9/4/2015 INOVAGRI, Fortaleza, Brazil, Aug. 31, 2015 Evapotranspiration Estimation Incorporating FAO56 Methodology Richard G. Allen Professor of Water Resources Engineering Univ. Idaho – Kimberly, Idaho, USA Ayse Kilic Associate Professor University of Nebraska-Lincoln, USA Justin Huntington Associate Professor Desert Research Institute, Reno, NV, USA collaborators/acknowlegements – L.S. Pereira, J.L. Wright, W.O. Pruitt, M.E. Jensen, D. Raes, M. Smith
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9/4/2015 INOVAGRI, Fortaleza, Brazil, Aug. 31, 2015
Richard G. AllenProfessor of Water Resources EngineeringUniv. Idaho – Kimberly, Idaho, USAAyse KilicAssociate ProfessorUniversity of Nebraska-Lincoln, USAJustin HuntingtonAssociate ProfessorDesert Research Institute, Reno, NV, USA
collaborators/acknowlegements – L.S. Pereira, J.L. Wright, W.O. Pruitt, M.E. Jensen, D. Raes, M. Smith
Discussion Points• Brief Review of the Crop Coefficient
– Reference ET approach of FAO56
• Current Implementations
• Recent Applications
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9/4/2015 CIGR, Bari, Italy, Sept. 10, 2013
3/11 7/18 10/06
Daily ET
Ashton, Idaho, USA 1990 calendar year -- Potatoes
Evapotranspiration (ET) varies widely with •Time of Year •From Day to Day
Therefore, rigorous Equations and Models are needed
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Reference ET
FAO56 Reference ET:A Living Evaporation Index
)1(
)(273
)(408.0
2
2
uC
eeuT
CGRET
d
asn
n
ref
full Penman-Monteith
Standardized FAO56/ASCE Penman-Monteith
/
rr1
r)e(ecG)(R
ET
a
s
a
aspan
timeK
f (Solar Radiation) f (Temperature)f (Humidity)
Wind Speed
Cn andCd areconstants
50 s m-1
(daytime hourly)
70 s m-1
(24-hr)for grass
ASCE PM can be applied to clipped grass and to 0.5 m tall alfalfa
9/4/2015CIGR, Bari, Italy, Sept. 10, 2013
FAO and ASCEPenman-Monteithare traceable to theDavis, California and Kimberly, Idaho (USDA) Lysimeters
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-0.10
0.10
0.30
0.50
0.70
0.90
1.10
ET, m
m/h
our
0100 0300 0500 0700 0900 1100 1300 1500 1700 1900 2100 2300Time of Day
Etr Lys. 2 alfalfa
Kimberly Lysimeters - September 4,1990Data from Dr. J.L Wright ASCE Standardized Penman-
Monteith(alfalfa reference) at Kimberly, Idaho- hourly time step
-0.10
0.10
0.30
0.50
0.70
0.90
1.10
ET, m
m/h
our
0100 0300 0500 0700 0900 1100 1300 1500 1700 1900 2100 2300Time of Day
Etr Lys. 2 alfalfa
Kimberly Lysimeters -September 7, 1990
9/4/2015CIGR, Bari, Italy, Sept. 10, 2013
0
2
4
6
8
10
12
Evap
otra
nspi
ratio
n, m
m/d
ay
100 125 150 175 200 225 250 275 300Day of Year
Lysimeter ASCE P-M
Kimberly, Idaho 1969
Full cover alfalfa - Data from Dr. J.L. Wright
Good day-to-day correspondance with lysimeter
Daily Timestep
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Crop Coefficients
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Crop Coefficient = ET/ETref
Time of Season, days
Kc
Kc mid Kc end
Kc ini
0.2
0.4
0.6
0.8
1.0
1.2
0.0
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Crop Coefficient Curve Types
Kc
140150
160170
180190
200210
220230
240
Day of the Year
0.3
0.5
0.7
0.9
1.1
1.3
FAO
Wright (1981, 1982)
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Single or Dual Kc ???
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Kc measured by Lysimeter
Wet Soil Evaporation “Spikes”
(Ke)
Kc
130 150 170 190 210 230 2500.0
1.2
0
200
Day of the Year
Precipitation and Irrigation, mm
Sweet Corn-- Kimberly, Idaho, 1976
0.2
0.4
0.6
0.8
1.0
40
80
120
160
I
I
I
I I
I
I
P PP
I
I
data courtesy of Dr. J.L. Wright, USDA-ARS
“Single” Curveaveraging evaporation “Spikes”
each dot is one day
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The “Dual Kc” method SplitsSoil Evaporation from Transpiration
Basal Kc Curve(Kcb)
Wet Soil Evaporation “Spikes”
(Ke)
Kc
130 150 170 190 210 230 2500.0
0.2
0.4
0.6
0.8
1.0
1.2
0
40
80
120
160
200
Day of the Year
Precipitation and Irrigation, mm
Sweet Corn Kimberly, Idaho, 1976
I
I
I
I I
I
I
P PP
I
I
Evap.=18%
data courtesy of Dr. J.L. Wright, USDA-ARS
“Mean” Kc Curve Kc = KsKcb + Ke
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‘Dual’ Kc Procedure
K = K K + K
K = water stress (0 - 1)K = basal K (dry surface)K = evaporation coefficient
scbe
cbc s e
c
ETETref
=
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Evaporation Coefficient - Ke
De ~ 150 mmTEW = Total Evaporable Water
E = K ET s e ref
TEW ~ 10 to 35 mm
(Soil)
FAO-56 Simple Drying Function
Skin Evaporation(Allen, 2011)
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Three-Stage Enhancement (2005) to FAO-56 Ke model
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Skin Evaporation Enhancement (2011) to FAO-56 Ke model
FAO-56 Kemodel vs. Kimberly Lysimeter
– Bare Soil
Conclusion: Skin Enhancement is Important for Precip. Events < 10 mm. Model can be applied on daily or hourly timestep
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Why Apply the Dual Kc method for estimating water depletion?
• Advantages– Kc value varies with wetting frequency
– Kc estimates can be made during wintertime when process is only evaporation from soil
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Partial Surface Wetting/Drying
Es
Rs= evaporation
Partial Wetting of Surface
f = min(1 - f , f )wcew
wfcf cfewfef
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Some Example Applications of the FAO-56 Dual Kc Method in the United States
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Comparison of Aggregated Estimates against ET from Irrigation Scheme-wide Water Balance
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Imperial Irrigation District: Aggregated FAO-56 vs. ET by Water Balance ~ 200,000 irrigated ha
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Water Balance of the Imperial ProjectET = Inflow - Surface Outflow
+ Precipitation- Δ Soil Water- Deep Percolation
• accuracy of annual ET from the Imperial Valley water balance is +/-5% (95% C.I.)
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0
50,000
100,000
150,000
200,000
250,000
300,000
350,000Ac
re-F
eet p
er m
onth
Jan. Feb Mar. Apr. May June July Aug Sept.Oct. Nov. Dec.KcETo (Pot.) ETcWB ETo
Total Project Evapotranspiration1990
(AF Values arescaled)
-- Used FAO-56 Grass Reference ETo and Linear Kcb + Ke
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0
50,000
100,000
150,000
200,000
250,000
300,000
350,000Ac
re-F
eet p
er m
onth
Jan. Feb Mar. Apr. May June July Aug Sept.Oct. Nov. Dec.KcETo (Pot.) ETcWB ETo
Total Project Evapotranspiration1991
(AF Values arescaled)
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0
50,000
100,000
150,000
200,000
250,000
300,000
350,000Ac
re-F
eet p
er m
onth
Jan. Feb Mar. Apr. May June July Aug Sept.Oct. Nov. Dec.KcETo (Pot.) ETcWB ETo
Total Project Evapotranspiration1996
(AF Values arescaled)
1990-96 Ratio =1.07SEE for monthly = +/- 16%
ET-Idaho – ET and Irrigation Water Requirements for the State of Idaho -- FAO-56 Dual Kc Basis
Operated 365 days/year
120 locations
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Cumulative Growing Degree Days used to Estimate Kc Development. Using CGDD creates some similarity in the Kcb shape
Comparison with Eddy Covariance —Illustrate Low Sensitivity to Kcb mid
9/4/2015 INOVAGRI, Fortaleza, Brazil, Aug. 31, 2015
9/4/2015 INOVAGRI, Fortaleza, Brazil, Aug. 31, 2015
FAO-56 Dual Kc Example Spreadsheet-- Annex 8 of FAO-56 -- available at:http://extension.uidaho.edu/kimberly/2013/04/guidelines-for-computing-crop-water-requirements/
Modified here to use Alfalfa Reference
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Kcb mid = 1.00
Kcb mid = 1.05
Irrigated Field – Impact of Kc mid
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Kcb mid = 1.15
Kcb mid = 0.95
Irrigated Field – Impact of Kc mid
Conclusion: It is difficult to determine correct separation in T and E and correct Kc mid using measured ET only
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Apples, Cherries, Pears - fc = 0.5 (1) Peaches - fc = 0.8 (4)
Peaches - fc = 0.6 (3)
Citrus - fc = 0.7 (8) Mango - fc = 0.7 (10)
Olive - fc = 0.6 (11)
Grapes - table - fc = 0.65 (14)
Grapes - table - fc = 0.45 (1), Almonds - fc = 0.5 (1)
Peaches - fc = 0.45 (5)
Peaches - fc = 0.29 (6) Citrus - fc = 0.38 (9)
Olive - fc = 0.4 (12)
Olive - fc = 0.25 (13)
Olive - fc = 0.1 (13)
Palms - fc = 0.7 (1)
Grapes - wine - fc = 0.5 (1)
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4Kc measured
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Kc fr
om K
d
Orchard Kc’s from literature
1 FAO56 (Allen et al., 1998)2 Girona et al. (2003)3 Girona et al. (2005)4 Johnson, et al. (2006)-microspray, 5 Ayars 6 Paco et al. (2006)7 FAO56 (Allen et al., 1998)8 Consoli et al (2005)9 Alba et al. (2006)10 de Alzevedo et al. (2003)11 Pastor- Orgaz (1994)12 Villalobos (2000) (fc= .4)13 Testi et al (2004)
Good agreement between Predicted and Measured Kc
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Conclusions on Kc• The Kc ETr method is robust and
transferable• The Kc incorporates a number of factors
affecting ET• Kc curves can be tailored based on
– weather data– fraction of ground cover
• The dual Kc provides good estimation of impacts of evaporation from soil
Thank You
9/4/2015 CIGR, Bari, Italy, Sept. 10, 2013
9/4/2015 CIGR, Bari, Italy, Sept. 10, 2013
Spatial ETref from Gridded Weather Data Sets• large gridded weather bases include:
– the European Centre for Medium-Range Weather Forecasts (ECMWF) (deBruin et al. 2012 has ETo)
– North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS).
– ECMWF and GLDAS data sets are produced for the whole globe at 1 degree spatial resolution (100 km) or finer, and for specific regions at 12 km resolution.
– Time steps range from hourly to 24-h for calculation of reference ET.
– The data may be “Arid” and needs “conditioning”• We need good spatial Precipitation Data
9/4/2015INOVAGRI, Fortaleza, Brazil, Aug. 31, 2015