Key note presentation at the 2nd International Forum on Water and Food, 10-14 November, 2008, Addis Ababa, Ethiopia

1. The Basin Focal Projects of
the CPWF
An interesting journey

2. Journey plan (mainly retrospective)
Journey
starts First lap Second Third lap
Global or lap How much do
Where are we all
local people gain
going? Where’s the
problem? from water?
water?
Who’s on the bus?
Fourth
lap
Fifth lap Poverty,
What can impacts?
change?

3. Journey
starts
Where are we all
going?
Who’s on the bus?
The water and food problem

4. World food crisis
• Reasons
– Declining supply
– Increasing demand
– Biofuels
– Commodity speculation

5. World food crisis
• Reasons
– Declining supply rm
e
-t
Mid
– Increasing demandrm
te
Lo ng-
– Biofuels
– Commodity speculation

6. Basis of food demand:
Time for each billion 1800-2050
…plus increased meat consumption
(Molden 2007)

7. Until recently, food demand has
been met globally
300
Food Production
250
Food Production
200 per capita
Index (1961=100)
Cropland per
150 capita
Food Prices
100
50
A success
0
1961 1971 1981 1991 2001 story

8. But this leads to increasing conflict with other users
Agriculture uses > 70% of water

9. …exacerbates World Water Crisis:
Declining per capita availability of water
‘000 m3
16
14 Africa
12
10
8 World
6 Asia
4
2
MENA
0
1960 1990 2025

10. ….enter the CPWF
• We need to improve the efficiency of
water use, …. more “crop per drop” in
agriculture, which is the largest
consumer of water.
CPWF Proposal 2002

11. Need for more strategic information
A strong imperative for action
The global food and water crisis
CPWF But how are these
coupled?
phase 1
Many good projects on the ground
Change ultimately must be realized on the ground

12. Basin focal projects
• Strategic research projects
– 9+1 basins
• Intended to fill the ’middle-ground’
– link project activities with the global problem
• Need to examine how water, agriculture
and poverty are coupled

13. First of 4 BFPs started in 2005
IWMI
CSIRO
Niger
IRD
UC Davis

14. 6 remaining BFPs started in 2008
IFPRI
IWMI
IRD IWMI
KCL Niger
FANRPAN

15. Journey
starts First lap
Where are we all
How to
describe the
…to local
going?
problem? Global …
Who’s on the bus?

16. Global -to local
GLOBAL
Basin scale
Systems interact
Local Scale
Local impacts on land use
and livelihoods

17. Analyzing Water Food Livelihood systems in
basins
Second
Water
lap
Analysis of
water use
Where’s the
de wa asin
d d
Ot nds
sy on
at an e
m te g
m
w m as
water?
he fo
ste
a
de ncre
in
r
cre
I
r
er
r
Second lap Second
Basin-
Analysis of Increased demand on
Food
water
Where’s the food system People
lap
scale
poverty
productivity in
water? Where’s the
analysis
basins
water?

18. Journey
starts First lap Second
Global or lap
Where are we all
local
going? Where’s the
problem?
water?
Who’s on the bus?
Water in basins

19. Some basins are wetter than others
1
ET (normalised for Etp)
0.8
0.6
Volta Mekong
0.4 Indus Ganges
Yellow Sao Francisco
Limpopo Niger
0.2
Nile
Karkheh
0
0 0.5 1 1.5
Rainfall (Normalised for Etp)
From Mac Kirby

20. Water use supports varied livelihoods
M
M eko ng
1,19 5 b cm
Ganges
1,167 bcm
Sa o Fr a nc i s c o
G
622 bcm
SF
Nile Suppy limit
Ni
2,042 bcm
Capacity limit
1.0
Ganges
ET / ETot
p
Sao Francisco
Lim popo
229 bcm
L Fish
0.5 Mekong
Volta
Crops
Nile
Limpopo
Yellow River
Livestock
Karkeh Indus
Yellow
YR
384 bcm Irrigation
0.0 Andean
0.00 0.50 1.00 1.50 2.00
K ar kheh
K
2 1, 4 0 2 mcm
Net runoff Rain / ETpot
Rainfed cropping
Grass
Woodland / other
Irrigation

21. Hydrology matters to livelihoods
Songkhram Wet Songkhram Dry
David Blake

22. Rainfed ag. by far the
biggest user 0.35
Rainfall
Evaporation or Rainfall (m)
0.30 ETo
0.25
0.20
0.15
0.10
0.05
0.00
Jan Feb M Apr M Jun Jul Aug Sep O N Dec
ar ay ct ov
45000
Calculated
40000
Observed
35000
30000
Flow,
25000
20000
15000
10000
0.35
Rainfall
5000
Evaporation or Rainfall (m)
0.30 ETo
0.25
0 0.20
1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 0.15
0.10
0.05
0.00
Jan Feb M Apr M Jun Jul Aug Sep O N Dec
ar ay ct ov
Nile 0.35
Rainfall
Evaporation or Rainfall (m)
0.30 ETo
0.25
0.20
0.15
0.10
0.05
0.00
From Kirby et al., W-Use Jan Feb M Apr M Jun Jul Aug Sep O N Dec
ar ay ct ov

23. Volta
Devaraj de Condappa

24. Water use
Sao Francisco
0.30
Rainfall
Evaporation or Rainfall (m)
0.25 ETo
0.20
0.15
0.10
0.05
0.00
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
From Kirby et al., W-Use
accounts

25. Water use Niger 0.4
Rainfall
ETo
Evaporation or Rainfall (m)
0.3
0.2
0.1
0.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
0.4
Rainfall
Evaporation or Rainfall (m)
ETo
0.3
0.2
0.1
0.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
0.4
Rainfall
Evaporation or Rainfall (m)
ETo
0.3
0.2
0.1
0.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
0.4
Rainfall
Evaporation or Rainfall (m)
ETo
0.3
0.2
From Kirby et al., W-Use 0.1
accounts 0.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

26. But irrigation a major
user in Asia
Ganges
From Kirby et al., W-Use
accounts

27. Basin water use and population
(Preliminary analysis)
Indus Ganges
Water use (mcm) Water use (m cm)
0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 0 100,000 200,000 300,000 400,000
Irrigated
Irrigated
Woodland +
Woodland +
Grass
Grass
Rainfed
Rainfed
400 350 300 250 200 150 100 50 0
200 150 100 50 0
population (millions)
population (millions)
Mekong
Yellow
Water use (mcm) Water use (m cm)
0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 0 100,000 200,000 300,000 400,000 500,000
Irrigated Irrigated
Woodland + Woodland +
Grass Grass
Rainfed Rainfed
200 150 100 50 0
population (millions) 50 45 40 35 30 25 20 15 10 5 0
population (millions)
Relative values better than absolutes

28. Volta Lim popo
Water use (m cm ) Water use (m cm)
0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 0 50,000 100,000 150,000
Irrigated
Woodland +
Grass
Rainfed
20 15 10 5 0 20 15 10 5 0
population (m illions) population (millions)
Sao Francisco Nile
Water use (m cm ) Water use (mcm)
0 50,000 100,000 150,000 200,000 250,000 300,000 0 200,000 400,000 600,000 800,000 1,000,000
Irrigated
Woodland +
Grass
Rainfed
20 15 10 5 0 200 150 100 50 0
population (m illions) population (millions)

29. Grassland and rainfed dominate area Global Land cover classes – 2000 (UNEP)

30. In Asia, irrigation supports high population density Irrigation (IWMI)

31. Population density (persons per km2) – (CIESIN -2000)

32. Journey
starts First lap Second Third lap
Global or lap How much do
Where are we all
local people gain
going? Where’s the
problem? from water?
water?
Who’s on the bus?
Water productivity

33. Basic concept:
Water productivity must respond faster than demand
Demand
System WP response
crisis
time

34. In some places, water productivity is responding to demand
0.800
3
VN, Mekong Delta
Rice Water productivity, kg/m
0.600
Vietnam
VN Central
Highlands
0.400
Laos
0.200 Cambodia
NE Thailand
0.000
1990 1995 2000 2005
Year
Mac Kirby, 2007

35. Other basins, response low or patchy
Volta
IRD, 2007
Potential= 1-2 kg/m3

36. Actual Water-Productivity [the gain per m3 water
consumed] much lower than potential
Volta
IRD, 2007
Potential= 1-2 kg/m3

37. Livestock can be a major contributor to total W-Productivity

38. Fish? All we know for sure is that their contribution
is under-estimated – even in Mekong
1500 1,000
Cambodia 800
Laos
GVP, million $
GVP, million $
1000 600
400
500
200
0
0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Year
Year
Crop Livestock Fish low estimate
Crop Livestock Fisheries Fish - high estimate
5000
Thailand
5000
Vietnam
4000
GVP, million $
4000
GVP, million $
3000
3000
2000
2000
1000
1000
0
1995 1996 1997 1998 1999 2000 2001 2002 2003 0
Year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Crop Livestock Fish low estimate Crop Year
Livestock Inland fisheries

39. Full range of WPr will include
• Irrigated crops
• Rainfed
• Livestock
• Fisheries
– Capture
– Aquaculture
…most systems highly mixed

40. Journey
starts First lap Second Third lap
Global or lap How much do
Where are we all
local people gain
going? Where’s the
problem? from water?
water?
Who’s on the bus?
Fourth
lap
Poverty
impacts?

41. Water agriculture and
poverty
Measurable livelihood impacts

42. Water availability seems less influential than
gain per volume used (water productivity)
Per capita income vs.
GNI vs Water
water availability
50,000
40,000
GNI ($/cap PPP)
30,000
20,000
10,000
0
-500 0 500 1000 1500 2000 2500
-10,000
Size of bubble proportional to agriculture contribution to GDP
3
Water availability (m /cap)
World Bank, 2007

43. • The poorest tend to rely on agriculture
Agriculture vs GNI
50,000
Gross National Income ($/capita)
40,000
30,000
20,000 Size of bubble
proportional to rural
10,000 population
0
-10 0 10 20 30 40 50
-10,000
Agricultural contribution to GDP (% )
World Bank, 2007

44. Dynamics likely to be very different according to relative
function of agriculture
Agriculture agriculture to GDP
% Contribution of contribution to growth (%)
volta
Mekong
Sao Karkheh
Francisco
World Bank, 2007
% Rural poor

45. São Francisco: Drought is one poverty factor…of many
Drought
Poor
education
Access to
credit
Marcello Torres
et al., 2008

46. Karkheh, Iran: Farmers almost the poorest
Proportion below poverty line
Karkheh BFP team

47. .. Mekong
What people do can affect (shared) assets
Dam development
Changing land use,
shifting cultivation,
sustainability,
sedimentation
Seasonal water
shortage, poor soils,
low rice productivity
Fish &
environmental
impacts of upstream Salinisation, water
quality, highly
developed
Complex but understandable
Eric Kemp-Benedict, 2008

48. Journey
starts First lap Second Third lap
Global or lap How much do
Where are we all
local people gain
going? Where’s the
problem? from water?
water?
Who’s on the bus?
Fourth
lap
Fifth lap Poverty,
What can impacts?
change?
Interventions

49. Global-to-local coupled systems
GLOBAL
water and food systems considered separately
both impact on livelihoods
Basin scale
Systems interact through
(Unspecified) transfers
Local Scale
Local systems considered individually
Local impact not referenced to broader systems

50. Volta: Analysing effects of small reservoirs
(v 1.0)
• Trade-off:
– 2-fold increase in small
farmers irrigated area in
Burkina Faso
– vs.:
• Bagré (Burkina Faso):
– 20% reduction in inflows
(-200 mcm/y)
– national trade-off.
• Akosombo (Ghana):
– 1% reduction in inflows
(- 330 mcm/y)
– transboundary trade-off.
De Condappa and Volta BFP team

51. Sao Francisco:
Detailed hydro-
economic
modelling
Effect of water
constraints on
profit, labour….
Steve Vosti and SF BFP team

52. Conclusions
• Water use
– Huge volumes pass through agriculture
– Grassland a major user in African basins
– Irrigation supports vast numbers in Asia
• Water productivity
– Well below potential
– Major systems (eg LS) not accounted
• Water poverty
– Few direct relationships
– Ability to use water seems most important
– Ability strongly determined by system

53. Journey
starts First lap Second Third lap
Global or lap How much do
Where are we all
local people gain
going? Where’s the
problem? from water?
water?
Who’s on the bus?
Fourth
lap
Final lap Fifth lap Poverty,
What can impacts?
change?
Where to next?

54. Interventions within the CP itself
• Use BFPs to help “locate”
projects and topics firmly in
basins
– Status and opportunities for rainfed
productivity
– Basin-scale multiple users
– Pressure and change in basins
• Help feed impact pathways
– Data
– Analysis & insight
– New partners

55. Thank you
Special thanks to all BFPs