SEBS
Surface Energy Balance System for
estimation of turbulent heat fluxes and
evapotranspiration
Z. (Bob) Su
International Institute for Geo-Information Science
and Earth Observation (ITC),
Enschede, The Netherlands
B_SU@ITC.NL, www.itc.nl/wrs
Monday 3 September 2007, Lecture D1La6
Earth Observation of
Water Cycle
Water Storage
in Ice and Snow
Infilt
So i l
Surface
Runoff
ratio
n
Mois
Radiation
Vapour Transport
(35%)
Precipitation
(100%)
Water Resources
Management
Condensation
(65%)
Evaporation/
Transpiration
(65%)
Evaporation
(100%)
ture
River Discharge
(35%)
Groundwater Storage & Flow
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
2
Learning Objectives
1. To understand basic ideas of the Surface Energy
Balance System
2. To familiarize with the steps used in SEBS for the
derivation of different flux terms
3. To understand the most critical processes in
surface energy balance
4. To familiarize with the applications of SEBS
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
3
Land-Atmosphere Interactions
Lecture D1La6
Advection
Water &
vapour
Gases
Precipitation
(Phase change)
(Conduction)
Latent Heat
(diffusion/convection)
Wind
Soil Heat
Biochemical
Processes
Monday 3 Sept 2007
Sensible Heat
ion
diat
r Ra
Sola
Thermal radiation
- Terrestrial Water, Energy and Carbon Cycles
SEBS
Z. (Bob) Su
4
Structure of
the
atmospheric
boundary
layer
considered in
SEBS
Free Atmosphere
~ 10 2-3 m
Planetary (Convective)
Boundary Layer (PBL)
Blending height
m
Atmospheric
Surface Layer (ASL)
~ 10 -1~1 m
Roughness sublayer
~ 10 -3 m
Inertial sublayer
Transition layer
Viscous sublayer
~ 10
Monday 3 Sept 2007
PBL height
1~2
Lecture D1La6
SEBS
Wind profile
Interfacial sublayer
Z. (Bob) Su
5
Barrax Test Site, Spain
- Situated in the area of La Mancha, in the west of
the province of Albacete, 28 km from Albacete
- Geographic coordinates: 39º 3’ N; 2º 6’ W
- Altitude (above sea level): 700 m
Corn
Bare Soil
Water Body
Garlic
Green Grass
Vineyard
Reforestation
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
6
Surface Radiation Balance
Monday 3 Sept 2007
Lecture D1La6
SEBS
Surface thermal
radiation
Atmospheric
thermal radiation
Reflected solar radiation
Solar Radiation
R n = (1 − α ) ⋅ R swd + ε ⋅ R lwd − ε ⋅ σ ⋅ T 04
α : albedo
ε : emissivity
T0 : Surface Temperature
Z. (Bob) Su
7
Data from EAGLE/SPARC Campaign 2004, Barrax, Spain
Barrax 2004 Radiation @ Vineyard
1200
1000
SW_inc
SW_out
LW_inc
LW_out
800
600
400
200
0
196
197
198
199
200
201
202
203
-200
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
8
Surface Energy Balance Terms
Rn = G0 + H + LE
G0
Monday 3 Sept 2007
Lecture D1La6
LE
H
Rn
G0 = Rn ⋅ [ f c ⋅ Γc + (1 − f c ) ⋅ Γs ]
Wind
[α , ε , T0 , f c ]
SEBS
Z. (Bob) Su
9
Scintillometer Data from EAGLE/SPARC Campaign 2004, Barrax,
Spain
Barrax 2004 Fluxes @ Vineyard
800
600
400
200
0
196
197
198
199
200
201
202
203
-200
Rnet
G_avg
H-LAS
LE_Rest.
-400
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
10
Remote sensing of heat fluxes and evaporation - a brief history of the developments in the Netherlands
Analytical vs (semi-)empirical approach
Menenti, 1980, Menenti, 1984,
(two-layer combination eq.
for a drying soil)
Nieuwenhuis et al., 1989
e.g. E=a+b*T0
Bastiaassen, 1995
Surface Energy Balance Algorithm for Land (SEBAL)
(require simultaneous presence of
absolute dry and absolute wet pixels
-> applications in irrigation management
Menenti, 1993
(personal note doubting the success
of pure analytical approach)
Menenti & Choudhury, 1993
extended Jackson et al., 1981, 1988’s
Crop Water Stress Index (surface scaling)
to Surface Energy Balance Index
(PBL scaling with kB_1=2.3, Bw=2.9)
(->applications Aral sea, Menenti et al. 2001)
Su, Pelgrum, Menenti, 1999
correction in SEBAL for a theoretical problem and
extension to include NWP fields with a up-scaling,
down-scaling scheme
Su, 2001, 2002 extended SEBI concept with
the kB_1 model of Su, Schmugge, Kustas & Massman, 2001
and BAS of Brutsaert, 1999 (Surface and PBL scaling)
Surface Energy Balance System (SEBS)
Roerink, Su, Menenti, 2000
Simplified Surface Energy Balance Index
(fitting dry and wet limiting cases in data)
(S-SEBI)
(->coupling to NWP fields: Jia et al. 2001, ATSR data
->extension to parallel-source: Su & Rauwerda 2001, ATSR data
->estimation of daily, monthly, annual evaporation: Li et al. 2001
->drought monitoring: Su et al. 2001, 2003)
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
11
Schematic representation of SEBS
(Radiometric observables) (r0, T0),
(RS observables or estimates) (fc, LAI, hc),
(Surface observation, radiosonds, NWP fields) (TPBL, VPBL, PPBL, qPBL, Rs, Rld)
Preprocessing to derive radiation balance terms
Submodel to derive roughness length for heat transfer
(Su, Schmugge, Kustas, Massman, 2001)
Submodel to derive stability parameters
(ASL scaling or PBL scaling, Brutsaert, 1999)
Energy balance at limiting cases
(Menenti, Choudhury,1993)
Energy balance terms
(Rn, G0, H, λE, Λ)
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
12
Remote sensing of heat fluxes and evaporation
- SEBS Single source, SEBS Parallel-source
fc
T0
Hv
Hs
Rahv
Rahs
Tv
Ts
Wind
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
13
Rn = G0 + H + λE
λEdry = Rn − G0 − H dry ≡ 0, or
H dry = Rn − G0
SEBS Basic Equations
Su, 2002, HESS, 6(1),85-99
λEwet = Rn − G0 − H wet , or
H wet = Rn − G0 − λEwet
ρC p es − e ⎞
⎛
⎟⎟
H wet = ⎜⎜ (Rn − G0 ) −
⋅
γ ⎠
rew
⎝
λEwet − λE
λE
Λr =
= 1−
λEwet
λEwet
H − H wet
Λr = 1−
H dry − H wet
H = (1 − Λ ) ⋅ (R n − G )
Λ r ⋅ λ E wet
Λ=
=
Rn − G
Rn − G
λE
λ E = Λ ⋅ (R n − G )
Monday 3 Sept 2007
Lecture D1La6
⎛ Δ⎞
⎜⎜1 + ⎟⎟
⎝ γ⎠
SEBS
Z. (Bob) Su
14
Energy Balance Residual Method - Turbulent Heat Fluxes
u*
u=
k
⎡ ⎛ z − d0 ⎞
⎛ z0 m ⎞⎤
⎛ z − d0 ⎞
⎟⎟ − Ψm ⎜
⎟ + Ψm ⎜
⎟⎥
⎢ln⎜⎜
⎝ L ⎠
⎝ L ⎠⎦
⎣ ⎝ z0 m ⎠
L = −
ρ C p u *3θ v
kgH
G0
Monday 3 Sept 2007
Lecture D1La6
LE
⎞
⎛ z − d0 ⎞
⎛ z0h
⎟⎟ − Ψh ⎜
⎟ + Ψh ⎜
⎝ L ⎠
⎝ L
⎠
H
Rn
⎡ ⎛ z − d0
H = ku * ρ C p (θ 0 − θ a )⎢ ln ⎜⎜
⎣ ⎝ z0h
⎞⎤
⎟⎥
⎠⎦
−1
Wind, air temperature, humidity
(aerodynamic roughness,
thermal dynamic roughness)
[z 0 m , d 0 , z 0 h ] ? [Ta , u , q ] ?
SEBS
Z. (Bob) Su
15
The scalar roughness height for heat transfer
(
z 0 h = z 0 m / exp kB
−1
)
The within-canopy wind speed profile extinction coefficient,
nec =
kB −1 =
kB
−1
s
C d ⋅ LAI
2u*2 u (h )
2
kC d
(
u*
4Ct
1 − e − nec
u (h )
( )
= 2.46 Re *
Monday 3 Sept 2007
14
2
)
z0 m
u*
⋅
⋅
k
u
h
h
(
)
2
−1 2
+
kB
fc + 2 fc fs
s fs
*
Ct
− ln[7.4]
Lecture D1La6
SEBS
Z. (Bob) Su
16
SEBS - The Surface Energy Balance System
Input
SEBS Core Modules
Output
Meteorological Data
Boundary Layer
Variables
Boundary Layer
Similarity Theory
Turbulence
Heat Fluxes
Remote Sensing Data
Roughness for
Heat Transfer
Evaporative
Fraction
Surface Energy
Balance Index
Actual
Evaporation
VIS
NIR
Monday 3 Sept 2007
TIR
Lecture D1La6
SEBS
Z. (Bob) Su
17
General Methodology
•
Cloud cover
Atmospheric models
RS
RS
DEM
Regional
parameters
Ta, τ, L↓
DEM
Preprocessing
Monday 3 Sept 2007
Lecture D1La6
SYNOPS,
Climatology
Evaporative
Fraction,
soil moisture
SEBS
(Surface Energy Balance System)
SEBS
Postprocessing
Z. (Bob) Su
18
NOAA/AVHRR, LANDSAT, ASTER,
METEOSAT, AATSR, MODIS,
Atmospheric sounding,
In-situ meteorological
Observation
RS
DEM
RS
Numerical Weather
Prediction models
Regional Atmospheric State
Preprocessing
DEM
DN ⇒ Radiance/Reflectance at sensor
⇓
Radiance/Reflectance at surface
⇓
Albedo, temperature, vegetation cover, emissivity, incoming radiation, roughness
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
19
SEBS plug-in in BEAM
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
20
SEBS plug-in in BEAM
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
21
SEBS plug-in in BEAM - Roughness height for momentum transfer
These are default values and need to be adjusted according to actual phenological stage.
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
22
Results from SEBS
Sensible Heat
AHS 15 July 2004
(A. Gieske)
Sensible Heat
ASTER 18 July
2004
Monday 3 Sept 2007
Lecture D1La6
WM^-2
SEBS
Z. (Bob) Su
23
Some applications
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
24
Application to the Urumqi River Basin, NW China
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
25
6.0
4.0
Changji, measured
2.0
M engjin, calculated
Sep. 2nd
Aug.16th
Jul. 17th
Jun. 18th
May 1st
Apr. 7th
0.0
Oct. 2nd
Comparison to
measurements
(water surfaces)
Daily evaporation (mm)
8.0
Monthly evaporation (mm)
200
160
120
80
Wulapo Station, measured
40
Wulapo Reservoir, calculated
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
Nov
Oct
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
0
26
250
Chaiwopu Lake
200
Eas t mountain
Salt Lake
150
Mengjin Res er voir
100
Des er t
50
Wulapo Res er voir
0
Monday 3 Sept 2007
O
ct
Ju
l
A
pr
River plain
Ja
n
Monthly evaporation (mm)
Monthly evaporation from different surfaces
in the Urumqi River Basin
Chaiwopu Bas in
Gobi P lain
Lecture D1La6
SEBS
Z. (Bob) Su
27
Spatial Distribution of Annual Evaporation
over the Urumqi River Basin
•Nort
h
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
28
1200
9
1000
1. Desert
2. Gobi Plain
3. Mid-mountain
4. Salt Lake
5. Chaiwopu Basin
6. Forest zone
7. Bayi Reservoir
8. Mengjin eservoir
9. Chaiwopu Lake
8
Ea (mm/a)
SEBS-HANTS
7
800
4
600
3
6
400
5
2
200
1
0
0
200
400
600
800
1000
1200
Ea (mm/a)
Field measurements
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
29
Applications to the Netherlands
(Methods to determine z0m)
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
30
Monthly evaporation during 1995
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
31
Annual evaporation in 1995
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
32
Validation of Atmospheric Models at Regional Scales
Scintillometer measurements, retrievals by SEBS
using ATSR data and RACMO PBL fields, and
simulation by RACMO (Jia, Su, vd Hurk, Moene,
Menenti, de Briun, 2002),
350
Tomelloso, RMSD=16.1 W m-2
Lleida, RMSD=40.4 W m-2
300
H Estimated
Badajoz, RMSD=18.3 W m-2
250
RMSD = 25.6 W m-2
200
150
100
50
50
150
250
350
H m easured
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
33
Conclusions
– The Surface Energy Balance System (SEBS) is briefly introduced.
– SEBS is scale invariant, so that it can be applied easily to different
scales. Data of high or low spatial resolution from all sensors in the
visible, near-infrared and thermal infrared frequency ranges can be
used in the system.
– Based on a set of case studies, SEBS has proven to be capable to
estimate turbulent heat fluxes and evaporation from point to
continental scale with acceptable accuracy for low vegetation.
– The results demonstrate that SEBS algorithm can be used for spatialtemporal estimation of actual evaporation with an acceptable
accuracy.
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
34
References/Further Readings
– Z. Su, 2002, The Surface Energy Balance System (SEBS) for estimation of
turbulent heat fluxes, Hydrology and Earth System Sciences, 6(1), 85-99.
– Z. Su, A. Yacob, Y. He, H. Boogaard, J. Wen, B. Gao, G. Roerink, and K. van
Diepen, 2003, Assessing Relative soil moisture with remote sensing data:
theory and experimental validation, Physics and Chemistry of the Earth, 28(13), 89-101.
– L. Jia, Z. Su, B. van den Hurk, M. Menenti, A. Moene, H.A.R. De Bruin,
J.J.B.Yrisarry, M. Ibanez, A. Cuesta, 2003, Estimation of sensible heat flux
using the Surface Energy Balance System (SEBS) and ATSR measurements,
Physics and Chemistry of the Earth, 28(1-3), 75-88.
– Z. Su, 2005, Estimation of the surface energy balance. In: Encyclopedia of
hydrological sciences : 5 Volumes. / ed. by M.G. Anderson and J.J. McDonnell.
Chichester etc., Wiley & Sons, 2005. 3145 p. ISBN: 0-471-49103-9. Vol. 2 pp.
731-752.
• H. Su, E.F. Wood, M.F. McCabe, Z. Su, 2007, Evaluation of remotely sensed
evapotranspiration over the CEOP EOP-1 reference sites, Journal of
Meteorological society of Japan, 85A, 439-459.
• Y. Oku, H. Ishikawa, Z. Su, 2007, Estimation of Land Surface Heat Fluxes
over the Tibetan Plateau Using GMS Data, Journal of Applied Meteorology
and Climatology, 46(2): 183-195.
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
35
EAGLE2006
(8 June – 2 July 2006)
EAGLE Netherlands Multi-purpose, Multi-Angle and Multi-sensor,
In-situ, Airborne and Space Borne Campaigns over Grassland and Forest
ESA, Italy
ITC, The Netherlands
University of Valencia, Spain
INTA, Spain
ITRES, Canada
DLR, Germany
WUR / ALTERRA, The Netherlands
LSIIT, France
NLR, The Netherlands
KNMI, The Netherlands
WUR / Meteorology Group, The Netherlands
RIVM, The Netherlands
WH Stichtse Rijnlanden, The Netherlands
MIRAMAP, The Netherlands
University of Washington, USA
University of South Carolina, USA
ISAFoM,
ISAFoM, Italy
Utrecht University, The Netherlands
Staatsbosbeheer,
Staatsbosbeheer, The Netherlands
Fugro,
Fugro, The Netherlands
Monday 3 Sept 2007
Lecture D1La6
SEBS
Z. (Bob) Su
36