assessing sea level rise risks in changing coastal ... · coastal systems are projected to be...

Assessing sea level rise risks in changing

coastal environments: a national assessment

supporting disasters management and

climate change adaptation

International Conference Risks, Security and Citizenship

Setúbal, Portugal 28/29 March 2019

Critto A., Torresan S., Furlan E., Dalla

Pozza P., Derepasko D., Michetti M.,

Mysiak J., Marcomini A.

Euro-Mediterranean

Centre on Climate

Change

Website: www.cmcc.it

Partners:

National Institute on Geophysics and Volcanology (INGV)

University of Salento (UNILE)

Centro Italiano di Ricerche Aerospaziali (CIRA)

University Ca' Foscari Venice

Eni Enrico Mattei Foundation (FEEM)

University of Sannio

University of Sassari

University of Tuscia

Associated centers:

Mediterranean Agronomy Institute of Bari

Pure and applied mathematics Research Centre (CRMPA)

SPACI Consortium

National Institute of Oceanography and Experiment Geophisics

(OGS)

Abdus Salam International Centre for Theoretical Physics (ICTP)

http://www.cmcc.it/it/

Euro-Mediterranean Centre

on Climate Change

Focal Point IPCC in Italy:CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici )

CMCC SCIENTIFIC DIVISIONS:

• OPA – Ocean Predictions and Applications (Lecce): models and methods for marine operational

forecasting.

• ODA - Ocean modelling and Data Assimilation (Bologna): numerical models for global marine

forecasts and the study of the interactions between the physical and biogeochemical processes of

oceans.

• CSP – Climate Simulations and Predictions (Bologna): models of the Earth system, climate

predictions and projections of climate change from seasonal to decadal scales.

• ASC - Advanced Scientific Computing (Lecce): optimization of models on emerging computational

structures and advanced analysis of large volumes of data.

• IAFES - Impacts on Agriculture, Forests and Ecosystem Services (Viterbo, Sassari): diagnosis and

prediction of the impacts on agriculture and terrestrial ecosystems, natural and semi-natural.

• REMHI - REgional Models and Hydrogeological Impacts (Capua): hydrological impacts related to

climate change and dynamic/statistical downscaling techniques.

• RAAS - Risk Assessment and Adaptation Strategies (Venice): methods for the analysis of

environmental impacts and risks related to climate change and natural hazards, and development of

strategies and plans for adaptation to climate change.

• ECIP - Economic analysis of Impacts and Policy (Venice): translate into economic values climate

scenarios, for designing the most appropriate policies to mitigate emissions and for adaptation to climate

change.

COASTAL ZONES are complex systems of strategic importance in different sectors:

• they are home to a large percentage of citizens worldwide;

• they are a major source of food and raw materials;

• they are a crucial link for transport and trade;

• they include valuable habitats and natural resources;

• they are favoured destination for leisure time and recreational activities.

In the last decades urbanization,

agriculture, industry, energy

production,

transportation and tourism posed

increasing pressures on coastal areas

habitat destruction, water and

soil contamination, coastal

erosion and resource depletion

the depletion of the limited resources of coastal

zones and the limited physical space is leading to

increasing conflicts of interests among different

stakeholders (e.g. aquaculture and tourism)

Climate change and coastal zones

Coastal systems are projected to be increasingly at

risk due to global climate change trough the 21th

century and beyond

(IPCC, 2007 and 2014).

BIOGEOPHYSICAL IMPACTS:

Sea-level rise.

Increasing flood-frequency probabilities.

Erosion.

Inundation.

Rising water tables.

Saltwater intrusion.

Negative consequences for biodiversity

and ecosystems.

SOCIO-ECONOMIC IMPACTS:

Direct loss of economic, cultural and

subsistence values through loss of land,

infrastructure and coastal habitats.

Increased flood risk of people, land and

infrastructure.

Damage to coastal protection works and

other infrastructure.

Impacts related to changes in water

management, salinity and biological activity.

Impacts on agriculture and aquaculture.….

A strategic approach is needed to ensure that timely and

effective adaptation measures are taken, ensuring

coherency across different sectors and levels of

governance.

The challenge for policy-

makers is to understand

climate change impacts

and to develop and

implement policies to

ensure an optimal level of

adaptation.

The aims for the scientific

community are to improve the

knowledge on climate impact and

vulnerability and to provide

methodologies and tools in order

to guide the development of

appropriate adaptation measures.

EC, 2009.

- The European Flood Directive 2007/60/EC - flood risk management plans / river and coastal

flooding

- The EU Strategy on adaptation to climate change - EU’s preparedness to current and future

climate impacts

- The Sendai Framework for Disaster Risk Reduction 2015-2030 - need to adopt a multi-hazard

approach.

- The Community Civil Protection Mechanism - coordinated, effective and efficient response to

disasters, joining prevention and preparedness actions.

Need of risk assessment protocols and tools able to deal with the complex interactions and dynamics between social and environmental systems, supporting the development of climate

adaptation and risk reduction measures.

Relevant EU and International policies

1. Objectives

Development of GIS-based maps and

indicators ranking the coastal areas at higher

risks

Improve risk

governance and

raise community

awareness towards

the impacts of

climate change and

sea level rise

Provide guidance

and criteria for risk

and vulnerability

assessment

http://www.savemedcoasts.eu

Aims to respond to the need of people and assets prevention from

natural disasters and sea level rise in Mediterranean coasts

DG-ECHO (European Civil Protection and Humanitarian

Aid Operations)

http://www.savemedcoasts.eu/

2. Case study area

Natura2000 sites cover 10.353,75 km2

(23,3% of the coastal area)

Main issues:

- Biodiversity loss

- Flooding

- Erosion

- Saltwater intrusion

- Land take

- Pollution

28,4 % of the population

living along the coastsMost densely populated areas of the country

A coastline of 8.970 km Including the islands

63 out of 107 provinces located

along the coast14.3 % of the national surface

Unique ecosystems and

habitats2314 ZSC

10-km wide band of land from the Italian coastline How is Italian coastal vulnerability going to evolve as a consequence

of climate and socio-economic changes?

3. Methodology and data

GIS

Models

Indicators

DSS

Riskassessmen

t

CVI- One of the most commonly used

method to assess coastal vulnerability to SLR

- Easy to use for a scoping or “first look” assessment

- Simplified approach useful for communication purposes

- Applicable to different geographic contexts

- Flexible for multi-scale vulnerability appraisal

- Expandable to include a variety of heterogeneous indicators

Multiple methodologies and tools to evaluate coastal vulnerability :

Ramieri et al. (2011); Zanuttigh et al. (2013); Torresan et al. (2016)


Coastal

Forcing

Economic

Sub-index

Social

Sub-index

Environmental

Sub-index

Combined

Coastal

Vulnerability

Index

• Extreme Sea Level

• Shoreline evolution trend

• Distance from shoreline

• Coastal slope

• Elevation

• Geological coastal types

• Land roughness

• Conservation designation

• Coastal protection structures

• Land use patterns

• GDP per capita

• People younger than 5 years

• People older than 65 years

Adapted from the multi-scale CVI by McLaughling & Cooper (2010)

Combined -CVI

Baseline Future scenario 2050

Extreme Sea Level

1969 - 2004

Extreme Sea Level 2039 -

2049 under RCP8.5

Corine Land Cover 2000LULC – CMCC - 2050

under RCP8.5

ISTAT – Population census

2001

ISTAT - Population projections

2007 - 2051

GDP - 2010 GDP - 2050 under SSP3


Baseline and future scenario for

ESL, land use, population and

GDP based indicators

RCP 8.5: “Worst case

scenario”; high

demographic growth, low

innovation, absence of

mitigation policies

SSP 3: high challenges for mitigation

and adaptation; little progress in

reducing resource consumption and

fossil fuel dependency, in addressing

local environmental issues; strong

environmental degradation in some

region. Low population growth in

industrialized countries and higher in

developing ones


ESL RP 5 RP 10 RP 20 RP 50 RP 100 RP 200 RP 500 RP 1000

BASELINE

MIN 0.82 0.89 0.95 1.00 1.03 1.06 1.10 1.12

MEAN 1.17 1.26 1.33 1.43 1.51 1.58 1.67 1.74

MAX 2.10 2.34 2.59 2.94 3.22 3.52 3.93 4.27

20

50

RCP 4.5

MIN 1.03 1.10 1.16 1.20 1.24 1.27 1.30 1.33

MEAN 1.37 1.46 1.53 1.63 1.71 1.78 1.87 1.95

MAX 2.35 2.59 2.84 3.18 3.46 3.75 4.16 4.49

RCP 8.5

MIN 1.03 1.13 1.19 1.24 1.27 1.31 1.34 1.37

MEAN 1.37 1.49 1.57 1.67 1.75 1.82 1.92 1.99

MAX 2.35 2.66 2.91 3.27 3.55 3.85 4.26 4.60

Scenarios: Historical

RCP 4.5

RCP 8.5

Grid resolution: 0.2°(~ 11 km)

Temporal coverage: Baseline: 1969-2004

Future: decades among 2039-

2049 timeframe

ESL = RSLR + (tide) + (ss-w)

(Vousdoukas et al., 2017)

Climate Forcing: Extreme Sea Level scenarios (ESL)

Mean [m]

Baseline - 100 years Return Period

2039 -

2049

cm

2039-2049 2039-2049

10

3


Land-use related indicators (i.e. land roughness and land use pattern) are based on the recent

LULC maps developed by using the LULC-CMCC model (Santini and Valentini, 2011)

Temporal coverage:

Baseline scenario 2000Future scenario 2050

Future projections based on 5 parameters constraining land use changes: - Climate model projections- Demographic change- Protected areas- Transition matrix- Neighboring influence

Emission scenario: RCP8.5

Two scenario selected for the combined-CVI:- Baseline (based on the Corine Land Cover map 2000)- Future scenario 2050, considering climate model projections, high demographic change, presence of protected areas, transition matrix and neighboring influence between land use classes

Future scenario 2050

Resolution: 500 m


Economic indicators are based on GDP projections developed by Murakami & Yamagata, (2016)

Selected socio-economic pathways: SSP3

Future projections based on the downscaling of 3 parameters into a 0.5-degree grids:

- Urban population- Non-urban population- GDP

(Murakami & Yamagata, 2016)

Temporal coverage:


Billion US$ in 2005 year rate

Baseline 2010

GDP tot 2010: 1641 billion US$


Future scenario based on 3 demographic parameters constraining population changes: - Fertility- Survival- Migration patterns

Social indicators developed based on data collected and modelled by ISTAT, 2001 and 2008

Temporal coverage:

Baseline scenario 2001 (census data)

Future scenario 2051


GIS-based physical, environmental and

socio-economic indicators spatially

evaluated by:

Aggregating information at the

provincial scale (nuts3 level) based on:

• Percentage

• Mean values

Reclassification of variables according to

their capacity to determine detrimental

changes to coastlines (1 – 5)


Variable Unit

Score

Very low Low Moderate High Very high

1 2 3 4 5

Coastal forcing indicators

Extreme Sea Levels (ESL) m < 1 1 – 1.6 1.6 – 2.2 2.2 – 2.8 > 2.8

Environmental indicators

Shoreline evolution trend %

Less than 20% of the

shoreline is in erosion

or in accretion (per

region)

/

Between 20% and 60%

of the shoreline is in

erosion or in accretion

(per region)

/

More than 60% of the

shoreline is in erosion or

in accretion (per region)

Distance from shoreline m > 4500 4500 - 2100 2099 - 900 899 - 300 < 300

Coastal slope % > 1/10 1/10 - 1/20 1/20 - 1/30 1/30 - 1/50 1/50 - 1/100

Elevation m > 30 20 to < 30 10 to < 20 5 to < 10 < 5

Geological coastal type %> 70% of “likely non-

erodible segments”/

“likely non-erodible

segments” between

40% and 70%

/< 40% of “likely non-

erodible segments”

Land roughness / Urban areas Forest and water bodiesShrub land, grassland,

sparse vegetationAgriculture Bare areas

Conservation designation / Absent European international National

Coastal protection

structures%

> 50% of protected

coast

31-50% of protected

coast

21-30% of protected

coast5-20% of protected coast < 5% of protected coast

Social indicator

Population < 5 years / < 9871 9872 - 15230 15231 - 21644 21645 - 35733 > 35734

Population > 65 years / < 41243 41244 - 57008 57009 - 76078 76079 - 106784 > 106785

Economic indicators

Gross domestic product -

GDP$ > 31000 31000 – 25000 24000 - 17000 16000 - 9000 < 9000

Land use pattern /

Water bodies,

marsh/bog and moor,

sparsely vegetated

areas, bare rocks

Natural grasslands,

coastal areasForest Agriculture

Urban and industrial

infrastructure

Based on scenarios

developed by Vousdoukas et

al., 2017

Based on scenarios

developed by Santini &

Valentini, 2011Based on scenarios

developed by ISTAT, 2008Based on scenarios

developed by Murakami &

Yamagata, 2016

Coastal Forcing (CF) sub-index = [(sum of CF indicators) – 1]/4x 100

Environmental (Env) sub-index = [(sum of Env indicators) – 9]/36 x 100

Social (S) sub-index = [(sum of S indicators) – 1]/4x 100

Economic (Econ) sub-index = [(sum of Econ indicators) – 2]/8x 100

CVI = (Env sub-index + CF sub-index + S sub-index + Econ sub-index) / 4

Sum of the values of the relative

variables

Normalization of the resulting output elaborating it as percentage

of the range of scores possible (maximum and minimum)

Standardization in the range 0-100

Average of the four sub-indices values

National - Coastal Vulnerability IndexAdapted from the multi-scale CVI by McLaughling & Cooper (2010)


4. Results and discussionNumber of

provinces with

moderate scores

increases; very high

and medium scores

expand along the

coast

RCP 8.5 scenario

confirms and worsen

the results of the

RCP4.5 in the

Adriatic coast

Very high and high

scores located along

the North Adriatic

Sea region, low

values along most of

the rest of the coastline

0

41

11

47

0

27

24

2 10

0

27

22

3 11

Coastal forcing

sub-index

Baseline Future 2050 scenario

RCP4.5

Future 2050 scenario

RCP8.5

4. Results and discussion

Very low and low scores in North-

East provinces (Trieste and

Gorizia) due to higher coasts,

steeper slopes and less dynamic

shorelines

Higher scores especially along the North

Adriatic and North Tyrrhenian coasts, all

featured by gentle slopes and low-lying coastal

areas

Baseline

Environmental

sub-index

From maps related to the

environmental indicators a great

environmental heterogeneity of the

Italian coasts is highlighted

By comparing baseline and future scenarios a

slight decrease in the overall score of the

environmental sub-index can be observed in some

areas due to land use changes


Social

sub-index

Slight vulnerability

increase moving from

North to South Italy

Consistent increase of

the overall vulnerability

moving from baseline

to 2050 scenario due to

the rising number of

elderly living in Italy:

the population will reach

its ageing climax in

2045-2050, as cohorts of

the so-called “baby

boom” of 60s and 70s

The northern provinces

assume very high (80 –

100) vulnerability scores

due to the rising number

of children born in

those areas by emigrant

parents


Economic

sub-index

The output of the economic sub-index

highlights a great variety in

vulnerability scores among the

different provinces, mainly driven by the

GDP indicator, that strongly varies

along the country respect to the land

use pattern indicator

Comparing baseline with future

scenario, vulnerability is expected

to decrease according to the high

GDP growth projected for the

2050 scenario across most of the

Italian provinces

The reduction of the economic

vulnerability connected with the

decreasing vulnerability of the future

GDP indicator is counterbalanced by

the 2050 land use scenario: urban

areas are supposed to expand, thus

increasing the economic vulnerability of

the area of concern


Combined

CVI

0

13

42

8

0 0

14

36

12

1

The resulting GIS-based maps show CVI scores ranging from 20 to almost 80 across

all the Italian coasts and evaluated scenarios, positioning the investigated area mainly in the

moderate vulnerability class, due to the balancing of the different sub-indices alternatively, with the

coastal forcing sub-index predominating the characterization of vulnerability

Slight increase of the CVI score

between baseline and future

scenario driven by the rise in

vulnerability scores of the coastal

forcing and social sub-indices,

highlighting rising critical situations

linked with future climate threats

combined with demographic

changes

5. Conclusions

• Implementation of social and economic projections to better investigate the interconnections of climatic hazards with changes in social and economic systems, as well as their relationship with the surrounding environment.

• Adaptable to different spatial scales of analysis and geographic context, integrating different data at higher resolutions

• Useful to easily communicate and translate knowledge between the science and practitioners interfaces and to be implemented for national adaptation policies

• Evaluation of uncertainty by integrating climate, land use and economic social scenarios from different assumptions/models

• Lack of temporal coherence among the different scenarios for all the indicators

• Low spatial resolution of economic data not supporting the evaluation of economic dynamics of coastal areas

Thanks for your

attention !

[email protected]

6. Take home message

Need to apply more detailed

assessment processes in hot-spot

vulnerability areas integrating high

spatial resolution data

Lost of relevant local-scale information

during the evaluation of the

environmental and socio-economic

indicators at the provincial scale

Need for a clear and transparent

explanation of the applied

methodology allowing for a proper

interpretation and use of results

Final aggregated outcomes don’t

allow end users to easily understand

assumptions and criteria behind the

final CVI values

CVI captures a snapshot in time-

based current and future conditions

Need for spatio-temporal modeling

assessment methods allowing the

dynamic evaluation of interactions

among relevant parameters

01

02

03


Economic indicators are based on GDP projections developed by Murakami & Yamagata, (2016)

Selected socio-economic pathways: SSP3

Future projections based on the downscaling of 3 parameters into a 0.5-degree grids:

- Urban population- Non-urban population- GDP (Power Purchase Parity (PPP))

(Murakami & Yamagata, 2016)

Temporal coverage:


https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=about

Billion US$ in 2005 year rate

https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=about


Data TypeSpatial

domainYear Unit

Spatial

resolution

Time-frame/

Reference Period

GIS

Data

Format

Reference/Link

Extreme Sea Level Europe 2017

Total Water

Level

(SSH + WH)

~ 11 km

Historical: 1969-2004

Future: 2009-2099

according to RCP4.5 and

RCP8.5 emission scenarios

NetCDF (Vousdoukas et al., 2017)

Digital Elevation

Model

(EU-DEM v1.1)

Europe 2016

Elevation in

m above sea

level

25 m /GeoTIF

F

http://land.copernicus.eu/pan-european/satellite-derived-products/eu-

dem/eu-dem-v1.1

European

Reference GridEurope 2011 /

1 km, 10

km, 100 km

(plus 15 km

buffer)

/ Shape https://www.eea.europa.eu/data-and-maps/data/eea-reference-grids-2

Artificial ProtectionMediterranea

n2014 / 250 m / Shape (ISPRA, 2014)

Coastline Europe 2015 / / / Shapehttps://www.eea.europa.eu/data-and-maps/data/eea-coastline-for-

analysis-1

Administrative

BoundariesWorld 2015 / / / Shape http://gadm.org/

Geomorphology Europehttps://www.eea.europa.eu/data-and-maps/data/geomorphology-

geology-erosion-trends-and-coastal-defence-works

Shoreline evolution

trendItaly 2010 / 1:2000 / Shape

http://www.pcn.minambiente.it/geoportal/catalog/search/resource/detai

ls.page?uuid=%7BC49FEE18-000C-4B37-B062-E76BCAD5104F%7D

Land use/Land

coverItaly 2018 Class/ cell 500m

Baseline (CLC2000)

Future: 2050

GeoTIF

F

(Bucchignani, Mercogliano, Montesarchio, Manzi, & Zollo, 2013);

(Maselli et al., 2012); (Scoccimarro et al., 2011); (Weiland, Van Beek,

Kwadijk, & Bierkens, 2010)

Protected areas Europe 2017% protected

areas / cell/ /

GeoTIF

F(EEA, 2017)

Nationally

Designated Areas

(CDDA)

Europe 2017 / / / Shapehttps://www.eea.europa.eu/data-and-maps/data/nationally-designated-

areas-national-cdda-12#tab-gis-data

GDP Italy 2018 US $ 0.5° x 0.5°Baseline:

Future: 2050Raster (Murakami & Yamagata, 2016)

Population

projectionsItaly 2008 / / 2007 – 2051 Shape (ISTAT, 2008)

Population < 5

yearsItaly 2018 / / 2001 Shape

http://dati-censimentopopolazione.istat.it/index.aspx?queryid=1167

Population > 65

yearsItaly 2018 / / 2001 Shape http://dati-censimentopopolazione.istat.it/index.aspx?queryid=1168

Ge

ne

ral la

ye

rsC

oasta

l

forc

ing

En

viro

nm

enta

l

drive

rs

So

cio

-eco

no

mic

dri

ve

rs

http://land.copernicus.eu/pan-european/satellite-derived-products/eu-dem/eu-dem-v1.1

https://www.eea.europa.eu/data-and-maps/data/eea-reference-grids-2

https://www.eea.europa.eu/data-and-maps/data/eea-coastline-for-analysis-1

http://gadm.org/

http://www.pcn.minambiente.it/geoportal/catalog/search/resource/details.page?uuid=C49FEE18-000C-4B37-B062-E76BCAD5104F

https://www.eea.europa.eu/data-and-maps/data/nationally-designated-areas-national-cdda-12#tab-gis-data



Representative concentration

pathways (RCPs)

RCP 8.5 Rising radiative forcing pathway leading to 8.5 W/m² in 2100.

RCP 6Stabilization without overshoot pathway to 6 W/m² at stabilization

after 2100

RCP 4.5Stabilization without overshoot pathway to 4.5 W/m² at

stabilization after 2100

RCP 2.6 Peak in radiative forcing at ~ 3 W/m² before 2100 and decline

Radiative forcing is a measure of the energy absorbed and retained in

the lower atmosphere. It can be positive (heating) or negative (cooling)

and is affected by greenhouse gas concentration, aerosol concentration,

changes in land cover and natural drivers such as total solar irradiance.

There are 4 different RCPs and each of them defines a specific emission

trajectory and subsequent radiative forcing. The numbers in each RCP

refer to the amount of radiative forcing produced by greenhouse gases in

2100:

Projected changes-AR5

Temperature The globally mean surface temperature for the end of the 21st century

is projected to likely exceed 1.5°C for RCP4.5, RCP6.0 and RCP8.5.

Warming is likely to exceed 2°C for RCP6.0 and RCP8.5.

Source: IPCC AR5 (2014)

Sea level will continue to rise in the 21st century; under the RCP

scenarios, the rate of sea level rise will very likely exceed that observed

during 1971 to 2010 due to increase ocean warming and increased loss

of mass from glaciers and ice sheets.

Global mean sea level rise for

2081–2100 relative to 1986–2005

will likely be in the ranges of

0.26 to 0.55 m for RCP2.6,

0.32 to 0.63 m for RCP4.5,

0.33 to 0.63 m for RCP6.0,

0.45 to 0.82 m for RCP8.5

Projected changes – AR5

Sea level

Source: IPCC AR5 (2014)


Grid-based scenario representing total

GDP for the Italian case study

Downscaling of gridded values at the

nuts3 level

Computation of GDP per capita by

dividing the GDP gridded values at the

nut3 level by the number of inhabitants

living in each province

Scenario matrix architecture

The socio-

economic

reference

pathway axis

does not have a

specific direction

Combines

different socio-

economic

reference

assumptions as

described by

SSPs with

different future

levels of climate

forcing

The forcing

levels are

chosen to

correspond to

the forcing level

reached by the

representative

concentration

pathways

(RCPs)

Each cell,

combining a

SSP and forcing

level, represents

possible

scenarios that

combine

elements of

mitigation and

adaptation

policy

The architecture

The policy

assumptions

may vary within

a SSP, therefore

it can be defined

as an additional

axis within the

framework

Examples of Shared policy

reference assumptions

(SPAs) are assumptions on

mitigation policy (e.g.

uniform carbon price

versus detailed regulation)

and adaptation policy (e.g.

the level of international

cooperation).

Clearly,

relationships

exist between

the SSP, the

policy

assumptions,

and the forcing

level

Policy assumptions

Summ

ary of

SSPs

narrati

ves

SSP1 - Sustainability – Taking the Green Road

(Low challenges to mitigation and adaptation):

The world shifts gradually, but pervasively, toward a more

sustainable path, emphasizing more inclusive development that

respects perceived environmental boundaries. Management of the

global commons slowly improves, educational and health

investments accelerate the demographic transition, and the

emphasis on economic growth shifts toward a broader emphasis on

human well-being. Driven by an increasing commitment to achieving

development goals, inequality is reduced both across and within

countries. Consumption is oriented toward low material growth and

lower resource and energy intensity.

SSP5 - Fossil-fueled Development – Taking the Highway

(High challenges to mitigation, low challenges to adaptation)

This world places increasing faith in competitive markets, innovation and

participatory societies to produce rapid technological progress and

development of human capital as the path to sustainable development. Global

markets are increasingly integrated. There are also strong investments in

health, education, and institutions to enhance human and social capital. At the

same time, the push for economic and social development is coupled with the

exploitation of abundant fossil fuel resources and the adoption of resource and

energy intensive lifestyles around the world. All these factors lead to rapid

growth of the global economy, while global population peaks and declines in

the 21st century. Local environmental problems like air pollution are

successfully managed. There is faith in the ability to effectively manage social

and ecological systems, including by geo-engineering if necessary.

SSP2 - Middle of the Road (Medium challenges to mitigation and

adaptation):

The world follows a path in which social, economic, and technological

trends do not shift markedly from historical patterns. Development and

income growth proceeds unevenly, with some countries making relatively

good progress while others fall short of expectations. Global and national

institutions work toward but make slow progress in achieving sustainable

development goals. Environmental systems experience degradation,

although there are some improvements and overall the intensity of

resource and energy use declines. Global population growth is moderate

and levels off in the second half of the century. Income inequality persists

or improves only slowly and challenges to reducing vulnerability to societal

and environmental changes remain.

SSP3 - Regional Rivalry – A Rocky Road

(High challenges to mitigation and adaptation)

A resurgent nationalism, concerns about competitiveness and security, and

regional conflicts push countries to increasingly focus on domestic or, at most,

regional issues. Policies shift over time to become increasingly oriented toward

national and regional security issues. Countries focus on achieving energy and

food security goals within their own regions at the expense of broader-based

development. Investments in education and technological development decline.

Economic development is slow, consumption is material-intensive, and

inequalities persist or worsen over time. Population growth is low in

industrialized and high in developing countries. A low international priority for

addressing environmental concerns leads to strong environmental degradation

in some regions.

SSP4 - Inequality – A Road Divided

(Low challenges to mitigation, high challenges to adaptation)

Highly unequal investments in human capital, combined with increasing

disparities in economic opportunity and political power, lead to increasing

inequalities and stratification both across and within countries. Over time, a gap

widens between an internationally-connected society that contributes to

knowledge- and capital-intensive sectors of the global economy, and a

fragmented collection of lower-income, poorly educated societies that work in a

labor intensive, low-tech economy. Social cohesion degrades and conflict and

unrest become increasingly common. Technology development is high in the

high-tech economy and sectors. The globally connected energy sector

diversifies, with investments in both carbon-intensive fuels like coal and

unconventional oil, but also low-carbon energy sources. Environmental policies

focus on local issues around middle and high income areas.

Motivations

focuses on the Prevention Priority. It aims to

respond to the need for people and assets

prevention from natural disasters and sea level rise

in Mediterranean coasts

GENERAL OBJECTIVES:

Support civil protection to produce exhaustive risk assessments for different periods;

Improving governance and raising community awareness towards the impacts of s.l. rise;

Fostering cooperation amongst science, affected communities and civil protection organizations within and

between targeted Mediterranean areas.

SPECIFIC OBJECTIVES

Scansion of the current risk management capabilities and actions to identify best practices, existing prevention

protocols, lacks and rooms for improvement.

Advanced methods to develop multi-hazard assessments and existing databases for the Mediterranean basin

and for specific case studies for areas below or at less than 1 m above s.l..

To transfer information to society, policy makers and stakeholders.


Very low and low scores in

Trieste and Gorizia provinces due to higher coasts,

steeper slopes and less

dynamic shorelines

Higher scores along the Veneto and Emilia

Romagna coasts, the Gargano area and in

the Apulia and Tuscany regions, all featured

by gentle slopes and low-lying coastal areas

Baseline

Environmental

sub-index

A slight decrease in the overall score of the

environmental sub-index can be observed due to

land use changes expected in these areas,

influencing the spatial distribution of the connected

environmental indicator (i.e. land roughness)

Global mean sea level is rising and will continue to rise in the 21st century due to climate change

Low-lying and subsiding coasts are vulnerable to storm surges flooding and coastal erosion

Impacts on infrastructure, people safety, economic assets, cultural heritage, ecosystems.

Together with changing hazard frequency and intensity, changing patterns of exposure and vulnerability, will be

responsible of multi-risk scenarios.

Relevant EU and International policies:

- The European Flood Directive 2007/60/EC - flood risk management plans / river and coastal flooding

- The EU Strategy on adaptation to climate change - EU’s preparedness to current and future climate impacts

- The Sendai Framework for Disaster Risk Reduction 2015-2030 - need to adopt a multi-hazard approach.

- The Community Civil Protection Mechanism - coordinated, effective and efficient response to disasters, joining

prevention and preparedness actions.

Need of risk assessment protocols and tools able to deal with the complex interactions and dynamics between social and environmental systems, supporting the development climate

adaptation and risk reduction measures.

Motivations

assessing sea level rise risks in changing coastal ... · coastal systems are projected to be...

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