Evapotranspiration Estimation Incorporating FAO56...

9/4/2015 INOVAGRI, Fortaleza, Brazil, Aug. 31, 2015

Evapotranspiration Estimation Incorporating FAO56 Methodology

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


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


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


-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


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


Crop Coefficients


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


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)


Single or Dual Kc ???

9/4/2015

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


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


‘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

=


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)


Three-Stage Enhancement (2005) to FAO-56 Ke model


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


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

9/4/2015 ASABE June 22, 2010

Partial Surface Wetting/Drying

Es

Rs= evaporation

Partial Wetting of Surface

f = min(1 - f , f )wcew

wfcf cfewfef


Some Example Applications of the FAO-56 Dual Kc Method in the United States


Comparison of Aggregated Estimates against ET from Irrigation Scheme-wide Water Balance

9/4/2015

Imperial Irrigation District: Aggregated FAO-56 vs. ET by Water Balance ~ 200,000 irrigated ha

9/4/2015

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.)

9/4/2015

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

9/4/2015

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000Ac

re-F

eet p

er m

onth




9/4/2015

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000Ac

re-F

eet p

er m

onth




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


Cumulative Growing Degree Days used to Estimate Kc Development. Using CGDD creates some similarity in the Kcb shape

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Kcb

for A

SCE-

PM E

Tr

0.0 0.5 1.0 1.5 2.0 2.5 3.0Cum. GDD since planting, normalized

Potatoes 1972 Beans 1973 Beans 1974

Sugar Beets 1975 Field Corn 1976 Sweet Corn 1976

Peas 1977 Winter Wheat 1978 Spring Grain 1979

Basal Kcb for the ASCE PM ETr Methodbased on Kimberly Lys., Wright(1982)

-- Used Alfalfa Reference ETr and Curvilinear Kcb + Ke


Defined Dry Bean Season Lengths vs. Elevation Thermal-estimated Start and Thermal-estimated End

Season Length, Dry Beans - seed

0

20

40

60

80

100

120

140

0 1000 2000 3000 4000 5000 6000 7000 8000

Elevation

Day

s

Season mean mean - S.D. mean + S.D.

Elevation, ft


Alfalfa Season Lengths vs. Elevation across IdahoThermal-estimated Start and Frost Ended

Season Length, Alfalfa Hay

0

50

100

150

200

250

300

350

400

0 1000 2000 3000 4000 5000 6000 7000 8000

Elevation

Day

s

Season mean mean - S.D. mean + S.D.

Elevation, ft


3/11 7/18 10/06

Crop Coefficient

Daily ET

Ashton, 1990 calendar year -- Potatoes

Snow Cover

Kcb Kc act

ecbsactc KKK =K )ET KETand( ractcactc

Winter

Summer Winter

Operated 365 days/year


Annual ET vs. Precipitation -Desert

Salmon, Idaho 1930-1967 - Sagebrush

0

50

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350 400

Annual Precipitation, mm

Ann

ual E

T, m

mPotentialRecharge


Projection of Impacts of Climate Change on ET and Net Irrigation Water Requirements


West-Wide Climate Risk Assessment – Seven Major River Basins – US Bureau of Reclamation, DRI, UI

Huntington et al. 2015


Colorado River Basin


Baseline Values in the Basin

ETref ETcrop

Net Irrigation Water Requirement (NIWR)

Distribution of Irrigation


S1 – warmer, drierS2 – warmer, wetterS3 – hotter, drierS4 – hotter, wetterS5 – central tendency

Shifts in ET

-- Kc curves were a function of thermal units

2020 2080



Percent Change in ET

--- using FAO-56 Dual Kc Method


Percent Change in Net Irrigation Water Requirement

--- using FAO-56 Dual Kc Method


Mead, Nebraska –

Comparison with Eddy Covariance —Illustrate Low Sensitivity to Kcb mid



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


Kcb mid = 1.00

Kcb mid = 1.05

Irrigated Field – Impact of Kc mid

9/4/2015

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


Kcb mid = 1.05Zroot = 2.2 m

Kcb mid = 1.00Zroot = 1.5 m

Rainfed Field – Impact of Rooting Depth

Landsat 5 1984 – 2012 Landsat 7 1999 – 2017

Landsat 8 (LDCM)Feb. 2013 – 20xx(replaced Landsat 5)

8-daysapart

Kc’s from Space

Landsat is a “polar orbiter”

orbiting Earth each 90 minutes

returning to the same location (path) each 16 days.

http://landsathandbook.gsfc.nasa.gov/orbit_coverage/prog_sect5_2.html


Kc via METRIC-Landsat Energy BalanceMay/2/2000 – SouthCentral Idaho, USA

Crop Coefficient0.00

0.25

0.50

0.75

1.00

1.25

200,000 ha of Coverage – Kc produced by METRIC


June/19/2000


0.25

0.50

0.75

1.00

1.25


July/21/2000


0.25

0.50

0.75

1.00

1.25


August/14/2000


0.25

0.50

0.75

1.00

1.25

Potato (DOY 155-259)

y = 0.0631e2.9397x

y = 1.1299x - 0.0808

y = 1.1892x - 0.1892

y = 1.02x + 0.04

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.2 0.4 0.6 0.8 1 1.2

NDVI at surface

ETrF

Universal KcbexpUniversal KcblinearKcb custom

DOY 155

DOY 171

DOY 187

DOY 203

DOY 227

DOY 235

DOY 251

DOY 259

Kc_mean

Potatoes

Each point is one agricultural field. Each color is a Landsat date

NDVI

Kc

We can also calibrate NDVI-based Kc via Energy Balance

NDVI = Normalized Difference Vegetation Index

Evaporation from Soil

9/4/2015 Colorado Evapotranspiration Workshop March 12, 2010

60 100 140 180 220 260 3000.0

0.2

0.4

0.6

0.8

1.0

1.2

PotatoK

c

100 140 180 220 260 300 0.0

0.2

0.4

0.6

0.8

1.0

1.2

60 Day of Year

Use to Refine Local Information

Average “curve”

717 fields in the Twin Falls area

Sugar BeetsTwin Falls, Idaho 2000

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1/1/2000 3/2/2000 5/2/2000 7/2/2000 9/1/2000 11/1/2000 1/1/2001

Month

Mea

n K

c

Agrim et for 2000 Allen-Robison - 14 yr ave. METRIC for 2000

Comparing METRIC vs. traditional Kc ETref methods

(relatively good agreement among very independent approaches,including during the ‘shoulder’ periods when ground has partial cover)

Kcmean ETref (Kcb + Ke) ETref Energy Balance

(Kc = ETact / ETref)

FAO-56 dual Kc method

Kc traceable to lysimeterKc from Landsat Image

alfalfa reference ETr basis

Estimating Crop Coefficients from Fraction of Cover and Height

Why does Kc change between two fields of the same crop?

INOVAGRI, Fortaleza, Brazil, Aug. 31, 2015

(these are both grapes. Why isn’t the Kc the same?)

9/4/2015

minmin cfullcbdccb KKK+ K = K

--FAO-56 style approach

Kcmin = minimum Kcb for bare soil (~0.10-0.15)

Kd = density coefficient (0-1)

Kcb full = Kcb for full ground covered by vegetation

(assuming bare soil between vegetation)

Allen and Pereira 2009, Irrigation Science, ASABE Mono.

9/4/2015

Density Coeff.

Kd = density coefficient (0-1)ML = multiplier on fc eff (~1.5-2)

(to set upper flux limit per fraction of cover)fc eff = effective fraction of ground covered

(shaded) by vegetation (0-1)h = height, m (for radiation + microadvection)

effcLh

effc fMfK ,,1min 11

d

fc efffc


0 0.2 0.4 0.6 0.8 1Fraction of Ground Cover

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Hernandez‐Suarez (Vegetables)

Eq. 9 , h = 0.1 m

h = 0.4 m

h = 1 m

h = 3 mh = 5 m, M L=1.5

Fereres (1981) (Orchards)

K d

h = 5 m, M L=2.0

Density Coeff.

effcLh

effc fMfK ,,1min 11

d

fc efffc


Expanded Kco tables for OrchardsCrop Kc ini Kc mid Kc end Kcb ini Kcbmid Kcb endFruit TreesAlmonds

- no ground cover - high density (fceff = 0.7) 0.40 1.00 0.70 0.20 0.95 0.65- no ground cover - med. density (fceff = 0.5) 0.40 0.85 0.60 0.20 0.80 0.55- no ground cover – low dens. / young (fceff =

0.25) 0.35 0.50 0.40 0.15 0.45 0.35- active ground cover - high density (fceff = 0.7) 0.85 1.05 0.85 0.75 1.00 0.80- active ground cover - med. density (fceff = 0.5) 0.85 1.00 0.85 0.75 0.95 0.80- act. grnd cover – low dens. / young (fceff = 0.25) 0.85 0.95 0.85 0.75 0.90 0.80

Apples, Cherries, Pears- no ground cover - high density (fceff = 0.7) 0.50 1.15 0.80 0.30 1.10 0.75- no ground cover - med. density (fceff = 0.5) 0.50 1.05 0.75 0.30 1.004 0.70- no ground cover - low dens./ young (fceff = 0.25) 0.40 0.70 0.55 0.25 0.65 0.50- act. grnd cov., killing frost – h.dens. (fceff = 0.7) 0.50 1.20 0.85 0.40 1.15 0.80- act. grnd cov., killing frost – m.dens. (fceff=0.5) 0.50 1.15 0.85 0.40 1.10 0.80- act. grnd cov., killing frost – l.dens. (fceff = 0.25) 0.50 1.05 0.85 0.40 1.00 0.80- act. grnd cov., no frosts – h. dens. (fceff = 0.7) 0.85 1.20 0.85 0.75 1.15 0.80- act. grnd cov., no frosts – m. dens. (fceff = 0.5)3 0.85 1.15 0.85 0.75 1.10 0.80- act. grnd cov., no frosts – l. dens. (fceff = 0.25) 0.85 1.05 0.85 0.75 1.00 0.80

Pears

Apples, Cherries, Pears Peaches

Peaches

Peaches

CitrusMango

Grapes - table

Grapes - wine

PeachesApricots, Peaches, Stone Fruit

CitrusOliveOlive

Olive

Olive

Palms

0.0 0.2 0.4 0.6 0.8 1.0fc

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Mea

sure

d Kc

Orchard Kc’s from literature

no singular relationship between Kc and fc

Pears - fc = 0.35 (2)

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


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



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

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