Transcript Nitrogen Flows in Agricultural Systems: A Modeling Perspective

Assessment of Climate
Change Impact on Eastern
Washington Agriculture
Claudio O. Stöckle
Biological 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 CO2 Concentrations and Temperature
The 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).
Global Greenhouse Gas Trends
Source: IPCC
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)
1400
1400
Pullman (CCSM3)
1200
1000
1000
800
Precipitation
600
ETo
800
600
400
400
200
200
0
0
Baseline
1400
1200
Pullman (PCM1)
1200
2020
2040
2080
Sunnyside (CCSM3)
Baseline
1400
1200
1000
1000
800
800
600
600
400
400
200
200
0
0
Baseline
2020
2040
2080
2020
2040
2080
Sunnyside (PCM1)
Baseline
2020
2040
2080
Seasonal (April 1- Sept 30) Precipitation and
Potential Evapotranspiration ETo (mm)
1400
1400
Pullman (CCSM3)
1200
1000
1000
800
Precipitation
600
ETo
800
600
400
400
200
200
0
0
Baseline
1400
1200
Pullman (PCM1)
1200
2020
2040
2080
Baseline
1400
Sunnyside (CCSM3)
1200
1000
1000
800
800
600
600
400
400
200
200
0
Baseline
2020
2040
2080
2020
2040
2080
Sunnyside (PCM1)
0
Baseline
2020
2040
2080
Annual and Season Mean Temperature (oC)
Annual Mean Temperature
(oC)
Pullman
20
15
CCSM3
10
PCM1
5
0
Annual Mean Temperature
(oC)
25
25
Sunnyside
20
15
10
5
0
Baseline
25
Season Mean
Temperature (oC)
Season Mean
Temperature (oC)
25
Pullman
20
15
10
2020
2040
2080
Sunnyside
20
15
10
5
5
0
0
Baseline
2020
2040
2080
Baseline
2020
2040
2080
Annual Temperature Difference with Baseline (oC)
Sunnyside Annual
2020
2040
2080
CCSM3
1.9
2.8
3.6
PCM1
1.3
2.2
3.0
2020
2040
2080
CCSM3
1.8
2.9
3.8
PCM1
1.3
1.9
2.8
Sunnyside Seasonal
Change in frostfree period
(days)
Probability Distribution of Tmax (June/July)
45
40
CCSM3
CGCM3
ECHAM5
PCM1
Historical
Pullman
Tmax (oC)
35
30
25
20
15
10
0.0
0.2
0.4
0.6
0.8
Probability of equal or higher temperature
1.0
Probability Distribution of Tmin (April)
15
Sunnyside
Tmin (oC)
10
5
0
CCSM3
CGCM3
ECHAM5
PCM1
Historical
-5
-10
0.0
0.2
0.4
0.6
0.8
Probability of equal or lesser temperature
1.0
Schlenker and Roberts (2008) National Bureau of Economic Research
Corn
Schlenker and Roberts (2008) National Bureau of
Economic Research
What about Atmospheric CO2 increase?
Atmospheric CO2 Concentration
(PPM)
900
800
700
600
500
B1
400
A1B
A2
300
200
100
0
1900
1950
2000
2050
2100
Year
IPCC Projections
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
ClimGen
CropSyst has been used for climate
change assessment in studies
elsewhere.
The WSU weather
generator ClimGen
was used to
generate daily
series of projected
weather.
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
o
o
o
o
Pullman (winter and spring wheat, high
precipitation)
Saint John (winter and spring wheat,
intermediate precipitation)
Lind (winter wheat, low precipitation)
Othello (potatoes, irrigated)
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
to project atmospheric
CO2 concentration.
Atmospheric
CO2…
 The A1B IPCC emission scenario was used
800
700
600
500
400
300
200
100
0
1900
1950
2000
2050
2100
 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
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
Pullman (6.2 Mg/ha)
No CO2
CO2
2020
2040
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
2080
Lind (4.3 Mg/ha)
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
St. John (5.1 Mg/ha)
2020
2020
2040
2080
2040
2080
1.6
Pullman (4.4 Mg/ha)
1.4
Spring Wheat
1.2
1
No CO2
0.8
CO2
0.6
CO2 + Adaptation
0.4
0.2
0
2020
2040
2080
1.6
St. John (3.7 Mg/ha)
1.4
1.2
1
0.8
0.6
0.4
0.2
0
2020
2040
2080
Potatoes
1.6
Othello (81 Mg/ha)
1.4
1.2
1
No CO2
CO2
CO2 + Adaptation
0.8
0.6
0.4
0.2
0
2020
2040
2080
Apples
1.6
Sunnyside (61 Mg/ha)
1.4
1.2
1
No CO2
CO2
CO2 + Adaptation
0.8
0.6
0.4
0.2
0
2020
2040
2080
Codling Moth
250
Day of the Year
200
150
First Flight
First Generation
Second Generation
Fraction Third Generation
100
50
0
Historical
2020
2040
2080
Average Number of Days of Powdery
Mildew Risk
14
Grapes
12
Low
Medium
High
8
6
4
16
2
14
Cherries
0
Historical
2020
2040
12
2080
10
Days
Days
10
8
6
4
2
0
Historical
2020
2040
2080
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.