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METRIC / SEBAL Approaches to Regionalized Remote Sensing of EvapotranspirationPowerPoint Presentation

METRIC / SEBAL Approaches to Regionalized Remote Sensing of Evapotranspiration

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### METRIC / SEBAL Approaches to Regionalized Remote Sensing of Evapotranspiration

Richard G. Allen, Univ. Idaho – Kimberly

Development Partners:

Wim Bastiaanssen, WaterWatch, the Netherlands

Ayse Irmak, Univ. Nebraska-Lincoln

Ricardo Trezza, Univ. Idaho

Jan Hendrickx, New Mexico Tech

Justin Huntington, Desert Research Institute, Nevada

Jeppe Kjaersgaard, South Dakota State Univ.

NASA/USDA Evapotranspiration Workshop April 5-7, 2011

Presentation Coverage Evapotranspiration

- SEBAL/METRIC approach(es)
- Operational needs
- Model Calibration via Inversion
- Interpolation in Time
- Applications

Evapotranspiration Workshop April 5-7, 2011

R Evapotranspiration

n

ET = R - G - H

n

Why Energy balance?

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

(radiation from sun and sky)

ET

H (heat to air)

Basic Truth: Evaporation consumes Energy

G (heat to ground)

Evapotranspiration Workshop April 5-7, 2011

Energy balance gives us “actual” ET Evapotranspiration

We can ‘see’ impacts on ET caused by:

- water shortage
- disease
- crop variety
- planting density
- cropping dates
- salinity
- management

Evapotranspiration Workshop April 5-7, 2011

METRIC Evapotranspirationtm and SEBAL

Mapping EvapoTranspiration with high Resolution and Internalized Calibration

METRIC was derived from Surface Energy Balance Algorithm for Land

Allen et al., (2002, 2007)

Bastiaanssen et al., (1995, 1998, 2005)

Evapotranspiration Workshop April 5-7, 2011

METRICtm and SEBAL are, in general, complementary processes

North Evapotranspiration

Thousand Springs

Wood River Valley

Twin Falls

recent burn

basalt

100 miles

Burley

Craters of the Moon

Lake Walcott

Surface Temperature – southcentral Idaho – August 14, 2000

Large Contrast in LST

Irrigated Ag.

Desert

Evapotranspiration Workshop April 5-7, 2011

North Evapotranspiration

R

n

H

ET

Thousand Springs

G

Wood River Valley

Twin Falls

recent burn

basalt

Burley

Craters of the Moon

Lake Walcott

Heat Flux to Air – southcentral Idaho – August 14, 2000

Evapotranspiration Workshop April 5-7, 2011

North Evapotranspiration

R

n

H

ET

Thousand Springs

G

Wood River Valley

Twin Falls

recent burn

basalt

Burley

Craters of the Moon

Lake Walcott

Instantaneous ET – southcentral Idaho – August 14, 2000

Evapotranspiration Workshop April 5-7, 2011

North Evapotranspiration

Thousand Springs

Wood River Valley

Twin Falls

100 miles

Burley

24-hour ET – southcentral Idaho – August 14, 2000

500,000 irrig. acres

Desert

24-hour ET – Magic Valley, Idaho – August 14, 2000

--by METRIC Satellite-based ET Procedure

Lake Walcott

Evapotranspiration Workshop April 5-7, 2011

ASABE June 22, 2010

Satellite Energy EvapotranspirationBalances are ‘Plagued’ by Uncertainty, Bias, and Error in EB components

- Surface temperature
- Aerodynamic vs. Radiative Temperature
- Bias in Satellite Sensor Calibration
- Atmospheric Correction

- Air temperature
- Albedo calculation
- Net radiation calculation (incoming long-wave)
- Soil heat flux
- Aerodynamic resistance calculation
- Wind speed field
- Extrapolation of instantaneous ET to 24-hour periods

Evapotranspiration Workshop April 5-7, 2011

Challenge (BIAS): Evapotranspiration

Up to 2 K different from Trad (satellite)

Challenge (BIAS):

Uncertain Spatial Distribution of Tair (feedback between EB, Trad, Tair)

z2

dT

H

rah

z1

Sensible Heat Flux (H) – “Classical”H = r cp (Taero - Tair) / rah

Taero= aerodynamic temperature

rah = the aerodynamic resistance

u* = friction velocity

k = von karmon

constant (0.41)

Evapotranspiration Workshop April 5-7, 2011

Advantage: Evapotranspiration

rah ‘floats’ above the surface and is ‘free’ of zoh and some limitations of a single source approach

Advantage:

dT is inverse calibrated (simulated) (free of Trad vs. Taero vs. Tair)

z2

dT

H

rah

z1

Sensible Heat Flux (H) – CIMEC modelsH = (r ×cp× dT) / rah

dT= “floating” near surface temperature difference (K)

rah = the aerodynamic resistance

from z1 to z2

u* = friction velocity

k = von karmon

constant (0.41)

Evapotranspiration Workshop April 5-7, 2011

H Evapotranspiration

z

2

r

dT

ah

Tveg

z

1

Tsoil

METRIC and SEBAL assume dT to ‘float’ in the blended EBL above the canopy-soil complexEvapotranspiration Workshop April 5-7, 2011

CGIAR Workshop on “Surface Energy Balance Models of Agricultural Areas

from Earth Observation Data” Universidad Nacional Agraria La Molina (Peru), 13 March 2008

Solution to dT function: Evapotranspiration Use Inverse Modeling

- Calibrate against known ET at extreme conditions (end points)
- Incorporate biases of all inputs into the internal calibration
- Biases then fallout during the final estimation process

Evapotranspiration Workshop April 5-7, 2011

Calibration of EvapotranspirationSEBAL and METRIC CIMEC models:

ASCE Penman-Monteith

for 0.5 m (alfalfa) reference

is used for the ‘wet’ extreme

Inversion of H eqn:

Rn – G - 1.05 ETref alfalfa(METRIC)

or 0 (SEBAL – classical)

Rn - G

Evapotranspiration Workshop April 5-7, 2011

z Evapotranspiration

z

2

2

H

H

H

r

r

r

dT

dT

ah

ah

ah

z

z

1

1

Near Surface Temperature Difference (dT)- Tair is unknown and unneeded
- SEBAL and METRICtm assume a linear relationship between Ts and dT:
dT = b + aTs

Bastiaanssen ‘breakthrough’

Ts is used only as an index and can have large bias and does not need to represent aerodynamic surface temperature

Evapotranspiration Workshop April 5-7, 2011

bias EvapotranspirationRn-G biasH-cal biasdT biasH-pixel LE

Calibration of METRIC/SEBAL:The Sensible Heat (H)

Function calibrates around

Biases in many of the

Energy balance components:

(Biases exist in: net radiation, soil heat flux, aerodynamic stability, aerodynamic roughness, absolute surface temperature, atmospheric correction)

unbiased

biases

H = Rn – G – LE (for calibration)

LE = Rn – G – H (during application)

Biases cancel out

Evapotranspiration Workshop April 5-7, 2011

METRIC analyses suggest that the relationship between Relative ET and Ts can vary with land use (+/- 100%) even within one Landsat Scene and can be nonlinear due to buoyancy effects

May 22, 2002

August 26, 2002

Landsat P33, R34-35, New Mexico – Rio Grande

Therefore, good to consider albedo, soil heat flux, stability correction, roughness

Evapotranspiration Workshop April 5-7, 2011

Use ET Relative ET and TrF to extrapolate to 24-hours

Sugar beets

Assume simple scaling with the ET reference

Evapotranspiration Workshop April 5-7, 2011

Comparing METRIC vs. traditional Relative ET and TKcETref methods

(relatively good agreement among very independent approaches,

with some variation during the ‘shoulder’ periods when ground has partial cover)

Evapotranspiration Workshop April 5-7, 2011

Uses of Landsat-based ET to Cover Regional Areas Relative ET and T

Seasonal ET from METRIC and Landsat (100 mile x 200 mile area)

Evapotranspiration Workshop April 5-7, 2011

ASABE June 22, 2010

Cloud Mitigation Relative ET and T

Dr. Ayse Irmak, UNL

Adjusting for background evaporation at image time to derive “Correct” Monthly ET

ET from August 13 1997 not adjusted for

background soil evaporation

ET from August 13 1997 adjusted for

background soil evaporation

A daily Gridded Evaporation/Land Process model is run

Evapotranspiration Workshop April 5-7, 2011

ET – Precipitation ------Indication of Recharge / Depletion

Scottsbluff, NE

Use in

“high-res” hydrologic studies

Irrigated areas

Rangeland / Dryland Ag.

Evapotranspiration Workshop April 5-7, 2011

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