Discussion on using Evapotranspiration for Water Rights Management Rick Allen -- University of Idaho, Kimberly, Idaho

Partners and Collaborators:Jeppe Kjaersgaard, Magali Garcia, R. Trezza – University of IdahoTony Morse, W. Kramber – Idaho Dept. Water ResourcesWim Bastiaanssen – WaterWatch, M. Tasumi --Univ. Miyazaki, JapanJames Wright -- USDA-ARS

ET is calculated as a “residual” of the energy balance

ET = R - G - Hn

Rn

G (heat to ground)

H (heat to air) ET

The energy balance includes all major sources (Rn) and consumers (ET, G, H) of energy

Basic Truth: Evaporation consumes Energy

METRIC Energy balance

(radiation from sun and sky)

Therefore, we can account for impacts on ET caused by:

water shortage disease crop variety planting density cropping dates salinity management

(these effects can be converted into a crop coefficient)

Energy balance gives us “actual” ET

Interpolation of ETrF (i.e., Kc) for Monthly or Seasonal ET

n

miirirperiod ETxFETET 24

n

miir

n

miirir

periodr

ET

ETxFETFET

24

24

0

0.2

0.4

0.6

0.8

1

1.2

3/1

4/1

5/1

6/1

7/1

8/1

9/1

10/1

11/1

ET

rFSplined Satellite Date

Corn 2000

12/17/01

Comparison with Lysimeter Measurements:

Lysimeter at Kimberly (Wright)

1968-1991

Kimberly, Idaho – Periods between Satellites

Lysimeter data by Dr. J.L. Wright, USDA-ARS

Sugar Beets, 1989

Kimberly, Idaho

0

50

100

150

200

250

300

ET

d

urin

g p

erio

d, m

m

18-Apr

04-May20-May05-Jun

21-Jun07-Jul23-Jul

25-Sep

Lys. Kc on Sat. date x sum ETrSum. all lysimeter meas. (Truth)

SEBAL ET for period

Impact of using Kc from a single dayto represent a period: Kimberly 1989

METRIC ET for period

Perio

d of P

artia

l Cov

er

Sugar Beets

Seasonal ET - 1989

Cumulative ET in 1989 for Sugar Beets

0

100

200

300

400

500

600

700

800

4/1

/89

4/1

5/8

9

4/2

9/8

9

5/1

3/8

9

5/2

7/8

9

6/1

0/8

9

6/2

4/8

9

7/8

/89

7/2

2/8

9

8/5

/89

8/1

9/8

9

9/2

/89

9/1

6/8

9

9/3

0/8

9Cu

mu

lati

ve E

T (

mm

) fr

om

4/1

/89

SEBAL-ID Estimation Lysimeter Measurement

Error = 2.5%

0100200300400500600700800

Total

Lysimeter SEBALMETRIC

Lysimeter

718 mm

METRIC

714 mm

Sugar Beets

Comparison of Seasonal ET by METRICtm with Lysimeter

ET (mm) - April-Sept., Kimberly, 1989

0

100

200

300

400

500

Total

Lysimeter SEBAL

ET (mm) - July-Oct., Montpelier, ID 1985

SEBAL

405 mmLysimeter

388 mm

Comparison of Seasonal ET by SEBAL2000 with Lysimeter

Sharpening of Landsat 5 Thermal Band to 30 m

original (120 m thermal)sharpened (30 m thermal)

ETrF

Temp.

July2006

Sharpening of Landsat 5 Thermal Band to 30 m

Growing Season, 2006 – ET aggregated inside CLU’s

Comparison to Kc Curves

potato kc

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

potato ndvi

60 100 140 180 220 260 3000.0

0.2

0.4

0.6

0.8

1.0

Potato

0.2

0.4

0.6

0.8

1.0

60 100 140 180 220 260 300 0.0

Day of Year

ND

VI

Vegetation Index

METRIC applied to year 2000

Average “curve”

717 fields in the Twin Falls area

0 25 50 km

TwinFalls weather station42.66oN/114.45oW (Elev.1195m)

beet kc

60 100 140 180 220 260 3000.0

0.2

0.4

0.6

0.8

1.0

1.2

S.BeetK

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

516 fields

Kc near 1.0 indicating high production agriculture

wgrain kc

60 100 140 180 220 260 3000.0

0.2

0.4

0.6

0.8

1.0

1.2

W.GrainK

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

564 fields

alfalfa kc

60 100 140 180 220 260 3000.0

0.2

0.4

0.6

0.8

1.0

1.2

AlfalfaK

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

325 fields

Approaches – 1 (METRIC)Base ET estimates on METRIC --7 to 10 day lag time, high expense --can apply an ‘attainable’ efficiency to derive Diversion

requirement

Can normalize to NDVI to estimate stressCan compare with actual Diversions, ET/NDVI from a few other years (2000, 2003, 2006)Advantage – gives ‘actual’ ETDisadvantage Expensive and with time delay One ‘look’ each 16 days only, at best Some native uncertainty in ET estimates (+/-10%?)

“in-season injury assessment”

Approaches – 2 (Satellite NDVI)

Base ET estimates on NDVI --quick, one day lag time, low expense --apply an ‘attainable’ efficiency to derive Diversion

requirement

Compare with actual DiversionsAdvantage quick, low cost can use SPOT, IRS, etc. if the current LS fails

Disadvantage May not see ET reductions caused by stress (water

shortage) “Injury” based on act. vs. required diversions

“in-season injury assessment”

Approaches – 3 (no satellite)

Calculate ratio of running average Diversion to running average reference ET (from weather data) Compare to other years (> 20)Advantage quick, inexpensive longer time series for context (>20 years for

Agrimet)

Disadvantage May need to normalize for cropping patterns May need to normalize for shift to sprinklers

“in-season injury assessment”

“basal” Kc

“mean” Kc

0.0

0.2

0.4

0.6

0.8

1.0C

rop C

oeffic

ient (E

TrF

)

0.0 0.2 0.4 0.6 0.8 1.0NDVI

3 June 19 June 21 July

717 Potato Fields,

2000

“basal” Kc

“mean” Kc

0 25 50 km

TwinFalls weather station42.66oN/114.45oW (Elev.1195m)

34

34

refref

refrefNDVI

“basal” Kc

“mean” Kc

0

0.2

0.4

0.6

0.8

1

1.2

0 0.2 0.4 0.6 0.8 1

NDVI

Kc

6/3 6/19 7/5 multi-field average (for 12 images Mar-Oct)

Potato“mean” Kc

0

0.2

0.4

0.6

0.8

1

1.2

0 0.2 0.4 0.6 0.8 1 NDVI as

K cr

Alfalfa Beans Beet Corn Potato-S Potato-L Sgrain Wgrain

K cr = 1.17 NDVI as + 0.05 R 2 = 0.94

Kcm

“mean” Kc vs. NDVI Well-watered fieldsMagic Valley, 2000

“mean” Kc vs. NDVI

0

0.2

0.4

0.6

0.8

1

1.2

0 0.2 0.4 0.6 0.8 1

NDVI (toa)

Kc (

ET

rF)

Alfalfa Sugar Beet CornPotato S.Grain W.GrainETrF = 1.25 NDVI

May to September 2000Magic Valley, IdahoAverages of 100's of fieldseach satellite date

Well-watered fields

Development of a seasonal Kc curve from NDVI – Comparison against 1989 Lysimeter data at Kimberly for Landsat Overpass Dates (Kc and NDVI were then splined between dates to obtain daily ET estimates)

0

0.2

0.4

0.6

0.8

1

1.2

4/1

/89

5/1

/89

6/1

/89

7/1

/89

8/1

/89

9/1

/89

10

/1/8

9

ND

VI,

Kc

Sugar Beets

0

0.2

0.4

0.6

0.8

1

1.24

/1/8

9

5/1

/89

6/1

/89

7/1

/89

8/1

/89

9/1

/89

10

/1/8

9

ND

VI,

Kc

NDVIas

Kcr

Grass

0

200

400

600

800

1000

Grass Sugar Beet

ET

(m

m/6

mo

.)

VI based est.

Lysimeter meas.

Comparisons between daily ET determined by METRIC for specific crops and ET determined from the general Kcm vs. NDVIsurf relationship, year 2000, Magic Valley, averaged over 100’s of sampled fields

Comparisons between 5-day ET determined by METRIC for specific crops and ET determined from the general Kcm vs. NDVIsurf relationship, , year 2000, Magic Valley, averaged over 100’s of sampled fields

Alfalfa 1001 5.0 5.4Beans 479 8.5 8.5Beet 904 -1.7 -2.2Corn 846 -6.3 -4.4

Potato-S 733 2.0 1.6Potato-L 846 -1.5 -1.8S.Grain 720 -0.9 -1.0W.Grain 837 -1.4 -0.3

Standard Error - 4.6 4.3

CropsMETRIC ET

(mm)

Kc from NDVI at

satellite (%)

Kc from NDVI corrected to surface (%)

Error (%) in seasonal ET estimated using Kc estimated using the NDVI (normalized difference vegetation index) relative to seasonal ET calculated by METRIC – positive values indicate overestimation.

0

200

400

600

800

1000

1200

Se

as

on

al E

T (

mm

)

Alfa

lfa

Bea

ns

Bee

t

Cor

n

Pot

ato-

S

Pot

ato-

L

Sgr

ain

Wgr

ain

ET (METRIC)

ET (NDVIas)

“Performance” of Irrigation Projects

Mar Apr May Jun Jul Aug Sep Oct

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Project wide Crop Coefficient -- METRIC Twin Falls Tract -- 220,000 acres -- Alfalfa Reference Basis

2000

2003Kc

March, Sept., and Oct. unavailable for 2003 due to clouds

Irrigation Project Performance -- Idaho

Apr May Jun Jul Aug Apr-Aug

0.0

0.2

0.4

0.6

0.8

1.0

Evapotranspiration as a Ratio of Diversion plus Precipitation

2000

2003

Rat

io

Twin Falls Canal Company, Idaho

Irrigation Project Performance -- Idaho

“basal” Kc

“mean” Kc

0.0

0.2

0.4

0.6

0.8

1.0C

rop C

oeffic

ient (E

TrF

)

0.0 0.2 0.4 0.6 0.8 1.0NDVI

3 June 19 June 21 July

717 Potato Fields,

2000

“basal” Kc

“mean” Kc

34

34

refref

refrefNDVI

Can the NDVI-based Kc pick up ‘stress’ caused by water shortage?

Stress? orRandom errorin Kc estimate?

Year 2000: Mean 24-h Evapotranspiration from METRIC

0

1

2

3

4

5

6

7

8

9

6/3 6/19 7/5 7/21 8/14 8/22

Landsat Overpass Date

Me

an

ET

24

mm

A&B GW

A&B GW (Item -G)

A&B SW

N of A&B GW

S of A&B SW

W of A&B GW

W of A&B SW

NW of A&B Mixed

Year 2000: M ean ETrF (i.e ., Kc) from M ETRIC

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

6/3 6/19 7/5 7/21 8/14 8/22

Landsat Overpass Date

Me

an

ET

rF

A&B GW

A&B GW (Item -G)

A&B SW

N of A&B GW

S of A&B SW

W of A&B GW

W of A&B SW

NW of A&B Mixed

Year 2000: M ean NDVI from M ETRIC

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

6/3 6/19 7/5 7/21 8/14 8/22

Landsat Overpass Date

Me

an

ND

VI

A&B GW

A&B GW (Item -G)

A&B SW

N of A&B GW

S of A&B SW

W of A&B GW

W of A&B SW

NW of A&B Mixed

Year 2000: Ratio of M ean ETrF to M ean NDVI

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

6/3 6/19 7/5 7/21 8/14 8/22

Landsat Overpass Date

Me

an

ET

rF/

me

an

ND

VI

A&B GW

A&B GW (Item -G)

A&B SW

N of A&B GW

S of A&B SW

W of A&B GW

W of A&B SW

NW of A&B Mixed

High because of evaporation from surface floodingor high because of no stress??

Issues

If NDVI (and thus ET) is ‘low’ is it because: shift in crop types due to market shift in crop types because of perceived

water shortage (i.e., internal mitigation) chronic shortage of water during

development cool spring – late/retarded development warm summer – accelerated ripening

Approaches – 1 (METRIC)Base ET estimates on METRIC --7 to 10 day lag time, high expense --can apply an ‘attainable’ efficiency to derive Diversion

requirement

Can normalize to NDVI to estimate stressCan compare with actual Diversions, ET/NDVI from a few other years (2000, 2003, 2006)Advantage – gives ‘actual’ ETDisadvantage Expensive and with time delay One ‘look’ each 16 days only, at best Some native uncertainty in ET estimates (+/-10%?)

“in-season injury assessment”

Approaches – 2 (Satellite NDVI)

Base ET estimates on NDVI --quick, one day lag time, low expense --apply an ‘attainable’ efficiency to derive Diversion

requirement

Compare with actual DiversionsAdvantage quick, low cost can use SPOT, IRS, etc. if the current LS fails

Disadvantage May not see ET reductions caused by stress (water

shortage) “Injury” based on act. vs. required diversions

“in-season injury assessment”

Approaches – 3 (no satellite)

Calculate ratio of running average Diversion to running average reference ET (from weather data) Compare to other years (> 20)Advantage quick, inexpensive longer time series for context (>20 years for

Agrimet)

Disadvantage May need to normalize for cropping patterns May need to normalize for shift to sprinklers

“in-season injury assessment”

Impact of Irrigation System Type on ET-- south-central Idaho -- 2003

METRIC Analyses by Lorite, Allen and Robison

Impact of Irrigation System Type on ET-- south-central Idaho -- 2003

METRIC Analyses by Lorite, Allen and Robison

Impact of Irrigation System Type on ET-- south-central Idaho -- 2003

METRIC Analyses by Lorite, Allen and Robison