Ifpri Veolia Study 2011

8/11/2019 Ifpri Veolia Study 2011

1/77

Sustaining growth via water

productivity: 2030/2050

scenarios

Final results document


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Veolia has recently extended its external thought-partnership to broader

water resource issues

Core questions on water andgrowth futures

Given the imperative of water for

underpinning growth

what are the growth levels thatcan be sustainedgiven todays

water productivity?

to what extent can gains in

efficiency andwater productivity

(output per drop) enable higher

levels of growth?

Veolia has been working onanswering these questions in 2010

with its partners

Detailed, linked global modelsof

water, food, and energy (IFPRI

IMPACT-WATER model)

Discrete scenariosof growth

and water productivity

Water

demand

(growth

drivers)

Water

supply

Water stress and

risk to growth!


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Contents

2

Framework for analysis

Growth and productivity to 2050

Appendix

Mainresults


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Both supply and demand pressures lead to water stress and

associated risks

Demand pressures Supply pressures

Population growth direct

Increased domestic /urban use

Increased food demand Economic growth

Increased urban wateruse

Increased industrialwater use

More water-intensivediets

Climate change

Increased crop waterdemand

More reservoirevaporation

Spatial / temporalmismatchbetween supplyand demand

More expensive supplycurveto transport water

Continued water qualitydeterioration

Climate change pressures

Reduced availability withincreased intensity

Increase in frequencyand intensity of extremeevents damage toinfrastructure & unreliablesupply

In some cases, decline inrenewable water

Localized groundwater overdraft

Pressures onecosystems(quantity andquality impacts)

Impact on costand viability of

activities, andincreasedcompetitionacross water-using sectors

Economic /political conflict

Impacts of Water Stress

Risk to growth!Demand also impacted byinternational food tradeand local policies


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The modeling approach1 uses the water stress index to

indicate the gap between water supply and demand

Demand

Agriculture

Irrigation

Livestock

Rainfed production

Effective irrigation efficiency at the riverbasin level

Industrial

Efficiency gains in water-usingindustries; water demand for electricitygeneration based on energy mix

Domestic

Water efficiency gains on consumption Adjustments to reflect leakage rates

Environmental requirements

Trade

Moves agricultural commodities tocountries and regions with higherdemand

Population growth

Increased domestic / urban use

Increased food demand

Economic growth Affecting agriculture, domestic and

industrial water use

More water-intensive diets withincreasing wealth

Supply

Water stress index-Internal renewable waterresources withdrawn:

0-20%: No/moderate

stress

20-40%: Water stress

>40%: Water scarcity

SOURCE: Team analysis

Drivers of supply and demand

Phase 1

Effective rainfall Internal renewable water supply

Climate change impacts

Increased evapotranspirationdemand

Changes in renewable watersupply

Non-irrigation water supply

(including desalination)

Irrigation water supply

Changes in water supply

infrastructure Reservoir storage, irrigation

infrastructure

Groundwater supply

Pumping capacity Water quality deterioration

Reflected in leaching requirementsfor irrigation

1 Assumptions: Domestic, industrial, livestock needs and minimum environmental flows satisfied first


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Today, over 20% of global GDP already at risk due to water stress

> 50

< 20

20 - 30

30 - 40

40 - 50

No data

Percent of renewable water resources

withdrawn

Existing water stress for major river basins, 2010

SOURCE: IFPRI; Team analysis

The global water/foodapproach is used toexplore interactionsbetween water andgrowth

Focus is on globallevel and food tradeimpacts on water

Certain localsituations within riverbasins can be muchworse off thanindicated by averagevalues (geographyand annual average)

1819

46 59

> 40%

20 - 40%

0 - 20%

GDP (%)Population (%)

2236

Low stress

Medium tohigh stress(at risk)


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G r o w t h s c e n a ri o s established to measure the change for water

requirements sector-by-sector and country-by-country

High-level description

High

growth

Medium

growth

(default)

Low growth

High growth estimates

Developed (+2.4)/ middle income (4.8%) anddeveloping countries (+5.6%)

BRIC1 countries estimated separately(5.2%/+3.9%/8.4%/9.1%)

Consensus estimates for most likely future GDP

performance

Developed economies (2.1%), middle income (4.0%)and developing countries (4.3%)

Brazil (4.4%), Russia (3.4%), India (5.9%) and China(6.8%)

Minimum growth forecasts

Developed (1.6%) /middle income (3.9%) anddeveloping countries (3.3%)

BRIC1 countries estimated separately(2.9%/3.2%/5.9%/6.8%),

1 Brazil, Russia, India, China

SOURCE: Global Insight, Team analysis

Overall assumptions

and methods

Use of per-country

forecasts until 2040,

linear extrapolation

of trend from 2040-

2050

Differentiation

between

developing/middle

income and

developed countries

Growth assumptions

also reflected in fooddemand

Growthscenarios


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Growth is linked to dietary needs-- ~4% growth globally is needed to

provide sufficient nutrition for a population of 9.1 Bn in 2050Scenario: BAU, 2050

100% =

6.8 billion

people

< 2,000

2,000 - 2,500

2,500 - 3,000

> 3,000

2010

8

35

41

16

19

1513 15

5051 50

16 21 24

1115

100% =

9.1 billion

people

High

growth

(~4.3%)

Medium

growth

Low

growth

(2.9%)

Population clustered by daily available kilo calories

Percent

Between low and high growth additional 700 million

people will haveaccess to > 2,000 kilo calories per day

2050

1.0 Bnpeople

Threshold forunder-nutrition

1.7 Bnpeople

SOURCE: IFPRI

1.7 Bnpeople

0.5 Bnpeople


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P r o d u c t i v i t y s c e n ar i o s can be higher or lower than a business-as-usual

trajectory, also established by sector

Grey productivity Business-as-usual Blue Productivity

No water productivity

improvements achieved,

resulting reactive

environmental behavior

Onlyminor energy

efficiency gainsreached

Energy demand growingby

~20% in OECD and ~130% inNon-OECD countries, with

corresponding water use

Energy mixshift to nuclear

and thermo electrical power

generation as assumed be

IEA World Energy Outlook for

"Current scenario"

Domestic sectorshows

moderate improvementsin

leakage reductionand water

efficiency gains

50% of water productivity

leversare achieved in

industry

Energy demand increaseat

~19% in OECD and ~110% in

Non-OECD countries, with

corresponding water use

Energy mix with slight shift

towards renewable energy

mix, but with high share of

conventional thermal electric

generation

Domestic sectorshows

high improvementsin

leakage reductionand water

efficiency gains

Majority of water

productivity potential

achieved in industry

Energy demand growingat

~19% in OECD and ~110% in

Non-OECD

High share of renewable

energyincreasing from ~19%

(2008) to 29% (2030) with

biomass produced from

waste material or otherwise

without water impacts

Lower water

p r o d u c t i v i t y

Higher water


SOURCE: IFPRI, Team analysis

Water Productivityscenarios


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Drivers of waterproductivity under

low-carbon growth

Grey BAU Blue

H i gh w ater


A low-carbon energy mix impacts water productivity in terms of higher

usage of biomass but also higher energy efficiency

Water impacts of optimizing

for low-carbon energy

On balance, a low- carbon

energy scenario has slightly

lower water productivity than

BAU

The water impacts of biomass

(some irrigation) and

hydropower (evaporation)

from reservoirs outweigh

water savings from efficiencygains

Energy mix impacts

Strong emphasis is on renewableenergy generation accounting

for >25% of energy sources

Hydropower and biomass increase,

with increases in water use

Energy efficiency impacts

Energy efficiency causes energy

demand to increase at a lower pace,

Energy demand growing 0.7%p.a. (vs. 2.1% in BAU)

Lower increase of water use from

conventional energy

Water productivity scenarios

Low w ater



Low

Carbon


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Example: Growth is at risk when water stress levels

rise, while increasing water productivity can reduce risk

Sectoral growth in

agriculture, energy and

industrydrive increases

in water requirements

Growth rates become

at riskwhen levels of

water stress grow

beyond thresholds

Higher-levels of

productivitycan enable

growth while maintaining

sustainable withdrawalsratios

49.2 47.4 44.9 32.6

28.4 27.0 25.8 19.2

23.7 22.5 21.5 16.2

High

Medium

Low

Growth

Grey Low

carbon

BAU Smart

blue

Water productivity

Example: Water stress inBrahmani river basin, India

Percent of total renewable

water

RIVER BASIN EXAMPLE

- BRAHMANI RIVER, INDIA

Moderate stress (>20%)

Water stress (20-40%)

Water scarce (>40%)

Growth at risk due to high

water stress levels (>40%)



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Contents

12



Appendix

Mainresults


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Executive Summary (1/2)


1 >40% water stress

2 Year 2000 prices

Alreadytoday 36% of global population(2.5 Bn people) live in water scarce regions1 and22% of

the world's GDP(9.4 trillion USD2) is produced in those areas1

Under business-as-usual water productivity and medium GDP growth, 50% of population

(4.7 Bn people, 70% of 2010 global population) and 45% of GDP (63 trillion USD 2, 1.5x 2010global GDP ) will live/origin in regions at risk due to water stress by 2050

2

For China and India and many other rapidly-developing countries, water scarcity will

begin to materially risk growth alone in these 2 countries 2.7 Bn peoplewill live in areas

of high water stress

a

Low-income countries will be stronger affected with39% of low-income countries

experiencing much more severe shifts towards water stress than wealthier/more

industrialized countries

b

However, also many of the most advanced regions of the industrialized worldwill have tocope with water scarcity and its effects on growth, e.g. California

c

I I. B u s i n e s s - as - u s u a l l ev e l s o f w a t er p r o d u c t i v i t y i s n o t s u f f i c i e n t t o r e d u c e r i s k s

a n d e n s u r e s u s t a i n a b i l it y

I . T o d a y m a n y r e g i o n s a l re ad y e x p e r ie n c e w a t e r s t r e s s ( a n d r i s k ) d u e t o p o p u l a t i o n

a n d ec o n o m i c g r o w t h


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At medium growth, a grey water productivity scenario results in a noticeable increase in

water stress compared to business-as-usualwith additional 450 million people and 5.6 trillion

GDP at risk by 2050

3

Executive Summary (2/2)


1 Year 2000 prices

Productivity improvement in domestic and industrial sectors can make significant contributions

in reducing the share of population and GDP at risk on top of improvements in agriculture

6

In ablue water productivity scenario at medium growth,countries invest in additional water

productivity, significantly de-risking growth with ~1 billion peopleand USD ~17 trillion GDP less

from regions which are at-risk due to high water stress as compared to business-as usual by 2050

4

The blue productivity scenario helps both developing (e.g. China) and developed (e.g.

California) economiesreduce risk by moving towards sustainable water stress levels

a

For other growth regions like India, blue productivity helps, but is still insufficient These countries will face difficult choices on priorities for water allocationb

Additional social benefits occur in a "blue" productivity world, e.g. more than 20% less

malnourished children compared to business-as-usual

c

I II . F u t u r e g r o w t h a n d s u s t a i n ab i l i t y i s d e p en d e n t o n g a i n s i n w a t er p r o d u c t i v i t y

Underhigh GDP growth in a grey world 60% of global population and economy will be in

scarce areaschallenging seriously the possibility of achieving this high growth. Only a Blue

world enables to achieve high growth with an exposure similar to the one of business-as-usual

with medium growth. A medium growth Blue world offers the best balance for sustainability.

5

On balance, water stress in a low carbon world remains close to business-as-usual levels ,

as water savings from energy efficiency balances increases in water use due to biomass

cultivation. However, this only holds if 2nd and 3rd generation biomass will become available!

7


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Already today, water-scarce regions account for 36% of global

population (2.5 Bn) and 9.4 trillion USD (22%) of global GDP

How many people live inwater short areas (%)?

How much GDP is generated in

water scarce regions (%)?

> 50

< 20

20 - 30

30 - 40

40 - 50

No data

> 40%

20 - 40%

0 - 20%

2010

36

18

46

> 40%

0 - 20%

19

22

2010

20 - 40%

59

2010

SOURCE: IFPRI; team analysis

2.5 Bn people

9.4 trillion

USD2

Water stress, percent of total renewable water

withdrawn

1 >40% water stress

2 Year 2000 prices

1


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Under business-as-usual water productivity and medium growth, 52%

of population and 45% of GDP are in regions at risk due to water stress

> 40%

20 - 40%

0 - 20%

2050

52

16

32

2010

36

18

46

> 40%

20 - 40%

0 - 20%

2050

45

25

30

2010

22

19

59

Business as usual (BAU) water productivity, medium growth,2050

1 >40% water stress

2 Year 2000 prices


How many people live inwater short areas?


water scarce regions?

4.7 Bn

people,

70% of

2010 pop.

Increase

by 90%

compared

to 2010

63 trillion

USD2

1.5 x 2010

total GDP

Increase

by 570%compared

to 2010


withdrawn > 50

30 - 40

40 - 50< 20

20 - 30

No data

2


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0

10

20

30

40

50

60

7080

90

100

110

120

0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 4,5 5,0 5,5 6,0 6,5

Water stress of selected countriesPercent

GDP growthPercent

USA

IND

CHN

For China and India and many other rapidly-developing

countries, water stress will pose a risk to growth


Size of bubble reflects size of population

AS

EU

OC

NA

SA

AF

Size of bubble reflects

size of population

0 - 20%

20 - 40%

> 40%Water stress, percent of total renewable water withdrawn

3.1 Bn people will

live in regions

where water

scarcity putsgrowth at risk

Water stress 2050 over GDP growth 2010-2050 Medium growth

2a


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Under business-as-usual, water scarcity will especially

impact low-income1 countriesLow-income countries

High-income countries


Water stress by country, GDP2 per capita

Percent of total renewable water withdrawn

2010 2050

1 300%

Low income, high

water stress area

Scenario BAU medium growth

542050

2010 25

+29

Average water stress3

Percent of total renewable water

withdrawn

Low-income countries

20

20

7

17 372050

2010 27

+10

High-income countries


size of population

0

20

40

60

80

100

120

1,000100

KEN

IRQ

IRNIND

CHN

ALG

10,000

GDP per capitaUSD

100,000

0

20

40

60

80

100

120

GDP per capitaUSD

100,00010,0001,000100

KEN

IRQ

IND

IRN CHN

ALG

2b


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Many industrialized countries e.g. US will have to cope with water

scarcity risking growth in highly important areas, e.g. California

US river basins


> 50

30 - 40

40 - 50< 20

20 - 30

No data

0

20

40

60

80

2010 2020 2030 2040 2050

4131

Water stress by selected US river basin 1

Percent

Great Lakes

Columbia

California

Arkansas

Northeast

Southeast

Red Winnipeg

Ohio

Missouri

Mississippi

California

increasesstress by

10%,placing

growth "at risk"

Water stress willincreaseforall USriver basins

Average water stressincrease by~11%-points1 between2010 - 2050

1 River basins Colorado, Great Basin & Rio Grande showing water stress of >100% excluded

Water stress, percent of total renewable water withdrawn Medium Growth

2c


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Grey medium growth, 2050

A "grey" scenario, without productivity increases water stress, with an

additional 450 m people and 5.6 trillion GDP at risk compare to BAU


> 50

< 20

20 - 30

30 - 40

40 - 50

No dataWater stress, percent of total renewable water

withdrawn

2050-

Grey

55

17

28

2050-

BAU

52

16

32

> 40%

20 - 40%

0 - 20%

> 40%

20 - 40%

0 - 20%

2050-

Grey

49

24

27

2050-

BAU

45

25

30



Increase

of 3% to

BAU

Add'l 450

million at

risk

Increase

of 4% to

BAU

~5.6

trillionUSD

addition-

ally at risk


3


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"Blue" high-productivity scenario medium growth, 2050

In a blue world, water stress can be substantially reduced, with ~1 Bn

people and 17 trillion USD2 GDP coming from less water scarce areas1



withdrawn

> 40%

20 - 40%

0 - 20%

2050-

Blue

38

2050-

BAU

41

2116

32

52

38

2050-

BAU

33

2050-

Blue

45

25

30

28

> 40%

20 - 40%

0 - 20%



Decrease

of 11% to

BAU

1 Bn peo-

ple in less

scarce

regions

Decrease

12% com-

pared to

2010

17,000 Bn

USD2 in

less scarce

regions


> 50

< 20

20 - 30

30 - 40

40 - 50

No data

1 >40% water stress

2 Based on year 2000 prices

4


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0

20

40

60

80

100

120

140

GDP per capitaUSD

100,00010,0001,000100

FRA

UKR

ETH VIE

ALG

CHN

IND

USA

KEN

FRA

UKR

ETH VIE

ALG

JAP

KEN

USA

The blue world will in particular help developing (e.g. China) and

developed areas (e.g. US) to de-risk their growth targets


Water stress by country over GDP per capita1

Percent

1 Year 2000 prices

Medium growth

BAU (med)

Blue (med)


size of population

0 - 20%

20 - 40%

> 40%

By growing blue

70% of

economies,including China,

US, France, etc.

can stay below

the 40%-scarcity

threshold

4a


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Even highly industrialized countries like US will face critical water

scarcity with out investing in water productivity

SOURCE: IFPRI

20

30

40

50

US Water stressin Percent

GDP per capitain USD

80,00060,00040,00020,000

27%

43%

36%

27%


size of population

4a

Blue (med)

Grey (med)

BAU (med)

Water

s c a r c i t y

2010 2050 2050

If no investments are

made, US becomes

water scarcein 2050

Even under business asusual, water scarcity

increases until 2050

Productivity gains in blue

scenario enable theUS to

remain at the same

water stress levelas in

2010

Water stress 2050 over GDP per capita Medium growth


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For other growth regions like India, "blue" productivity helps, but is

insufficient -- difficult choices for water will need to be made


1 River basins IEC & Lun showing water stress of >300% excluded for illustration purpose

Water stress, percent of total renewable water withdrawn Medium growth

US river basins

> 50

30 - 40

40 - 50< 20

20 - 30

No data

Water stress by selected US river basin1

Percent

Some river basins in India show extreme water scarcity of

more than 100% water stress

All areas increase stress level between 2010-2050 by 36%-

points1 on average

Additional demand reduction (crop change, imports) or

policy changes may be needed to reduce water stress/risk

0

50

100

150

200

250

300

2010 2020 2030 2040 2050

Mahi Tapti

Langcang

Brahmaputra Easten Ghats

Indus

Cauvery

Sahyada

Krishna

Ganges

Chotanagpui

Brahmani

Godavari

Many basins

severely over-

exploting ground-water

4b


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Additional social benefits occur in a "blue" world, e.g. more than 20%

less malnourished children compared to business-as-usual

Child malnutrition

Million of cases

91,2

115,5116,8115,9

Low

Carbon

Grey BAU Blue

-21%

Description

Higher water productivity

in a blue world scenario

leads to water savings

across sectors and

increased availability and

use in water-scarce

Consequently food

production increases and

prices drop

Further assumptions:

Increase in female

secondary education &

access to safe drinking

water (MDG vision) The number ofmalnourished children

could bereducedin the blue scenario

by 21% to 91 million in 2050

Scenario medium growth, 2050

SOURCE: IFPRl; team analysis

4c


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28 34

15

2050-Blue

0 - 20%

2050-Grey

60 51

12

> 40%

20 - 40%

Under high GDP growth a grey scenario will increase risk for

820 m people and 15.5 trillion USD of GDP1 compared to a blue

pathway

1822

24 30

20 - 40%

0 - 20%

2050-

Blue

47

2050-

BAU

58> 40%

Low vs. high-productivity scenario high growth, 2050

1 >40% water stress

2 Based on year 2000 prices


How many people live in water short

areas?

How much GDP is generated in water

scarce regions?

Water stress, percent of total renewable water withdrawn> 50

< 20

20 - 30

30 - 40

40 - 50

No data

11%

deviation

15.5 trillion

USD2 inless scarce

regions

(>30%

2010 GDP)

Difference

of 9%

820 million

people in

less scarce

regions

Blue - high

productivity

Grey - low

productivity

5


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GDP

growth

Percent

22

19

59

Share of GDP

generated in

water stress

regions

2010

58

18

24

54

20

26

47

22

30

49

2427

46

2430

33

28

38

Grey

45

26

28

Low

Carbon

42

25

33

BAU

42

24

34

Smart

Blue

3022

48

Share of GDP generated in water stress regions

2050

High

SOURCE: IFPRI

> 40%

20 - 40%

0 - 20%

5

1 Year 2000 prices

20

26

54

45

2530

Med

Low

81,800Bn USD1

66,300Bn USD1

63,500BnUSD1

A smart blue scenario supports high growth at the level of BAU for

medium growth. A medium growth Blue world represents the best

compromisebalancing growth and sustainability

46,500Bn USD1


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55

1728

54

1432

52

1632

41

21

38

Grey

52

16

32

Low

Carbon

51

16

33

BAU

49

16

35

Smart

Blue

40

18

42

GDP

growth

High

Med

Low

Share of population in water stress regions

2050

A smart blue scenario supports high growth at the level of BAU for

medium growth. A medium growth Blue world represents the best

compromisebalancing growth and sustainabilityPercent

36

18

46

Share of

population in

water stress

regions

2010

60

1228

56

14

30

56

14

30

51

15

34

> 40%

20- 4 0%

0 - 20%

SOURCE: IFPRI

5

5.5 Bnpeople

4.7 Bnpeople

4.6 Bnpeople

3.7 Bnpeople


30/77

| 29SOURCE: IFPRI

0

10

20

30

40

50

60

70

80

90

100

110

120

Water stress by countryin Percent


100,00010,0001,000100

ZIMUSA

UKR

KEN

JAP

IND

CHN

ALG

Water stress over GDP per capita, 2010

Size of bubble reflects number of population

NA

OC

SA

AF

AS

EU

5 A high growth grey scenario would be unsustainable

Scenario Grey high growth, 2010


31/77

| 30SOURCE: IFPRI

0

10

20

30

40

50

60

70

80

90

100

110

120

KEN

CHN

UKR

JAP

IND

ALG

USA

1,000 10,000100

ZIMUGA

TANETH

BUF

RWA


100,000




AS

EU

NA

OC

SA

AF




32/77

| 31SOURCE: IFPRI

0

10

20

30

40

50

60

70

80

90

100

110

120


RWA

ETH

TAN

UGA


100,00010,0001,000100

ZIM

JAP

IND

CHN

BUF



AS

NAAF

OC

SAEU

USA




33/77

| 32SOURCE: IFPRI

0

10

20

30

40

50

60

70

80

90

100

110

120

JAP

IND

CHN

ALG



100,00010,0001,000100

ZIM USA

UKR

KEN



NA

OC

SA

AF

AS

EU

5 A Blue scenario would sustain high growth

Scenario Blue high growth, 2010


34/77

| 33SOURCE: IFPRI

0

10

20

30

40

50

60

70

80

90

100

110

120



100,00010,0001,000100

ZIM

USA

UKR

KEN

JAP

IND

CHN

ALG



AF

AS

EU

OC

SA

NA




35/77

| 34SOURCE: IFPRI

0

10

20

30

40

50

60

70

80

90

100

110

120



100,00010,0001,000100

ZIM

JAP

IND

CHN



NA

OC

SA

AF

AS

EU

USA




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By growing blue 70% of economies, including China, US, Mexico, etc.

can stay below the 40%-threshold

Water stress over GDP per capita1

0

20

40

60

80

100

120

100,00010,0001,000100


CHN

ETH VIE

MEX

0

20

40

60

80

100

120

100,00010,0001,000100


CHNETH

MEX

USAVIE

0

20

40

60

80

100

120

1,000100


100,00010,000

CHN

ETH VIE

MEX


size of population

SOURCE: IFPRI

Water stress by country

Percent

BAU Grey Smart Blue

Low stress

Medium stress

High stress

1 2000 prices

5

Medium growth

INDIND

IND

USA

USA


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Even at high growth, a blue water productivity trajectory can reduce

water stress improvements over a grey, low productivity scenario

0

20

40

60

80

100

120

140

160

180

200


1,000,000100,00010,0001,000100

CHN

IND

FRA

UKR

ETHVIE

ALG

JAP

KEN

USA


1 Year 2000 prices

5

High growth

Blue (high)

Grey (high)

With pursuing

high water

productivity,some

economies can

even in a high

growth scenario

stay below the

40% water-

scarcity

threshold

Water stress by country over GDP per capita1

Percent


size of population

0 - 20%

20 - 40%

> 40%


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20

30

40

50

60

Population

60,000,00050,000,00040,000,00030,000,000

Water stress in medium GDP growth1 (2.6%)Percent of renewable water used

California must grow its economy with high water productivity in order

to keep water stress levels below 40%


Water stress in California by water productivity scenario High water productivity

No additional productivity

Business-as-usual

31% 30%

41%

49%

20

30

40

50

60

Water stress in high GDP growth1 (2.9%)Percent of renewable water used

Population

60,000,00050,000,00040,000,00030,000,000

36%

49%

58%

Only high water productivityleads to a stress

levelbelow 40% thresholdregardless GDP growth1 Estimate based on Global Insight (2010-2040), extrapolated between 2040-2050

Water

s c a r c i t y

Water

s c a r c i t y

2010 2050 2010 2050

31%

5


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Change in share GDP produced in water stress

regions (medium growth, 2050)Percent

Domestic and industrial sectors can make significant contributions

in reducing the share of population and GDP at risk


1 Year 2000 prices

2. Domestic and industrial water demands

are first satisfied

Percent

0 - 20%

20 - 40%

> 40%

6

Change in share of people living in water stress

regions (medium growth, 2015)Percent

16 1822 21

32 34 36 38

BAU+

domesticand

industrial

productvity

Blue

product-ivity

across all

sectors

(including

agric.)

4142

BAU+

domesticproductvity

only

48

BAU

52

25

25 31 28

30 34 35 38

333441

BAU

45

360 million fewerpeopleliving in water

scarce areas

5.6 trillion USD1 of

global GDP is in

regions where stress

levels reduced

Additional540 millionfewer peopleliving in

water scarce regions

Addl 9 trillion USD1

is in regions where

stress levels reduced

BAU+

domesticand

industrial

productvity

Blue

product-ivity

across all

sectors

(including

agric.)

BAU+

domesticproductvity

only

Without policy changes2 (not included in model) increased agricultural

water efficiency may incentivize more withdrawals, and actually lead to

higher withdrawals in some water scarce basins, limiting real water savings


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| 39

On balance, water stress in a low carbon world remains close to

business-as-usual levels as biomass moves beyond first-generation

and energy efficiency is pursued


32 32

BAU

52

16

Lowcarbon

53

15 +1

Share of people living in

water stress regions, 2050

Percent

24 25

30 30

BAU

45

Low

carbon

46

+1

Share of GDP generated in

water stress regions, 2050

Percent

Water demand for crops

increases only marginally

as by2030 second-

generation biofuelsare

increasingly used

Improved energy

efficiencydirectly

decreases water demandasless electricitygrows

only by 1.7% p.a.

compared to 2.1% in

BAU scenario

Food prices for corn

increases by 4%due to

biomass competition

A low carbon world has

a strongfocus on

energy efficiency

measures and

renewable energy

generation

Renewable energy

generation decreaseswater productivity

through

Evaporation lossesof hydropower

Water demand forcropsused for first-

generation biofuels

Description of low-

carbon energy scenario Water impacts

> 40%

20 - 40%

0 - 20%

Water stress index

7


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Appendix

Input parameters

Maps Methodology

Industrial assumptions

Agricultural assumptions

Impact model description


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Appendix

Input parameter

Maps Methodology





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Megatrend scenarios Parameter overview (1/2)

SOURCE: IEA, WEF, Team analysis

Driver

Residential

Industrial

Climate change

Low Carbon Smart blue

Efficiency gain onconsumption

Leakage reduction

Energy demand

Energy mix

Energy water

productivityimprovement

Mining demand

Mining mix

Mining waterproductivityimprovement

DevelopedMiddle IncomeDeveloping

Infrastructure:Good (40% lkg)

IEA scenarios

IEA scenarios

Water productivity

improvement other

industries1

High efficient

Medium efficientLow efficient

BAU

CSIRO A1B

1,0 % p.a.0,5 % p.a.0,0 % p.a.

0%

- 10%- 20%

"New policy"

10%

"New policy"

10%

10%

Grey

CSIRO A1B

0,5 % p.a.0,3 % p.a.0,0 % p.a.

-0%

+ 5%- 10%

"Current policy"

0%

"Current policy"

0%

0%

CSIRO A1B

1,0 % p.a.0,5 % p.a.0,0 % p.a.

0%

- 10%- 20%

Green Energy "450"

10%

Green Energy "450"

10%

10%

CSIRO A1B

2,0 % p.a.1,5 % p.a.1,0 % p.a.

0%

- 25%- 30%

"New policy" assuming

biomass usage in lowwater stress regions or

from waste

30%

"New policy" assumingbiomass production in

low water stressregions or from waste

30%

30%

1 Based on industry average (Beverage, Pulp&Paper, Chemicals, Food, Steel, Others) using China, South Africa, US & Australia

SOURCE

IFPRI

Expert interviews

Expert interviews

IEA World Energy

Outlook 2010, WorldEconomic Forum

McKinsey knowledge

documents (Chinadeepdive, South Africa

deepdive, Industryfactpack)

IEA World EnergyOutlook 2010, World

Economic Forum

McKinsey knowledgedocuments

McKinsey knowledge

documents (China

deepdive, South Africadeepdive, Industryfactpack, Water impact

on business)

Environmental flow

requirements

10%10% 10% 10% IFPRI


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| 434343

Megatrend scenarios Parameter overview (2/2)

SOURCE: IFPRI

Driver 2010-2050

Agriculture Change in

agricultural GDP

growth,implemented as

change in cropyield growth

Low Carbon Smart blue

Change in

irrigated areaexpansion

Change in basin

efficiency

(gradual declineuntil 2030,

constant between2030-2050)

BAU

- 2.5%

- 5%

- 5%- 20%

- 15%- 10%

no change to BAU

medium growth

scenario

Grey

no change to BAU

medium growth

scenario

-0.15

-0.1

-0.1-0.12

-0.1-0.1

no change to BAU

medium growth

scenario

SOURCE

IFPRI

IFPRI

IFPRI

Change inagricultural GDP

growth,

implemented aschange in crop

area growth

-2.5%-10%

-10%

-20%-15%

-10%

IFPRIDevelopedMENA, Central Asia

Eastern Europe

SSA, SA and LACIndia

China/Other East Asia

Developed

MENA, Central AsiaEastern Europe

SSA, SA and LACIndia

China/Other East Asia

Developed

MENA, Central Asia

Eastern EuropeSSA, SA and LAC

IndiaChina/Other East Asia

Other changes n.a.n.a. 27% increasedfirst-generation

biofuel demand

over BAU

Increased crop

transpirationefficiency leading

to 10% increase inirrigated yields

Increase soil water

holding capacity by

20% over baseline)

Increase in female

sec edu & accessto safe drinking

water (MDG vision)

IFPRI-

Developed

MENA, Central Asia

Eastern EuropeSSA, SA and LAC

IndiaChina/Other East Asia

Low Med HighGDP- growth Low Med High Low Med High Low Med High

0%

0%

0%0%

0%0%

2.5%

5%

5%20%

15%10%

-0.15

-0.1

-0.1-0.12

-0.1-0.1

0%0%

0%

0%0%

0%

-0.15

-0.1

-0.1-0.12

-0.1-0.1

2.5%10%

10%

20%15%

10%

0%

0%0%

- 10%- 5%

- 2.5%

0%

0%0%

0%0%

0%

0%

0%0%

20%15%

10%

no change to BAU

medium growthscenario

- 2.5%

- 5%

- 5%- 20%

- 15%- 10%

0%

0%

0%0%

0%0%

2.5%

5%

5%20%

15%10%

0%

0%0%

-10%-5%

-2.5%

0%

0%0%

0%0%

0%

0%

0%0%

20%15%

10%

- 2.5%

- 5%

- 5%- 20%

- 15%- 10%

0%

0%

0%0%

0%0%

2.5%

5%

5%20%

15%10%

no change to BAUmedium growth

scenario


scenario


scenario

Basin efficiency

increase by 0.2

Results incl in doc

no change to BAU

medium growthscenario


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Appendix

Input parameter

Maps

2010

2030

2050

Methodology





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| 45

Maps for the 6 most likely scenarios were produced

Global maps were

produced for the most

likely scenarios

Maps covering the

years 2010 as well as

2030 and 2050 for

each indicated

scenario were

produced

Low

Water productivity

Low/Medium Medium/High

High

Grow

th

Medium

Low

High

Maps included

in then document


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Appendix

Input parameter

Maps

2010

2030

2050

Methodology





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>50


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Appendix

Input parameter

Maps

2010

2030

2050

Methodology





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| 49

>50


51/77

| 50

>50


52/77

| 51

>50


53/77

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>50


54/77

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>50


55/77

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>50


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Appendix

Input parameter

Maps

2010

2030

2050

Methodology





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| 56

>50


58/77

| 57

>50


59/77

| 58

>50


60/77

| 59

>50


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| 60

>50


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>50


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Appendix

Input parameter

Maps

Methodology





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Economic output and water efficiency determine water demand


Focus of new McKinsey/IFPRI scenarios

Description

Economic

output/

production

Key drivers of water sustainability

Economic growthdrives

activity requiring water

Water

productivity

Increasedproductivity

reduces water demand for

a set economic activity

Influenced by climatic

factors and infrastructure

Demand

Supply

Water

sustainability


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Implications of a top-down change to growth on water demand

are addressed by the model


Demand segmentsInput

Domestic

Agriculture

Growth

Industrial

Domestic water demand

correlated along an s-curve with

GDP per capita

Energy demand increases with

higher GDP per capita

Meat consumption increases

with higher GDP per capita

which has a higher water

demand than crops

Examples

Effects are calculated

by the IFPRI modelDefined by scenario

GDP

Model input

metric in italic

Any change inGDP growth

has to be

reflected by

manually

changing

agriculture GDP

in the model

Adjustments

done by IFPRI


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Water productivity calculated bottom-up from key drivers


1 Assuming no change in production mix

Water efficiency

IFPRI model inputs

Agriculture

Residential

Industrial

m3/agriculture - GDP

m3/GDP per capita

m3/GDP

Driver

Trade

Irrigationtechnology

Crop choice

Consumption

Leakage rate

Energy mix

Productivity

Exploration mix

Productivity

Productivity1

Sector

Energy

Mining, gas, andoil

Pulp and paper

Chemicals

Metals

Others

Description

Investments in water infrastructure reduce

leakage rates

Productivity gains due to a shift to dry cooling

in thermo electric generation is expected

Trade flows affect water productivity as crops

can be grown in regions with comparative

advantage

Irrigation technology significantly influenceswater productivity

Consumption efficiency determines per

capita water use

Choice of crops affects agricultural water

demand

The mix of electricity generation highly

influences water demand

Technological productivity gains, especially

in developing countries expected

Water demand of mining industry is highly

dependent of type of exploration

Sector specific technological improvements

driving water demand

Model input

metric in italic


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Appendix

Input parameter

Maps

Methodology





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Major sources of industrial water withdrawal are thermo electric and

mining industry

SOURCE: USGS

Domestic

2005

460100% =

Agriculture

Industry

34

54

12 7

Thermo

electric

Mining

Others

2005

91

2

Total water withdrawal in the USPercent, in 2005

Total industrial water withdrawal

in the USin Percent, in 2005

Water withdrawal for thermoelectric and mining covers >90%

of total industrial withdrawal

Break-down of

total US water

withdrawals using

estimates from

USGS in 2005

Water withdrawal

deviating from

actual water

consumption

figures


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Industrial water demand is highly dependent on thermo-

electric power generation

1 Coal, iron, sand, gravel

2 Crude petroleum

3 Natural gas

4 World Economic Forum

5 Department of Energy

SOURCE: USGS, WEF, DOE, IEA

US industrial

water withdrawals

using estimates

from USGS in

2005

Industrial water

disposition

calculated

bottom-up using

energy mix from

World Energy

Outlook

7

2

91

100

Others

Mining1, oil2,

and gas3

Thermoelectric

power generation

Total industrial

water demand

Industrial water withdrawal in the US

Percent

Estimates

based on

reportsfrom WEF4

and DOE5

34

15

51

100

Industrial water disposition

Percent


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Increased water demand by renewable energy generation is offset by

energy efficiency measures decreasing overall energy demand

SOURCE: IFPRI, IEA, Team analysis

Using IEA scenariosfor predicting future

energy demand and

future energy

efficiency for major

global regions

Water productivity

estimates of a paper

presented at the

World EconomicForum were used for

calculation

133910

132

Water demand

for energygeneration in low

carbon scenario

Additional water

demand due toRES

Water demand

reduction due toincreased

energy efficiency

Total water

demandfor energy BAU

Additional water consumption

mainlydriven by biofuelsand

hydrologicalwater consumption

Estimated water use for electricity generation

in km p.a., 2050


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Switching to low carbon energy production leads to significantly

increased water consumption

SOURCE: IEA, WEF, Cambridge Energy Research Associates,

US Department of Energy

Water consumption by

electricity generation1

in Tsd. km water

133

120

110

450

scenario

New

policies

Current

policies

+11%

Water consumption by

electricity generationincluding water

consumption of biofuels2

in Tsd. km water

133

154

235

331

120

110

464

355

264

+31%

Major scenario assumptions

No change in government

policyis assumed

23% of renewable energygeneration

Takescurrent policiesand

declared intentionsinto

account

Low carbon scenario

providing reasonable

chance ofconstraining

average global

temperature increase to 2

Celsius

45% of renewable energygeneration including

hydropowerLow carbon energy mix can signi-

ficantly increase water demand unless

second generation biofuels are used

in 2050

Direct effect

Indirect effect

Methodology

Using 2050scenario energy

mix estimate by

IEA

Average waterproductivity for

various

electricitygeneration

technologies

Waterconsumptionfigures adjusted

by production

levels of

scenarios

1 Using the same energy demand across scenarios

2 Assuming 100% of biofuels are grown from irrigated crops


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Input parameter

Maps

Methodology





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Different growth and efficiency scenarios are reflected by various

agriculture assumptions

SOURCE: IFPRI

Faster/slower GDP growth is also reflected in agricultural production growth/slowdowns, which can beachieved either by area expansion/slowing or agricultural productivity (yield) growth/slowing. Under the

BAU, Low Carbon, andSmart Blue scenarios,agricultural GDP growth is reflected inyield

improvements; whereas in theGREYscenario, agricultural growth is reflected as area expansion.

While water use efficiencies in domestic and industrial water use are directly implemented, we

represent changes in irrigation water use efficiency as changes ineffective irrigation efficiencyatthe basin level. We thus fully take into account the portion of diverted irrigation water that returns back

to river or aquifer systems and thus can be re-used repeatedly, usually by downstream users, thus

avoiding the limitation of the conventional irrigation efficiency concept that basically treats return flow

as losses.

We definebasin efficiencyis defined as the ratio of beneficial irrigation water consumption to total

irrigation water consumption. Our base year basin efficiency values range from 0.4 to 0.7. Given

trends in investment in water use efficiency enhancements, and the need to use water more efficiently

under growing water scarcity, we project small enhancements in over time, with levels increasing to

0.5-0.8 by 2050 under the baseline. An upper level of is set at 0.85 because it is impossible to reach

efficiency levels of 100 percent.

Growth assumptions

Productivity assumptions


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| 73

Additional assumptions for the low carbon scenario take increased

biomass production into account

SOURCE: IFPRI

For the Low Carbon Scenario, weincreasedthe use of first-generation feedstock for biofuel production in

line with the IEA scenario for increased biomass for energy production. The resulting increased biofuel production

in terms of millions of liters of biofuels are shown in the following table.

Example biofuel production estimates


Adriatic

Alpine_Europe

Alpine_EuropeArgentina

Argentina

Australia

Baltic

Baltic

Brazil

Brazil

British_Isles

British_Isles

...

6.15

87.52

18.02194.57

100.48

660.85

20.16

41.35

220.72

2,073.15

52.51

277.81

Region

Biodiesel

Biodiesel

EthanolBiodiesel

Ethanol

Ethanol

Biodiesel

Ethanol

Biodiesel

Ethanol

Biodiesel

Ethanol

...

Biofuel type

Million liters of increased biofuel production over

baseline for scenario of 27% increase in feedstock use


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In "blue" world an increased crop transpiration efficiency, increased soil

water holding capacity and improved water management are assumed

SOURCE: IFPRI

Increased crop transpirationefficiency leading to 10% increase in irrigated yieldsthis reflects improvements inthe plant structure that reduce improve the transpiration efficiency, which describes the ratio of the mass of carbon

dioxide taken up by plant photosynthesis versus the amount of water transpired

Increase soil water holding capacityby 20% over baseline-- Rainfed crops receive water either from

precipitation at the time it falls or from soil moisture. Soil characteristics influence the extent to which previous

precipitation events provide water for growth in future periods. Managing effective rainfallthat is, rainfall that can

be effectively used for crop growth improves rainfed crop productivity. Enhancing use of rainwater will be key to

ensuring future crop productivity enhancement in SSA, where 95 percent of all crops are grown on rainfed lands.

In addition, manymanagement practicesthatimprove the effective use of rainfall, such as water harvesting

and reduced tillage, can also provide broader environmental benefits through reduced soil erosion especially in

arid and semi-arid regions. Advanced tillage practices, contour plowing (typically a soil-preserving technique), andprecision leveling are all examples of practices that can improve infiltration and evapotranspiration, thus increasing

the share of rainfall that can be used effectively for crop growth, while also minimizing soil erosion. Moreover,reducing the amount of soil tillage reduces emissions of carbon stored the soil, providing an effective strategy for

greenhouse gas mitigation. For rainfed water management and soil maintenance, the model assumes an

increase in soil water holding capacity (SWHC). Specifically, SWHC increases 20 percent over BAU levels.

Increase in female secondary education & access to safe drinking water(MDG vision). For access to safe

drinking water, we implemented an increase in access reflecting increased investments and awareness under the

smart blue scenario. By 2030, most developing countries will have achieved 100 percent access to safe drinking

water. Safe drinking water and sanitation is also linked with enhanced female education. For female secondary

education, we implemented a 2% improvement in 2010 and add another 2% improvement for each of the following5-year increments until the total improvement was 10% then maintain 10% improvement thereafter.



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Appendix

Input parameter

Maps

Methodology





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IMPACT is a partial equilibrium model of the agricultural sector,

representing a competitive agricultural market for crops and livestock

Demandis a function ofprices,income, andpopulation growth Worldagricultural commodity pricesare determined annuallyat levels that

clear international markets

Growthin crop production in each country is determined by crop and input

prices, therate of productivity growth and area growth

IMPACT generates projections for crop area; yield;production;demand for

food, feed, and other uses;prices; andtrade

Forlivestock, IMPACT projects numbers, yield,production,demand,prices,

andtrade

IMPACTincludes30 agricultural commoditiesand 115 economic regions,

representing most developing countries; 126 global (aggregated) river basins;

and281 global food production units, defined by intersections of economic

regions and river basins

IMPACT incorporates a water simulation model to assess water supplyanddemandand respectiveimpacts on food supply and demand

Ifpri Veolia Study 2011

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