assessment of future scenarios of climate and land-use changes in the imprints test-bed areas

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Assessment of future scenarios of climate and land-use changes 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, * a CETaqua Water Technology Centre, Barcelona, Spain b European Commission Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy c Bristol Glaciology Centre, Bristol, United Kingdom d SMC Catalan Meteorological Service, Barcelona, Spain e CRAHI 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 km 2 ) 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. E-mail address: [email protected] (D. Velasco). available at w ww.s c ienc ed irec t.c o m journal homepage: www.elsevier.com/locate/envsci 1462-9011/$ see front matter # 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.envsci.2011.03.003

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Page 1: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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

Page 2: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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

Page 3: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

Fig. 1 – Location of IMPRINTS selected test-beds.

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 7886

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

Page 4: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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.

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 7 887

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-

Page 5: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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.

Page 6: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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.

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 7 889

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

Page 7: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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.

Page 8: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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.

Page 9: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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.

Page 10: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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).

Page 11: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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

Page 12: Assessment of future scenarios of climate and land-use changes in the IMPRINTS test-bed areas

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

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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.

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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.

r e f e r e n c e s

Arpe, K., Hagemann, S., Jacob, D., Roeckner, E., 2005. Therealism of the ECHAM5 models to simulate the hydrologicalcycle in the Arctic and North European area. NordicAssociation for Hydrology 36 (4–5), 349–367.

Barredo, J.I., 2009. Normalised flood losses in Europe: 1970–2006.Natural Hazards Earth System Sciences 9, 97–104.

Barredo, J.I., 2010. No upward trend in normalised windstormlosses in Europe: 1970–2008. Natural Hazards Earth SystemSciences 10, 97–104.

Barredo, J.I., Engelen, G., 2010. Land use scenario modeling forflood risk mitigation. Sustainability 2 (5), 1327–1344.

Barredo, J.I., Gomez Delgado, M., 2008. Towards a set of IPCCSRES urban land use scenarios: modelling urban land use inthe Madrid region. In: Paegelow, M., Camacho Olmedo, M.T.(Eds.), Modelling Environmental Dynamics. Springer, Berlin,Heidelberg, pp. 363–385.

Barredo, J.I., Kasanko, M., McCormick, N., Lavalle, C., 2003.Modelling dynamic spatial processes: simulation of urbanfuture scenarios through cellular automata. Landscape andUrban Planning 64 (3), 145–160.

Barredo, J.I., Demicheli, L., Lavalle, C., Kasanko, M., McCormick,N., 2004. Modelling future urban scenarios in developingcountries: an application case study in Lagos, Nigeria.Environment and Planning B: Planning and Design 32, 65–84.

Barrera-Escoda, A., Cunillera, J., 2010. Study of the precipitationevolution in Catalonia using a mesoscale model (1971–2000).Advances in Geosciences 26, 1–6.

Batty, M., 2005. Cities and Complexity: Understanding Citieswith Cellular Automata, Agent-Based Models, and Fractals.The MIT Press, Cambridge, Massachusetts.

Bouwer, L.M., 2011. Have disaster losses increased due toanthropogenic climate change? Bulletin of the AmericanMeteorological Society 92 (1), 39–46.

Christensen, J.H., Christensen, O.B., 2007. A summary of thePRUDENCE model projections of changes in Europeanclimate by the end of this century. Climatic Change 81, 7–30.

Cofino, A., San-Martın, D., Gutierrez, J., 2007. A Web portal forregional projection of weather forecast using GRIDMiddleware. In: Computational Science – ICCS.

Covey, C., AchutaRao, K., Cubasch, U., Jones, P., Lambert, S.J.,Mann, M.E., Phillips, T.J., Taylor, K.E., 2003. An overview ofresults from the coupled model intercomparison project.Global and Planetary Change 37 (1–2), 103–133.

Dankers, R., Feyen, L., 2009. Flood hazard in Europe in anensemble of regional climate scenarios. Journal ofGeophysical Research 114, D16108.

de Nijs, T.C.M., de Niet, R., Crommentuijn, L., 2004. Constructingland-use maps of the Netherlands in 2030. Journal ofEnvironmental Management 72 (1–2), 35–42.

EC, 2007. Directive 2007/60/EC of the European Commission of26 November 2007 establishing a Floods Directive on theassessment and management of flood risks. http://ec.europa.eu/environment/water/flood_risk.

EEA, 1993. CORINE Land Cover – Technical Guide, Office forOfficial Publications of European Communities,Luxembourg.

Eickhout, B., Prins, A.G., 2008. EURURALIS 2.0. Technicalbackground and indicator documentation. Bilthoven. TheNetherlands, Wageningen University and Research andNetherlands Environmental Assessment Agency (MNP).

Feyen, L., Barredo, J.I., Dankers, R., 2009. Implications of globalwarming and urban land use change on flooding in Europe.In: Feyen, J., Shannon, K., Neville, M. (Eds.), Water andUrban Development Paradigms – Towards an Integration ofEngineering, Design and Management Approaches. CRCPress, Balkema, Leiden, The Netherlands, pp.217–225.

FIC, 2006. Informe de ejecucion del primer hito del contrato:Generacion de Escenarios de cambio Climatico en Andalucıa,Expdte 539/2006/I/00.

IPCC, 2000. Special report on emissions scenarios – a specialreport of working group III of the Intergovernmental Panelon Climate Change.

Jacob, D., Gottel, H., Kotlarski, S., Lorenz, Ph., Sieck, K., 2008.Klimaauswirkungen und Anpassung in Deutschland – Phase1: Erstellung regionaler Klimaszenarien fur Deutschland.Forschungsbericht 204 41 138 UBA-FB 000969.Umweltbundesamt.

Jenkinson, A.F., 1955. The frequency distribution of the annualmaxima (or minima) values of meteorological elements.Quarterly Journal of the Royal Meteorological Society 81,158–171.

Kundzewicz, Z.W., Parry, M.L., Cramer, W., Holten, J.I.,Kaczmarek, Z., Martens, P., Nicholls, R.J., Oequist, M.,Rounsevell, M.D.A., Szolgay, J., 2001. Europe. Climate Change2001: Impacts, Adaptation, and Vulnerability.pp. 641–92.

Lehner, B., Doll, P., Alcamo, J., Henrichs, T., 2006. ClimaticChange 75 (3) 273–299.

Nakicenovic, N., Swart, R., 2000. Special Report on EmissionsScenarios. Cambridge University Press, pp. 612.

Pontius, R., Boersma, W., Castella, J.-C., Clarke, K., de Nijs, T.,Dietzel, C., Duan, Z., Fotsing, E., Goldstein, N., Kok, K.,Koomen, E., Lippitt, C., McConnell, W., Mohd Sood, A.,Pijanowski, B., Pithadia, S., Sweeney, S., Trung, T.,Veldkamp, A., Verburg, P., 2008. Comparing the input,output, and validation maps for several models of landchange. The Annals of Regional Science 42,11–37.

Reginster, I., Rounsevell, M., 2006. Scenarios of future urbanland use in Europe. Environment and Planning B: Planningand Design 33, 619–636.

San-Martın, D., Cofino, A., Herrera, S., Gutierrez, J.M., 2008. TheENSEMBLES Statistical Downscaling Portal. An End-to-EndTool for Regional Impact Studies.

Sante, I., Garcıa, A.M., Miranda, D., Crecente, R., 2010. Cellularautomata models for the simulation of real-world urbanprocesses: a review and analysis. Landscape Urban Planning96, 108–122.

Solecki, W.D., Oliveri, C., 2004. Downscaling climate changescenarios in an urban land use change model. Journal ofEnvironmental Management 72 (1–2), 105–115.

Verburg, P.H., Soepboer, W., Veldkamp, A., Limpiada, R.,Espaldon, V., 2002. Modeling the spatial dynamics of regionalland use: the CLUE-s model. Environmental Management 30,391–405.

Verburg, P., Schulp, C., Witte, N., Veldkamp, A, 2006.Downscaling of land use change scenarios to assess thedynamics of European landscapes. Agriculture, Ecosystemsand Environment 114 (1), 39–56.

Verburg, P.H., Eickhout, B., van Meijl, H., 2008. A multi-scale,multi-model approach for analyzing the future dynamics ofEuropean land use. The Annals of Regional Science42 (1), 57–77.