1) The document discusses the development of a global hydrological model (IGHM) to simulate the global water cycle and quantify water availability under climate change for integrated assessment modeling of global food and water systems. 2) IGHM simulates the natural hydrological cycle on a 0.5 degree grid at monthly time steps and has been calibrated and validated against observed runoff data with good results. 3) Model simulations of historical and future climate scenarios show changes in runoff patterns and amounts at the global scale that could impact water resources availability.

1. Tingju Zhu, Claudia Ringler, Mark W. Rosegrant
Development of a Global Hydrological Model for
Integrated Assessment Modeling of
Global Climate Change
International Food Policy Research Institute
Washington, DC
World Environmental & Water Resources Congress 2013, Cincinnati, OH

2. 2
Global Hydrologic Modeling in the Context of
“Water4Food”
 Irrigation is the largest water user, and key for securing
future food supply
• Accounting for 70% global water withdraw, and 90%
global water consumption
• Accounting for less than 20% of global cropland, but
contributing ~40% of global cereals production
 Integrated modeling of global water and food systems
requires spatially explicit simulations of water availability
 Climate change impacts and adaptations modeling (for
water management and agriculture) require quantifying
hydrological responses to climate change

3. Source: Shiklomanov (2000)
Global Water Consumption
0
500
1000
1500
2000
2500
1900 1920 1940 1960 1980 2000
Volume(km
3
/yr)
Global Water
Consumption
Irrigation Water
Consumption

4. 4
Global Hydrologic Modeling in the Context of
“Water4Food”
 Irrigation is the largest water user, and key for securing
future food supply
• Accounting for 70% global water withdraw, and 90%
global water consumption
• Accounting for less than 20% of global cropland, but
contributing ~40% of global cereals production
 Integrated modeling of global water and food systems
requires spatially explicit simulations of water availability
 Climate change impacts and adaptations modeling (for
water management and agriculture) require quantifying
hydrological responses to climate change

5. “Linking” Models
 Global Hydrologic Model (IGHM) simulates natural
hydrological cycle, providing a consistent estimation
of water availability over space and time
 Water Management Model simulates human
interventions to water resources systems, enabling
tests of policy and investment scenarios
 Together, the “water models” estimate the effects of
water stress on agricultural production, which affect
trade, consumption, and malnutrition

6. IMPACT – Partial Equilibrium Agricultural Sector Model
Source: Rosegrant et al. (2012)

7. Spatial Units of IMPACT Model Simulations
River Basins
Food Producing Unit

8. 8
Linking Global Hydrology Model to Water Management Simulation
Source: Zhu and Ringler (2012)

9. 9
Scope vs. Complexity – How detailed is detailed enough for
global water modeling?
Determinants of model complexity
• Research questions
• Data availability and quality
• Understanding of processes and settings
• Applicability to a wide range of climatic
conditions
Scale-related issues
• Processes take place on all scales. Analysis
of the smallest scale only does not provide
information on processes that take place on
larger scales.
• Sub-grid variability of model parameters --
spatial heterogeneity in a large grid cell

10. 10
IGHM Main Structure and Major Assumption
 GRPET n 





 Spatial Resolution: 0.5˚ latitude x 0.5˚ longitude grid cells covering the entire global
land surface except the Antarctic
 Temporal Resolution: Monthly simulation over multi-decadal period
Potential Evapotranspiration - Priestley-Taylor equation
Runoff Generation
Variable soil moisture holding capacity
within a grid cell
Linear reservoir representing
groundwater modulation of base flow
Source: Zhu and Ringler (2012)

11. 11
0
100
200
300
400
500
600
700
8000
1000
2000
3000
4000
5000
6000
7000
Jan-71
Jan-72
Jan-73
Jan-74
Jan-75
Jan-76
Jan-77
Jan-78
Jan-79
Jan-80
Jan-81
Jan-82
Jan-83
Jan-84
Jan-85
Jan-86
Jan-87
Jan-88
Jan-89
Jan-90
Jan-91
Jan-92
Jan-93
Jan-94
Jan-95
Jan-96
Jan-97
Jan-98
Jan-99
Jan-00
Precipitation
Runoff
(a) Botswana Precip
Qsim
Qobs
Nash-Sutcliffe model efficiency coefficient is 0.913 in the calibration
period (1971-85) and is 0.906 in the validation period (1986-2000).
IGHM Model Runoff Calibration and Validation for Botswana
Catchment of the Limpopo River Basin
Source: Zhu and Ringler (2012)

12. Source: GPCC v5
Mean Annual Precipitation 1971-2000

13. Source: IGHM simulation (2013)
Mean Annual Potential ET 1971-1990

14. Source: IGHM simulation (2013)
Open water evaporation (lakes and rivers)
Runoff Simulation - Annual

15. Source: IGHM simulation (2013)
Runoff Simulation - January

16. Source: IGHM simulation (2013)
Runoff Simulation - July

17. Source: IGHM simulation (2013)
Runoff Simulation Jan-Dec

18. 179
1570
1749
3762
4700
4916
8684
13232
0 2000 4000 6000 8000 10000 12000 14000
Middle East & North Africa
Europe Developed
South Asia
Sub-Saharan Africa
North America
Europe & Central Asia
East Asia & Pacific
Latin America & Caribbean
Source: IGHM simulation using the 1971-2000 climatology. Unit: km3/yr.
Water Resource Distribution

19. Mean Annual Runoff Changes under CSIRO-A1b Scenario in 2050
Source: IGHM simulation (2013)

20. Mean Annual Runoff Changes under CSIRO-b1 Scenario in 2050
Source: IGHM simulation (2013)

21. Mean Annual Runoff Changes under MIROC-a1b Scenario in 2050
Source: IGHM simulation (2013)

22. Mean Annual Runoff Changes under MIROC-b1 Scenario in 2050
Source: IGHM simulation (2013)

23. Conclusions
 Global hydrological modeling is needed for global
water and food system modeling, and other IAM
efforts
 Existing global database (e.g. climate, soil, LCLU,
typology) make possible hydrological modeling at
global scale
 Tradeoff between model complexity and spatial
scope
 Inter-model comparisons (e.g. Water-MIP) can
potentially improve model performance