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. WATBAL Streamflow PET WATBAL Streamflow PET CLIMATE Precip., Temp. Solar Rad. CLIMATE Precip., Temp. Solar Rad. WEAP Evaluation Planning WEAP Evaluation Planning CERES Crop water demand CERES Crop water demand CROPWAT Regional irrigation CROPWAT Regional irrigation SCENARIOS GCMs variability SCENARIOS GCMs variability SCENARIOS Population, Development, Technology SCENARIOS Population, 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 Rosenzweig 1, David C. Major 1, Kenneth Strzepek 2, Ana Iglesias 1, David Yates 2, Alyssa Holt 2, and Daniel Hillel 1 China Rest USA Brazil Argentina Hungary & Romania China Rest USA Brazil Argentina Hungary & Romania (<0.01%) Maize production in 1998 Soybean production in BrazilChinaUS 1995 Low High Population (millions) 2020

SCENARIOS GCMs variability SCENARIOS GCMs variability Daily climate (34 sites) Monthly climate (27 water regions) Process models CERES SOYGRO Yields Irrigation Phenology PET, ETc Kc CLIMATE CHANGE EFFECTS Phenology CO2 Kc Empirical model CROPWAT Net irrigation all crops TOTAL IRRIGATION DEMAND REGIONAL DATABASES Crops Soils Yields Management Spatial database Crop areas Irrig. 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 processes Modeled vs. observed monthly runoff for the Titsza water region Oct-79Oct-80Oct-81Oct-82Oct-83Oct-84Oct-85Oct-86 mm/day R 2 = 0.55 Ann. avg mod. = 208 mm Ann. avg obs. = 213 mm Modeled Observed Sub-surface runoff Soil moisture zone Evapotranspiration Effective precipitation Surface runoff Baseflow Relative depth Kaczmarek, 1993; Yates, 1996 Ken Strzepek, Univ. of Colorado, Boulder

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, 1997 Boston, MA

CurrentMPIGFDL GISS DanubeArgentinaBrazilChinaUSA Annual Runoff (m 3 x10 11 ) DanubeArgentinaBrazilChinaUS Annual Reliability (%) Change in annual runoff and water reliability for the 2020s with change climate scenarios

Possible decadal surprises Change 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 stress High stress Low stress No stress Reference 1995 Reference 2010 GISS 2010GISS 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 P2 P5 G2 G5 P1 P2 P5 G2 G5

Testing adaptation with crop models

Nitrogen Leached: Effect of Precipitation Corn Growing Season Growing Season Precipitation Nitrogen Leached