Talk given at the European geophysics Union Conference (EGU) in 2014 on my paper published in PNAS, Vol. 110 no. 11 4230-4233 (2013): Water Controlled Wealth of Nations.

1. 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/
!!!!!!!!!!!!!!!!!!!!!
Our!research!spans!from!statistical!mechanics
to!organization!of!ecosystems...
29#01#2013
Claudio!wrote!his!thesis.!Good!luck!with!it!
In!the!spirit!of!the!motto!"interdisciplinarity!is!dialog"!the!aim!of!the!Lab!is!to
face!biological!and!ecological!problems!in!collaboration!with!experts!of!the!field.
Not!mixing!our!expertises,!but!summing!them!up.!
!!!!!!!!!!!!!!!
ABOUT!US NEWS
Home Research People Publications Teaching Collaborators Opportunities Contacts
PNAS, Vol. 110 no. 11 4230-4233 (2013)

2. South
Sudan
Libya
2012
Proportion 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 and
undermines economic
growth.
(U.K.)
***
No data
Very 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

3. 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

4. •
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]

5. TFM
=trade
food
matrix
TFMy
(i,j)
=
volume
of
commodity
y
traded
from
i
and
nation
j.
The Virtual Carrying Capacities of Nations
€
aij
y
= Θ[TFMy (i, j)]
€
wij
y
= TFMy (i, j)⋅ VWy (i)
Suweis
et
al.,
GRL
2011
€
VWE (i) = wij
y
j=1
N
∑
y
∑
KV
i
= Kloc
i
+
VWI (i) −VWE (i)
Wc
i

6. Water Wealth of Nations
€
dxi
dt
= αi xi 1−
xi
Ki
⎛
⎝
⎜
⎞
⎠
⎟
€
K →Kloc or KV
γi =
1
xi(t)
[xi(t + Δt) − xi(t)]
Δt
→αi
€
xi(t) =
Ki x0,ieαi t
Ki + x0,ieαi t
− x0,i
Countries Demographic Dynamics
x << Kloc; Kloc > x > KV ; x ≈ Kloc; x > KV

7. 4.1 107
Argentina
9.6 107
Brazil
3.1108
USA
7.8 107
Germany
1990 2010 2030 2050 2070
6 107
Italy
1.110
8
Mexico
5.6107
UK
year [t]
x(t)
x(t)
x(t)
x(t)
x(t)
x(t)
x(t)
1970
1990 2010 2030 2050 2070
year [t]
1970
1990 2010 2030 2050 2070
year [t]
1970
1990 2010 2030 2050 2070
year [t]
1970
1990 2010 2030 2050 2070
year [t]
1970
1990 2010 2030 2050 2070
year [t]
1970
1990 2010 2030 2050 2070
year [t]
1970
€
K = KV
€
K = Kloc
Water Global Unbalance
€
Data
Water
Rich
Virtual
Water
Dependent

8. 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. 106
CostaRica
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
1.4107
Guatemala
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
1.6 108
Nigeria
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
3.4 107
Uganda
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
Popula8on
Years
aIer
1970

9. 20 40 60 80 100
7.5106
Austria
20 40 60 80 100
2.2 105
8. 105
Bahrain
20 40 60 80 100
9.6106
Belgium
20 40 60 80 100
1.7 107
Chile
20 40 60 80 100
5.3 106
Finland
20 40 60 80 100
1.8106
Gambia
20 40 60 80 100
7.8 107
Germany
20 40 60 80 100
5.3 107
Italy
20 40 60 80 100
6.5 106
Libya
20 40 60 80 100
1.1108
Mexico
20 40 60 80 100
3.9106
Norway
20 40 60 80 100
6.9 106
PapuaNewGuine
20 40 60 80 100
2.9 107
Peru
20 40 60 80 100
1.5 106
Qatar
20 40 60 80 100
1.3107
Senegal
20 40 60 80 100
5.8106
SierraLeone
20 40 60 80 100
5.3 106
Slovakia
20 40 60 80 100
4.5107
Spain
20 40 60 80 100
1.2106
Swaziland
20 40 60 80 100
8.1106
Sweden
20 40 60 80 100
9.7 105
Trinidad Tobago
20 40 60 80 100
5.6107
UK
20 40 60 80 100
4.7 106
UnitedArabEmirates
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. 10
5
Cyprus
5.2 10
6 Eritrea
6.4 10
7
France
7.5 10
7
Iran
1.6 10
7
Netherlands
2.9 10
6
Oman
1.1 10
7
Portugal
7. 6 10
6
Switzerland
€
K = KV
€
K = Kloc
€
Data
Popula8on
Years
aIer
1970

10. Modelling Sustenability of VW Dependent
Countries Population
dxi
dt
= ↵ixi
✓
1
xi
Ki
loc
◆
for i=Rich Water
dxj
dt
= ↵jxj
0
@1
xi
Kj
loc +
PRich
i
aji
di
(Ki
loc xi)V Wi
V Wj
1
A for i=VW dependent
⇢ System
of
coupled
differential
equations
j
Diets!
Water
Rich
Virtual
Water
Dependent
€
aijGraph
Topology

11. Results & Effect of Network Topology
Posi8ve
feedback
between
demographic
growth
and
technological
innova8ons
Sta8c
4.5 10
8
5.0 10
8
5.5 10
8
6.0 10
8
2020 2040 2060 2080 21002000
Times [years]
Xvwd
β = 0.08
β = 0.04
β = 0
4.5 108
5.0 108
5.5 108
6.0 108
6.5 108
7.0 108
2020 2040 2060 2080 21002000
Xvwd
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

12. No effect of trade
Net Importers
Net Exporters
Food Scarce
Using Food Trade Data - Temporal Networks
Temporal Food Trade Patterns and Stability, in preparation

13. Group A Group B Group C Group D
1995 2000 2005 2010
0
10000
20000
30000
40000
50000
Years @yD
RTHyL-CHyL@calD
1995 2000 2005 2010
0.6
0.8
1.0
1.2
1.4
Years @yD
CV@KTDêCV@KLD
Out[479]=
Group A Group B Group C Group D
5 10 15 20 25
2400
2600
2800
3000
Years @tD
GroupDiet@calD
Balance
Fluctua8on
of
the
avaliable
resources
Diet
Does globalization
Increases stability?

14. -0.2 -0.1 0.0 0.1
0
5
10
15
20
25
Re@lD
PDF
y=1991 y=1997 y=2003 y=2009
x mode
1995 2000 2005
Year
0.009
0.010
0.011
0.012
0.013
0.014
»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

15. • 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 2010
Years @tD
2 ¥ 107
4 ¥ 107
6 ¥ 107
8 ¥ 107
Pop@tD
Egypt
1990 1995 2000 2005 2010
Years @tD
5.0¥ 106
1.0¥ 107
1.5¥ 107
2.0¥ 107
Pop@tD
Australia

16. 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

17. Thanks for your attention!
Full reference: PNAS, Vol. 110 no. 11 4230-4233 (2013)
Contacts
SamirSuweis
Questions?