ifpri veolia study 2011
TRANSCRIPT
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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
p r o d u c t i v i t y
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
p r o d u c t i v i t y
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
p r o d u c t i v i t y
SOURCE: IFPRI, Team analysis
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%)
SOURCE: IFPRI, Team analysis
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Contents
12
Framework for analysis
Growth and productivity to 2050
Appendix
Mainresults
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Executive Summary (1/2)
SOURCE: IFPRI, Team analysis
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)
SOURCE: IFPRI, Team analysis
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
SOURCE: IFPRI; team analysis
How many people live inwater short areas?
How much GDP is generated in
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
Water stress, percent of total renewable water
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
SOURCE: IFPRI; team analysis
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
SOURCE: IFPRI; team analysis
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 bubble reflects
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
SOURCE: IFPRI; team analysis
> 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
SOURCE: IFPRI; team analysis
> 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
How much GDP is generated in
water scarce regions?
Increase
of 3% to
BAU
Add'l 450
million at
risk
Increase
of 4% to
BAU
~5.6
trillionUSD
addition-
ally at risk
How many people live inwater short areas?
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
SOURCE: IFPRI; team analysis
Water stress, percent of total renewable water
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%
How much GDP is generated in
water scarce regions?
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
How many people live inwater short areas?
> 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
SOURCE: IFPRI; team analysis
Water stress by country over GDP per capita1
Percent
1 Year 2000 prices
Medium growth
BAU (med)
Blue (med)
Size of bubble reflects
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 bubble reflects
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
SOURCE: IFPRI; team analysis
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
SOURCE: IFPRI; Team analysis
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
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0
10
20
30
40
50
60
70
80
90
100
110
120
Water stress by countryin Percent
GDP per capitain USD
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
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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
Water stress by countryin Percent
100,000
GDP per capitain USD
Water stress over GDP per capita, 2030
Size of bubble reflects number of population
AS
EU
NA
OC
SA
AF
5 A high growth grey scenario would be unsustainable
Scenario Grey high growth, 2030
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0
10
20
30
40
50
60
70
80
90
100
110
120
Water stress by countryin Percent
RWA
ETH
TAN
UGA
GDP per capitain USD
100,00010,0001,000100
ZIM
JAP
IND
CHN
BUF
Water stress over GDP per capita, 2050
Size of bubble reflects number of population
AS
NAAF
OC
SAEU
USA
5 A high growth grey scenario would be unsustainable
Scenario Grey high growth, 2050
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0
10
20
30
40
50
60
70
80
90
100
110
120
JAP
IND
CHN
ALG
Water stress by countryin Percent
GDP per capitain USD
100,00010,0001,000100
ZIM USA
UKR
KEN
Water stress over GDP per capita, 2010
Size of bubble reflects number of population
NA
OC
SA
AF
AS
EU
5 A Blue scenario would sustain high growth
Scenario Blue high growth, 2010
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0
10
20
30
40
50
60
70
80
90
100
110
120
Water stress by countryin Percent
GDP per capitain USD
100,00010,0001,000100
ZIM
USA
UKR
KEN
JAP
IND
CHN
ALG
Water stress over GDP per capita, 2030
Size of bubble reflects number of population
AF
AS
EU
OC
SA
NA
5 A Blue scenario would sustain high growth
Scenario Blue high growth, 2030
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0
10
20
30
40
50
60
70
80
90
100
110
120
Water stress by countryin Percent
GDP per capitain USD
100,00010,0001,000100
ZIM
JAP
IND
CHN
Water stress over GDP per capita, 2050
Size of bubble reflects number of population
NA
OC
SA
AF
AS
EU
USA
5 A Blue scenario would sustain high growth
Scenario Blue high growth, 2050
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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
GDP per capitain USD
CHN
ETH VIE
MEX
0
20
40
60
80
100
120
100,00010,0001,000100
GDP per capitain USD
CHNETH
MEX
USAVIE
0
20
40
60
80
100
120
1,000100
GDP per capitain USD
100,00010,000
CHN
ETH VIE
MEX
Size of bubble reflects
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
GDP per capitain USD
1,000,000100,00010,0001,000100
CHN
IND
FRA
UKR
ETHVIE
ALG
JAP
KEN
USA
SOURCE: IFPRI; Team analysis
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 bubble reflects
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%
SOURCE: IFPRI, Team analysis
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
SOURCE: IFPRI; team analysis
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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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
SOURCE: IFPRI; team analysis
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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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameters
Maps Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameter
Maps Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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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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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
no change to BAUmedium growth
scenario
no change to BAUmedium growth
scenario
Basin efficiency
increase by 0.2
Results incl in doc
no change to BAU
medium growthscenario
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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameter
Maps
2010
2030
2050
Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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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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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameter
Maps
2010
2030
2050
Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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>50
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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameter
Maps
2010
2030
2050
Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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>50
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>50
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>50
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>50
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>50
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>50
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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameter
Maps
2010
2030
2050
Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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>50
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>50
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>50
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>50
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>50
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>50
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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameter
Maps
Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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Economic output and water efficiency determine water demand
SOURCE: Team analysis
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
SOURCE: Team analysis
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
SOURCE: Team analysis
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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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameter
Maps
Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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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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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameter
Maps
Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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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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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
Major scenario assumptions
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.
Major scenario assumptions
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Contents
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Framework for analysis
Growth and productivity to 2050
Appendix
Input parameter
Maps
Methodology
Industrial assumptions
Agricultural assumptions
Impact model description
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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