This document summarizes approaches to modeling the linkages between water and agriculture in economic models. It provides examples of global and regional models that have incorporated water constraints and relationships. Key challenges include capturing both the physical quantities and spatial dimensions of water use, as well as limitations in data on irrigated areas and water allocation. The document concludes with a quantitative experiment simulating the impacts of groundwater declines in northern India on global food production, prices, and trade.

1. Imposing constraints on water in
market projections
Accounting for environment in market models
Siwa Msangi
IFPRI
World Market Outlook Conference
Washington DC, USA
8-9 June, 2015

2. The linkage between water and food
Next to land, water is one of the most important
resources supporting agriculture
• It’s not always managed (as in rainfed agriculture)
– but remains essential to growth
• In biophysical modelling of crop growth – water is a
key yield-limiting factor (along with nitrogen) and is
always made explicit
• In economic modelling of agriculture – water tends
to only appear in activity-based farm models (if at
all) – esp if irrigation is involved

3. Various approaches and key
challenges to modeling water and
agriculture linkages
Page 3

4. Water in Ag farm or market models
Water fits more ‘naturally’ into farm-level ag models
• It can be accounted for as one of the inputs to
production (w/in an explicit yield or prodn function)
• Even if yield is fixed and input use is accounted for
by Leontief coeffs – water can be a constraint
• Even w/o explicit pricing of water (which is rare in
agriculture) – shadow values can be derived
• W/in a multi-market framework – the yield-water
relationship becomes more reduced-form and the
representation of water tends to become less
explicit – except for a few cases where water
accounting modules have been added

5. Examples of mkt models with water
Type of model Name (institution) Key features
Global PE IMPACT (IFPRI) Inter-sectoral water alloc model determines
avail for ag. Supported by hydrological balance
model and calculation of yield-water
relationship
Watersim (IWMI) Approach largely based on IMPACT – different
way of representing basin efficiencies and
water alloc rules
GLOBIOM (IIASA) Disagg prodn systems into rainfed/irrig,
includes irrig tech & costs, EPIC captures
water-balance & crop cons use (no non-ag use)
Global CGE GTAP-W Numerous variants of GTAP-based models
incorporating water
• Calzadilla, Tol, Redahnz – now a formalized
GTAP-W database
• Mirage variant
Regional PE CAPRI (IPTS/U Bonn) Exploratory effort to incorporate water
(starting with 2 NUTS regions – Andalusia and
mid-Pyrenees) – w/irrig & water use modules

6. Model examples with water (cont)
Type of model Name (institution) Key features
Regional PE USMP/REAP (USDA) Regional math programming model
which can take resource constraints like
water directly into account
Various ag sector
models (ASME – Egypt)
Math programming models with
explicit constraints and yield-water
relationships
SWAP model (Univ
California)
Uses explicit prodn function – linked to
statewide hydrological model to obtain
surface & GW availability
Country-level
PE-GE analysis
Terry Roe & Xinshen
Diao (various papers
with co-authors 2000-
2005)
Combines a top-to-bottom and
bottom-up linkage b/w country-level
CGE model for Morroco to illustrate:
• The impact of trade policy changes
on farm-level water use
• The impact of changes in property
rights & water mgmt on mkts, prices
and other sectors at country-level

7. Key challenges to capturing water
The question of ‘quantities vs prices’ applies to how one choses
to capture water in ag farm or mkt models
• Primal vs dual – many find it preferable to capture the
physical aspects of water use in ag (kg per m3) rather than
the cost side (given rare pricing of water)
• The biophysical requirements of crop growth wrt water are
fairly well-known and can be captured in agronomic
modelling approaches (i.e. yld penalties)
• There is a spatial as well as a temporal dimension to water –
it matters when in the crop cycle the deficit happens, and
where water is located relative to the crops that need it (for
irrigation)
• The water dimensions of livestock are typically not well-
captured in any modeling (biophysical or economic)
• Nothing on aquaculture either (esp for inland systems) - data
• Water quality dimensions are also rarely addressed

8. Key challenges (cont.)
As in all aspects of modelling agriculture – data is
always a challenge (more so for some regions)
• Getting a good handle of how much irrigated area
there really is – can be challenging for some regions
• Sometimes the definition of what really is irrigated is
not straightforward (e.g. the Fadama in Nigeria)
• Often times there are discrepancies between various
sources of data (OECD, FAO Aquastat, Kassel/U
Frankfurt)
• This is a key piece of data to have if doing basin-
level water modelling in order to determine the
balance between ET, runoff, precip, deep percolation

9. Quantitative Experiment:
Groundwater Depletion in India &
Implications for Global Food
Balance
Page 9

10. Simple quantitative experiment
• In this experiment, we simulate what would
happen if the groundwater availability in northern
India (Gujarat, Rajasthan, Haryana, Uttar Pradesh,
Madhya Pradesh, Bihar) were to decrease
dramatically over 2010-2020
• Essentially halving the water available for irrigation
(since GW supplies ~50% irrigated area)
• Simulated over the corresponding IMPACT basins
(Indus, Ganges, Mahi-Tapti & Luni basins)
• Observe the impact on food production, prices,
consumption and malnutrition in India & the world
Page 10

11. Ganges
Mahi-Tapti
Luni
Indus
Key Indian basins targeted in scenario

12. Global cereal production changes
Page 12

13. Shifts in global cereal net trade to
compensate
Page 13

14. Increases in global cereal prices
Page 14

15. Page 15
 A more widespread problem in India would be even more
dramatic ( “Too Big to Fail” !)
 Similar effects would be observed if the North China
Plain were subjected to such a scenario
 This is purely illustrative of the importance of India to the
global food balance – and the implications of it falling into
deficit due to environmental impacts
 This underscores the importance of water for food
Summary
The impact of groundwater declines in northern India
have a sizable impact on food production, trade and
security in both India and the world
Page 15

16. Conclusions
• Water is one of the key constraints to ag –
but not widely captured in ag mkt model
• Need to take the first step – separate
harvested area b/w irrigated & rainfed
– If rainfed – enters as an exog factor
– if irrigated – is part of on-farm mgmt decisions
• Tend to prefer the biophysical approach to
capture the impacts on yield
• Ag water can be valued but is rarely priced –
therefore a mkt-based alloc is more of a
“scenario” rather than the baseline case

17. Thank you!