The Basin Focal Projects of the CPWF

An interesting journey

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?

Journey starts

Where are we all going?

Who’s on the bus?

The water and food problem

World food crisis

• Reasons

– Declining supply

– Increasing demand

– Biofuels

– Commodity speculation

World food crisis

• Reasons

– Declining supply

– Increasing demand

– Biofuels

– Commodity speculation

Mid-te

rm

Long-t

erm

Basis of food demand:

Time for each billion 1800-2050

(Molden 2007)

…plus increased meat consumption

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

But this leads to increasing conflict with other users

Agriculture uses > 70% of water

…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

….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

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?

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

Niger

First of 4 BFPs started in 2005

UC Davis

IRD

CSIRO

IWMI

Niger

6 remaining BFPs started in 2008

KCL

IRD

FANRPAN

IWMI

IWMIIFPRI

First lap How to

describe the problem?

Journey starts

Where are we all going?

Who’s on the bus?

Global ……to local

Global -to local

GLOBAL

Local Scale

Local impacts on land use and livelihoods

Basin scaleSystems interact

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

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

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

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

Hydrology matters to livelihoods

David Blake

Songkhram Wet Songkhram Dry

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

Devaraj de Condappa

Volta

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

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

Ganges

From Kirby et al., W-Use

accounts

But irrigation a major user in Asia

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

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)

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

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

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

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

Basic concept: Water productivity must respond faster than demand

crisis

response

time

Demand

System WP

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

Volta

Other basins, response low or patchy

Potential= 1-2 kg/m3

IRD, 2007

Volta

Actual Water-Productivity [the gain per m3 water

consumed] much lower than potential

Potential= 1-2 kg/m3

IRD, 2007

Livestock can be a major contributor to total W-Productivity

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

Full range of WPr will include

• Irrigated crops

• Rainfed

• Livestock

• Fisheries

– Capture

– Aquaculture

…most systems highly mixed

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?

Water agriculture and poverty

Measurable livelihood impacts

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

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

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

São Francisco: Drought is one poverty factor…of many

Marcello Torres et al., 2008

Drought

Poor education

Access tocredit

Karkheh, Iran: Farmers almost the poorest

Karkheh BFP team

Propor ti on bel ow poverty li ne

.. 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

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

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

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

Sao Francisco:

Detailed hydro-economic modelling

Effect of water constraints on profit, labour….

Steve Vosti and SF BFP team

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

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

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

Thank you

Special thanks to all BFPs