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Drink. Water Eng. Sci. Discuss., 5, 265–289, 2012
www.drink-water-eng-sci-discuss.net/5/265/2012/
doi:10.5194/dwesd-5-265-2012
© Author(s) 2012. CC Attribution 3.0 License.
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Received: 2 May 2012 – Accepted: 17 May 2012 – Published: 28 June 2012
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Published by Copernicus Publications on behalf of the Delft University of Technology.
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Correspondence to: R. Jacinto (jacinto.rita@gmail.com),
M. J. Cruz (cruz.mjoao@googlemail.com)
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CCIAM, SIM, Faculty of Sciences, University of Lisbon, C1, Sala 1.4.39, Campo Grande,
1749-016 Lisboa, Portugal
5, 265–289, 2012
Water use scenarios
as a tool for
adaptation
R. Jacinto et al.
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Abstract
Introduction
Conclusions
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R. Jacinto, M. J. Cruz, and F. D. Santos
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Water use scenarios as a tool for
adaptation to climate change of
a water supply company
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Climate change has already had effects on the natural environment, and much bigger
changes are projected for this century (IPCC, 2007; EEA, 2008). In Europe, especially in the south, water availability and water stress are already a concern (Henrichs
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1 Introduction
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The project ADAPTACLIMA, promoted by EPAL, the largest Portuguese Water Supply
Utility, aims to provide the company with an adaptation strategy in the medium and
long term to reduce the vulnerabilities of its activities to climate change. We used the
special report emissions scenarios (SRES) of the IPCC (Intergovernmental Panel on
Climate Change) to produce local scenarios of water use. Available population SRES
for Portugal were downscaled to the study area using a linear approach. Local land use
scenarios were produced using the following steps: (1) characterization of the present
land use for each municipality of the study area using Corine Land Cover and adapt
the CLC classes to those used in the SRES; (2) identification of recent tendencies
in land use change for the study area; (3) identification of SRES tendencies for land
use change in Europe; and (4) production of local scenarios of land use. Water use
scenarios were derived considering both population and land use scenarios as well
as scenarios of change in other parameters (technological developments, increases in
efficiency, climate changes, or political and behavioural changes).
The A2 scenario forecasts an increase in population (+16 %) in the study area while
the other scenarios show a reduction of resident population (−6 to 8 %). All scenarios,
but especially A1, show a significant reduction in agricultural area and an increase
in urban area. Regardless of the scenario, water use will progressively be reduced
until 2100. These reductions are mainly due to increased water use efficiency and
reduction of irrigated land. The results concord with several projects modelling water
use at regional and global level.
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et al., 2002; EEA, 2008). Climate change will further affect water availability and water consumption (EEA, 2008). Thus, there is a growing scientific and policy interest
for water resources analyses on the global and regional scale (Mäerker et al., 2003;
Menzel et al., 2007). Climate and socioeconomic drivers such as population and economic growth, land use and technological evolution may have a great impact on water
resources and stress (Menzel et al., 2007; Shen et al., 2008).
At the European level, several studies looked into water resources availability and
stress in the future (Henrichs et al., 2002; Mäerker et al., 2003; Menzel et al., 2007).
However the results differ between authors. Henrichs et al. (2002) projected a reduction
in total water withdrawals in Western Europe and attributed that reduction to technological evolution and to households and industry efficiency. Menzel et al. (2007) concluded
that in Southern Europe the water stress and water withdrawals will increase due to
irrigation demand and climate change.
In Portugal, there are published projections for the future population, such as the National Statistics Institute projections made for the country up to the middle of the XXIst
century (INE, 2008) and the study “Climate change: Mitigation Strategies in Portugal”
(MISP, 2007) with projections of the SRES scenarios downscaled for Portugal up to the
end of the XXIst century.
The project ADAPTACLIMA-EPAL aims to provide socioeconomic scenarios for population growth, land use and water use for an area which includes the Portuguese
basin of the Tagus River (Fig. 1) with all the municipalities that are supplied directly
or indirectly by EPAL, and the west aquifers of continental territory of Portugal. In total, 106 municipalities were included in the study area, of which, 34 are supplied by
EPAL. Projections of future water withdrawals will contribute to EPAL, as well as to
other stakeholders and policy makers. Other tasks of the project will include modelling
future climate and water availability. All the produced data will be analysed and used in
order to provide data to put in place a robust adaptation strategy to reduce vulnerability
to future changes. In this paper we will evaluate potential future water stress for EPAL
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2 Materials and methods
3. Transparency;
4. Plausibility of the results.
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The terminology local scenario was adopted for our results while for IPCC scenarios the
term SRES was used. At the national scale, there are also INE’s population projections.
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2. Consistency with the original scenario (SRES scenarios);
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1. Consistency with local data observed (for the historic or base period);
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Water use scenarios
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Local scenarios1 of water use until the end of the century were explored, not only for
the EPAL system, but also for all other systems that compete for water resources, such
as agriculture. We used the four IPCC SRES scenarios (A1, A2, B1 and B2) (IPCC,
2000) to produce climate and hydrological scenarios for the project. These scenarios
are in widespread use, therefore allowing to compare and validate our results (Drunen
et. al., 2011). The SRES set various scenarios with changes in population, economic
growth, technology, energy consumption, and greenhouse gas emissions (IPCC, 2007;
Shen et al., 2008). Several studies produced water consumption scenarios for Europe
for the XXI century based on SRES (e.g. Seckler et al., 1998; Märker et al., 2003;
Flörke, 2005; Alcamo et al., 2007; Bates et al., 2008; Shen et al., 2008; Kok et al.,
2009).
Linear regionalization (Fig. 2) of the SRES for the study area was applied, because
it is the most transparent and simple method available (Vuuren et al., 2007, 2010).
Regionalization followed the next criteria (Vuuren et al., 2006, 2010):
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by presenting socioeconomic scenarios for population growth, land use and water use
for the project area.
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2.1 Present water use by activity sector
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Data of water use per capita, by sector and municipality, was collected from the following sources: National Water Plan (INAG, 2001), Instituto Nacional de Estatistica (INE),
EPAL (internal data for the period 2000–2010) and National Inventory of Water Supply
Systems and Waste water (INSAAR, 2007).
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The main steps of the methodology are summarised in Fig. 3. The evolution of water
use depends on several factors such as population and land uses (e.g. Boland, 1998;
Houghton-Carr et al., 2008). In addition, other parameters were taken into account,
namely developments in technology, as well as changes in climate and consumer behaviour.
The downscaling for water use was done following three steps which are outlined
below.
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Water use scenarios
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Abstract
2.2 SRES scenarios – coefficients of change in demand factors
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1. Population – The CIESIN (Center for International Earth Science Information
Network), has developed a database containing regionalized SRES scenarios for
population and GDP at the country scale (CIESIN, 2002). Using the base population of the National Statistics Institute (INE) estimated for 2005 (INE, 2006), local
population scenarios for each municipality were built for the study area by applying the CIESIN growth rates downscaled for Portugal. Given the size of the study
area (and homogeneous characteristics in relation to the larger area, e.g. Portugal, the linear method of downscaling (O’Neill et al., 2001; Graffin et al., 2004)
was considered the most appropriate;
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The water consumption is determined by demand factors. These factors are the following ones:
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CLC, 2000 – http://etc-lusi.eionet.europa.eu/CLC2000/classes/index html
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5. Climate – we calculated a coefficient of change in consumption due to climate
change for each scenario and for each sector considering the available climate
scenarios for the study area and correlations obtained between consumption rates
and climate (SIAM II, 2006; EPAL, unpublished data).
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4. Behaviour and water pricing policies – we calculated a coefficient of change in
consumption due to changes in behaviours and policies for each sector of water
use and each scenario considering the studies referred in the previous point;
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3. Water use efficiency – we calculated coefficients of change in consumption efficiency for each sector of water use (Fig. 3) and each scenario considering available studies on scenarios of water consumption in Europe for the next century
(Sect. 3) (e.g. Seckler et al., 1998, Märker et al., 2003; Flork, 2005; Alcamo et al.,
2007; Bates et al., 2008; Shen et al., 2008; Kok et al., 2009);
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2. Land use – Corine Land Cover land use classes were reclassified by grouping
classes taking into consideration the classes used in SRES (Fig. 3). The sectors
of water use considered in the National Water Plan (INAG, 2001) were taken into
account. Local land use scenarios change in percentages for each municipality of
the study area were produced by applying linear downscaling on the trends of the
SRES scenarios for Europe and considering the characteristics of each county
and the trends observed in recent years (IPCC, 2007; Schröter et al., 2005; Verburg et al., 2006; Rounsevell et al., 2006). Since Lisbon municipality is already
mostly urban, urban expansion for Lisbon municipality was redistributed to neighbouring municipalities. This redistribution to the neighbouring municipalities was
done by analysing the recent tendencies (where the closest areas are more likely
to grow) and applying the same tendencies for the local scenarios.
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3. Technologies and behaviours might have effects on water consumption. It could
drop in all sectors due to technological developments, such as increases in recycled water, improvements in irrigation efficiency and reduction of losses (Mark
et al., 2003; Flörke, 2005; Kok et al., 2009). Technological improvements will be
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2. The effects of global warming increase the need for both domestic and agriculture water consumption (Bates et al., 2008). However, these increases should be
small, around 5 % in 50 yr (Bates et al., 2008). Scenarios A1 and A2 have the
highest temperature increases (and larger extensions of dry periods) and thus
the largest increases in water consumption needs;
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Water use scenarios
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1. Changes in land use, agricultural and industrial production are major forces of
changes in water consumption (Mark et al, 2003; Houghton-Carr et al., 2008). All
SRES scenarios indicate a significant reduction of the agricultural area (Table 3,
Section Results and Discussion);
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None of the studies which produced scenarios for water use in Europe for the XXIst
century could be directly applicable in this project for three different reasons. Firstly
these studies use different assumptions and scenarios. For example, Shen et al. (2008)
and Mark et al. (2003) do not consider changes considered in the SRES like reductions
of agricultural area in all scenarios, evaluating only the changes in consumption as
a function of changes in climate and behaviours. Secondly, they present scenarios
for different time periods. For example, Flörke (2005) presents scenarios only for the
2000–2030 period. And the third reason is that some of these studies do not consider
local characteristics and different dynamics between the different European countries.
Analysis of those studies were made to assess the general trends presented but with
the intention of applying them to the SRES scenarios and the reality of the study area.
Regardless of the study, general trends could be identified and are described below
(see also Table 1):
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3 Water use projections
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Scenarios were produced for the whole study area (106 municipalities) for water use
in the domestic, agriculture, industry and services sectors. Scenarios were also produced for the sub-area supplied by EPAL (34 municipalities) and for the municipalities
for which we had data for water use by sector (Lisbon and Batalha). For each sector the
following formula was used. Values for each parameter in the formula were obtained
considering available publications.
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where CScenarioXt = consumption in the scenario X and year t
Cb = consumption of water in the base year
∆Sectort = Net change in the demand sector between the base year and year t
(e.g. change in population, agricultural area or industrial activity)
Et = Coefficient of efficiency gains between the base year and year t
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CScenarioXt =Cb · ∆Sectort · Et · Compt · Climat
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4. The evolution of population will also have influence in water consumption. This
will decrease in all scenarios except A2.
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higher in scenarios A1 and A2. These trends are forced by worsening water shortages. According to Kok et al. (2009), it is likely that the increasing water scarcity
in the southern countries of Europe will lead national governments to implement
more efficient water rates, helping to reduce demand. The EU will impose more
savings and water recycling, as well as sustainable urban drainage systems on
a large scale for cities that are in water stress (especially in scenarios A2 and
B1). The same authors reported the possibility of using desalination in coastal
areas around the Mediterranean to provide water to some metropolitan areas.
Water markets provide higher levels of funding for the government to invest in
water saving devices at different scales (family, neighbourhood, city, etc.) (Kok
et al., 2009). In B1 and B2 scenarios, there will be a tendency to improve water
sustainability, reducing waste and reducing consumption per capita;
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In Table 1 we compiled the main trends in the forcing factors (land use, population,
climate, efficiency, behaviour, politics) which affect water use. Only one scenario (A2)
indicates an increase in the resident population of the study area of around 16 % by the
end of the century (Fig. 5). The remaining scenarios indicate a reduction in the population from 6 to 8 %. All scenarios, but especially A1, indicate a significant reduction in
agricultural area and an increase in urban area (Fig. 6).
The main trends of the SRES for land use changes in Europe, have been identified in
several publications (e.g. Schröter et al., 2005; Verburg el al., 2006; Rounsevell et al.,
2006; IPCC, 2007) and are resumed in Table 3. All scenarios, but especially A1, show
a significant reduction in agricultural area and an increase in urban area.
Comparing the results for our local scenarios in the Fig. 6 and the SRES European
tendencies from different authors (Schröter et al., 2005; Verburg el al., 2006; Rounsevell et al., 2006; IPCC, 2007) in Table 2, it is possible to see that our local scenarios are
coincident in the urban and agriculture land use, but not in grassland. Our results show
that this last type of land use will diminish while the European SRES tendencies are to
maintain.
Regardless of the scenario, water use will progressively be reduced until 2100 (Table 4). These reductions are mainly due to increased water use efficiency and reduction
of irrigated land. Even if a warmer and drier future climate will lead to a rise in water
demand for irrigation and for domestic use, none of the scenarios shows an increase in
water use. Also, even when we consider a significant increase in population (scenario
A2), overall water consumption will be reduced. Our results thus seem to indicate that
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Compt = Coefficient of change in behavior between the base year and year t
Climat = Coefficient of change in consumption due to changes in climate between the
base year and year t.
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behavioural and technological factors will be the main factors in shaping future water
use in the study area.
The projections of future water withdrawals presented in this paper are based on a
range of assumptions regarding agricultural, industrial, and domestic water use. That
is why we used four different scenarios, which indicate different possible futures in
terms of socio-economic developments. All scenarios project reduced water use in
all the sectors analyzed, which increases confidence in the results. Furthermore, our
results agree with several projects that model water use at a regional or global level
(e.g. Seckler et al., 1998; Menzel et al., 2007). Henrichs et al. (2002), for example,
have modelled water use up to 2070 by considering a simple scenario where present
water use trends are prolonged into the future and have obtained a decrease in water
withdrawals in Western Europe, mainly resulting from gains in the efficiency of water
use. The experiences of many countries show that water use intensity decreases after
reaching a saturation amount, mainly due to industrial restructuring and water use
efficiency improvements in production processes (Shen et al., 2008). Thus, although
projected changes in water withdrawals strongly depend on the assumptions regarding
socio-economic factors such as economic and industrial growth (Henrichs et al., 2002),
which are largely uncertain, it seems that most scenarios indicate the same long-term
trends in reduction of water use.
However, these results need to be considered carefully, also taking into analysis
scenarios of climate and hydrological change. In Portugal, water use is extremely correlated to the temperature, and the warm season is also the dry season, with higher
consumption rates. Therefore there is already some predisposition to water stress, especially in the south of continental territory and during summer months. During the 20th
century there has been a clear trend towards drier conditions, with decreases in rainfall and moisture availability in most Mediterranean regions; severe drought episodes
(from both meteorological and hydrological contexts) have become more frequent and
persistent, namely in the Iberia area (Sousa et al., 2011). In Portugal the total annual
precipitation has been considerably reduced during the last decades as it rained for less
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5 Conclusions
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Acknowledgements. This study was supported by EPAL. We are thankful to EPAL’s Climate
Change working group, who has supplied valuable information. We are also thankful to Nuno
Grosso, Mário Pulquério, David Avelar and Tiago Lourenço for their contributions in this project.
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Water use scenarios
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The results of this study show that all different scenarios considered indicate reductions in water use in the study area. Another important result is that behavioural and
technological factors are determinant in shaping future water use in the study area.
In Portugal, water use inefficiency corresponds to about 41 % of the total withdrawals
as the National Water Plan (2001) referred. Thus, it is not surprising that there can be
enormous gains in water efficiency, especially in the agricultural and industrial sectors.
The scenarios are a useful framework for thinking about the future and a fundamental
step for EPAL to prepare a long-term adaptation strategy to climate change meant to
contribute to the reduction of vulnerability of different future societies. EPAL successful
adaptation to climate change is vital for the economic activities and the local population.
The tasks that look at the impacts in the resources (quantity and quality of water) will
also need to be taken into account in the process, so that the adaptation occurs in
a sustainable way. To build a consistent strategy for climate change adaptation, both
climate and socioeconomic scenarios are important, while socioeconomic scenarios
can decrease the decision failures.
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number of days (SIAM II, 2006). Global climate models project a decrease in precipitation, an increase in temperatures and evapotranspiration, and an enlarged dry season
for the study area (SIAM II, 2006). Our results show that socio-economic changes may
reduce water consumption and therefore the risk of increased water stress due to climate change may be lower than previously expected.
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House, J. I., Kankaanpää, S., Leemans, R., Metzger, M. J., Schmit, C., Smith, P., and Tuck,
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++
––
≈
–
≈
––
≈
–
+
–
–
–
Agricultural area
Coefficient of change in water use for crops due to climate change
Coefficient of change in agricultural water use due to efficiency
––
++
–
––
++
–
–
+
–
–
+
–
Total Agriculture Water Use
––
––
–
–
Population
Coefficient of change in behaviour
Coefficient of change in consumption due to climate change
Coefficient of change in domestic water consumption due to efficiency
–
≈
+
–
+
≈
+
–
–
–
+
–
–
–
+
–
Total Domestic Water Use
–
≈
––
––
Coefficient of industrial growth
Coefficient of change in industry water use due to efficiency
Total Industry Water Use
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Source: Adaptaclima-EPAL project report (2011).
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Table 1. Main trends in the various forcing factors for water use for each scenario. Legend: (+)
indicates an increase, (++) indicates a substantial increase, (≈) indicates no change or very
small changes, (–) indicates a decrease; (– –) indicates a substantial decrease.
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CIESIN
A1 e B1
INE
central
INE
low
INE
high
INE
without
migrations
% total grow 2005–2060
−8.33 %
3.76 %
−0.86 %
−1.94 %
−15.70 %
13.47 %
−23.32 %
% total grow 2005–2100
−6.07 %
19.61 %
−8.09 %
Source: Adaptaclima-EPAL project report (2011).
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CIESIN
B2
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Table 2. Percentage of Growth on the INE (2008) projections and scenarios of CIESIN (2002).
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B1
B2
–––
+++
+
+
++
≈
+
––
++
+
+
+
≈
≈
––
++
+
++
+
≈
++
–
+
≈
+
+++
≈
++
Adaptaclima-EPAL project report (2011).
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Agriculture
Urban
Industry
Biofuel
Forests
Grassland
Protected Areas
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Table 3. Main trends in land use changes in the SRES for Europe.
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3
1 443 548 958
2 194 069
237 702 531
6 466 211
A2
B1
B2
22.7 %
60.2 %
87.60 %
65.70 %
46.6 %
59.4 %
98.25 %
63.90 %
37.5 %
28 %
48.72 %
48.72 %
52.2 %
58.3 %
49.77 %
74.12 %
Source: Adaptaclima-EPAL project report (2011).
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Agriculture1
Industry2
Domestic2
Services2
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Table 4. Water consumption by sector in the project study area Adaptaclima-EPAL in the base
year (2000) and scenarios (percent of base year values) for 2080. 1 – Baseline data: National
Water Plan 2001, Corine Land Cover 2000, 2 – Baseline data: INSAAR 2007, Corine Land
Cover 2000.
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Fig. 1. Study Area. Source: Adaptaclima-EPAL project report (2011).
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Fig. 2. Downscaling methods in Socioeconomic Scenarios. Source: adapted from Vuuren et
al. (2006).
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Fig. 3. Resumed methodology for water withdrawals projections. Source: Adaptaclima-EPAL
project report (2011).
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Fig. 4. Land Use Downscaling Methodology. Source: Adaptaclima-EPAL project report (2011).
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ure 4 - Land Use Downscaling Methodology. Source: Adaptaclima-EPAL pro
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Milions
5
4,5
B2
4
3,5
3
2005 (INE)
2040
2080
2100
Fig. 5. Population local scenarios. Source: Adaptaclima-EPAL project report (2011).
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Population evolution for the study area
5,5
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l scenarios for land use change for: a) agriculture, b) grassland and c)
Fig. 6. Local scenarios for land use change for: (a) agriculture, (b) grassland and (c) urban.
Source: Adaptaclima-EPAL project report (2011).
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