Energy Crops and their Implications on Surface Energy

and Water Balance

Yang SongRahul Barman and Atul Jain

University of Illinois, Urbana-Champaign, Urbana, ILEmail: song81@illinois.edu

AcknowledgementsU.S. National Science Foundation

Current Bioenergy Crops considered in the US

Switchgrass Corn Miscanthus

Biophysical parametric differences

Canopy Structural, C & N allocation differences

Phenological differences

Variation in water and thermal energy consumption

ObjectivesExamine potential productivity and their spatial variability of main bioenergy crops

Assess the impact of different bioenergy crops on energy and water balance

Temporal and spatial patterns of

• Evapotranspiration • Radiation (albedo effect)

Research ApproachField Experiments

Simulation Experiment DesignExperiment 1: Grow corn over the US (BASE CASE)

Experiment 2: Grow Miscanthus over the US Calculate biophysical (e.g., GPP, LH, Sensible HF) and biogeochemical variables 

Simulation Period: 2000‐2010

Climate data

NARR reanalysis 

Climate data

Biophysical & Biochemical Model 

(ISAM‐Land)

Soil texture Data

CDL land use data

Soil Color Data

ISAM Land ModelBiophysical

Photosynthesis and Energy processesCanopy temperature, photosynthesis and stomatalconductance based on two-big-leaf (sunlit and shaded) schemeHeat and momentum exchange fluxes between canopy and atmosphere calculated as a function of atmospheric stability, canopy height and stomatalconductance.

Soil/snow hydrology processLayered soil water redistribution calculation related to specific root depth of species.

BiogeochemistryCarbon-Nitrogen cycling in soils and vegetation

ISAM-Land-Surface Model

Energy

Hydrology

Carbon

 and

 Nitrogen

 Cycling

Calculate fluxes of carbon, nitrogen, energy, water, and the dynamical processes that alter these fluxes

• 18 Biome types 0.5 x 0.5 degree resolution

• 30 minutes temporal scale• Season-to-interannual

variability (penology)

Perennial Grasses Phenology

MaximumGrowth

Leaf senescence

Plant senescence

NormalGrowth

Dormancy

Emergence

Canopy close

Spring frostSpring frost

baseT > T base

Cold Tem

Spring frostSpring frost

Lodging DamageLodging Damage

ColdHot and dry

Hot and dry

Offset of greenness

Harvest

Cold

Fall Frost

Fall Frost

GDD (400-1100)

GDD (500-1600)

GDD (750-2400)

GDD (1000-3500)

GDD (1700-4200)

Days(15~30)

Days(0~51)

Days(0~130)

Days(0~56)

Dynamic Carbon Allocation for Perennial Grasses

Source: Arora and Boer (2005)

• Soil water stress (WS ) -Advantageous allocation to roots

• Light stress (LS) -Advantageous allocation to leaves and stem

• Water stress (WS) and Temperature stress (TS) - Advantageous leaf loss to litter

GPP

Leaf Stem root

LitterRespiration

LS WSLS

WSTS

Annual Crop Phenologyand Carbon Allocation

Root stem leaf

Root stem leaf

Root stem leaf grain

stem grain

Dynamic allocation in each step 

based on thermal condition(PHU)

Senescence step 

seedling  step 

Leaf vegetative step 

Emergencestep

PHU>=1.0  or cold temperature

PHU<=0.55

PHU<=0.65

PHU<=0.2

Gdd0>Gdd0min & T > Tbase, PHU=0,

Flowering  step 

Thermal ScheduleDominated 

Heat unit indexPHU= gdd/gddmax

gdd‐growing degree days based on base temperature( degree C)

gddmax‐potential maximum growing degree days for mature (degree C)

Model Calibration-GPPMiscanthus-Urbana Site

Field data and validated parameter sources: Dohleman and Long (2009)

Dohleman et al. (2009)Bonan et al. (2011)

Corn-Mead Ameriflux Site

0

5

10

15

20

25

30

151 181 211 241 271

Daily Assim

ilatio

n Ra

te(g 

C/m2/da

y)

Time(days)

Daily Carbon Assimilation rate in 2001

GPP_2001

y = 0.93xR² = 0.83

0

5

10

15

20

25

30

0 5 10 15 20 25 30

Simulated

Measured 

Measured vs. Simulated Daily Carbon assimilation rate from 2001 to 2006 

GPP

Field data and validated parameter sources:Verma et al, 2005

Model Calibration-Hydrology

0.1

0.2

0.3

0.4

0.5

150 180 210 240 270 300 330 360

Soil Water (m

3 /m

3 )

Days

2007  Simulated_SW

Measured_SW

Modeled vs. Measured Soil Water Content (0-90 cm)

Miscanthus-Urbana Site

0.1

0.2

0.3

0.4

0.5

150 180 210 240 270 300 330 360

Soil Water (m

3 /m

3 )

Days

2008

Measured_SW

Simulated_SW

Observed data sources: Mclsaac et al (2010)

Modeled vs. Measured Soil Water Content (0-100 cm)

0

0.01

0.02

0.03

0.04

0.05

0.06

165 195 225 255 285 315 345

Soil Water (m

3 /m

3 )

Days

Simulated SW

measured SW

0

0.01

0.02

0.03

0.04

0.05

0.06

165 195 225 255 285 315 345

Soil Water (m

3/m3)

Days

Simulated SW

Measured SW

2001

2002

Observed data sources: Verma et al, 2005

Corn-Mead Ameriflux Site

Model Calibration-Heat Fluxes

‐150

‐100

‐50

0

50

100

150

165 195 225 255 285 315 345

Sensible Heat(W/m

2 )

Days

Measured SHSimulated  SH

‐50

0

50

100

150

200

250

165 195 225 255 285 315 345

latent

Heat(W/m

2)

Days

Measured LHSimulated LH

Sensible Heat in 2001

Latent Heat in 2001

Miscanthus Urbana Site

0

100

200

300

400

500

600

2006 2007 2008 Avg

Evap

otranspiratio

n(mm)

Time

Measured

Simulated

Evapotranspiration during growing season(mm/year)

Observed data sources: Mclsaac et al (2010)

Observed data sources: Verma et al, 2005

Corn-Mead Ameriflux Site

Model ValidationDistribution

of validated

sites

Mean Miscanthus Harvested Yield(t/ha) during experimented years for each sites

0

200

400

600

800

1000

1200

120 150 180 210 240

Above grou

nd Biomass(g C/m

2 )

Days

Simulated AG_biomass

Measured AG_biomass

Corn-Bondville Sites

Daily accumulated aboveground biomass in 2001

Source of Data:

Maughan et al., 2011Dohleman and Long (2009) ; Propheteret al., 2010American Fluxes: bondville sites

0

5

10

15

20

25

Yield(t/ha

)

Measured

Simulated

Modeled Average Yield (t/ha) for the Period 2001-2010

Mean Miscanthus yield

Mean Corn Grain Yield

Monthly climate data (precipitation and temperature) and its impact on Miscanthus yield

250260270280290300310

020406080

100120

2000

‐12000

‐52000

‐92001

‐12001

‐52001

‐92002

‐12002

‐52002

‐92004

‐12004

‐52004

‐92005

‐12005

‐52005

‐92006

‐12006

‐52006

‐92007

‐12007

‐52007

‐92008

‐12008

‐52008

‐92009

‐12009

‐52009

‐92010

‐12010

‐52010

‐9

Tempe

rature(K)

Precipita

tion(mm) Accumulated Rain mean temperature

2007 Drought Year

Miscanthus Yield

2004 Wet Year

Monthly climate data (precipitation and temperature ) and its impact on Corn yield

250260270280290300310

020406080

100120

2000

‐12000

‐52000

‐92001

‐12001

‐52001

‐92002

‐12002

‐52002

‐92004

‐12004

‐52004

‐92005

‐12005

‐52005

‐92006

‐12006

‐52006

‐92007

‐12007

‐52007

‐92008

‐12008

‐52008

‐92009

‐12009

‐52009

‐92010

‐12010

‐52010

‐9

Tempe

rature(K)

Precipita

tion(mm) Accumulated Rain mean temperature

2007 Drought Year

Corn Grain Yield

2004 Wet Year

Effect of Miscanthus relative to Corn

y = 0.0002x ‐ 0.0567

‐0.2

‐0.15

‐0.1

‐0.05

0

0.05

0.1

2000

‐12000

‐52000

‐92001

‐12001

‐52001

‐92002

‐12002

‐52002

‐92004

‐12004

‐52004

‐92005

‐12005

‐52005

‐92006

‐12006

‐52006

‐92007

‐12007

‐52007

‐92008

‐12008

‐52008

‐92009

‐12009

‐52009

‐92010

‐12010

‐52010

‐9

Albe

do effe

cty = ‐0.1094x + 13.777

‐30‐20‐100

102030405060

2000

‐12000

‐52000

‐92001

‐12001

‐52001

‐92002

‐12002

‐52002

‐92004

‐12004

‐52004

‐92005

‐12005

‐52005

‐92006

‐12006

‐52006

‐92007

‐12007

‐52007

‐92008

‐12008

‐52008

‐92009

‐12009

‐52009

‐92010

‐12010

‐52010

‐9

Evap

otranspiratio

n(mm/m

onth)

Comparison of Spatial pattern of difference in heat balance between Miscanthus and Corn in a drought and wet year

2007 Drought Year(Miscanthus-Corn)

Albedo Evapotranspiration

Albedo Evapotranspiration

2004 Wet Year(Miscanthus-Corn)

Strengthened Cooling effect

ConclusionsMiscanthus and Corn production has strong spatial and temporal variability over the US.

High productivity is in midwest-US. Temporal pattern are strongly controlled by climate variability (tem and precip).

Miscanthus has larger latent heat loss to atmosphere due to its higher evapotranspiration rate. This effect could cool the earth’s surface.

Over the time this effect will be mitigated due to limitation of water availability.

Compared to corn, Miscanthus has lower albedo due to higher canopy interception during the beginning and later part of growing season, but higher albedo during the peak of growing season due to its larger LAI. Wet climate condition could strengthen cooling effect of Miscanthus to the surface by increased albedo and evapotranspiration rate, compared to corn.

Thank You