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The Basin Focal Projects of the CPWF
An interesting journey
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Journey plan (mainly retrospective)
First lap Global or
local problem?
Journey starts
Where are we all going?
Who’s on the bus?
Second lap
Where’s the water?
Third lap How much do people gain from water?
Fourth lap
Poverty, impacts?
Fifth lap What can change?
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Journey starts
Where are we all going?
Who’s on the bus?
The water and food problem
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World food crisis
• Reasons
– Declining supply
– Increasing demand
– Biofuels
– Commodity speculation
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World food crisis
• Reasons
– Declining supply
– Increasing demand
– Biofuels
– Commodity speculation
Mid-te
rm
Long-t
erm
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Basis of food demand:
Time for each billion 1800-2050
(Molden 2007)
…plus increased meat consumption
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0
50
100
150
200
250
300
1961 1971 1981 1991 2001
Index (1961=100)
Food Production
Food Productionper capita
Cropland percapita
Food Prices
Until recently, food demand has been met globally
A success story
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But this leads to increasing conflict with other users
Agriculture uses > 70% of water
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…exacerbates World Water Crisis: Declining per capita availability of water
0
2
4
6
8
10
12
14
16
1960 1990 2025
Africa
World
Asia
MENA
‘000 m3
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….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
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Need for more strategic information
A strong imperative for actionThe global food and water crisis
Many good projects on the groundChange ultimately must be realized on the ground
CPWF phase 1
But how are these coupled?
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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
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Niger
First of 4 BFPs started in 2005
UC Davis
IRD
CSIRO
IWMI
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Niger
6 remaining BFPs started in 2008
KCL
IRD
FANRPAN
IWMI
IWMIIFPRI
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First lap How to
describe the problem?
Journey starts
Where are we all going?
Who’s on the bus?
Global ……to local
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Global -to local
GLOBAL
Local Scale
Local impacts on land use and livelihoods
Basin scaleSystems interact
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Analyzing Water Food Livelihood systems in basins
Water
Food PeopleIncreased demand on food system
Increased
demand on
water system
Other
demand
s for
water
increasin
g
Second lap
Where’s the water?
Analysis of water use
Second lap Where’s the
water?
Analysis of water
productivity in basins
Second lap
Where’s the water?
Basin-scale poverty analysis
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First lap Global or
local problem?
Journey starts
Where are we all going?
Who’s on the bus?
Second lap
Where’s the water?
Water in basins
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Some basins are wetter than others
0
0.2
0.4
0.6
0.8
1
0 0.5 1 1.5
Rainfall (Normalised for Etp)
ET (norm
alised for Etp)
MekongGanges
Sao Francisco
IndusVolta
Limpopo Niger
Nile
Yellow
Karkheh
From Mac Kirby
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Water use supports varied livelihoods
Andean0.0
0.5
1.0
0.00 0.50 1.00 1.50 2.00
Rain / ETpot
ET / ET pot
Capacity limit
Suppy limit
Ganges
Mekong
Sao Francisco
Volta
Yellow River
NileLimpopo
IndusKarkeh
Fish
Livestock
Crops
Yellow
384 bcmYR
Limpopo
229 bcm
L
Nile
2,042 bcmNi
Sa o F r a n c i s c o
6 2 2 b c m
SF
M ekong
1,19 5 bcmMGanges
1,167 bcmG
Woodland / other
K a r kh eh
2 1 , 4 0 2 mcm
K
Grass
Irrigation
Rainfed croppingNet runoff
Irrigation
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Hydrology matters to livelihoods
David Blake
Songkhram Wet Songkhram Dry
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Nile
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
1951 1956 1961 1966 1971 1976 1981 1986 1991 1996
Flow,
Calculated
Observed
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Evaporation or Rainfall (m) Rainfall
ETo
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Evaporation or Rainfall (m) Rainfall
ETo
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Evaporation or Rainfall (m) Rainfall
ETo
From Kirby et al., W-Use
Rainfed ag. by far the
biggest user
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Devaraj de Condappa
Volta
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0.00
0.05
0.10
0.15
0.20
0.25
0.30
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Evaporation or Rainfall (m
)
Rainfall
ETo
Water use Sao Francisco
From Kirby et al., W-Use
accounts
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Water use Niger
0.0
0.1
0.2
0.3
0.4
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Evaporation or Rainfall (m
)
Rainfall
ETo
0.0
0.1
0.2
0.3
0.4
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Evaporation or Rainfall (m
)
Rainfall
ETo
0.0
0.1
0.2
0.3
0.4
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Evaporation or Rainfall (m
)
Rainfall
ETo
0.0
0.1
0.2
0.3
0.4
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Evaporation or Rainfall (m
)
Rainfall
ETo
From Kirby et al., W-Use
accounts
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Ganges
From Kirby et al., W-Use
accounts
But irrigation a major user in Asia
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Indus
200 150 100 50 0
population (millions)
0 50,000 100,000 150,000 200,000 250,000 300,000 350,000
Water use (mcm)
Basin water use and population
Woodland +
Grass
Irrigated
Rainfed
Yellow
200 150 100 50 0
population (millions)
0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000
Water use (mcm)
Mekong
50 45 40 35 30 25 20 15 10 5 0
population (millions)
0 100,000 200,000 300,000 400,000 500,000
Water use (mcm)
Ganges
400 350 300 250 200 150 100 50 0
population (millions)
0 100,000 200,000 300,000 400,000
Water use (mcm)
Woodland +
Grass
Irrigated
Rainfed
Woodland +
Grass
Irrigated
Rainfed
(Preliminary analysis)
Relative values better than absolutes
Woodland +
Grass
Irrigated
Rainfed
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Limpopo
20 15 10 5 0
population (millions)
0 50,000 100,000 150,000
Water use (mcm)
Volta
20 15 10 5 0population (millions)
0 50,000 100,000 150,000 200,000 250,000 300,000 350,000
Water use (mcm)
Sao Francisco
20 15 10 5 0
population (millions)
0 50,000 100,000 150,000 200,000 250,000 300,000
Water use (mcm)
Woodland +
Grass
Irrigated
Rainfed
Woodland +
Grass
Irrigated
Rainfed
Nile
200 150 100 50 0
population (millions)
0 200,000 400,000 600,000 800,000 1,000,000
Water use (mcm)
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Global Land cover classes – 2000 (UNEP)Grassland and rainfed dominate area
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Irrigation (IWMI)In Asia, irrigation supports high population density
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Population density (persons per km2) – (CIESIN -2000)
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First lap Global or
local problem?
Journey starts
Where are we all going?
Who’s on the bus?
Second lap
Where’s the water?
Third lap How much do people gain from water?
Water productivity
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Basic concept: Water productivity must respond faster than demand
crisis
response
time
Demand
System WP
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In some places, water productivity is responding to demand
Mac Kirby, 2007
0.000
0.200
0.400
0.600
0.800
1990 1995 2000 2005
Year
Water productivity, kg/m
3Rice
VN, Mekong Delta
Vietnam
VN CentralHighlands
Laos
CambodiaNE Thailand
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Volta
Other basins, response low or patchy
Potential= 1-2 kg/m3
IRD, 2007
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Volta
Actual Water-Productivity [the gain per m3 water
consumed] much lower than potential
Potential= 1-2 kg/m3
IRD, 2007
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Livestock can be a major contributor to total W-Productivity
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0
1000
2000
3000
4000
5000
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
GVP, million $
Crop Livestock Inland fisheries
0
500
1000
1500
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003Year
GVP, million $
Crop Livestock Fisheries Fish - high estimate
0
1000
2000
3000
4000
5000
1995 1996 1997 1998 1999 2000 2001 2002 2003Year
GVP, million $
Crop Livestock Fish low estimate
0
200
400
600
800
1,000
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Year
GVP, million $
Crop Livestock Fish low estimate
Fish? All we know for sure is that their contribution is under-estimated – even in Mekong
Cambodia
Thailand
Laos
Vietnam
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Full range of WPr will include
• Irrigated crops
• Rainfed
• Livestock
• Fisheries
– Capture
– Aquaculture
…most systems highly mixed
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First lap Global or
local problem?
Journey starts
Where are we all going?
Who’s on the bus?
Second lap
Where’s the water?
Third lap How much do people gain from water?
Fourth lap
Poverty impacts?
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Water agriculture and poverty
Measurable livelihood impacts
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Water availability seems less influential than gain per volume used (water productivity)
GNI vs Water
-10,000
0
10,000
20,000
30,000
40,000
50,000
-500 0 500 1000 1500 2000 2500
Water availability (m3/cap)
GNI ($/cap PPP)
Size of bubble proportional to agriculture contribution to GDP
Per capita income vs. water availability
World Bank, 2007
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Agriculture vs GNI
-10,000
0
10,000
20,000
30,000
40,000
50,000
-10 0 10 20 30 40 50
Agricultural contribution to GDP (%)
Gross National Income ($/capita)
• The poorest tend to rely on agriculture
Size of bubble proportional to rural
population
World Bank, 2007
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Dynamics likely to be very different according to relative function of agriculture
Agricultur e contribution to growth (%)
World Bank, 2007
% Rural poor
% Contribution of agriculture to GDP
volta
Sao Francisco
Karkheh Mekong
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São Francisco: Drought is one poverty factor…of many
Marcello Torres et al., 2008
Drought
Poor education
Access tocredit
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Karkheh, Iran: Farmers almost the poorest
Karkheh BFP team
Propor ti on bel ow poverty li ne
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.. Mekong What people do can affect (shared) assets
Complex but understandable
Dam developmentChanging land use, shifting cultivation,sustainability, sedimentation
Seasonal water shortage, poor soils, low rice productivity
Fish & environmental impacts of upstream Salinisation, water
quality, highly developed
Eric Kemp-Benedict, 2008
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First lap Global or
local problem?
Journey starts
Where are we all going?
Who’s on the bus?
Second lap
Where’s the water?
Third lap How much do people gain from water?
Fourth lap
Poverty, impacts?
Fifth lap What can change?
Interventions
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Global-to-local coupled systems
GLOBALwater and food systems considered separately
both impact on livelihoods
Local ScaleLocal systems considered individually
Local impact not referenced to broader systems
Basin scaleSystems interact through(Unspecified) transfers
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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
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Sao Francisco:
Detailed hydro-economic modelling
Effect of water constraints on profit, labour….
Steve Vosti and SF BFP team
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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
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First lap Global or
local problem?
Journey starts
Where are we all going?
Who’s on the bus?
Second lap
Where’s the water?
Third lap How much do people gain from water?
Fourth lap
Poverty, impacts?
Fifth lap What can change?
Where to next?
Final lap
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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
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Thank you
Special thanks to all BFPs