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Water-controlled wealth of nations: Using Water Footprints to Estimate Nations
Carrying Capacities and Demographic
Sustainability
Samir Suweis, Andrea Rinaldo, �
Amos Maritan and Paolo D'Odorico �
Welcome to Amos Maritan Lab
Page 1 of 2http://www.pd.infn.it/~maritan/
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Our! research! spans! from! statistical!mechanicsto!organization!of!ecosystems...
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Claudio!wrote!his!thesis.!Good!luck!with!it!
In!the!spirit!of!the!motto!"interdisciplinarity!is!dialog"!the!aim!of!the!Lab!is!toface!biological!and!ecological!problems!in!collaboration!with!experts!of!the!field.Not!mixing!our!expertises,!but!summing!them!up.!
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PNAS, Vol. 110 no. 11 4230-4233 (2013)
SouthSudan
Libya
2012Proportion of total population undernourished, 2010-12 The map shows the prevalence of undernourishment in the total population as of 2010 – 2012. The indicator is an
estimate of the percentage of the population having access to an amount of energy from food insufficient to maintain a healthy life. Further information is available at www.fao.org/publications/sofi/en/
Source: FAO, IFAD and WFP. 2012. The State of Food Insecurity in the World 2012: Economic growth is necessary but not sufficient to accelerate reduction of hunger and malnutrition. Rome.
© 2012 World Food Programme
The designations employed and the presentation of material in the maps do not imply the expression of any opinion whatsoever on the part of WFP concerning the legal or constitutional status of any country, territory or sea area, or concerning the delimitation of frontiers.
* The Line of Control in Jammu and Kashmir agreed on by India and Pakistan is represented approximately by a dotted line. The final status of Jammu and Kashmir has not yet been agreed on by the parties.
** A dispute exists between the governments of Argentina and the United Kingdom of Great Britain and Northern Ireland concerning sovereignty over the Falkland Islands (Malvinas).
*** Final boundary between the Republic of Sudan and the Republic of South Sudan has not yet been determined.
It costs on average just US 25 cents a day to feed a hungry child and change her life forever.
While food is the most basic of human
needs required for survival, on average, 1 in 8 people
go to bed hungry each night.
Hunger kills, maims, reduces IQ,
lowers wages, reduces school attendance andundermines economic
growth.
(U.K.)
***
No dataVery low
undernourishment
<5%
Moderately low undernourishment
5-14%
Moderately high undernourishment
15-24%
High undernourishment
25-34%
Very high undernourishment
35% and over
Missing or insufficient
comparative data
***
State of Palestine
Food Security: physical, social and economic access to sufficient, safe and nutritious food to meet dietary needs for a productive and healthy life (World Food Summit of 1996).
FOOD SECURITY
Figure . Annual water use per capita (data from Falkenmark et al., 2004).
"Over the coming decades, feeding a growing global population and ensuring food and nutrition security for all will depend on increasing food production. This, in turn, means ensuring the sustainable use of our most critical <inite source -‐ water”
Ban Ki-moon, World Water Day, 15 march 2012
The Water footprints or Virtual Water concept
• WF determined using bottom-‐up hydrological modeling at 5 by 5 arc spatial resolution. • Average values are calculated over 10 years periods. • Calibration: AQUASTAT and UN statistical division database (FAO, 2010b, UNSD, 2010°).
The Local Carrying Capacities of Nations
MekonnenMM, Hoekstra AY (2011)
Schema8c diagram of water withdrawals in the H08 model [Hanasaki et al., 2008]
TFM =trade food matrix
TFMy (i,j) = volume of commodity y traded from i and nation j.
The Virtual Carrying Capacities of Nations
€
aijy =Θ[TFMy(i, j)]
€
wijy = TFMy(i, j)⋅ VWy(i)
Suweis et al., GRL 2011
€
VWE(i) = wijy
j=1
N∑
y∑
€
KVi = Kloc
i +VWI (i) −VWE (i)
Wci
Water Wealth of Nations
€
dxidt
= α ixi 1−xiKi
⎛
⎝ ⎜
⎞
⎠ ⎟
€
K →Kloc or KV
γ i =1xi(t)
[xi(t + Δt) − xi(t)]Δt
→α i
€
xi(t) =Kix0,ie
α i t
Ki + x0,ieα i t − x0,i
Countries Demographic Dynamics
€
x <<Kloc; Kloc > x > KV ; x ≈ Kloc; x > KV
4.1 107
Argentina9.6 107
Brazil
3.1108
USA
7.8 107
Germany
1990 2010 2030 2050 2070
6 107Italy
1.1 108Mexico
5.6 107
UK
year [t]
x(t)
x(t)
x(t)
x(t)
x(t)
x(t)
x(t)
1970
1990 2010 2030 2050 2070year [t]
1970
1990 2010 2030 2050 2070year [t]
1970
1990 2010 2030 2050 2070year [t]
1970
1990 2010 2030 2050 2070year [t]
1970
1990 2010 2030 2050 2070year [t]
1970
1990 2010 2030 2050 2070year [t]
1970
€
K = KV
€
K = Kloc
Water Global Unbalance
€
DataWater Rich
Virtual Water Dependent
20 40 60 80 100
4.1 107
Argentina
20 40 60 80 100
2.2107
Australia
20 40 60 80 100
105
Belize
20 40 60 80 100
9.6 107
2. 108
Brazil
20 40 60 80 100
3.4 107
Canada
20 40 60 80 100
1.8 106
5. 106CostaRica
20 40 60 80 100
6.0 106
1.4 107
Ecuador
20 40 60 80 100
8.7 106
2.4 107
Ghana
20 40 60 80 100
5.4106
1.4107Guatemala
20 40 60 80 100
6. 105
2. 106
GuineaBissau
20 40 60 80 100
5.2 106
2.2 107
IvoryCoast
20 40 60 80 100
1.1 107
Cuba
20 40 60 80 100
1.2 108
2.3108
Indonesia
20 40 60 80 100
1.1 107
2.8 107
Malaysia
20 40 60 80 100
2.6 107
5.0 107
Myanmar
20 40 60 80 100
4. 106
NewZealand
20 40 60 80 100
2.4106
6. 106
Nicaragua
20 40 60 80 100
5.6 107
1.6 108Nigeria
20 40 60 80 100
2.5 106
6. 106
Paraguay
20 40 60 80 100
3.7 107
6.8 107
Thailand
20 40 60 80 100
9.4 106
3.4 107Uganda
20 40 60 80 100
3. 106
Uruguay
20 40 60 80 100
3.1108
USA
20 40 60 80 100
4.3 107
8.9 107
Vietnam
€
K = KV
€
K = Kloc
€
Data
Popu
la8o
n
Years aIer 1970
20 40 60 80 100
7.5 106
Austria
20 40 60 80 1002.2 105
8. 105
Bahrain
20 40 60 80 100
9.6 106
Belgium
20 40 60 80 100
1.7 107Chile
20 40 60 80 100
5.3 106
Finland
20 40 60 80 100
1.8 106Gambia
20 40 60 80 100
7.8 107
Germany
20 40 60 80 100
5.3 107
Italy
20 40 60 80 100
6.5 106Libya
20 40 60 80 100
1.1 108Mexico
20 40 60 80 100
3.9106
Norway
20 40 60 80 100
6.9 106PapuaNewGuine
20 40 60 80 100
2.9 107Peru
20 40 60 80 100
1.5 106Qatar
20 40 60 80 100
1.3107Senegal
20 40 60 80 100
5.8106SierraLeone
20 40 60 80 100
5.3 106
Slovakia
20 40 60 80 100
4.5 107Spain
20 40 60 80 100
1.2 106
Swaziland
20 40 60 80 100
8.1 106
Sweden
20 40 60 80 100
9.7 105
Trinidad Tobago
20 40 60 80 100
5.6 107
UK
20 40 60 80 100
4.7 106UnitedArabEmirates
20 40 60 80 100
2.4 107
Yemen
20 40 60 80 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100
20 40 60 80 100 20 40 60 80 100 20 40 60 80 100 20 40 60 80 100
100
8. 105
Cyprus5.2 10
6 Eritrea6.4 107
France
7.5 107
Iran
1.6 107
Netherlands2.9 106
Oman1.1 107
Portugal7. 6 106
Switzerland
€
K = KV
€
K = Kloc
€
Data
Popu
la8o
n
Years aIer 1970
Modelling Sustenability of VW Dependent Countries Population
dx
i
dt
= ↵
i
x
i
✓1� x
i
K
i
loc
◆for i=Rich Water
dx
j
dt
= ↵
j
x
j
0
@1� x
i
K
j
loc
+
PRichi
aji
di(K
i
loc
� x
i
)
VWiVWj
1
Afor i=VW dependent
⇢ System of coupled differential equations
j
Diets!
Water Rich Virtual Water Dependent
€
aijGraph Topology
Results & Effect of Network Topology
Posi8ve feedback between demographic growth and technological innova8ons
Sta8c
4.5 108
5.0 108
5.5 108
6.0 108
2020 2040 2060 2080 21002000Times [years]
X vwd
! = 0.08! = 0.04! = 0
4.5 108
5.0 108
5.5 108
6.0 108
6.5 108
7.0 108
2020 2040 2060 2080 21002000
X vwd
Years
Random graph
Small world network
Scale-‐free network
Topological properties similar to those observed in the real global VW trade network
Kloc(t)=Kloc(1+ε(t)) and decreasing Wc(t)
Rockström, J., et al. GRL 39.15 (2012).
β = cooperative strength
No e!ect of trade
Net Importers
Net Exporters
Food Scarce
Using Food Trade Data - Temporal Networks
Temporal Food Trade Patterns and Stability, in preparation
Group A Group B Group C Group D
1995 2000 2005 2010
0
10000
20000
30000
40000
50000
Years @y D
RTHyL-
CHyL@calD
1995 2000 2005 20100.6
0.8
1.0
1.2
1.4
Years @y D
CV@K TDêCV
@K LD
Out[479]=
Group A Group B Group C Group D
5 10 15 20 25
2400
2600
2800
3000
Years @t D
Group
Diet@c
alD
Balance
Fluctua8on of the avaliable resources
Diet
Does globalization Increases stability?
-0.2 -0.1 0.0 0.10
5
10
15
20
25
Re@lD
y=1991 y=1997 y=2003 y=2009
x mode
1995 2000 2005Year
0.0090.0100.0110.0120.0130.014
»x Mode» A
B
1995 2000 2005
4
6
8
10
12
14
16
Year
Re@lD>0
Stability of the Food trade Network
If Re(λi > 0) xi(t) is very sensitive to external perturbations
Effect of the network
• Side-‐effects of the globalization of resources
• Unbalance between the rate of growth in water rich countries and the water resources exported to virtual water dependent countries
• Decreasing stability in time of the food-‐demographic coupled system
Conclusions & Perspectives
1990 1995 2000 2005 2010Years @t D
2¥ 107
4¥ 107
6¥ 107
8¥ 107Pop@t D Egypt
1990 1995 2000 2005 2010Years @t D
5.0¥ 106
1.0¥ 107
1.5¥ 107
2.0¥ 107
Pop@t D Australia
Conclusions & Perspectives
• Is there any optimal network topology in terms of water saving?
• How to quantify waste or detrimental links in the virtual water trade networks?
• Robustness to perturbations and fragility of the network
• Estimate the uncertainity of VW footprint calculations
• Create public and shared databases so to work with the same data
• Data on Food Stock, Food Waste,…
MODELLING
DATA ANALYSIS
Thanks for your attention!
Full reference: PNAS, Vol. 110 no. 11 4230-4233 (2013)
Contacts
SamirSuweis Questions?