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Agriculture and Water Resources
Cynthia Rosenzweig and Max Campos
AIACC Trieste Project Development Workshop
Availability of water for agriculture in the coming decades depends not only on changing climate, but also on population, economic development, and technology
Linking Regional Water Supplies and Water Demands
Water Availability: Five International Case Studies
Rosenzweig et al., 1999, 2001
Linking a suite of models in order to improve projections of water availability, by taking potential changes in both water supply and demand into account.
WATBALStreamflow
PET
WATBALStreamflow
PET
CLIMATEPrecip., Temp.
Solar Rad.
CLIMATEPrecip., Temp.
Solar Rad.
WEAP
EvaluationPlanning
WEAP
EvaluationPlanning
CERESCrop water
demand
CERESCrop water
demand
CROPWATRegionalirrigation
CROPWATRegionalirrigation
SCENARIOSGCMs
variability
SCENARIOSGCMs
variability
SCENARIOSPopulation, Development,
Technology
SCENARIOSPopulation, Development,
Technology
• Runoff, water demands, and water system reliability
• Environmental stress due to human use of water resources
• Crop yields based on consistent projections of changes in water supply and demand
Cynthia Rosenzweig1, David C. Major1, Kenneth Strzepek2, Ana Iglesias1, David Yates2, Alyssa Holt2, and Daniel Hillel1
China
Rest
USA
BrazilArgentina
Hungary & Romania
China
Rest
USA
Brazil
Argentina
Hungary & Romania (<0.01%)
Maize production in 1998
Soybean production in 1998
0
200
400
600
800
1000
1200
1400
1600
Brazil China US
1995
Low
High
Population (millions)2020
SCENARIOSGCMs
variability
SCENARIOSGCMs
variability
Dailyclimate
(34 sites)
Monthlyclimate
(27 water regions)
ProcessmodelsCERES
SOYGRO
Yields Irrigation
Phenology PET, ETc
Kc
CLIMATECHANGEEFFECTS Phenology
CO2 Kc
Empiricalmodel
CROPWAT
Net irrigationall crops
TOTALIRRIGATION
DEMAND
REGIONALDATABASES
Crops Soils
YieldsManagement
Spatialdatabase
Crop areasIrrig. efficiency
Crop yields and water demands
are estimated with process based crop models (calibrated and validated).
The ratios (Kc) between simulated and actual crop ET are used to estimate regional water demand with CROPWAT.
Irrigation demand is adjusted by a regional irrigation efficiency.
Crop water demand model interactions
Water supply calculated using WATBAL
PET calculation by Priestley-Taylor (ensuring consistency with the crop models
WATBAL is run for 50 yrs of climate change and variability scenarios, using SAMS WG.
Schematic of WATBAL processesModeled vs. observed monthly runoff for the Titsza water region.
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
Oct
-79
Oct
-80
Oct
-81
Oct
-82
Oct
-83
Oct
-84
Oct
-85
Oct
-86
mm
/day
R2 = 0.55Ann. avg mod. = 208 mmAnn. avg obs. = 213 mm
ModeledObserved
Sub-surfacerunoff
Soil moisture zone
EvapotranspirationEffective precipitation
Surfacerunoff
Baseflow
Relativedepth
Kaczmarek, 1993; Yates, 1996Ken Strzepek, Univ. of Colorado, Boulder
Harbin (China)
0
1
2
3
4
5
6
0 50 100 150 200 250 300 350
Day of Year
ET
0 (m
m/d
ay)
HARA
w bHARA
Dier Songhua Jian
Nen Jian
Songhua Jian
Grand Island (Nebraska)
0
1
2
3
4
5
6
7
8
0 50 100 150 200 250 300 350
Day of Year
ET
0 (m
m/d
ay)
GNEA
w bGNEA
Low er Missouri
Working with Multiple Models: Consistency at different Spatial Scales
Balance of water supply and demand is undertaken in the Water Evaluation and Planning (WEAP) model.
Population and GDP drivers are used to calculate future industrial, municipal, and domestic water use, and forecast increases in irrigation areas. (UN population forecasts and economic forecasts of The Netherlands Central Planning Bureau.)
WEAP schematic for the water regions in the US Corn Belt
Stockholm Environment Institute, 1997Boston, MA
Current MPI GFDL GISS
0
2
4
6
Danube Argentina Brazil China USA
An
nu
al R
un
off
(m3 x
1011
)
50
60
70
80
90
100
Danube Argentina Brazil China US
An
nu
al R
elia
bil
ity
(%)
Change in annual runoff and water reliability for the 2020s with change climate scenarios
Possible decadalsurprises
0
2 0
4 0
6 0
8 0
1 00
1 99 0 2 00 0 2 01 0 2 02 0 2 04 0 2 04 0 2 05 0
Year
Per
cent
age
R eliab ilityD em and m et
400
300
200
100
50O N D
MonthsJ F M A M J J A S
Run
off
(cfs
) CurrentGFDLMPIHCChange in
seasonality
Key Water Resource Results
Strzepek et al., 1999
Demand to supply ratio (environmental stress) measures degree of economic development and impacts on ecosystems.
If the demand to supply ratio is low, then there is ample water for ecosystem services.
Projected change in environmental stress for the Danube water regions
Medium stressHigh stress
Low stressNo stress
Reference 1995 Reference 2010
GISS 2010 GISS 2020
Reference 2020
P1 Juvenile phase (growing degree days base 8 C from emergence to end of the juvenile phase)
P2 Photoperiod sensitivity
P5 Grain filling duration (growing degree days base 8 form silking to physiological maturity)
G2 Potential kernel number
G5 Potential kernel weight (growth rate)
Crop Coefficients Corn
Adaptation: Optimizing crop varieties
P1
P2P5
G2G5
P1
P2P5
G2G5
Irrigation Demand mm/ha Base ClimateEffect of Cultivar and Planting Date
0
50
100
150
200
250
300
350
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Cultivars
day 100
day 110
day 120
day 130
Testing adaptation with crop models
Nitrogen Leaching (kg/ha) Base ClimateEffect of Cultivar and Planting Date
15.3
15.4
15.5
15.6
15.7
15.8
15.9
16
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Cultivars
day 130
Nitrogen Leached: Effect of Precipitation
47.848.1
47.950.4
47.848.1
47.9
50.4
0 50 100 150 200 250
1
2
3
4
. sowing to flowering floweing to maturity
434
469.3
483.1
493.8
400 420 440 460 480 500
1
2
3
4
growing season precipitation
10.912.6
14.115.7
0 5 10 15 20
1
2
3
4
nitrogen leached
Corn Growing Season
Growing Season Precipitation
Nitrogen Leached
