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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