Modeling Effects of Climate Changeon

Evapotranspiration and Crop YieldsIn

California’s Central Valley

Michael Tansey – USBRFrancisco Flores & Chuck Young – SEI

Justin Huntington - DRI

CWEMF Annual MeetingApril 2012

Conceptual Model

Water (Soil) Nutrients (Soil)

Energy (Atmosphere)

Biomass

PrecipitationHumidityWind

Solar radiationTemperatureCO2

Plant Responses to Climate Factors

(°C) (kPa) (MJ m-2 d-1) (ppm)

Temp VPD Solar Rad CO2

Transpiration(mm)

Crop Yield(ton/ha)

Plant Responses to Temperature Changes

Crop specific Optimal temperature growth rangeCrop specific Basal temperature (Tb) required for onset of growing

seasonCrop specific growing period based on Potential Heat Units (PHU)

HU = Tavg – TbCrop specific Potential rate of canopy development (LAI) and

senescence

Optimal Growth

ReducedGrowth

Start of Growth Harvest

Full CanopyMax LAI

Plant Responses to CO2 Changes

Crop specific response to maximum canopy Leaf Area Index (LAI)Crop specfic response to Stomatal ConductanceCrop specific Radiation Use Efficiency (RUE) response to

production of Plant biomass and Yield

C3 Plants Only

Max LAI vs CO2 Max RUE vs CO2 SC vs CO2

Plant Responses to Humidity Changes

Crop specific response to humidity changes (VPD = es-ea) on Stomatal Conductance (SC)

CO2 effect on leaf temperature included in Stomatal Conductance calculations

Crop specific response to humidity (VPD) changes on RUE affects Plant biomass and Yield

Vpd thresholdVpd threshold

Max RUE

Min RUE

Stomatal Conductance vs VPD Radiation Use Efficiency vs VPDMax SC

Crop Yield Responses to Heat and Water Stress

Crop specific response of Potential Harvest Index (PHI) based on accumulated Heat Unit Index (HUI) during growth period

Crop specific response of Actual Harvest Index (AHI) to Water Stress Index (WSI) during the growing period

PHI vs HUI AHI vs WSI

Max Yield Max Yield

Plant Transpiration (Penman‐Monteith) (mm/d)

NR CR=f [ gs , CO2, VPD, LAI ]VPD=f [ T, RH ]

Plant Growth (ton/ha)

LAI=f [ HU, CO2, PSF ] RUE=f [ CO2 ] PAR=f [ SR, LAI ]

PSF=f [ TSF, WSF]

Plant Growth WSF=f [APT, PPT]

VPD

HU=f [T, CBT)

Crop Yield (ton/ha)HU

APT: actual plant transpiration (mm)

AR: aerodynamic resistance  (s/m)CBT: crop base temperature (°C)CH: canopy height (m)CO2: carbon dioxide (ppm)CR: canopy resistance (s/m)gs: leaf conductance (mol/m2 s)HU: heat units LAI: leaf area index LAWS: Land Atmosphere Water SimulatorNR: net radiation (MJ/m2 d)PAR: photosynthetic active 

radiation (MJ/m2 d)PSF: plant stress factorPPT: potential plant transpiration 

(mm)RH: relative humidityRUE: radiation use efficiency 

(kg ha‐1/MJ  m‐2)SR: solar radiation (MJ/m2 d)T: mean dailytemperature (°C)Topt : optimum temperature (°C)TSF: temperature stress factorUS: wind speed (m/s)VPD: vapor pressure deficit  (kPa)WSF: water stress factor

Legend

gs =f [VPD, CO2)

TSF=f [T, CBT, Topt]

LAWS ‐> APT

LAWS Crop Model Calibration4 CIMIS Station Calibration

LocationsGerberDavisFirebaughShafter

24 Crops Calibrated to ITRC ETc & SWAP Model PA Yields

Alfalfa, Almonds, Apples & Citrus

Corn, Corn Silage, CottonDry Bean, Fresh Tomato

&LettuceMelon, Olive, Onion-Garlic, &

OrchardsPasture, Potato & Processed

TomatoRice, Safflower & Sugar BeetsVineyards & Winter Wheat

Central Valley WEAP PA Model Sub-Regions

Crop Model Calibration – CIMIS Station QA

Solar Radiation Adjustments

1. Remove measured solar radiation (Rs) outliers by setting their values to the clear sky solar radiation (Rso)

2. Calculate the ratio Rs/Rso for each day and save the top 20% of Rs/Rso for each monthly period

3. Divide the daily Rs by the top 20% Rs/Rso ratio for each monthly period

4. This is just one way to adjust, there are others, but this approach seems to work well for large datasets….

Crop Model Calibration – CIMIS Station QADaily Relative Humidity Extremes

Adjustments (Extremes Derived from Hourly RH)

1. Remove daily RHmax outliers

2. Adjust daily RHmax so that the daily RHmax reaches 100% at least several days per year

3. It is wrong that UC Davis hourly RH never reaches close to 100%....

4. Other ways to adjust, but this is simple, and preserves the seasonality

Crop Model Calibration – Gerber - Tomatoes

Climate Change Simulations

1. Emissions Scenario

2. Global Climate

Simulation

3. Downscaled Climate

Projections

San Francisco Bay

6. Operations Models

5. Simulation Models

7. Benefits/Impact Models

4. Scenario Selection

A1FI

B2

A2

B1

A1T

A1B

Climate Scenario Selection

0.0

0.5

1.0

1.5

2.0

2.5

-30.0 -20.0 -10.0 0.0 10.0 20.0 30.0

Tem

per

atu

re C

han

ge

(C)

Precipitation Change (%)

Relationship Between Changes in Mean Annual Temperature and PrecipitationScenarios - 10 NN Method

Feather River Basin (Example)

112 GCMs

Q1 (10NN)

Q2 (10NN)

Q3 (10NN)

Q4 (10NN)

T50

P50

T10

P10

T90

P90

T25

P25

T75

P75

Q2 (drier, more warming)

Q4 (wetter, less warming)Q1 (drier, less warming)

Q3 (wetter, more warming)

Q5

Scenario Development

Hybrid Delta Ensemble Method

o Base 1950-1999LLNL Archive BCSD

o 4 CIMIS locationsFuture Projections

o 2020o 2050o 2080

Uncertainty Scenarioso s1 = < warm, driero s2 = < warm, wettero s3 = > warm, driero s4 = > warm, wettero s5 = central 25-75%

S1 less warm, drier S2 less warm, wetter

S3 warmer, drier S4 warmer, wetter

S5

Climate Scenario Meteorological Parameter Estimation

Penman-Montheith daily ET calculation requires daily Solar Radiation, Actual Vapor Pressure and Wind Speed data

Solar Radiation may estimated from the theoretical Clear Sky Radiation (a function of Date and Location) and the Maximum and Minimum Air Temperatures from the BCSD climate projections

Actual Vapor Pressure (ea) is calculated from the Dew Point Temperature (Tdew) (a function of Relative Humidity and Air Temperature)

Dew Point Depression (Ko) is defined as the difference between Tmin – TdewAt a given location Ko varies relatively consistently on a monthly basis from year to

yearThus projected daily Tdew is estimated from projected daily Tmin – monthly

historical average KoProjected daily Wind Speed are estimated using monthly historical average Wind Speeds

from the CIMIS station data

Spatially Downscaled and Bias Corrected Global Climate Model projections contain only Maximum and Minimum Temperature, Precipitation, historical Wind Speed data from NWS stations

Solar Radiation EstimationApplication of a modified Thornton and Running empirical equation (1999)

Basic premise - during cloud cover Tmax decreases and Tmin increases due to downward emission of reflected long wave radiation at night

In general the Thornton-Running equation estimates Rs well over the ranges of Rs measured, especially during the growing season when it matters most

( )( )[ ]5.1minmaxexp9.01 TTBRR sos −−−=

Windspeed is seasonality consistent from year to year such that we can estimate future windspeed from historical monthly means

Given the difficulty in estimating windspeed at the 2m level from GCMs due to scale issues, and the lack of archiving windspeed in most projections, this is a safe and conservative way to estimate windspeed required in the Penman-Monteith

Windspeed Estimation

Dewpoint Temperature EstimationDaily Tdew is estimated as

Tdew = Tmin – Ko (mean monthly)

where Ko = mean monthly dewpoint depression (Tmin – Tdew) determined from historical CIMIS data

Using mean monthly historical Tmin-Tdew to estimate future Tdew preserves regional and local scale advection that the area of interest actually experiences and avoids biases in GCM projections of ea

Estimating ea from Tdew is a conservative way to predict future vapor pressure deficit (es – ea) required in the Penman-Monteith

Both es and ea will go up as Tmax and Tmin goes up, therefore the VPD (es – ea) will stay relatively constant

Climate Projectionss1 – Less warming, Driers2 - Less warming, Wetters3 – More warming, Driers4 – More warming, Wetters5 – Central region 25-75 percentiles

Climate Scenario CO2 Projections Estimation

Climate Scenario Meteorological Projections

Davis

Climate Scenario S5 Crop Transpiration ProjectionsAnnuals - Base Period Planting Date & PHUs

Gerb

erFi

reba

ugh

Shaf

ter

Davis

Climate Scenario S5 Crop Growing Period ProjectionsGe

rber

Fire

baug

hSh

afte

r

Davis

Climate Scenario S5 Crop Yield ProjectionsGe

rber

Fire

baug

hSh

afte

r

Crop Model Planning Area Results

4 CIMIS Station Climate Projections 2020,2050, 2080

GerberDavisFirebaughShafter

24 Central Valley PA crop acreages assumed to remain constant in future

Central Valley WEAP PA Model Sub-Regions

Climate ET Planning Area ProjectionsDavis Gerber

Firebaugh Shafter

Climate Yield Planning Area ProjectionsDavis Gerber

Firebaugh Shafter