development of a global hydrological model for integrated assessment modeling

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

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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

Source: Shiklomanov (2000)

Global Water Consumption

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Volu

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km

3/y

r)

Global Water Consumption

Irrigation Water Consumption

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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

“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

IMPACT – Partial Equilibrium Agricultural Sector Model

Source: Rosegrant et al. (2012)

Spatial Units of IMPACT Model Simulations

River Basins

Food Producing Unit

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Linking Global Hydrology Model to Water Management Simulation

Source: Zhu and Ringler (2012)

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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

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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


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(a) Botswana Precip

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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: GPCC v5

Mean Annual Precipitation 1971-2000

Source: IGHM simulation (2013)

Mean Annual Potential ET 1971-1990


Open water evaporation (lakes and rivers)

Runoff Simulation - Annual


Runoff Simulation - January


Runoff Simulation - July


Runoff Simulation Jan-Dec

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Middle East & North Africa

Europe Developed

South Asia

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North America

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Latin America & Caribbean

Source: IGHM simulation using the 1971-2000 climatology. Unit: km3/yr.

Water Resource Distribution

Mean Annual Runoff Changes under CSIRO-A1b Scenario in 2050


Mean Annual Runoff Changes under CSIRO-b1 Scenario in 2050


Mean Annual Runoff Changes under MIROC-a1b Scenario in 2050


Mean Annual Runoff Changes under MIROC-b1 Scenario in 2050


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

development of a global hydrological model for integrated assessment modeling

Engineering