Physical and Biological Processes that Controls W t V E h b t V t tiWater Vapor Exchange between Vegetation

and the Atmosphere

Dennis BaldocchiDepartment of Environmental Science, Policy and Management

University of California, Berkeley

Contributions from the Biometeorology Lab

Youngryel RyuJ h Fi hJosh FisherSiyan Ma

Xingyuan ChenGretchen MillerM tthi F lkMatthias Falk

Kevin Tu

Outline

• Processes, Supply vs Demand, Short and Long Time scalesShort– Short

• Energy• Meteorology

– Long• Leaf area indexLeaf area index• Nutrition• Plant Functional type

– Short to Long• Surface Conductance• Soil Moisture

• Time– Day/Night– Seasonal– Interannual

• Space– Land Use– PBL/Landscape– Globe

Water and the Environment: Bi h i l E h d l i l ViBiogeophysical-Ecohydrological View

PBL ht

Transpiration/Evaporation

AvailableEnergy

LAI Sensible Heat

Water

SurfaceConductance

p

Photosynthesis/RespirationRespiration

Carbon

NutrientsLitterSoil Moisture

Processes and Linkages:R l f Ti d S S lRoles of Time and Space Scales

continent

Weather modelEcosystemDynamics

Biogeo-chemistry

landscape

region/biomeWeather model Dynamics

λE HR

Species,Functional

Type

ppt, Ta, P, ea,u,Rg,L Ac Gc

canopy

landscape

Biophyscial Model

λE, HRn

Leaf Area, N/C,Ps capacity

Biophysical model

, g, c, c

secon

day

year

centurnds

ys rs ries

Penman Monteith Equationq

λρ

γ γE

s R S C G D

s Gn p H

H=

− + ⋅ ⋅ ⋅

+ +

( )

Function of:

γ γsGs

+ +

•Available Energy (Rn-S)•Vapor Pressure Deficit (D)•Aerodynamic Conductance (Gh)•Surface Conductance (Gs)Surface Conductance (Gs)

Eco-hydrology:y gyET, Functional Type, Physiological Capacity and Drought

?

λEeq

?

λE/λ

?

θ?

Effects of Functional Types and Rsfc on Normalized Evaporation

1.75

2.00

wheatcorn

E eq

1.25

1.50jack pineoak-savanna

λE/ λ

E

0.75

1.00

0 00

0.25

0.50

Rcanopy (s m-1)10 100 1000 10000

0.00

Rc is a f(LAI, N, soil moisture, Ps Pathway)

Stomatal Conductance Scales with N, via Photosynthesis

Stomatal Conductance Scales with Photosynthesis

80

Photosynthetic Capacity Scales with Nitrogen

Stomatal Conductance scales with Nitrogen

mol

m-2 s

-1)

0.10

0.12

0.14

0.16

0.18

0.20

oak, varying lightCa: 360 ppmTa: 25 C

mol

m-2

s-1

)

40

60after Schulze et al (1994)

al c

ondu

ctan

ce (

mm

s-1)

6

8

10

12

14

A ( mol m-2 s-1)

0 1 2 3 4 5 6 7 8

g s (

mm

0.00

0.02

0.04

0.06

0.08

V cmax

(µm

0

20

leaf nitrogen (mg g-`1)

5 10 15 20 25 30 35 40

max

imum

sto

mat

a

0

2

4

6

A (µmol m s )

Na (g m-2)

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Wilson et al. 2001, Tree PhysiologySchulze et al 1994. Annual Rev Ecology

Integrated Stomatal Conductance Scales with Photosynthetic Capacity and LAI

0.018

LAI =1

0.012

0.014

0.016LAI =1LAI =2LAI =3LAI - 4LAI =5

Gs (

m s

-1)

0.006

0.008

0.010

0 000

0.002

0.004

Vcmax (µmol m-2 s-1)

20 40 60 80 100 1200.000

CANVEG Computations

Effects of Leaf Area and Photosynthetic Capacity on Normalized Evaporation:Well Watered ConditionsWell-Watered Conditions

1.3 Priestley-Taylor= 1 26

1.1

1.2= 1.26

QE/

QE,

eq

0.9

1.0

0.7

0.8

Vcmax*LAI

0 20 40 60 80 100 120 140 160 180 2000.6

Vcmax LAI

Canveg Model, Baldocchi and Meyers, 1998 AgForMet

Effects of Leaf Area and Photosynthetic Capacity on Normalized Evaporation:

Watered Deficits

Boreal Forest

1 3

Watered-Deficits

1.2

1.3

k=8.0

k=10

k=7.0

QE,

eq 1.0

1.1

QE/

Q

0.8

0.9

0 6

0.7

Vcmax*LAI

0 20 40 60 80 100 120 140 160 180 2000.6

LAI and Ps Capacity also affects Soil vs Total Evaporation

0.30

0.20

0.25Q

E,so

il/QE

0.15

0.05

0.10

LAI * Vcmax

0 20 40 60 80 100 120 140 160 180 2000.00

cmax

Canopy Surface Conductance does not equal the Canopy Stomatal Conductance

Crop: Rsoil = 1500 s m-1

2.00crop Rsoil = 500 s m-1

1 50

1.75G

can/

int g

s dl

1.25

1.50

0.75

1.00

Vc max (µmol m-2 s-1)

20 40 60 80 100 1200.50

Be Careful about using Gcan to compute isotopic discrimination

Forest Biodiversity is Negatively Correlated with Normalized Evaporation

Temperate/Boreal Broadleaved ForestsSummer Growing Season

1.2

1.0

1.1

λ E/λ

Eeq

0.8

0.9

0.6

0.7

Number of Dominant Tree Species (> 5% of area or biomass survey)

0 1 2 3 4 5 6 7 80.5

Baldocchi, 2005 In: Forest Diversity and Function: Temperate and Boreal Systems.

Use Appropriate and Root-Weighted Soil Moisture ( ) ( )

( )0

z

z

z dP z

dP z

θθ =

∫

∫ ( )0

dP z∫

Soil Moisture, arthimetic average

Soil Moisture root weighted

Chen, Baldocchi et al, in prep.

Soil Moisture, root-weighted

ET and Soil Water Deficits:a d So ate e c tsRoot-Weighted Soil Moisture

Grassland1.0

eq

1.00

1.25

summer rain

Oak Savanna

eq

0.6

0.8

λ E/λ

Ee

0.25

0.50

0.75

λE/λ

Ee

0.2

0.4

θ, weighted by roots (cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.400.00

θ weighted by roots (cm3 cm-3)

0.00 0.05 0.10 0.15 0.20 0.25 0.300.0

Baldocchi et al., 2004 AgForMet

ET and Soil Water Deficits:W t P t ti lWater Potential

p ( )

1.25annual grassland

0.8

1.0

predawn water potentialsoil water potential

oak savanna

λE/λ

Eeq

0.50

0.75

1.00

λ E/λ

Eeq

0.4

0.6

-3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.00.00

0.25

-5 -4 -3 -2 -1 00.0

0.2

soil water potential (MPa)soil water potential (MPa)

5 3 0

Root-Weighted Soil Moisture Matches Pre-Dawn Water Potential

ET of Annual Grass responds to water deficits differently than

Baldocchi et al., 2004 AgForMet

Trees

Leaf Area Index scales with Water Balance Deficits

10

various functional types:Baldocchi and Meyers (1998)savanna:Eamus et al. 2001Oak Savanna, CA

LAI

1 b[0]: -0.68b[1]: 0.84r ² : 0.69

[N]ppt/Eeq

0.1 1 10 1000.1

Nocturnal Transpiration from Blue Oak

Fisher et al. 2006, Tree Physiology

Seasonal and Annual Time Scales

Annual Grassland, 2004

14

) 10

12

14

Actual LEPotential LE

λE (M

J m

-2 d

-1

6

8

λ

2

4

Day

0 50 100 150 200 250 300 3500

Potential and Actual Evaporation are Decoupled in Semi-Arid System

Interannual Variation ET

Vaira 2004

5

2001: 301 mm

Oak Savanna

5

2002: 389 mm

mm

d-1

) 3

42002: 292 mm

2003: 353 mm 2004 : 284 mm

mm

d-1

) 3

42003: 422 mm2004: 340 mm2005: 484 mm

E (m

1

2 ET

(m

1

2

Day

0 50 100 150 200 250 300 3500

Day

0 50 100 150 200 250 300 3500

Annual ET of Annual Grassland varies with Hydrological Growing Seasonyd o og ca G o g Seaso

Ryu, Baldocchi, Ma and Hehn, JGR-Atmos, submitted

Growing Season Length and ET, Temperate Forest

5

6

1996 St t d121

Oak Ridge, TN

4

5

Are

a In

dex

3

4

5 1996, Starts d1211997, Starts d108

(mm

d-1

) 3

4

1996: 492 mm 1997: 519 mm

Leaf

A

1

2

E

1

2

Day

0 50 100 150 200 250 300 3500

Day

0 50 100 150 200 250 300 3500

Year with Longer Growing Season (13 days)Year with Longer Growing Season (13 days) Evaporated More (27 mm).

Other Climate Factors could have confounded results, b t R (5 43 5 41 GJ 2) d T (14 5 14 9 C)but Rg (5.43 vs 5.41 GJ m-2) and Tair (14.5 vs 14.9 C)

were similar and rainfall was ample (1682 vs 1435 mm)

Wilson and Baldocchi, 2000, AgForMet

Year to Year differences in ET is partly due to differences in Growing Season Length

CANOAK

690

700

Slope: -1.68 mm/day

Temperate Deciduous ForestOak Ridge, TN

7

Leaf out: D90

ET

(mm

y-1

)

650

660

670

680p y

(mm

d-1

)

3

4

5

6 D100D110D120D130

E

620

630

640

650

ET

0

1

2

3

Date of Leaf-Out

80 90 100 110 120 130 140620

Day

0 50 100 150 200 250 300 3500

Field data show that ET decreases by 2.07 mm for each day the start of the growing season is delayed

ET: Spatial ScaleET: Spatial Scale

Landscape DifferencesOn Short Time Scales, Grass ET > Forest ET

1.0

Monthly Averages

O S o t e Sca es, G ass o est

0.8

LE/L

Eeq

0.6

L

0.2

0.4

Savanna Woodland

0 2 4 6 8 10 12 14 160.0

Savanna WoodlandAnnual Grassland

Gs (mm s-1)

Ryu, Baldocchi, Ma and Hehn, JGR-Atmos, submitted

Role of Land Use on ET:On Annual Time Scale Forest ET > Grass ET

California Savanna

440

On Annual Time Scale, Forest ET > Grass ET

) 380

400

420

440or

atio

n (m

m y

-1

320

340

360

380

Eva

po

260

280

300

320

Oak WoodlandAnnual Grassland

Hydrological Year

02_03 03_04 04_05 05_06 06_07240

260

Ryu, Baldocchi et al, JGR-Atmos, submitted

•Savanna Uses More Water than Grassland•Savanna Soil holds about 78 mm more Water•Annual ET Decreases with Rg•Rg is negatively correlated with Rain and Clouds•System is Water not Radiation Limited

Different Land Use

440

460

(mm

y-1

)

360

380

400

420

Eva

pora

tion

300

320

340

360

17.4 17.6 17.8 18.0 18.2 18.4240

260

280 Oak Savanna WoodlandAnnual Grassland

<Rg> (MJ m-2 d-1)

Ryu, Baldocchi, Ma, Hehn, JGR-Atmos, submitted

Stand Age also affects differences between ET of forest vs grassland

Plynlimon, Wales

o o est s g ass a d

) 700

800

900

grassland conifer forest

ratio

n (m

m y

-1)

500

600

700

Evap

or

300

400

500

Year

1970 1975 1980 1985 1990 1995 2000 2005 2010200

Marc and Robinson, 2007 HESS

Assessing Spatial g pAverages with Subgrid

Variabilityy

E Es A s A C Dg D gp a a[ ]

' ' ( ' ')( ( / '))

λρ

=+ + +

+ + +

A C D( )

s g g g ra s a s( ( / '))γ γ+ + +

E EsA r C Dg r

s g g rAs s A p a Dga D ga

a s gr ga rs

[ ]( )

( ( / ))λ

σ σ ρ σ σγ γ σ σ

=+ + +

+ + +

Sub-Grid Variability:MODIS d IKONOSMODIS and IKONOS

0.1

Oak/grass savannagrassland

σ2 ND

VI

0.01

1 10 100 10000.001

∆x

Use Power Law scaling to Estimate small scale Variance

Baldocchi et al 2005 TellusE f x f x f x

xx[ ( )] ( ) ( ) ( )= +

∂∂

12

2

22σ

Errors in ET ScalingErrors in ET Scaling

E f x f x f xx

x[ ( )] ( ) ( ) ( )= +∂

∂12

2

22σ

x∂2

Baldocchi et al 2005 Tellus

Linking Water and Carbon:Potential to assess Gc with Remote Sensing

0.8

(mol

m-2

s-1)

0.4

0.6

Annual Grassland

-2 -1

0.00 0.01 0.02 0.03 0.04 0.05 0.06

Gc

0.0

0.2Regr. Coef:b[0]: 0.117b[1]: 9.908r ²: 0.793

Ac rh/Ca (mol m2s

1)

s-1) 0.20

0.25

0.30

oak savanna

Gc (

mol

m-2

s

0.05

0.10

0.15

b[0]: 8.53e-3b[1]: 8.97b[2]: 736.0r ²: 0.812

Xu + DDB, 2003 AgForMetAc rh/Ca (mol m-2 s-1)

0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.0140.00

Gc Exhibits Scale ‘Invariance’

30

40FLUXNET Data

y"

0

10

20

30"B

all-B

erry

40Stomatal Conductance SurveyDennis Baldocchi; UC Berkeleyy

BV98BV99BV97BV00

WBW

96LW

98W

BW97

HV99DU99BL9

8W

R99AB97LW

97CP97NO97SO98SO98BO97GU97NW

00W

BW95

PF99NB96

0

10

20

30 Dennis Baldocchi; UC Berkeley

Ball-

Berr

y

P. ban

ksian

a

P. mari

ana

Eucalyp

tus gr

andis

Eucaly

ptus g

randis

Eucaly

ptus g

randis

Androp

ogon g

erardi

iP. a

bies

P. abie

s

Acer r

ubrum

P. ban

ksian

a

Triticu

m aesti

vum

Bothrio

cholo

a cau

casia

Tripsa

cum da

ctyloi

des

Pinus f

lexilis

Zea m

ays

Gossy

pium hi

rsutum

Quercu

s ilex

Eucaly

ptus g

randis

Eucaly

ptus g

randis

Eucaly

ptus g

randis

Eucaly

ptus g

randis

Eucaly

ptus g

randis

Acer s

acch

arum

Acer s

acch

arum

Fagus

Pistac

ia len

tiscu

sBetu

laPice

a

Dactyl

is.glo

merata

Polygo

num vi

viparu

m

Rhinan

thus.

Alector

oloph

P. vivi

parum

Vaccin

ium m

ytrtill

us

Plantan

us or

iental

isPrun

us

0

R

Processed by M. Falk

Fisher et al Global ET Model

Total Latent heat flux ics LELELE ++ fwet

10RHflux

Canopy Transpiration ( ) ncTgwet Rfff

γα

+∆∆

−1

fgfAPAR

f

IPAR

APAR

ff

11 bSAVIm +

Soil Evaporation( ) ( )GRfff ns −

+∆∆

−+γ

α)1( wetSMwet

fIPAR

fcfT

22 bNDVIm +

IPARf

⎟⎟

⎠

⎞

⎜⎜

⎝

⎛⎟⎟⎠

⎞⎜⎜⎝

⎛ −−

2

expλ

opta TT

Intercepted Evaporation ncRf

γα

+∆∆

wet

T

fSM

Topt

⎠⎝

VPDRH

{ }VPDaAPARa RHTfT maxat

VPDRH A measure for downscaling ETRH A measure for downscaling ET with Drought???

Fisher, Tu and Baldocchi, RSE in press

Global ET, 1989, ISLSCP

ET (mm/y) reference

613 Fisher et al

286 Mu et al. 2007

467 Van den Hurk et al 2003

649 Boslilovich 2006

560 Jackson et al 2003

Fisher et al, in press

Global ET pdf, 1989, ISLSCP

Fisher et al.

ConclusionsConclusions• Biophysical data and theory help explain powerful ideas p y y p p p

of Budyko and Monteith that provide framework for upscaling and global synthesis of ET– ET scales with canopy conductance, which scales with LAI and py ,

Ps capacity, which scales with precipitation and N

Be CarefulBe Careful

• Short-Term Differences in Potential and Actual ET may not hold at Annual Time ScalesET may not hold at Annual Time Scales– Grass has greater potential for ET than Savanna

• Sub-Grid Variability in surface properties can produce huge errors in upscaled ET at the 1 km Modis Pixel Scale

Present and Past Biometeorology ET Team

Funding: US DOE/TCP; NASA; WESTGEC; Kearney; Ca Ag Expt Station

FluxNET WUEFluxNET WUE6000

FLUXNET 20075000

P (g

C m

-2 y

-1)

3000

4000

GP

P

1000

2000

LE (mm y-1)

0 200 400 600 800 1000 1200 14000

LE (mm y )

Global ET JulyJuly

Fisher et al, in press

Budyko Curve, Fluxnet data

1.4

1.0

1.2

Ea/

ppt

0.6

0.8

0.2

0.4

Rn/(λ ppt)

0 1 2 3 40.0

Photosynthesis > 200yRespiration

CO2

Limited Lear Area andSparse Canopy Reduce ET,

too60

80

100

120

140

160

180

140

Quercus alba (Wilson et al)Quercus douglasii (Xu and Baldocchi)

20 40 60 80 100 120 140 160 180

20

40

Sh t i

Vcm

ax

20

40

60

80

100

120

Ps Capacity must be Great,For Short Periodθ v

(%)

0.1

0.2

0.3

0.4

0.5

0.6

0.05 m0.50 m

Short growing season with available moisture

DOY100 150 200 250 300 350

0

Broadleaved, Deciduous Trees

250

300

0.0

Savanna, 2005

600

700

StomatalClosure so

Evaporation >Precipitation

Leaf N and Leaf Thicknessmust support Ps

Machinery

60 80 100 120 140 160 180 200

Am

ass

(nm

ol g

-1 s

-1)

0

50

100

150

200

Quercus douglasii

0 50 100 150 200 250 300 350

Wat

er F

lux

0

100

200

300

400

500

ET ppt

Specific Leaf Area (m2 g-1)

60 80 100 120 140 160 180 200

data of Reich et al and Xu and Baldocchi

Day

Interannual Variation ET:Grassland

Vaira 2004

5

4

2001: 301 mm 2002: 292 mm 2003: 353 mm 2004 : 284 mm

mm

d-1

) 3

E (m

1

2

0 50 100 150 200 250 300 3500

1

Day

0 50 100 150 200 250 300 350

Inter annual Water BalanceOak Savanna

5

2002 389

4

2002: 389 mm2003: 422 mm2004: 340 mm2005: 484 mm

ET

(mm

d-1

)

2

3

E

1

Day

0 50 100 150 200 250 300 3500

Day

Savanna, 20041.0

RH

vpd

0 4

0.6

0.8

0.0

0.2

0.4VPDRH

Day

0 50 100 150 200 250 300 350

0 4

0.5

A measure for downscaling ET

met

ric S

oil M

oist

ure

0.2

0.3

0.4

with Drought???

0 50 100 150 200 250 300 350

Vol

um

0.0

0.1 surface0.20 m0.50 m

Day

Fisher et al. Remote Sensing Environment, in press