Assessment of Climate Change Impact on Eastern Washington

Agriculture

Claudio O. StöckleBiological Systems

Engineering,Washington State University

USA

Objective

Assess the potential impact of climate change and elevated atmospheric CO2 concentration on selected crops in eastern Washington, region that produces most of the state’s agricultural output value.

Correlation between COCorrelation between CO22 Concentrations and Temperature Concentrations and Temperature The current concentration is the highest in 800,000 years, as determined by ice core dataThe current concentration is the highest in 800,000 years, as determined by ice core data

a The 800,000-year records of atmospheric carbon dioxide (red; parts per million, p.p.m.) and methane (green; parts per billion, p.p.b.) from the EPICA Dome C ice core together with a temperature reconstruction (relative to the average of the past millennium) based on the deuterium–hydrogen ratio of the ice, reinforce the tight coupling between greenhouse-gas concentrations and climate observed in previous, shorter records. The 100,000-year ‘sawtooth’ variability undergoes a change about 450,000 years ago, with the amplitude of variation, especially in the carbon dioxide and temperature records, greater since that point than it was before. Concentrations of greenhouse gases in the modern atmosphere are highly anomalous with respect to natural greenhouse-gas variations (present-day concentrations are around 380 p.p.m. for carbon dioxide and 1,800 p.p.b. for methane).b The carbon dioxide and methane trends from the past 2,000 years. Ed Brook, Nature 453, 291 (2008).

Source: IPCC

Global Greenhouse Gas Trends

General Circulation Models Four GCMs were selected for this study:

PCM1, CCSM3, ECHAM5, and CGCM3.

PCM1 projects less warming and CCSM3 more warming for eastern WA. The other two GCMs are intermediate.

The GCMs project an increase in precipitation (3 to 9% by 2020 and 2080, respectively) with some differences in distribution, and with a larger relative increase in the winter.

Annual Precipitation and Potential Evapotranspiration ETo (mm)

Seasonal (April 1- Sept 30) Precipitation and Potential Evapotranspiration ETo (mm)

Annual and Season Mean Temperature (oC)

Sunnyside Annual2020 2040 2080

CCSM3 1.9 2.8 3.6PCM1 1.3 2.2 3.0

Sunnyside Seasonal2020 2040 2080

CCSM3 1.8 2.9 3.8PCM1 1.3 1.9 2.8

Annual Temperature Difference with Baseline (oC)

Change in frost-free period (days)

Pullman

Probability of equal or higher temperature

0.0 0.2 0.4 0.6 0.8 1.0

Tm

ax (

o C)

10

15

20

25

30

35

40

45CCSM3 CGCM3 ECHAM5 PCM1 Historical

Probability Distribution of Tmax (June/July)

Probability Distribution of Tmin (April)

Sunnyside

Probability of equal or lesser temperature

0.0 0.2 0.4 0.6 0.8 1.0

Tm

in (

oC

)

-10

-5

0

5

10

15

CCSM3 CGCM3 ECHAM5 PCM1 Historical

Schlenker and Roberts (2008) National Bureau of Economic Research

Corn

Schlenker and Roberts (2008) National Bureau of Economic Research

What about Atmospheric CO2 increase?

IPCC Projections

Atmospheric CO2 concentration(mol mol-1)

Rel

ativ

e c

ha

ng

e

Atmospheric CO2 concentration(mol mol-1)

Rel

ativ

e c

ha

ng

e

Relative change of Radiation-use efficiency for wheat and maize simulated with the CTP model (Stockle and Kemanian, 2009)

Free-Air CO2 Enrichment (FACE) Experiments

Long et al. (2004) Annual Rev. Plant Biol. 55

Long et al. (2004) Annual Rev. Plant Biol. 55

Sour Orange Trees (13 years of data)

Idso and Kimball BA (2001) Env Exp Bot 46

Assessment Approach Relied on crop simulation modeling with

interpretation based on literature and expert opinions.

CropSyst, a cropping systems model developed at WSU was used for the assessment.

Insect and disease models were used to complement the evaluation.

CropSyst has been tested and applied in all continents and under a wide range of climatic

conditions

ClimGenClimGen

The WSU weather generator ClimGen was used to generate daily series of projected weather.CropSyst has been used for climate

change assessment in studies elsewhere.

Assessment Approach Focus on the major agricultural

commodities in terms of economic value: apples, potatoes, and wheat.

Wheat is the dominant dryland crop.

Potato is the main irrigated annual crop.

Apple is the main irrigated tree fruit crop.

Assessment Approach Daily weather data for the years 1975-2005

were used to establish a baseline for change.

Projections of daily precipitation and temperature from the four GCMs were used to define three climate change scenarios:

2020 (2010 – 2039)2040 (2030 – 2059)2080 (2070 – 2099)

Assessment Approach The following locations (crops) were

included in the analysis:

o Pullman (winter and spring wheat, high precipitation)

o Saint John (winter and spring wheat, intermediate precipitation)

o Lind (winter wheat, low precipitation)o Othello (potatoes, irrigated)o Sunnyside (apples, irrigated)

Assessment Approach Computer simulations of crop growth and

yield assumed adequate supply of water and nutrients and good control of pests and diseases.

The only variables were climate change and CO2 elevation.

The impact of possible irrigation water shortages was assessed in a complementary effort (hydrology sector).

Assessment Approach The A1B IPCC emission scenario was used

to project atmospheric CO2 concentration.

Crop biomass productivity (a parameter that affects several simulated processes including crop water use) was assumed to increase 20% with a CO2 change from 370 to 600 PPM (FACE experiments).

Results

Winter Wheat

Spring Wheat

Potatoes

Apples

Codling Moth

Average Number of Days of Powdery Mildew Risk

Conclusions It is projected that the impact of climate

change alone on selected but economically important crops in eastern WA would be generally mild in the short term (i.e., next couple of decades), but increasingly detrimental with time (potential yield losses reaching 25% for some crops by the end of the century).

Conclusions However, the projected CO2 increase is

expected to provide significant mitigation to the effect of warming.

In fact, if the projected beneficial effect of CO2 elevation are fully realized, some crops may obtain important yield gains.

Adaptation based on changes in management (e.g., planting dates) or on new research (e.g., better adapted varieties) can provide additional mitigation or further enhance CO2 effects.

Conclusions Caveats to consider:

o Possible changes in the frequency and persistence of extreme temperature effects are not well represented in current climate projections

o We have assumed good control of pests and diseases, but these could affect crops in ways not described here

o Availability of irrigation water may become a significant limiting factor in some areas.

Conclusions Caveats to consider:

o Focus of the study is on yields, but quality can be affected even when yields increase.

o The economic cost of adaptation (e.g., management for increased pest control or greater nitrogen fertilization requirements) should be accounted for in future studies.

Thank you.