THE PENMAN-MONTEITH METHOD
FOR REFERENCE
EVAPOTRANSPIRATION AND
ASSOCIATED CROP COEFFICIENTS
Richard Allen, University of Idaho-Kimberly
Ayse Kilic, University of Nebraska-Lincoln
March 17, 2015
DSI – Turkish National Commission for
Hydrology – Water Balance Workshop for Turkey
March 16-20, 2015
Istanbul
Topics
a. Benefits of using standardized Penman-Monteith
reference ET calculation
b. QAQC of weather data
c. Crop coefficients
d. Determination of crop coefficients from METRIC Remote
Sensing of ET
What is Reference ET?
• Reference ET (ETref) is:
• ET from a well-defined and consistent surface
• dense, uniform and extensive vegetation
• well-watered vegetation
• ETref represents the majority of weather-based effects on
ET
• ETref should be based on physics
,a
What is Reference ET?
• Two Vegetation Types are used for
Reference ET:
• Clipped Grass (ETo)
• Cool season grass (fescue or perennial
ryegrass)
• Mowed to 8 to 15 cm height
• Extensive cover (~ 50 m or more)
• Full-cover Alfalfa (ETr)
• Dense stand with no cutting effects
• 30 to 70 cm height
• Extensive cover (~ 50 m or more)
Standardized PM Reference ET
FAO + American Society of Civil Engineers
Universal
The single standardized Penman-Monteith equation can be applied to
a) grass and alfalfa and b) for daily or hourly timesteps
Cn
0.408  (R n  G )  
u 2 (e s  e a )
T  273
ETref 
   (1  Cd u 2 )
(FAO-56 PM ETo )
Calculation Time Step
Daily or monthly
Hourly during daytime
Hourly during nighttime
Short Reference,
ETo
Tall Reference,
ETr
Cn
Cd
Cn
Cd
900
37
37
0.34
0.24
0.96
1600
66
66
0.38
0.25
1.7
Units for ETo,
ETr
Units for Rn, G
mm d-1
mm h-1
mm h-1
MJ m-2 d-1
MJ m-2 h-1
MJ m-2 h-1
(ASCE PM ETr hourly)
Reasons for
Standardization of Reference ET (PM)
• Common, international and national basis
for expression of Evaporative demand
• Consistency in calculation of
Evapotranspiration
• Promotes accurate transfer of Crop
Coefficients
Benefits of Using FAO-PenmanMonteith Reference ET
• Crop coefficients are available for a large
number of crops
• Crop coefficients are usually
transferrable to new areas because of
the physical basis of the PM equation
• PM equation can be used with only air
temperature data, if necessary
Kimberly Lysimeters - September 4,1990
ASCE Standardized
Penman-Monteith
(alfalfa reference)
at Kimberly, Idaho
Data from Dr. J.L Wright
E T , m m /h o u r
1.10
0.90
0.70
0.50
- hourly time step
0.30
0.10
010003000500070009001100130015001700190021002300
Time of Day
Etr
Lys. 2 alfalfa
Kimberly Lysimeters -September 7, 1990
1.10
E T , m m /h o u r
-0.10
- Good Accuracy
0.90
0.70
0.50
0.30
0.10
-0.10
3/17/2015
010003000500070009001100130015001700190021002300
CIGR,
Bari, Italy, Sept.
Time
of Day
10, 2013
Etr
Lys. 2 alfalfa
Good day-to-day correspondance with lysimeter measurements
Kimberly, Idaho 1969
Evapotranspiration, mm/day
12
Lysimeter
ASCE P-M
10
8
6
4
2
Full c ov er alfalfa - Data from Dr. J .L. Wright
0
100 125 150 175 200 225 250 275 300
Day of Year
3/17/2015
CIGR, Bari, Italy, Sept.
10, 2013
ASCE Manual 70 Comparisons (1990)
TABLE L.13 Summary of Statistics and Ranking of Methods for Monthly Estimates of ET at All Locations1
All Months
Peak Month
Weighted
Rank
Method
%2
SEE3
b4
r5 ASEE6
%
SEE
b
r ASEE
SEE7
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10) (11) (12)
(13)
1
Penman-Monteith
101
0.36
1.00
0.99
0.36
97
0.52
1.03
0.99
0.47
0.40
2
1982 Kimberly-Penman
107
0.53
0.95
0.98
0.49
107
0.79
0.96
0.98
0.73
0.59
3
Penman (1963)
106
0.57
0.99
0.97
0.57
99
0.95
1.07
0.96
0.81
0.67
4
Penman (1963), VPD #3
113
0.67
0.93
0.97
0.57
105
0.77
1.00
0.96
0.77
0.68
5
1972 Kimberly Penman
112
0.74
0.93
0.96
0.67
102
0.72
1.03
0.97
0.70
0.72
6
FAO Radiation
114
0.73
0.91
0.97
0.59
110
0.88
0.95
0.96
0.78
0.73
7
FAO-24 Blaney-Criddle
108
0.68
0.95
0.96
0.64
106
0.98
0.98
0.94
0.97
0.76
8
FAO-24 Penman (c = 1)
121
0.91
0.88
0.96
0.65
111
0.84
0.95
0.96
0.76
0.82
9
Jensen-Haise
85
0.84
1.11
0.95
0.71
83
1.44
1.15
0.92
1.06
0.95
10
Hargreaves et al. (1985)
108
0.88
1.00
0.93
0.88
101
1.47
1.07
0.87
1.39
1.05
11
FAO-24 Corrected Penman 127
1.16
0.82
0.96
0.65
122
1.53
0.86
0.93
1.00
1.10
12
FAO-24 Pan
100
0.92
0.94
0.92
0.88
95
1.58
1.03
0.82
1.57
1.11
13
SCS Blaney-Criddle
101
1.16
0.99
0.87
1.15
103
1.31
1.05
0.89
1.26
1.20
13
Pan Evaporation
118
1.34
0.82
0.92
0.87
113
1.82
0.88
0.83
1.56
1.35
14
Turc
90
1.30
1.20
0.89
1.07
85
2.26
1.31
0.84
1.49
1.46
15
Priestley-Taylor
85
1.29
1.22
0.90
1.02
86
2.34
1.28
0.78
1.72
1.48
1
All equations were adjusted for the reference crop of the lysimeter (excluding FAO-PPP-17, Businger-van Bavel, Thornthwaite, and Christiansen pan
methods in former table 7.20).
2
Average percentage of lysimeter measurements.
3
Standard error of the estimate or ET estimates in mm d-1 that have not been adjusted by regression.
4
Regression coefficient (slope) for regression through the origin of lysimeter versus equation estimate.
5
Correlation coefficient for regression through the origin of lysimeter versus equation estimate.
6
Standard error of estimate for ET estimates in mm d-1 that have been adjusted by regression through the origin.
7
Weighted standard error of estimated calculated as 0.7(Col. 4) + 0.33(Col. 7) + 0.3[0.67(Col. 9) + 0.33(Col. 12)].
Overall Ranking
ASCE Manual 70 Conclusion
• Methods Using Primarily Air Temperature
•
• Of the temperature methods, the SCS Blaney-Criddle method
and Thornthwaite method (not included in the tables), were
generally the poorest in estimating lysimeter ET of all methods
evaluated. The SCS Blaney-Criddle typically underestimated
reference ET in the arid climates and overestimated both peak
and seasonal ET in humid climates.
• . The Hargreaves-Samani method tended to underestimate ET
by about 10 percent in arid climates. The FAO Blaney-Criddle
method provided good estimates of both peak and seasonal ET
at the arid lysimeter locations.
ASCE PM -- Daily vs. Hourly Timestep
20
Davis, California
CIMIS Station
2008 – 2012
18
y = 1,005x + 0,182
R² = 0,957
24-h Timestep Ref. ET, mm d-1
16
14
Grass Reference
12
10
8
Conclusion:
You can use
hourly or daily
weather data
6
4
2
0
0
2
4
6
8
10
12
14
16
Summed Hourly Reference ET, mm d-1
18
20
ASCE PM -- Daily vs. Hourly Timestep
20
y = 1,025x + 0,434
R² = 0,944
18
Davis, California
CIMIS Station
2008 – 2012
24-h Timestep Ref. ET, mm d-1
16
14
Alfalfa Reference
12
10
8
Conclusion:
You can use
hourly or daily
weather data
6
4
2
0
0
2
4
6
8
10
12
14
16
Summed Hourly Reference ET, mm d-1
18
20
Example crop coefficients for the Grass
Reference ETo
Source:
FAO-56 and
American
Society of
Agricultural
Engineers –
Design and
Operation of
Irrigation
Systems, 2008.
3/17/2015
3/17/2015
FAO-Style Crop Coefficient = ET/ETref
K
c
m
i
d
• simple,
relatively
accurate
K
c
e
n
d
1
.
2
1
.
0
0
.
8
K
c K
0
.
6
c
i
n
i
0
.
4
0
.
2
0
.
0
T
i
m
e
o
f
S
e
a
s
o
n
,
d
a
y
s
3/17/2015
Kc from Lysimeter
each dot is one day
Sweet Corn-- Kimberly, Idaho, 1976
Kc
Precipitation and Irrigation, mm
“Single” Curve
averages
Evaporation
from wet soil
200
1.2
160
1.0
0.8
120
0.6
80
I
0.4
I
I
I
I
I
0.2
P
0.0
I
I
130
P
P
150
40
I
170
190
210
Day of the Year
230
250
0
data courtesy of Dr. J.L. Wright, USDA-ARS
3/17/2015
The “Dual Kc” method Splits
Soil Evaporation from Transpiration
Sweet Corn
Kimberly, Idaho, 1976
Basal Kc Curve1.0
(Kcb)
160
K
0.8
c
Wet Soil
Evaporation
“Spikes”
(Ke)
120
0.6
Evap.=18%
I
0.4
I
I
I
I
I
P
0.0
I
I
0.2
130
40
I
P
P
150
80
170
190
210
Day of the Year
230
250
0
Precipitation and Irrigation, mm
“Mean” Kc Curve 1.2
200
data courtesy of Dr. J.L. Wright, USDA-ARS
3/17/2015
„Dual‟ Kc Procedure
ET K = K K + K
=
c
s
cb
e
ETref
K s = water stress (0 - 1)
Kcb= basal K c (dry surface)
Ke = evaporation coefficient
3/17/2015
The “Dual Kc” method Splits
Soil Evaporation from Transpiration
Sweet Corn
Kimberly, Idaho, 1976
Basal Kc Curve1.0
(Kcb)
160
K
0.8
c
Wet Soil
Evaporation
“Spikes”
(Ke)
120
0.6
Evap.=18%
I
0.4
I
I
I
I
I
P
0.0
I
I
0.2
130
40
I
P
P
150
80
170
190
210
Day of the Year
230
250
0
Precipitation and Irrigation, mm
“Mean” Kc Curve 1.2
200
data courtesy of Dr. J.L. Wright, USDA-ARS
3/17/2015
Evaporation Coefficient - Ke
FAO-56 Simple Drying Function
Es = K e ETref
Skin Evaporation
(Allen, 2011)
TEW = Total Evaporable
Water
(Soil)
TEW ~ 10 to 35 mm
De ~ 150 mm
3/17/2015
Kc from Lysimeter
Precipitation and Irrigation, mm
Using FAO
style
straight line
method
each dot is one day
200
1.2
Kc
0.0
130
150
170
190
210
Day of the Year
230
250
data courtesy of Dr. J.L. Wright, USDA-ARS
Colorado Evapotranspiration Workshop March 12, 2010
3/17/2015
Estimating Humidity, Solar Radiation,
Wind Speed when only Air temperature is
The Penman-Monteith equation “requires”:
Available
When Unavailable:
• Tdew = Tmin – Ko
•
•
•
•
Air temperature
Humidity (dewpoint temperature (Tdew))
Solar Radiation
Wind Speed
• – Ko is a fixed „offset‟ that can vary from month to month.
•
• Solar Radation = f(Tmax – Tmin)
-- (Thornton-Running)
• Wind Speed = Long-term monthly averages
Based on Guidelines in FAO-56 (Allen et al., 1998)
(For more information: Google for “ETIdaho” www.kimberly.uidaho.edu/ETIdaho/ )
(there is no reason not to apply the Penman-Monteith method)
QAQC OF WEATHER
DATA
“Visual Analyses based on
Theoretical Relationships”
QAQC = quality assessment and quality control (correction)
Software: REF-ET -- free at:
http://extension.uidaho.edu/kimberly/2013/04/ref-et-referenceevapotranspiration-calculator/
(just Google “REF-ET”)
Clear Sky Curve
24-hour
Solar Radiation
Measured
Corrected by
multiplying by
1.14 for day 90 to
day 250 for year
1992
x 1.16 for day 90
to day 240 for
year 1993
Corrected
Visual Scanning of Hourly RH Data
Example of QAQC process of Max. Daily RH% at UC Davis CIMIS station
Base adjustments on ratios between theoretical clear sky solar radiation and top percentiles of measured data
Before Correction – Sensor Drift
Max Daily RH%
•
After Correction – No Sensor Drift
Max Daily RH%

Slide courtesy of Justin Huntington, DRI
BIASES IN “SOME”
GRIDDED WEATHER
DATA SETS
Gridded Weather Data Sets
• In the future we will calculate Reference ET from Gridded
Weather data sets:
• NLDAS (North American Land Data Assimilation System) ~ 16 km
• GLDAS (Global Land Data Assimilation System) ~ 32 - 64 km
• These data sets are derived primarily from:
• radiosonde air profiles
• weather data from (dry) airports
• Therefore, data can be „too hot‟ and „too dry‟ compared to
Agriculture
• These gridded data can be „adjusted‟ using
• bias correction using agricultural point data (such as TARGEM)
• conditioning algorithms based on profile theory
The Need for “bias correction” or “conditioning”:
NARR Tair vs. Irrigated vapor pressure - Idaho
3.0
Actual Vapor Pressure (ea) .
ea, Agrimet - Twin Falls
ea, NARR-Twin Falls
2.0
1.0
0.0
7/13/2008
7/18/2008
7/23/2008
7/28/2008
8/2/2008
Date
Three-hourly vapor pressure data from NARR over Kimberly, ID, during May 2008,
compared with measurement at USBR Agrimet weather station (TWFI) near Kimberly. The
Agrimet station is over irrigated grass and has double the humidity than the NARR data
that is impacted by ambient data from nonirrigated weather sources.
Impact of Site Aridity on ETo
and „correction‟ using “Conditioning functions” for air
temperature, humidity and wind speed
Conclusion: Using extremely arid weather data reduces
vapor pressure, increases air temperature and increases
wind speed measurements. In this example, that caused
a 32% overstatement of reference ET. Conditioning the
data reduced the overstatement of ET to 6%.
DETERMINATION OF
CROP COEFFICIENTS
FROM SATELLITEBASED ET MAPPING
(METRIC)
Growing Season ET at 30 m resolution for the Eastern Snake
Plain of Idaho, USA
April – October,
2006 ET
Idaho Falls
Ketchum
~160 km
American Falls
Oakley
April 5-7, 2011
NASA/USDA
Workshop on
Evapotanspiration
ET features at 30 m resolution
April – October, 2006 ET from
METRIC-Landsat
25 km
April 5-7, 2011
NASA/USDA
Workshop on
Evapotanspiration
3/17/2015
1.21.2
1.01.0
Kc
0.80.8
Sampling Kc from Satellite-ET
Potato
717 fields in the Twin Falls area
Average “curve”
0.60.6
0.40.4
0.20.2
0.00.060
60
100
100
140
140
180
180
Day of Year
220
220
260
260
Landsat Overpass Dates
300
300
3/17/2015
Development of “Local” Crop coefficients
Samples from 717 POTATO fields in southern Idaho, 2000
Average curve
Early plant/harvest
Late plant/harvest
Kc curve for
Late planting?
METRIC Kc curves reflect
local practices and field management
Kc curve for
Early planting?
3/17/2015
Sampling Kc (Kc = ETrF) from Satellite-ET images
Each „blue dot‟ is one field.
alfalfa kc
Sampling of METRIC estimates for ET from alfalfa for
>300 fields in southcentral Idaho on Landsat overpass
days.1.21.2
325 fields
Alfalfa
1.01.0
Kc
0.80.8
0.60.6
0.40.4
0.20.2
0.00.060
60
100
100
140
140
180
180
Day of Year
220
220
260
260
300
300
Comparing METRIC vs. traditional Kc ETref methods
alfalfa reference ETr basis
(Kc = ETact / ETref)
Sugar Beets
Twin Falls, Idaho 2000
1.2
Mean Kc
1.0
0.8
FAO-56 dual Kc method
0.6
0.4
0.2
0.0
Kc from Landsat Image
Kc traceable to lysimeter
1/1/2000 3/2/2000 5/2/2000 7/2/2000 9/1/2000 11/1/2000 1/1/2001
Month
(relatively good agreement among very independent approaches,
including during the „shoulder‟ periods when ground has partial cover)
Agrimet for 2000
Kcmean ETref
Allen-Robison - 14 yr ave.
(Kcb + Ke) ETref
METRIC for 2000
Energy Balance
3/17/2015
Comparing METRIC vs. traditional Kc ETref methods
Dry Beans
Twin Falls, ID 2000
1.2
Mean Kc
1.0
0.8
0.6
0.4
0.2
0.0
1/1/2000 3/2/2000 5/2/2000 7/2/2000 9/1/2000 11/1/200 1/1/2001
0
Month
Agrimet for 2000
Agrimet for 2000
Allen-Robison - 14 yr ave.
Allen-Robison - 14 yr ave.
METRIC for 2000
METRIC for 2000
Comparing METRIC vs. traditional Kc ETref methods
Field Corn
Twin Falls, Idaho 2000
1.2
Mean Kc
1.0
0.8
0.6
0.4
0.2
0.0
1/1/2000
3/2/2000
5/2/2000
7/2/2000
9/1/2000 11/1/2000 1/1/2001
Month
(relatively good agreement among very independent approaches,
with some variation during the „shoulder‟ periods when ground has partial cover)
Agrimet for 2000
Allen-Robison - 14 yr ave.
METRIC for 2000
Comparing METRIC vs. traditional Kc ETref methods
Mean Kc
Potatoes
Twin Falls, Idaho 2000
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
1/1/2000 3/2/2000 5/2/2000 7/2/2000 9/1/2000 11/1/2000 1/1/2001
Month
(relatively good agreement among very independent approaches,
including during the „shoulder‟ periods when ground has partial cover)
Agrimet for 2000
Allen-Robison - 14 yr ave.
METRIC for 2000
There are Multiple entries for Kc for Fruit Trees in FAO-56 Kc tables ––
These can be calculated from fc (Allen and Pereira, 2009, Irrigation Science)
Crop
Kc ini
Kc mid
Kc end
Kcb ini
Kcb mid Kcb end
Fruit Trees
Almonds
- 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 cover33 - 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
- 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
Apples, Cherries, Pears
3/17/2015
Measurements by Grattan et al. 1998 (and Hanson and May,
1.2
1
Basal Crop Coefficient
Basal Crop Coefficient
1.2 2006)
Cantaloupe
1
Onion
0.8
0.8
0.6
0.6
0.4
0.4
0.2
UCD (Grattan et al.)
0.2
Kd based func.
Kd based func.
0
0
0
20
40
60
80
Percent Ground Cover
0
100
1.2
1
1
Basal Crop Coefficient
1.2
Basal Crop Coefficient
UCD (Grattan et al.)
Strawberry
20
40
60
80
100
Percent Ground Cover
120
Tomato
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
UCD (Grattan et al.)
Hanson and May 2006 Kd based func.
Kd based func.
0
0
0
20
40
60
80
Percent Ground Cover
100
0
0.2
0.4
0.6
0.8
1
Fraction Ground Cover
1.2
3/17/2015
Colorado Evapotranspiration Workshop March 12, 2010
COMPARISON OF ETC
FROM KC ETO WITH ETC
FROM WATER BALANCE
3/17/2015
Colorado Evapotranspiration Workshop March 12, 2010
Example: Imperial Valley, California, USA
~200,000 ha
USA
Mexico
Allen et al., 2005, ASCE J. IDE
3/17/2015
Water Balance of Imperial Irrigation
District
ET = Inflow - Surface Outflow
+ Precipitation
- Δ Soil Water
- Deep Percolation
More than 40 types of crops modeled
Acreage of each crop changed each year
• accuracy of annual ET from the water balance is +/- 5%
(95% C.I.)
3/17/2015
FAO-56 PM grass reference ETo and Dual Kc method were used
Total Proj ect Ev apotranspiration
1990
Acre-Feet per month
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
(AF Values are
s c aled)
J an.F ebMar.A pr.MayJ une
J ulyAug
S eptOc
. tN
. ovD. ec .
KcETo (Pot.)
ETcWB
ETo
3/17/2015
Total Proj ect Ev apotranspiration
1991
Acre-Feet per month
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
(AF Values are
s c aled)
J an.F ebMar.A pr.MayJ une
J ulyAug
S eptOc
. tN
. ovD. ec .
KcETo (Pot.)
ETcWB
ETo
3/17/2015
Total Proj ect Ev apotranspiration
1992
Acre-Feet per month
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
(AF Values are
s c aled)
J an.F ebMar.A pr.MayJ une
J ulyAug
S eptOc
. tN
. ovD. ec .
KcETo (Pot.)
ETcWB
ETo
3/17/2015
Total Proj ect Ev apotranspiration
1993
Acre-Feet per month
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
(AF Values are
s c aled)
J an.F ebMar.A pr.MayJ une
J ulyAug
S eptOc
. tN
. ovD. ec .
KcETo (Pot.)
ETcWB
ETo
3/17/2015
Total Proj ect Ev apotranspiration
1994
Acre-Feet per month
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
(AF Values are
s c aled)
J an.F ebMar.A pr.MayJ une
J ulyAug
S eptOc
. tN
. ovD. ec .
KcETo (Pot.)
ETcWB
ETo
3/17/2015
Total Proj ect Ev apotranspiration
1995
Acre-Feet per month
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
(AF Values are
s c aled)
J an.F ebMar.A pr.MayJ une
J ulyAug
S eptOc
. tN
. ovD. ec .
KcETo (Pot.)
ETcWB
ETo
3/17/2015
Total Proj ect Ev apotranspiration
1996
Acre-Feet per month
350,000
1990-96 Rat io =
1. 07
SEE f or monthly
= +/ - 16%
300,000
250,000
200,000
150,000
100,000
50,000
0
(AF Values are
s c aled)
J an.F ebMar.A pr.MayJ une
J ulyAug
S eptOc
. tN
. ovD. ec .
KcETo (Pot.)
ETcWB
ETo
3/17/2015
Conclusions
• The Kc ETr method using Penman-Monteith method is
relatively accurate and transferable
• The Kc incorporates important factors affecting ET
• The dual Kc provides good estimation of impacts of
evaporation from soil
• Satellite-based ET (from METRIC) can be used to
produce Kc curves for:
• new crops
• new areas
• new planting periods
• water-stressed areas
THANK YOU