Transcript Michigan Irrigation: Opportunities and Challenges for

Climate Change and Agriculture
in the Great Lakes Region
Potential Impacts of Climatic
Variability and Change
Jeffrey A. Andresen
Dept. of Geography
Michigan State University
Climate Change and
Agricultural Productivity
• Crop, forage productivity and production costs
– Changing temperature, precipitation
– CO2 enrichment
– Occurrence of extremes
Climate Change and
Agricultural Productivity
• Soil suitability
– Soil Erosion
– Oxidation of organic matter
Climate Change and
Agricultural Productivity
• Livestock productivity and production cost
–
–
–
–
–
Animal mortality
Feed conversion rates
Rates of gain
Milk production
Conception rates
Climate Change and
Agricultural Productivity
• Irrigation water supply
– Changes in precipitation frequency and totals
– Changes in groundwater recharge rates
– Changes in nonagricultural usage
Year
1991
1985
1979
1973
1967
1961
1955
1949
1943
1937
1931
1925
1919
1913
1907
1901
1895
Temperature (C)
Mean Annual Observed Temperatures
Regional Average, 1895-1996
10
9
8
7
6
5
4
3
Year
1991
1985
1979
1973
1967
1961
1955
1949
1943
1937
1931
1925
1919
1913
1907
1901
950
900
850
800
750
700
650
600
550
500
1895
Precipitation (mm)
Total Annual Observed Precipitation
Regional Average, 1895-1996
Annual trends (yr-1) for selected simulated
variables, soybean, 1895-1996
SPPT
SPET
SET/ PET
PAVfp
DS
Yield
WUE
(mm)
(mm)
(mm)
(mm)
(kg/ha)
(kg/ha/mm)
Chatham
.722
.126
.190*
.235*
-.032
9.188*
.024*
Coldwater
.066
-.326*
.079*
.167
-.236*
1.783
.007
Eau Claire
.227
-.133*
.084*
.000
-.233*
4.543*
.009*
Grand
Rapids
1.881*
.090
.224*
.250*
-.308*
9.652*
.020*
Madison
.465
.047
.080*
.185*
-.079
4.944*
.010*
Waseca
1.286*
-.373*
.193*
.479*
-.294
15.069*
.032*
Worthington
-.235
-.564*
.126*
.167
-.164
6.390*
.014*
Station
* Trend significant at a=0.05 level
Projected Changes in Climate:
Great Lakes Region
• While considerable differences and
uncertainty exist, the majority of future
climate simulations suggest a warmer and
wetter climate across the region.
Estimated changes in national crop
production in 2030 relative to 2000
Soybeans
(Reilly et al., 2001)
Dryland
Irrigated
Yield
Yield
+11 to
+1 to +21%
+20%
+7 to +49%
+23%
Irrigation
Water Use
-32 to
+57%
0 to +18%
Soft Wheat
-3 to +58%
-5 to +5%
-26 to +3%
Potatoes
+7 to +8%
-4 to –1%
-3 to 0%
Crop
Corn
Ratios of GCM-projected future and POR historical
scenario crop yields averaged over all stations
Alfalfa
Scenario
Maize
Soybean
HADCM2
CGCM1
HADCM2
CGCM1
HADCM2
CGCM1
Future
without
CO2 vs.
Historical
1.06
1.06
1.11
1.26
1.13
1.24
Future
with CO2
vs.
Historical
1.18
1.16
1.23
1.40
1.64
1.81
Future
with CO2
vs. Future
without
CO2
1.11
1.09
1.11
1.11
1.45
1.46
Simulated Historical and Projected Future Growing Season
and Water Balance for Maize, Bay City, MI
Precipitation
(mm)
Evapotranspiration (mm)
Time
Period
HAD
CGCM
HAD
2026 –
2035
410
2090 –
2099
394
Historical
Runoff(mm)
Drainage(mm)
Change in
storage(mm)
CGCM
HAD
CGCM
HAD
CGCM
HAD
CGCM
314
-460 -432
-50
-20
-7
-5
106
143
267
-394 -364
-53
-29
-5
-4
57
130
321
-410
-48
-7
145
Agricultural strategies for coping
with climate change
• Adaptation
– Learn to change, adapt
• Mitigation
– Reduction of carbon and other GHG
• Carbon sequestration
• Production of fuels/energy from biomass/animal
waste
• Reduction of CH4 and N2O
• Use of alternative energy sources in production
Cumulative Simulated Frequency Distributions
of Adapted vs. Non-adapted Crop Cultivars,
2000-2099, with HADCM2 Model Data,
Coldwater, MI
1
Non-Adapted
Adapted
0.8
p(x)
0.6
0.4
0.2
0
0
2
4
6
8
Yield (tons/ha)
10
12
14
Probability Distribution of Simulated
Dryland Double Crop Soybean Yields
by Planting Date
Adrian, MI, 1895-2000
2500
Yield (kg/ha)
2000
1500
1-Jun
15-Jun
1-Jul
15-Jul
1000
500
0
1
0.8
0.6
0.4
Probability
0.2
0
Probability Distribution of Simulated
Irrigated Double Crop Soybean Yields
by Planting Date
Adrian, MI, 1895-2000
4500
4000
3500
Yield (kg/ha)
3000
1-Jun
15-Jun
1-Jul
15-Jul
2500
2000
1500
1000
500
0
1
0.8
0.6
0.4
Probability
0.2
0
Summary
• A changing climate leads to many potential
challenges for agricultural production systems.
• Observed climate has become wetter and
cloudier in the Great Lakes Region, especially
during the last 50 years.
• The single most important climatological
variable associated with crop yields regionally is
precipitation. Growing season length and GDD
accumulation were relatively more important at
northern study sites.
Summary (continued)
• The warmer and wetter climate suggested by the
many GCM projections for our region would
suggest yield increases for many crops. Yields of
some crops in the region might decline.
• A significant portion of any future yield increases
will be associated with CO2 enrichment.
• Recent research results suggest greater agronomic
potential for northern sections of the region, even
with less suitable soils.
• More research is needed, especially regarding
indirect impacts of climate change and extreme
events.