assessment of future scenarios of climate and land-use changes in the imprints test-bed areas
TRANSCRIPT
Assessment of future scenarios of climate and land-usechanges in the IMPRINTS test-bed areas
A. Cabello a, M. Velasco a, J.I. Barredo b, R.T.W.L. Hurkmans c, A. Barrera-Escoda d,D. Sempere-Torres e, D. Velasco e,*aCETaqua Water Technology Centre, Barcelona, SpainbEuropean Commission – Joint Research Centre, Institute for Environment and Sustainability, Ispra, ItalycBristol Glaciology Centre, Bristol, United KingdomdSMC – Catalan Meteorological Service, Barcelona, SpaineCRAHI – Research Centre on Applied Hydrometeorology, Technical University of Catalonia, Gran Capitan 2-4, 08034 Barcelona, Spain
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7
a r t i c l e i n f o
Published on line 2 April 2011
Keywords:
Climate change
Extreme events
IMPRINTS
Flash floods
Debris flows
Downscaling
a b s t r a c t
The main objective of this work is to identify and evaluate the potential impacts produced by
climate and land-use changes in six European test-bed basins (Llobregat, Guadalhorce,
Gardon d’Anduze, Linth, Verzasca and Sambuco). Data to build future scenarios that can
modify the different basins’ flash flood and debris flow risk level has been analyzed in this
paper. High resolution climate scenarios have been obtained from several European projects
and/or National initiatives, depending on each case. Climatic variables have been widely
analyzed, with a special focus on extreme precipitation. Typical generalized extreme value
(GEV) distributions have been fitted to observed and projected rainfall data to assess impacts
in the frequency distributions of extreme rainfall up to 2100. Regarding climate, the main
conclusion is the importance of using data at the maximum spatial and temporal resolution
applying downscaling methodologies adapted to basin scale (test-bed areas ranging from
approx 200 to 5000 km2) and oriented to obtain extreme rainfall values.
In general, high variability has been detected, obtaining very different results for the
different models and scenarios. Data corrections may lead to better representations of
present situations and, therefore, more reliable future projections, but currently some of
them are not suitable for extreme precipitation assessment.
Regarding land-use changes, a cellular automata-based model has been used (MOLAND)
to simulate the 2000–2040 period taking the CORINE land-use dataset as input data.
Llobregat, Guadalhorce and Gardon d’Anduze basins have been identified as potentially
interesting for simulating urban land-use dynamics due to the existence of important urban
areas within their limits. The assessment of the rural land-use changes has been carried out
using the results from the EURURALIS project (2000–2030 period), available for all the basins.
The results of this paper are framed in the FP7 project IMPRINTS that has the aim of
analyzing impacts of future changes to provide guidelines for mitigation and adaptation
measures and, in general, to improve the application of the EC Flood Risk Management
Directive.
# 2011 Elsevier Ltd. All rights reserved.
* Corresponding author.
avai lab le at w ww.s c ienc ed i rec t . c o m
journal homepage: www.elsevier.com/locate/envsci
E-mail address: [email protected] (D. Velasco).
1462-9011/$ – see front matter # 2011 Elsevier Ltd. All rights reserved.doi:10.1016/j.envsci.2011.03.003
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7 885
1. Introduction and objectives
One of the most important natural hazards in Europe are
floods. They have important social impacts, in addition to the
damage they can cause. Thus, flood risk management is a
critical component of public safety and quality of life.
Extreme events are expected to increase all over Europe
due to global change (Dankers and Feyen, 2009). Some
researchers conclude that in critical regions, extreme events
like floods and droughts with an intensity of today’s 100-year,
may recur every 10–50 years by the 2070s (Lehner et al., 2006).
In particular, flash floods (FF) and debris flows (DF), triggered
by local intense precipitation events, are likely to be more
frequent throughout Europe (Christensen and Christensen,
2007; Kundzewicz et al., 2001). Climate and land-use changes
are expected to modify current flood risk all over the world.
Consequently, the Floods Directive (FD; EC, 2007) integrates
the effects of climate change in assessing risks. Flood risk
management plans must assess the probable impacts of
climate change on the frequency and intensity of the
precipitation causing the floods.
Within IMPRINTS project, supported by the European
Community’s Seventh Framework Programme (Contract
FP7-ENV-2008-1-226555), impacts of future changes, including
climatic, land-use and socioeconomic changes on FF and DF
risk are analyzed, to provide guidelines for mitigation and
adaptation measures. The main objective of the project is to
contribute to the reduction of loss of life and economic
damage through the improvement of the preparedness and
the operational risk management of FF and DF generating
events, as well as contributing to sustainable development
through reducing damages to the environment.
The aim of the present work is to identify and evaluate the
future climate (precipitation) patterns and land-use changes
in the test-bed basins included in the project. Different
methodologies and data sources have been used and
compared in the study in order to detect potential coherent
trends and regionalized scenarios. Six different test-bed
basins are included in the study as FF and DF prone areas (2
located in mountainous catchments in the Alps and 4 in
Mediterranean catchments). The results of the present
analysis will be applied later in the risk management and
assessment tool that will be available at the end of the
IMPRINTS project (in 2012).
2. Description of IMPRINTS test-beds
Selected Mediterranean catchments are Llobregat and Gua-
dalhorce basins in Spain (ES), Gardon d’Anduze in France (FR)
and Sambuco basin in Italy (IT).
Llobregat basin is located in Catalonia, in the Northeast
part of the Iberian Peninsula. It covers a total area of 5000 km2
and its elevation ranges from sea level up to 1259 m. Llobregat
River, which has a length of 156.6 km, has its main source in
the Pyrenees Mountains. In relation to the climatic conditions
of this area, the average annual rainfall over the region is
about 600 mm and one third of this precipitation can fall in
less than 48 h. Floodplains are quite densely populated areas
and, since Llobregat basins are FF prone areas, weather
forecasting, and measurement of rain and prevention of floods
are subjects of major social interest in Catalonia.
The second Spanish basin is the Guadalhorce basin
(3157 km2), which is the main watershed in Malaga province
(Southern Spain) and includes 13 municipalities and it has a
population of 132,928 inhabitants. Three dams for volume
regulation purposes are located in the upstream reach of the
basin. The rainfall distribution of the area is well defined,
being autumn and winter the wettest seasons, when torrential
FF are quite frequent.
The Gardon d’Anduze basin is located in the northeastern
part of the Languedoc and it is integrated in the Gardons’
basins system. The Gardon d’Anduze River has a length of
30 km and its watershed has an area of 545 km2. The river has
its spring in the Cevennes Mountains at 1500 m and discharges
in the Gard River at 200 m. The Gard River will later flow into
the Rho ne River. The Gardon d’Anduze catchment area is
covered basically by forest (80% of the territory) and urbanized
areas are only concentrated in a few villages (around 7000
inhabitants in the whole basin). As a Mediterranean regime,
most of the rain is concentrated in autumn and spring, and
occasionally in summer, when there are very intense storms,
that can lead to important accumulations of rain (sometimes
even reaching 1/3 of the total annual precipitation).
The fourth Mediterranean test-bed is the small Sambuco
catchment. Its extension is approximately 7 km2 and it is
located on the Costa Amalfitana (Napoly, Italy). This region is
varied, with an uneven morphology, represented nearly
exclusively by dolomite and limestone cliffs from Mesozoic
age, covered by pyroclastic materials. Numerous faults and
fractures are placed in the area leading to a strong tectonic
activity and a prone high risk area for DF occurrences.
Regarding the alpine catchments, the Linth and Verzasca
basins are studied. The Linth basin is located on the northern
side of the Swiss Alps and covers an area of about 685 km2. The
basin shows a range of elevation between 435 and 3610 m a.s.l.
Forests cover 20% of the basin. The portion of rocks and bare
soil areas is 34%. Large parts of the watershed are used for
pasture (31%) while in the upper part there are some small
glaciers, which make about 4% of the total basin area. Water
stored in two big reservoirs in spring and summer (melting
period) is released for production of peak electricity. The
Verzasca basin, on the other hand, is located in the south of
Switzerland (south of the Alps), and covers an area of 186 km2.
Its elevation range is 490–2870 m a.s.l. Forests (30%), shrub
(25%), rocks (20%) and alpine pastures (20%) are the predomi-
nant land cover classes. The discharge regime is governed by
snowmelt in spring and early summer and by heavy rainfall
events in fall.
3. Extreme rainfall analysis
3.1. Description of methodology and available data
As presented in Fig. 1 all the test-bed basins are located in the
Mediterranean and Alpine regions which, due to the high
variability of their climates, are very vulnerable areas to
climate change. Therefore, it is crucial to assess the potential
Fig. 1 – Location of IMPRINTS selected test-beds.
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changes that may occur. To do that, data from different global
and regional models have to be studied. As their uncertainty
has been shown to be typically large (e.g. Arpe et al., 2005;
Covey et al., 2003), several models and scenarios will be
studied, obtaining a range of values which may be able to
represent the future situation. The use of climatic data at the
maximum possible resolution is crucial. However, in general it
has been observed that available climatic models are not
properly optimized for the extreme events representation.
This is especially clear in this case, where the impacts of
climate change in such localized phenomena as FF and DF
events are needed to be assessed. The different climate
models and scenarios used can be found in Table 1.
Table 1 – Characteristics of the climate models and observatio
Basin Institution Downscalingmethod
Model
GCM
Llobregat SMC Dynamical ECHAM5-MPIOM MM
Observations Alt
MPI-MET Dynamical ECHAM5-r3 RE
METO-HC Dynamical HadCM3Q0 Ha
Observations Spa
Guadalhorce FIC Statistical CGCM2 FIC
Observations AE
MPI-MET Dynamical ECHAM5-r3 RE
METO-HC Dynamical HadCM3Q0 Ha
Observations Spa
Linth UBA Dynamical ECHAM5-MPIOM RE
Verzasca UBA Dynamical ECHAM5-MPIOM RE
Sambuco UC Statistical ECHAM5-MPIOM UC
Observations –
As the main objective of this study is to obtain variables to
evaluate the potential changes in frequency and/or intensity
of FF and DF events, the analysis of extreme precipitation
constitutes the key aspect of the present work. The first
approach to model annual maxima of precipitation timeseries
was based on extreme value distributions such as Gumbel,
Frechet and negative Weibull. It was in 1955 when the
generalized extreme value (GEV) distribution was developed
(Jenkinson, 1955) to combine the three above mentioned
classical extreme value distributions. The application of GEV
has been adopted in the proposed methodology for consis-
tence reasons. Using GEV distributions, the intensity-return
period relationships are obtained for each test-basin. As this
n datasets used in the test-bed basins.
Outputresolution
SRESscenarios
Controlperiod
Futurescenarios
RCM
5 15 km, 6 h A2, B1 1971–2000 2001–2100
ava-Ortiz 3 km, daily 1971–2000
MO 25 km, daily A1B 1961–2000 2001–2100
dRM3Q0 25 km, daily A1B 1961–2000 2001–2100
in 02 20 km, daily 1950–2003
analogs Station, daily A2, B2 1961–2000 2011–2100
MET Station, daily 1961–2000
MO 25 km, daily A1B 1961–2000 2001–2100
dRM3Q0 25 km, daily A1B 1961–2000 2001–2100
in 02 20 km, daily 1950–2003
MO 10 km, hourly A2, A1B, B1 1951–2000 2001–2100
MO 10 km, hourly A2, A1B, B1 1951–2000 2001–2100
analogs Station, daily A1B, A2 1971–2000 2011–2040
2071–2100
Station, daily 1971–1999
Fig. 2 – Spatial pattern of differences in mean monthly precipitation values between the control period and the 2071–2100
average for the A2 scenario with the SMC model in the Llobregat basin.
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paper is focusing in the FF and DF assessment, it is crucial to
analyse events with high return periods. In this case, in order
to obtain 150 years return period curves (Figs. 3–7) time series
of 130, 140 and 150 years (depending on the model) have been
used in the procedure; additionally, GEV curves obtained for
the control period have been included in the figures as a key
reference for a proper comparison to resulting GEV curves for
the future projections data. In order to compare both periods,
historical GEV distributions (which have been adjusted to
available 30 years long observation datasets) are extrapolated
to larger return periods.
For the Llobregat basin, Servei Meteorologic de Catalunya
(SMC), one of the IMPRINTS project partners, has provided
high-resolution climate data for the 1971–2100 period (Barrera-
Escoda and Cunillera, 2010). The control period is 1971–2000
and the future projections cover 2001–2100 for the Catalonia
region taking into account 2 emission scenarios from the
Intergovernmental Panel on Climate Change (IPCC): A2 and B1
(IPCC, 2000). In addition, climate data from the 6th Framework
Programme (6FP) project ENSEMBLES have also been used:
models from the Max Planck Institute (MPI-MET) and the
Hadley Centre (METO-HC), which cover a domain that includes
the whole Europe. Using three different climate models it is
possible to compare their results and evaluate the uncertainty
associated with their projections.
The second Spainsh basin, Guadalhorce, has been studied
by the Fundacion para la Investigacion del Clima (FIC), which
carried out a study to elaborate climate change scenarios for
the Andalusian region (FIC, 2006). Two different general
circulation models (GCMs) (only one included in this study)
and a statistical downscaling method developed by this
research centre (FIC analogs) were used. Besides FIC data,
the same model runs from the ENSEMBLES project that were
analyzed for the Llobregat basin have been also used in the
Guadalhorce basin.
For both Swiss basins, Linth and Verzasca, high-resolution
climate scenarios were obtained from the Max Planck Institute
for Meteorology in the framework of the REMO/UBA project
(Jacob et al., 2008). In this case, the uncertainty has been
assessed by using three CO2 emission scenarios from the IPCC:
A1B, A2 and B1 (IPCC, 2000).
For the Sambuco basin, no national or regional project has
been identified. Due to the small size of this basin, a statistical
downscaling seemed to be a better option. In the framework of
the ENSEMBLES project, University of Cantabria (UC) devel-
oped the Statistical Downscaling Portal (SDP) to facilitate the
downscaling task to end-users through a user-friendly web
portal (Cofino et al., 2007; San-Martın et al., 2008), where users
can obtain downscaled data for the chosen region, test and
validate different GCM’s and several statistical techniques.
This tool has been applied to the Sambuco basin and output
results analyzed herein.
For the Gardon d’Anduze basin, data was obtained with an
important delay due to administrative issues, and therefore
the climatic study for this basin has not been included in this
paper.
Before starting with the analysis results, the different
models have been validated. In the case of the SMC
projections, the performance of the model has already been
assessed in the test-bed region by the developers (Barrera-
Fig. 3 – GEV fitted to the annual maxima daily precipitation for the observations (1971–2000), control period (1971–2000)
(dashed) and climate projections series (1971–2100) (solid) simulated with the climate models showing those cases that
provide maximum and minimum values for the Llobregat basin.
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7888
Escoda and Cunillera, 2010). In the other cases, a validation
comparing different variables from the control period and
observation datasets in each one of the test-bed areas was
necessary.
Three different aspects of both, mean daily temperature
and cumulative daily precipitation have been studied in the
model validation phase: intra-annual variability, seasonal
variability and probability density functions (Gaussian kernel).
In general, all the models studied show good performances
regarding these mean variables.
Further discussion regarding the validation and behaviour
of the models used in each test-bed is included in next
sections. In any case, the work presented in this paper
constitutes a general view of the more detailed study focused
Fig. 4 – GEV fitted to the annual maxima daily precipitation for
(dashed) and climate projections series (1961–2100) (solid) simu
provide maximum and minimum values for the Guadalhorce b
on the climate analysis carried out within the IMPRINTS
project.
3.2. Results in the Llobregat basin
First of all, results of the daily mean precipitation values have
been assessed. A clear decreasing trend appears in the three
models used for the Llobregat basin. Mean precipitation
decreases over the whole 21st century, reaching anomalies
that range between 0 and �40 mm/month for the 2071–2100
period depending on the model and IPCC scenarios. The
spatial patterns show similar results for all the models, being
the spatial description of the SMC model much more accurate
due to the finer grid used (Fig. 2).
the observations (1961–2000), control period (1961–2000)
lated with the climate models showing those cases that
asin.
Fig. 5 – GEV fitted to the annual maxima daily precipitation for the control period (1951–2000) (dashed), and climate
projections series (1951–2100) (solid) simulated for the scenarios that provide maximum and minimum values for Linth
basin.
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Extreme precipitation has been widely studied in this
paper, as this is the triggering factor of FF and DF events.
Firstly, a comparison between the annual maximum precipi-
tation values for the control period and the observation
datasets available has been carried out. Fig. 3 shows only
results associated with those scenarios and/or climate models
that provide maximum and minimum annual maxima
precipitation values. SMC model presents the best results of
the three, as the GEV fitted to the projections provided by the
model and the observations show small differences. On the
other hand, the two models from the ENSEMBLES project
present a poorer performance, showing an overestimation of
the magnitude of extreme events.
After checking the ability of the models to fit observations,
the analysis of future scenarios shows diverse results. METO-
Fig. 6 – GEV fitted to the annual maxima daily precipitation for
projections series (1951–2100) (solid) simulated for the scenarios
basin.
HC results show large temporal variability between the
beginning and the end of the 21st century, being impossible
to detect a clear future trend. Still, considering the whole
century, the model is able to describe a general decrease of the
intensity of the extreme events. This decrease is specially
pronounced in the north-eastern part of the basin, the same
area where the largest decrease in mean precipitation was
localized.
MPI-MET model is the model analyzed with the poorest
extreme precipitation results. Its spatial and temporal
variability are extremely high and hence, it is not possible
to detect any trend.
SMC model results include A2 and B1 scenarios. In this
case, a clear increasing trend in the annual maximum
precipitation is detected, especially in the southern part of
the control period (1951–2000) (dashed), and climate
that provide maximum and minimum values for Verzasca
Fig. 7 – GEV fitted to the annual maxima daily precipitation for the observations dataset (1971–1999) and control period
series (1971–2000) (dashed) simulated for the Sambuco basin.
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7890
the basin. This increase becomes larger with higher return
periods. On the other hand, some small areas in the north-east
show a slight decrease. In general, scenario B1 shows a more
moderate situation than A2.
From the results of the three different models analyzed, it
can be concluded that SMC model seems to simulate better
extreme precipitation. In any case, one of the main aims of this
work was to assess the uncertainties associated with climate
data. This has been accomplished by comparing results from
three different regional circulation models (RCMs) driven by
two GCM and forced by three IPCC-SRES scenarios. Variability
described can be observed again in Fig. 3, where the GEV
curves showing the maximum and minimum annual maxima
precipitation values, together with its control and observa-
tion’s curves are plotted.
Even if in some cases, the analysis of extremes exhibits
differences between projections and observations, this is
important to show the uncertainties associated with climate
results and the necessity to evaluate it.
3.3. Results in the Guadalhorce basin
Future projections for the two ENSEMBLES models show slight
decreases of the mean precipitation values that become larger
over time. In the case of the FIC model results, a decreasing
trend is also observed, and is especially marked in the last
years of the century. No significant differences can be detected
between results from A2 and B2 scenarios. As a statistical
downscaling technique is used, results have been obtained at a
station level and they show high spatial variability, presenting
some adjacent stations trends with an opposite sign.
Again, to assess the skill of the model to describe extreme
precipitation, a comparison between GEVs fitted to the control
and the observations annual maximum precipitation series
has been carried out (Fig. 4). MPI-MET and FIC models present
opposite results. In the first case the model shows an
overestimation of the intensity of the extreme precipitation,
whereas FIC model presents an underestimation. A bias
correction method might be applied in the future to improve
the models results. In this case, errors seem to increase with
return periods and, therefore, correction factors should follow
this same pattern.
On the other hand, METO-HC model presents an overesti-
mation of the annual maxima precipitation for the northern
region of the basin and an underestimation for the southern
one. FIC model results include A2 and B2 scenarios, but no
remarkable differences can be observed between them in the
extreme precipitation analysis. In addition, no trend can be
detected by studying different future periods (first and last
decades of the 21st century) and no spatial pattern is observed
at the basin level.
MPI-MET model shows the poorest results regarding
extreme precipitation. Spatial and temporal variability of
the results is extremely high and, therefore, it makes
impossible to detect any trend.
After the analysis and comparison of the three different
models in the Guadalhorce basin, it can be concluded that they
present larger variability than in the Llobregat basin case.
Comparison of the different scenarios gives some non
expected results, such as A1B scenario showing higher
precipitation values for the same return period than A2 that
is supposed to be more severe. But again, as one of the aims of
this work was to assess the uncertainties associated with
climate projections, this can be observed in Fig. 4.
3.4. Results in the Linth and Verzasca basins
On average, summer precipitation is expected to decrease and
winter precipitation to increase. The trend over the future
scenarios is that there is a slight decrease in the amount of
precipitation for A2 and A1B scenarios, while it increases for
B1. Analysis of the annual maxima precipitation shows that an
increase in the magnitude of extreme precipitation can be
expected (Fig. 5). Such an increase in the recurrence interval of
certain extreme precipitation events might have an influence
on the occurrence of FF and DF.
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7 891
It should be mentioned, however, that in this case only data
from one model chain (ECHAM5-MPIOM-REMO) is used. As
mentioned before and due to the high uncertainty associated
with climate projections, it would be useful to repeat the
present analysis using different global and/or regional models.
In this case, the comparison can be carried out only among the
three different IPCC scenarios analyzed.
Regarding the Verzasca basin, and in a similar way to the
results of the Linth basin, it is expected that, on average,
summer precipitation decreases and winter precipitation
increases. Both A2 and A1B scenarios show a decrease in
the overall amount of precipitation but it is expected to
increase for B1. Generally, for A2 and B1, an increase in the
magnitude of extreme precipitation is observed (Fig. 6), while
A1B results do not show any increase in the occurrence of
extreme events. Still, from the results obtained, it is possible to
conclude that an increase in the occurrence of FF and DF
events should be expected.
3.5. Results in Sambuco basin
In this case only one climate model has been used to obtain
climate projections for mean temperature and daily precipi-
tation: the UC analogs method driven by ECHAM 5 from the
Statistical Donwscaling Portal developed by the University of
Cantabria. In the validation phase it has been shown that the
seasonal cycle is not well represented by the model, which
overestimates winter and summer precipitation and under-
estimates autumn precipitation. In order to check the ability of
the statistical downscaling method to reproduce the frequen-
cy of rainfall events, dry periods have been calculated for each
season. The model simulates precipitation events much more
frequently than it is shown by observations. This leads to a
pattern of homogeneous precipitation that does not adjust to
reality. Because of this, the method seems to present a poor
skill in simulating extreme precipitation events. The under-
estimation of this type of rainfall is too important, making this
method not suitable for the detection of extremes (Fig. 7). As
commented before, analyzing precipitation frequency along
the year, it is clear that the model simulates more days of rain
in all seasons than those observed. The model distributes total
precipitation homogeneously along the whole year, diminish-
ing in this way the extreme precipitation values.
As it has been stated, the results of this model do not fit the
purpose of this study that is mainly the assessment of extreme
events in a localized area.
4. Analysis of land-use change
4.1. Urban land-use
4.1.1. MethodologyThe objective of this task is the implementation of urban land-
use change models for the simulation of climate change
scenarios in three selected test-bed areas. The land-use
scenarios will be input into risk assessment analyses in a
later stage in the IMPRINTS project, since they might describe
potential changes in the exposure component within the risk
equation in the test beds. Within this framework, impacts
resulting from changes in both natural and socio-economic
drivers will be assessed.
Scenario simulations of urban land-use dynamics have
been implemented in three basins having large anthropogenic
effects, i.e. Llobregat (ES), Guadalhorce (ES) and Gard (FR). The
MOLAND cellular automata (CA) model has been used for this
purpose. The CA model comprises several factors that drive
land-use dynamics in a probabilistic approach. Barredo et al.
(2003, 2004) defined the process of urban land-use dynamics as
a probabilistic system, in which the probability that a place in
a city is occupied by a given urban land-use type at a given
time step is a function of accessibility, suitability, zoning
status (not available in this study), and the neighbourhood
effect measured for each specific land-use type at each specific
time step. In addition, a stochastic parameter is included for
simulating the degree of stochasticity that is characteristic in
most social and economic processes. The factors used in the
implementation of the model are: (1) physical suitability,
which describes the degree to which the cell is fit to support
the particular land-use function and the associated economic
or residential activity; (2) accessibility, which represents how
the forecasted activity can fulfil the cell’s needs for transpor-
tation and mobility given the underlying transportation
system; (3) dynamic impact of land uses in the area
immediately surrounding the cell. A high attractiveness
increases the probability that the function will occupy the
cell, otherwise, the location will remain available for other
land uses. This process constitutes the highly non-linear
character of this model (Barredo and Engelen, 2010); and (4)
stochastic parameter, which determines the level of stochas-
ticity of the simulation.
The scenarios produced by the IPCC in the SRES (Nakice-
novic and Swart, 2000) have been used for the implementation
of the urban land-use scenarios. Scenarios A2 and B1 were
implemented in Llobregat and Gard, and A2 and B2 in
Guadalhorce. The scenarios produced cover a period until
2040. The set up of the meta-narrative descriptions is
considered to be the first step in climate change land-use
modelling studies (de Nijs et al., 2004; Reginster and
Rounsevell, 2006; Solecki and Oliveri, 2004). One storyline
was produced for each scenario describing the drivers that
they represent.
The second step for the implementation of the scenarios
is to quantify the demand for urban land-use for each meta-
narrative. In the present study, a similar approach to that of
Solecki and Oliveri (2004) and Barredo and Gomez Delgado
(2008) is followed. Thus, by assessing trends of urban land-
use conversion in the decade 1990–2000, land demand
datasets for each of the meta-narratives implemented have
been produced. Scenario A2, which represents a very rapid
urban growth, has been defined as having 20% more
conversion per year than the reference trend projection
(1990–2000). And scenarios B1 and B2 represent a decrease of
60% and 50% respectively per year conversion in relation to
the trend observed in reference period, as presented in
Table 2.
CORINE (EEA, 1993) land cover/use datasets have been used
as input data into the model. This European-wide dataset
creates the possibility of modelling large European areas using
a single implementation of the model.
Table 2 – Hectares of urban land-use. 1990, 2000 and 2006 as obtained from CORINE datasets. 2040 B1, B2 and A2, landdemands for the scenarios implemented.
Year/hectares
1990 2000 2006 2040 2040
Llobregat (ES) B1 A2
Cont. urban fabric 19,570 20,129 – 21,023 22,812
Disc. urban fabric 22,494 23,743 – 25,741 29,738
Ind/commercial 7994 11,206 – 16,345 26,624
Guadalhorce (ES) B2 A2
Cont. urban fabric 5309 5562 – 6068 6776
Disc. urban fabric 9250 10,252 – 12,256 15,062
Ind/commercial 1013 1327 – 1955 2834
Gard (FR) B1 A2
Cont. urban fabric 433 – 433 433 433
Disc. urban fabric 15,331 – 18,341 20,900 26,017
Ind/commercial 1255 – 1544 1790 2281
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7892
Before the implementation of the scenarios, the model has
been calibrated by using datasets from 1990 and 2000 for
Llobregat and Guadalhorce and 1990 and 2006 for Gard. Thus
the simulation period for the scenarios is 2000–2040 for the
first two study areas and 2006–2040 for Gard.
4.1.2. ResultsThe land-use scenarios for 2040 have been successfully
implemented in the 3 test-basins (see Figs. 8 and 9). The
two families of scenarios produced, A and B, show divergent
patterns of land-use change. A2 scenario shows a decrease in
the amount of natural and agricultural land during the
modelling period. This scenario shows a more scattered and
diffuse urban land-use pattern. Urban nuclei in peripheral
areas have grown more than the urban areas closer to the core
cities. This is considered a sprawled-like scenario, urban areas
move toward the outskirts with a very low proportion of
Fig. 8 – Urban land-use in Llobregat basin: (1990) urban land-use
(2040-A2) A2 urban land-use scenario for 2040; (2040-B1) B1 urb
readability of the map non-urban land-use classes are not inclu
infilling and large clusters of vacant land between the urban
nuclei. The proportion of low-density residential areas
increases as well. A rapid urban growth in this scenario is
also observed.
B1 and B2 scenarios show a much slower process of urban
growth. These scenarios could be the result of a series of
spatial planning regulatory measures and policies. The
simulated land-use shows a more compact urban land-use
pattern with a higher proportion of infilling than A2 scenario.
The conceptual implementation of CA models is founded
on complex systems theory. Models of complex systems
characterize the collective properties of a system from a large
set of local interactions. Hence, it is assumed that the overall
pattern of urban systems emerges from a myriad of interac-
tions at local level that led to the process of urban emergence
in the cellular landscape of the model (Batty, 2005). Addition-
ally, urban growth is a socio-economic process showing highly
from Corine 1990; (2000) urban land-use from Corine 2000;
an land-use scenario for 2040. Note that for a better
ded in this figure.
Fig. 9 – Urban land-use in Gard basin: (1990) urban land-use from Corine 1990; (2006) Urban land-use from Corine 2006;
(2040-A2) A2 urban land-use scenario for 2040; (2040-B1) B1 urban land-use scenario for 2040. Note that for a better
readability of the map non-urban land-use classes are not included in this figure.
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7 893
non-linear relationships, and in some circumstances could be
highly variable in the spatio-temporal domain. With this in
mind one has to be careful when using the results of this type
of models for assessing the impacts of natural disasters
(Barredo and Engelen, 2010). One critical aspect is the length of
the simulation period. A simulation period of 20–40 years is
often chosen by most studies (Solecki and Oliveri, 2004;
Barredo and Gomez Delgado, 2008; Pontius et al., 2008; Sante
et al., 2010). This is because model results within this range of
time produce a mid-term scenario with an acceptable level of
uncertainty. The overall accuracy obtained for the calibration
period for the three test-beds is 92%, 97% and 86% for
Llobregat, Guadalhorce and Gard respectively. The accuracy
of three simulations in this section is in line with previous
results of the model used (Barredo et al., 2003, 2004; Barredo
and Gomez Delgado, 2008) and with results from other similar
models showing an average overall accuracy of around 80%
(Pontius et al., 2008; Sante et al., 2010). Nevertheless, the
overall accuracy is not directly comparable because of
different model configurations, duration of the simulation
period, size and characteristics of the study areas and other
factors.
In order to translate these results into variables describing
potential impact on FF&DF risk levels, the exposure factor
affecting the risk equation can be assessed on the basis of
resulting land-use datasets, since exposure is among the
anthropogenic factors that contribute to FF damage potential.
Furthermore, changes in risk as consequence of societal
changes will be assessed by using the land-use scenarios
implemented in this section (e.g. Feyen et al., 2009).
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7894
4.2. Rural land-use
4.2.1. Data and methodologyThe main objective of this work was to assess the projected
rural land-use changes for the six test-bed basins. Future land-
use projections, carried out by the European project EURUR-
ALIS (Eickhout and Prins, 2008; Verburg et al., 2008) were used
to evaluate the land-use changes experienced by the six basins
from year 2000 to 2030. The project developed an exhaustive
study that determined the type of land-use for each 1 km2 cell
all over Europe in 2030, according to four different IPCC
scenarios: A1, A2, B1 and B2 (Nakicenovic and Swart, 2000).
The methodology followed in EURURALIS was based on
models at different scales. Several variables that affect,
directly or indirectly, the land-use were considered (demo-
graphic and economic trends, consumer preferences, world
trade regulations and policies, etc.). The spatially explicit
model CLUE (Verburg et al., 2006, 2002) was used to carry out
the downscaling of the national level changes in land-use to a
more accurate level, 1 km2 in this case. The global models
assessed the interaction between economy and natural
resources at a world level. Then, from changes in industry,
agriculture and services sectors, obtained through the global
models, and from spatial policies coming from the conditions
and assumptions of the proper scenario, CLUE model quanti-
Fig. 10 – Land-use maps for the Llobregat basin according to the
future (year 2030) situations.
fied land-use changes at 1 km2 resolution. Finally, a series of
assumptions were done for three periods (2010, 2020, 2030)
and for 16 different items such as population, macro-
economic growth, etc.
Originally, EURURALIS considered 17 different land-use
classes but they have been merged into 9 significant classes for
this study.
5. Results
Regarding the rural land-use changes in the Llobregat basin,
it can be highlighted that the largest increase of built-up
area occurs for scenario A1, which assumes a rapid
economic growth, and it is located mainly around the
Barcelona Metropolitan Area. Fig. 10 shows the projected
land uses until 2030 for four IPCC scenarios, adopting as a
reference the situation in 2000. Fig. 11 shows the numerical
results of land-use changes. As mentioned, built-up areas
are projected to increase, especially in A1, which almost
doubles the surface area of this category compared to the
reference situation. Forest area experiences a significant
increasing according to all scenarios at the expense of semi-
natural vegetated area that decreases in all scenarios except
for B1. Related to agriculture, arable land decreases in all
EURURALIS project results for the reference (year 2000) and
Fig. 11 – Land-use changes (in km2) for the 9 regrouped categories and 4 IPPC scenarios for the Llobregat basin according to
EURURALIS project.
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7 895
scenarios, except for A2, which maintains the extension of
this land-use type.
For the case of Guadalhorce basin, Fig. 12 show an
important increase of built-up area for all scenarios. This
increase is concentrated along the coast and around Malaga
city. Arable land may be significantly reduced in all scenarios.
Instead, semi-natural vegetation area increases in all cases.
The abandonment of arable land due to migrations to urban
areas and transformation of agricultural land into natural
vegetated areas is foreseen as a reasonable triggering factor.
The same conclusion might be applied to pastures.
Unlike the previous cases, Gardon basin results do not
show an increase of built-up area in the future. Indeed, Gardon
d’Anduze is basically a rural catchment and it remains like
that in all future scenarios. An increase in the fraction of forest
area can be highlighted caused by a decrease of natural
vegetation, pastures and arable land. Arable land and pastures
may be abandoned, leading to an increase of natural
vegetation and, later, forests.
Regarding Linth basin, the dominating changes are
urbanization (the amount of urban area doubles the reference
in 2000) and the increase of forest, at the expense of
agricultural land. This is probably related to the fact that
the treeline may move upward due to increasing tempera-
tures. Regarding the second Swiss basin, Verzasca, the most
dramatic change is the conversion of grassland into mostly
‘‘semi-natural’’ land and forest.
Unfortunately, due to the small size of Sambuco basin
(7 km2 area) and the resolution of EURURALIS results (1 km2)
the current analysis of land-use changes has not shown any
variation in the basin.
In general, besides the increase of urban areas shown in
most of the cases, there is another common trend: the
pastures and arable land zones decrease, whereas an increase
of semi-natural vegetated areas and forest appears.
Fig. 12 – Land-use changes (in km2) for the 9 regrouped categorie
to EURURALIS project.
This may seem a contradiction as climate models show a
temperature increase together with a precipitation decrease.
But as EURURALIS project made projections only until 2030,
climatic changes will not be as important as the social and
economic ones by this year. Therefore, the effects of the
abandonment of agriculture might be more decisive than the
climate changes. In addition, this model does not take into
account the effects of potential forest fires.
6. Conclusions and future work
The main objective of the present work within the framework
of the ongoing IMPRINTS project is to obtain regionalized
future scenarios for the six test-bed basins included in the
project. These scenarios will be later applied in the upcoming
FF/DF early warning tool that has to be developed in the frame
of the project. As the aim of this tool is to provide real time
warnings depending on the basin’s risk level, this task has
dealt with the variables that can significantly affect the risk
level in the future.
Climatic variables have been widely analyzed, with a
special focus on extreme precipitation. The importance of
using climate data at the maximum spatial and temporal
resolution to obtain results applicable at a basin level (test-
beds areas ranging from approx 200 to 5000 km2) has been
concluded, as shown in the cases of SMC model for the
Llobregat basin and the REMO/UBA project results for the
Swiss basins.
In general, a significant variability in the climate assess-
ment results has been observed, especially in those related to
extreme precipitation. Uncertainty associated with extreme
precipitation has been initially quantified by using different
GCMs, RCMs and IPCC emission scenarios for the different
test-bed areas. Summarizing, the frequency of extreme
s and 4 IPPC scenarios for the Guadalhorce basin according
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7896
rainfall events is highly dependent on the type of climatic
modelling (both GCM, RCM or statistical technique), time
horizon and selected IPCC scenario.
In addition, it has been observed that in most of the
situations, the models used are not optimized for the extreme
events simulation. For example, taking a look at Figs. 4 and 7, it
is easy to see that the control period of the model does not fit
the observations distribution, meaning that the extreme
rainfall events are not well described. Therefore, for a better
assessment of the extreme events, corrections might be
applied to the model data.
It was predictable that different models, especially if they
have a general scope (ENSEMBLES models have not been
regionalized for a precise region but they are applicable to the
whole Europe), show really different results. This constitutes a
useful conclusion for policy makers as it is extremely
important for them to be aware of the uncertainties associated
with climate projections. As it has been shown, some of them
do not even present accurate descriptions of the control
period. Still, as this paper shows preliminary work regarding
this issue, all the models must be kept for a further analysis
where the models will be corrected and the uncertainties
assessed.
Regarding land-use changes, urban and rural land types
have been analyzed separately for each test-bed. Future
changes in the rural land-use will mainly affect hazard levels;
however, changes in urban land-use can significantly increase
the exposure factor of the risk equation.
In the case of urban land-use, a set of scenarios was
implemented in three basins having large anthropogenic
dynamics, i.e. Llobregat (ES), Guadalhorce (ES) and Gard (FR). In
order to simulate urban growth, a cellular automata (CA)
model has been applied. The two families of IPCC emission
scenarios produced, A and B, show divergent patterns of urban
land change. First, A2 scenario shows a decrease in the
amount of natural and agricultural land during the modelling
period and the fraction of low-density residential areas
increases as well. There is a rapid urban growth in this
scenario. However, B1 and B2 scenarios show a much slower
process of urban growth. These scenarios could be the result of
a series of spatial planning regulatory measures and policies.
In this case the simulated land-use shows a more compact
urban land-use pattern than A2 scenario.
The urban growth scenarios reveal that different socio-
economic conditions can produce large differences in the
future shape of urban areas and, hence, different impacts in
future flood risk. These findings are indeed more relevant on
the light of the evidence indicating that the observed
economic loss increase from floods and other weather-related
disaster is caused primarily by increasing exposure and value
of capital at risk (Barredo, 2009, 2010; Bouwer, 2011). With this
in mind, and independently of the effects of anthropogenic
climate change, policy makers and spatial planners must play
a role of paramount relevance in flood risk mitigation through
the implementation of spatial planning measures at local
level.
Considerable uncertainty is evident in socio-economic
processes, and decision makers should be properly informed
about the risks and uncertainties dealing with urban land-use
dynamics and scenarios. The length of the simulation period is
only one of the issues to be addressed. Urban growth scenarios
for future flood risk assessment should serve for informed
decision making. Therefore the scenarios should be assessed
from the perspective of the many possible future paths as
consequence of changes in the multiple drivers at play in the
emergence of urban systems. A timely example is the effect of
the current global economic crisis in the urban land-use
dynamics in the test-beds. It is hard, and in many cases
impossible, to anticipate and model complex socio-economic
events such as the current global crisis. Hence, the assessment
of a wide range of long-term scenarios and a probabilistic
approach appears to be one option for informing uncertainty
to policy makers.
Regarding rural land-use, available results coming form the
EURURALIS project have been studied in each test-bed basin to
detect future changes in rural land-use categories. A common
clear trend has been identified in the increasing of built-up
areas (the only non-rural type) for all test-basins and IPCC
scenarios, but especially for A1 scenario. Secondly, the
decrease of pastures and arable land, and the consequent
increase of semi-natural vegetated area and forest, has been
concluded for all the basins. In the case of the Swiss basins,
this trend can be strongly associated with an increase of
temperatures, which makes the tree line move uphill and,
hence, increase the forest area.
Future incoming tasks within IMPRINTS will involve
identifying new zones of high potential risk within the test-
bed basins and evaluating the impact of the expected changes
described in the present analysis. Quantifying the different
impacts caused by the potential changes will involve the (1)
estimation of the new precipitation intensities associated
with certain return period. This will be done using the specific
GEV curves associated with the cells (or stations) of the
climate model corresponding to the chosen sub-basins.
Therefore, regionalized GEVs extracted in this work will be
particularized for smaller areas of the test-beds to obtain
more precise results. The need for bias correction of some of
these results will be assessed depending on each case. The (2)
estimation of modified runoff coefficients accounting for the
rural land-use changes and the (3) application to one sub-
basin with a significant proportion of urban area will be
carried out. By this, exposure levels will be modified when
accounting for the simulated changes in urban land-use. The
(4) assessment of vulnerability using stage-damage functions
associated with individual land-use classes, where available,
will be applied. And finally, a generic matrix of hazard-
intensity versus vulnerability for the exposed elements will
be defined.
The partial results presented in this paper, together with
the upcoming objectives described above, will finally provide
reliable guidelines for mitigation and adaptation measures to
cope with the potential effects of future changes at the final
stage of the project. These guidelines should include robust
and flexible measures valid for a wide range of possible
climate and land-use change scenarios. This will be the right
way to account for the large uncertainties associated with the
results presented and to ensure that no-regret solutions will
be implemented. Special attention will be paid to those
strategies oriented to effectively assess the application of the
Flood Risk Management in the framework of flash floods.
e n v i r o n m e n t a l s c i e n c e & p o l i c y 1 4 ( 2 0 1 1 ) 8 8 4 – 8 9 7 897
Acknowledgement
The authors thank the IMPRINTS project, that is being funded
by the EU FP7 (Contract number FP7-ENV-2008-1-226555),
whose support is gratefully acknowledged.
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