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Agriculture and Water Resources Cynthia Rosenzweig and Max Campos

Agriculture and Water Resources Cynthia Rosenzweig and Max Campos. AIACC Trieste Project Development Workshop. crosenzweig@giss.nasa.gov. Linking Regional Water Supplies and Water Demands.

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Agriculture and Water Resources Cynthia Rosenzweig and Max Campos

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  1. Agriculture and Water Resources Cynthia Rosenzweig and Max Campos AIACC Trieste Project Development Workshop crosenzweig@giss.nasa.gov

  2. Linking Regional Water Supplies and Water Demands Availability of water for agriculture in the coming decades depends not only on changing climate, but also on population, economic development, and technology

  3. SCENARIOS Population, Development, Technology SCENARIOS GCMs variability WATBAL Streamflow PET CLIMATE Precip., Temp. Solar Rad. CERES Crop water demand WEAP Evaluation Planning CROPWAT Regional irrigation 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. • 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

  4. Maize production in 1998 Argentina 1995 Brazil Low China Rest High 1600 Hungary & 1400 Romania USA 1200 Soybean production in 1998 1000 Population (millions) 2020 Argentina 800 Rest Brazil 600 China 400 USA Hungary & Romania (<0.01%) 200 0 Brazil China US Cynthia Rosenzweig1, David C. Major1, Kenneth Strzepek2, Ana Iglesias1, David Yates2, Alyssa Holt2, and Daniel Hillel1

  5. SCENARIOS GCMs variability Crop yields and water demandsare 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. Monthly climate (27 water regions) Daily climate (34 sites) REGIONAL DATABASES Crops Soils Yields Management Process models CERES SOYGRO Empirical model CROPWAT Yields Irrigation Phenology PET, ETc Kc CLIMATE CHANGE EFFECTS Phenology CO2 Kc Net irrigation all crops Spatial database Crop areas Irrig. efficiency TOTAL IRRIGATION DEMAND Crop water demand model interactions

  6. 2 R = 0.55 Ann. avg mod. = 208 mm Ann. avg obs. = 213 mm 1.80 1.60 1.40 Modeled vs. observed monthly runoff for the Titsza water region. 1.20 1.00 Effective precipitation Evapotranspiration 0.80 0.60 0.40 Modeled 0.20 Observed 0.00 mm/day Soil moisture zone Oct-79 Oct-80 Oct-81 Oct-82 Oct-83 Oct-84 Oct-85 Oct-86 Surface runoff Relative depth Sub-surface runoff Baseflow Water supplycalculated 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 Kaczmarek, 1993; Yates, 1996 Ken Strzepek, Univ. of Colorado, Boulder

  7. Working with Multiple Models: Consistency at different Spatial Scales

  8. 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

  9. 6 4 Annual Runoff (m3x1011) 2 0 Danube Argentina Brazil China USA 100 90 80 Annual Reliability (%) 70 60 50 Danube Argentina Brazil China US GISS Current MPI GFDL Change in annual runoff and water reliability for the 2020s with change climate scenarios

  10. 400 ) Current s f 300 GFDL c ( MPI f f HC o 200 n u R 100 50 O N D J F M A M J J A S Months Key Water Resource Results Possible decadal surprises Change in seasonality Strzepek et al., 1999

  11. Reference 2010 Reference 2020 Reference 1995 GISS 2010 GISS 2020 Medium stress High stress Low stress No stress Projected change in environmental stress for the Danube water regions • 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.

  12. Adaptation: Optimizing crop varieties Crop Coefficients Corn 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) P1 P2 P5 G2 G5

  13. Testing adaptation with crop models

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

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