ELECTRONIC SUPPLEMENTARY MATERIAL
Note: Section numbers refer to the main paper’s sections to which the information is being added.
1-
Introduction
Inventory
Midpoint
impacts
Inventory from
compensation
processes
Scarcity
/stress
Endpoint
Impacts
Compensation processes
Volume of
water
unavailable
to other
users
Distribution
of water
deprivation
Water deprived
for domestic
users
Water deprived
for agriculture
Water deprived
for fisheries
Water
Inventory
(Surface water,
renewable
groundwater,
fossil
groundwater)
Volume of
water to be
obtained
through
compensation
Socioeconomic
parameter
Volume of
water
deprived
causing
health
damages
Malnutrition
effect per m3
deprived (agri)
Impact on
human
health
Malnutrition
effect per m3
deprived (fish)
Change in flow
quantity
Assessment
of disruption
of water
balance
Water-related
diseases effect
per m3 deprived
(dom)
Terrestrial
species loss per
m3 deprived
Change in
groundwater
table level
Impact on
Ecosystems
Aquatic species
loss per m3
deprived
Change in flow
regime
Loss of water
quality
Overuse
assessment
Overuse of
renewable water
bodies
fossil
groundwater
depletion
Impact on
Ressources
Fig.S1: General water use impacts framework (adapted from Kounina et al). The dotted rectangle highlights the impact pathway for which
methods are compared in this paper.
Table S1: Summary of methods and their names
Impact assessed
Scarcity
Availability
Human Health
Reference
Frischknecht,
2008
Pfister, 2009
Name
M-SwissSc
Hoekstra, 2012
M-BWSSc
Boulay, 2011
M-BoulaySc
Boulay, 2011
M-BoulayAv
Veolia, 2010
M-WIIXAv
Pfister, 2009
Motoshita,
2010a
E-Pfister
E-Motoshita_dom
Motoshita,
E-Motoshita_agri
M- PfisterSc
Details
Midpoint, scarcity, withdrawal-to-availability,
power function
Midpoint, scarcity, withdrawal-to-availability,
logistic function
Midpoint, scarcity, consumption-toavailability, direct function
Midpoint, scarcity, consumption-toavailability, logistic function
Midpoint, availability, consumption-toavailability (quality specific), logistic function
Midpoint, availability, withdrawal-toavailability and distance to target for pollution
As published, agricultural deprivation
Effect factor as published, domestic
deprivation, then combined with M-PfisterSc
and distribution factor (DAU)
Adapted from presentation, agricultural
1
2010b
E-Motoshita_agri (no
TE)
Boulay, 2011
E-Boulay_marg
E-Boulay_distri
E-Boulay_agri
E-Boulay_dom
E-Boulay_marg_Q
E-Boulay_distri_Q
E-Boulay_agri_Q
E-Boulay_dom_Q
3.1.1
deprivation including trade effect , then
combined with M-PfisterSc and distribution
factor (DAU)
Adapted from presentation, agricultural
deprivation excluding trade effect , then
combined with M-PfisterSc and distribution
factor (DAU)
Simplified from publication (no quality),
considers agriculture as off-stream user
deprived (100%) and aquaculture as in-stream
user deprived.
Simplified from publication (no quality),
considers off-stream users to be deprived
proportionally to their use (agriculture and
domestic are included) and aquaculture as instream user deprived.
Simplified from publication (no quality),
represents a partial factor from EBoulay_distri for comparison purposes, only
for agricultural users.
Simplified from publication (no quality),
represents a partial factor from EBoulay_distri for comparison purposes, only
for domestic users.
As published, considers agriculture as offstream user deprived (100%) and aquaculture
as in-stream user deprived.
As published, considers off-stream users to be
deprived proportionally to their use
(agriculture and domestic are included) and
aquaculture as in-stream user deprived.
Represents a partial factor from EBoulay_distri for comparison purposes, only
for agricultural users.
Represents a partial factor from EBoulay_distri for comparison purposes, only
for quality users.
Scarcity indicators
Fig.S2 plots the normalized scarcity indicators from all methods against the WTA index. The underlying data used
to calculate this latter (WaterGap), differs from the ones used in M-SwissSc, which explains the observed
inconsistency of the data series. Please note that all values equal zero (60% of values for M-Boulay-Sc), cannot be
shown on the graph. The average values described in section 2.3 is also shown.
2
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
1.E+00
1.E+01
1.E+02
1.E+02
1.E+01
Log normalized scarcity methods
1.E+00
1.E-01
1.E-02
Pfister
1.E-03
Swiss
1.E-04
BWS
1.E-05
Boulay
1.E-06
WTA (equal line)
1.E-07
1.E-08
Average method
1.E-09
Log WTA
Fig.S2: Log graph of normalized scarcity methods against WTA for the main watersheds showing spread and differences
among methods.
Human health: Domestic user deprivation
1.E-10
1.E-08
1.E-06
1.E-04
1.E-02
1.E+00
1.E-011.E+00
Log E-Dom methods
1.E-02
1.E-03
1.E-04
1.E-05
1.E-06
1.E-07
Average Method
E-Boulay-dom
E-Motoshita_dom
a)
Log Motoshita_dom
1.E-08
1.E-09
1.E-08
Log Boulay dom SEE factor
3.1.4
1.E-06
1.E-04
1.E-02
1.E-02
1.E+00
1.E-03
1.E-04
1.E-05
1.E-06
1.E-07
1.E-10
1.E-11
b)
1.E-08
Log Motoshita dom SEE factor
Fig.S3: Comparison of human health model outcomes from domestic water deprivation impact pathways using Boulay and Motoshita
models. A) CF and b) socio-economic and effect factor (SEE), which excludes scarcity and distribution of affected users.
3
3.1.5
Human health: Agricultural user deprivation
While the consistency is higher between E-Motoshita_agri without trade effect and the two other models then it is
with trade effect included, the mean difference between models decreases in comparison with E-Pfister but increases
when comparing with E-Boulay_agri. This is because E-Boulay_agri shows higher results in general, and the
addition of the trade effect increases the results as well in E-Motoshita_agri.
1.E-09
1.E-07
1.E-05
1.E-03
1.E+00
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
1.E-02
E-Boulay_agri
1.E-06
E-Motoshita_agri_noTE
1.E-07
E-Motoshita_agri
1.E-08
1.E-09
E-Pfister
1.E-10
Log E-Pfister
1.E-07
1.E-05
1.E-03
Log E-Methods SEE
1.E-04
1.E-05
1.E+00
1.E-01
1.E-03
Average values
E-Boulay_agri SEE
1.E-03
E-Motoshita_agri SEE
1.E-04
E-Pfister SEE
1.E-05
1.E-06
E-Motoshita_agri
(noTE) SEE
1.E-07
1.E-08
1.E-11
1.E-12
Log E-Pfister SEE
1.E-09
1.E+00
1.E-01
1.E-01
1.E-02
Log CF suing E-Pfister EF
1.E-09
1.E+00
1.E-01
1.E-01
1.E-02
Log E-Methods agriculture deprivation
1.E-11
1.E-03
1.E-04
1.E-05
1.E-06
1.E-07
1.E-08
1.E-09
Log CF using E-Boulay EF
1.E-10
Fig.S4: Comparison of agriculture water deprivation impacts on human health. a) complete CF, b) Socio-economic and effect factors and c)
effect factors only.
3.1.6
Inventory-related choices
4
Temporal variations
Fig.S5: Difference between annual scarcity indicators calculated from annual data vs. from a withdrawal-based
weighted average of monthly data. Results are obtained with M-PfisterSc which scarcity indexes range from 0.01 to .1
Water Source
Fig.S6: Absolute difference in scarcity results between general scarcity indicators calculated using all water use and availability and
weighted-average of surface and groundwater scarcities, based on intensity of groundwater withdrawals. Results are obtained using
M-Boulay-Sc, which values range between 0 – 1.
Quality aspect
Out of the 600 regions of the world for which data was available (based on Boulay et al[30]), scarcity indicators are
higher when consuming water of good quality then of unspecified quality in 42% of the cases. No difference is
observed for the rest of the cases (58%), representing regions where general scarcity is already maximal (value of 1).
Consuming water of poor quality results in higher stress in about 21% of the cases, corresponding to region where
water quality is very poor. No difference is observed in 79% of cases, i.e. in regions where the average water quality
is poor. Degrading good quality into very poor quality, will result in higher impacts than consuming general water
(quality non-specified) in 39% of the cases, in countries with no general water scarcity, but with good quality water
scarcity. These will present impacts when considering water of a certain quality but not when considering all water
available.
5
3.1.7
Scarcity
5.0E+00
Function output based on CTA (normalized)
4.5E+00
4.0E+00
S-curve
3.5E+00
Linear
3.0E+00
BWS
2.5E+00
Swiss
2.0E+00
1.5E+00
1.0E+00
5.0E-01
0.0E+00
0.0E+00
5.0E-01
1.0E+00
1.5E+00
2.5E+00
3.0E+00
3.5E+00
4.0E+00
4.5E+00
1.E-06
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
1.E+00
Log of funtion output, based on CTA
algorithms (normalized)
b)
5.0E+00
CTA (normalized)
a)
1.E-07
2.0E+00
1.E+01
1.E+02
1.E+02
1.E+00
1.E-02
1.E-04
S-curve
1.E-06
Linear function
1.E-08
Direct (M-BWS-Sc)
1.E-10
Power function (M-Swiss-Sc)
1.E-12
Log CTA (normalized)
1.E-14
Fig.S7: Different model functions defining scarcity as a function of CTA a) normal scale and b)log scale.
6
3.2.3
Fig.S8: Difference of including or not domestic users
7