of the total estimated ET. Two variants of 

the eddy-covariance method were used to adjust turbulent flux 

measurements for daily energy-budget closure; one variant 

preserves the Bowen ratio (Bowen ratio energy-budget variant), and the other preserves the measured sensible heat flux 

(residual energy-budget variant). Relations between ET and 

several environmental variables (incoming solar radiation, air 

temperature, relative humidity, soil moisture, and net radiation) were explored.

Suspected hygrometer failure during the early part of the 

measurement period resulted in unreliable ET measurements 

determined by using the standard eddy-covariance and Bowen 

ratio energy-budget variant methods. The residual energybudget variant was selected for use in estimating a time series 

of daily ET rates for the measurement period. The range of 

the 12-month ET totals, based on the residual energy-budget 

variant, is relatively narrow (786 to 821 millimeters (mm)) for 

the period of record compared to the range of the 12-month 

rainfall totals (1,124 to 1,452 mm). Minimum and maximum 

ET values were measured during December–February and 

Figure 18. Daily measured and modified North American Regional Reanalysis simulated evapotranspiration, and volumetric soil 

mositure for the wetland site, Pinelands area, 2005–06.

Measured evapotransporation

Soil moisture

Modified North American Regional 

Reanalysis simulated evapotranspiration

EXPLANATION

0.00 

0.10 

0.20 

0.30 

0.40 

0.50

-1 

0 

1 

2 

3 

4 

5 

6 

7 

8 

Daily evapotranspiration, in millimeters

Volumetric soil moisture (0 to 30 centimeters below surface),

in cubic centimeters of water per cubic centimeter

N D J F M A M J J A S O N D J F M A M J J A S O N D 

2004 2005 2005 2006

9 
References Cited 27

July, respectively. Net radiation (r2 = 0.72) and air temperature 

(r2 = 0.73) were the dominant explanatory variables for daily 

ET. Air temperature was the dominant control on evaporative 

fraction with relatively more radiant energy used for ET at 

higher temperatures. During extended dry periods, soil moisture was shown to limit available energy partitioning into ET. 

As volumetric soil moisture fell below a threshold of 0.15, the 

evaporative fraction decreased until rain broke the dry period 

and the evaporative fraction sharply recovered. This observation indicates that lower water availability can result in lower 

rates of ET at this wetland site.

Annual ET totals measured at the wetland site were 

compared with those measured at three nearby upland sites 

dominated by oak, pine, or mixed oak and pine. A previous 

investigation by the U.S. Forest Service determined that, when 

averaged across all upland sites for all years of measurement 

(2005–09), annual upland ET was 606 mm/yr. The average annual ET measured at the wetland site during 2005–06 

(801 mm/yr) is about 32 percent higher than the average of 

that at the upland sites. The average annual ET at the wetland 

site is about 17 percent higher than ET at the upland sites 

when averaged over years without disturbance at a particular 

stand. Factors contributing to differences in ET rates among 

different sites and among different years include water availability, dominant plant species, and leaf area. Interannual 

variability of wetlands ET may be less than that of uplands 

ET because the upland sites are more susceptible to periodic 

drought conditions, disturbance by fire, and insect defoliation.

Three ET models (Priestley-Taylor, modified Hargreaves, 

and North American Regional Reanalysis) were evaluated 

to determine their utility in predicting ET at the wetland 

site using data that may be more readily available in other 

areas and for other time periods. Of the three models, the 

modified Hargreaves may be of the most practical use, as it 

replicated the measured daily ET values reasonably well, and 

data requirements were relatively easily met. The ET models described in this report are best applied to estimate ET at 

locations or during time periods for which the environmental 

conditions are similar to those prevailing during the period of 

record for which these models were calibrated. Precipitation 

during the study period at the nearby National Weather Service 

Indian Mills weather station was slightly higher than the longterm (1902–2011) annual mean of 1,173 mm, with 1,325 and 

1,396 mm of precipitation in 2005 and 2006, respectively.

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Sumner and others—Measurement and Simulation of Evapotranspiration at a Wetland Site in the New Jersey Pinelands—Scientific Investigations Report 2012–5118