Resilience of Critical Infrastructures to Climate Change (old)

EU CIRCLE Resilience Assessment
Methodology and Tool
Resilience of Critical
Infrastructure to
Climate Change

Course Objectives
By the end of the module, you will be able to:
1. Define Critical Infrastructure Resilience to
Climate Change
2. Understand the EU-CIRCLE model for
resilience assessment
3. Carry out a resilience assessment with the
Resilience Assessment Tool

Course Outline
6. Resilience
Assessment
Tool (RAT)
5. Resilience
indexes
4. Resilience
indicators and
metrics
3. Resilience
Assessment
Methodology
2. Resilience
capacities &
parameters
1. Critical
Infrastructure
Resilience

Section 1
What is Resilience of
Critical Infrastructure to
climate change?

Introduction
 Infrastructure systems are one of the defining features of modern societies as we rely
heavily upon them and their smooth operation to carry out our day-to-day activities.
 Infrastructures thus facilitate economic growth, protect human health and the
environment and promote welfare and prosperity.
 When infrastructure systems are damaged or fail, the smooth functioning of society is
disrupted, with negative impacts on our ability to continue in our daily activities, well-
being and security.
 Various disasters over past few decades including man-made and natural disasters, have
highlighted that avoidance of all threats at all times for all infrastructures is impossible

Resilience of Critical infrastructure
6
‘….[w]e cannot reroute hurricanes, intercept every cyber
attack, or prevent every disruption’
US National Infrastructure Advisory Council

Resilience of Critical infrastructure
 Infrastructure resilience is the ability to reduce
the magnitude and/or duration of disruptive
events.
 Infrastructure resilience to climate change is the
ability of a CI system to prevent, withstand,
recover and adapt from the effects of climate
hazards and climate change.

CI Resilience to Climate Change
Specifically, it is the ability of the critical infrastructure system:
 to prevent the impacts by minimising the exposure of critical infrastructure to hazards;
 to withstand the impacts from climatic hazards and climate change by reducing the magnitude and
number of impacts;
 to recover from the effects of climate hazards through the rapid restoration of services; and
 to adapt through modification and improvements to the CI system.

Section 2 Resilience Capacities of
Critical Infrastructure

Resilience Capacities of Critical
infrastructure
 In order to put resilience into
practice, we want to know
what properties indicate
resilience, how to measure or
assess their resilience, and
how to manage for resilience.
 There are several dimensions
to resilience that need to be
taken into consideration when
trying to achieve a holistic
approach for infrastructure
resilience.
Anticipatory
Absorptive
Coping
Adaptive
The ability of the CI system to anticipate and
reduce the impact
The ability of CI system to buffer, bear and endure the impacts
The ability of a CI system to be repaired easily and efficiently
The ability of CI system to face and manage adverse
conditions using available skills and resources
The ability of a CI system to adjust and to take
advantage of opportunities against potential impacts
Restorative

Anticipatory capacity
 The ability of a system to anticipate and
reduce the impact of climate variability and
extremes through preparedness and
planning.
 This is considered a proactive action before
a foreseen event to avoid disturbance, either
by avoiding or reducing exposure or by
minimising vulnerability to specific hazards
 As such it has close links to vulnerability,
hazards and prevention.
Anticipatory
Absorptive
Coping
Adaptive
The ability of the CI system to
anticipate and reduce the impact
The ability of CI system to buffer, bear and endure
the impacts
The ability of a CI system to be repaired easily
and efficiently
The ability of CI system to face and
manage adverse conditions using available
skills and resources
The ability of a CI system to adjust and
to take advantage of opportunities
against potential impacts
Restorative

Absorptive capacity
 The ability of a system to buffer, bear and
endure the impacts of climate extremes in
the short term and avoid collapse
 This is the first line of defence.
Anticipatory
Absorptive
Coping
Adaptive
The ability of CI system to buffer, bear and
endure the impacts
and efficiently
Restorative

Coping capacity
 The ability of people, organisations and
systems, using available skills and
resources, to face and manage adverse
conditions, emergencies or disasters.
 This is similar to absorptive capacity.
 The absorptive is immediately after a
disaster whereas coping can be for a
comparatively longer period.
Anticipatory
Absorptive
Coping
Adaptive
the impacts
and efficiently
manage adverse conditions using
available skills and resources
Restorative

Restorative capacity
 The ability of a system to be repaired easily
and efficiently.
 This capacity is associated with recovery too.
 In the context of critical infrastructure, system
repair is the distinguishing feature of
restorative capacity and it has been claimed
as the final line of defence that requires the
greatest amount of effort.
 Restorative capacity is not usually used
unless either the absorptive and adaptive
capacities are not able maintain an
acceptable level of performance or the
system is completely broken and unable to
perform.
Anticipatory
Absorptive
Coping
Adaptive
The ability of CI system to buffer, bear and
endure the impacts
The ability of a CI system to be repaired
easily and efficiently
manage adverse conditions using
available skills and resources
Restorative

Adaptive capacity
 The combination of assets, skills,
technologies and confidence to make
changes and adapt effectively to the
challenges posed by long term trends,
such as future climate change.
 One of the distinguishing features of
this capacity is the re-organisation
and change of standard operating
procedures and this is the second line
of defence.
Anticipatory
Absorptive
Coping
Adaptive
the impacts
and efficiently
The ability of a CI system to adjust
and to take advantage of
opportunities against potential
impacts
Restorative

Resilience Parameters
 The EU-CIRCLE resilience framework recognises five types of generic resilience
parameters. These parameters correspond to the critical infrastructure capacities and and are
a way of quantifying these capacities.
 These parameters are as follows:
 Anticipation,
 Absorption,
 Coping,
 Restoration, and
 Adaptation.

Section 3
EU CIRCLE Methodology
for enhancing resilience of
Critical Infrastructure to
climate change

EU-CIRCLE Resilience Framework -
Layered Approach
Climatic Hazard / Climate
Change (LAYER 1)
CI, their networks &
interdependencies
(LAYER 2)
Disaster Risks and Impacts
(LAYER 3)
Capacities of Critical
Infrastructure
(LAYER 4)
CI RESILIENCE
Resilience to
What?
Resilience of
What?
Asset Properties
Resilience
Parameters and
Indicators
• The resilience framework incorporates
risks, vulnerability and capacities of CIs
to Climate Hazards.
• This results in a 4 layered approach to
resilience.
• The approach has the flexibility to
modify each layer independently.
• Overall resilience however is achieved
through the overall interconnections
between the layers.

Layers of Resilience
 Resilience to what? –Climatic Hazards (CH), including current and future climate
change (Layer 1)
 Resilience of what ?– Critical Infrastructure (CI), their networks and
interdependencies (Layer 2)
 Disaster risks and impacts (Layer 3)
 Capacities of critical infrastructure (Layer 4)
 Asset properties associated with Critical Infrastructure and Climate Hazards
(contributes to Layers 1, 2 and 3)
 Resilience parameters (Contributes to Layer 3 and 4)
Climatic Hazard / Climate
Change (LAYER 1)
CI, their networks &
interdependencies
(LAYER 2)
Disaster Risks and Impacts
(LAYER 3)
Capacities of Critical
Infrastructure
(LAYER 4)
CI RESILIENCE

Steps of EU-CIRCLE resilience
assessment methodology
 In Step 1 climate and hazard conditions are modelled
(Layer1) and in Step 2 the attributes and
characteristics of a CI are defined (Layer 2).
 Step 3 takes input data obtained from Layer 1 and
Layer 2 and uses it to conduct a Risk analysis
(Layer3).
 The output data from Layer 3 results in the impacts
to a CI from a climate hazard, and are now input data
for Layer 4, which with CI data obtained from Layer 2,
feed into the Resilience assessment (Layer 4)

 If the level of resilience is acceptable, then no further steps
are taken.
 If the level of resilience is non-acceptable, then adaptation
measures are taken using the adaptation module. Once
adaptation measures have been taken the risk and
resilience assessments are conducted again to see if
resilience has been enhanced.
 This process is iterative, and continues until an acceptable
level of resilience has been achieved.
 This approach has the flexibility to modify each layer
independently and yet the collective output will be based on
the interconnection between the layers
Steps of EU-CIRCLE resilience
assessment methodology

Resilience
Assessment
Model
 In summary, the approach to conducting a
Resilience assessment model as follows:
1 - Determine the context of the
assessment.
2 - Undertake the assessment using
the questions relative to the context
above and select scores for each.
3 - Apply weightings to the scores, as
required.
4 - Generate resilience indexes for
categories and capacities and an
overall resilience index.

Section 4 EU-CIRCLE
Resilience Indicators

EU-CIRCLE Resilience indicators
 The EU-CIRCLE Resilience Indicators are generic in nature
 They were defined using the following 5 criteria:
1. Resilience indicators should not be related to a specific hazard,
2. Resilience indicators should not be related to a specific infrastructure sector,
3. Resilience indicators should not be redundant,
4. Resilience indicators should be understandable,
5. Resilience indicators should be measurable with simple metrics.

EU CIRCLE Resilience Indicators
 Independent of hazard type
 Independent of CI sectors
 Indicators are divided to category and subcategory
 Are the same at the level of individual CI Asset, CI Network and CI Network of Networks
 Each indicator is expressed with Resilience index (R = from 0 to 10)

EU-CIRCLE Resilience assessment
 The actual Resilience Assessment is carried out using 18 Resilience indicators
 The result of the Assessment is expressed as the Resilience index
 The resilience measurement is organised on different hierarchy levels: Highest level is the overall
resilience index (ORI) as a composite or aggregate indicator depicting the level of
achievement in the five aspects related to the resilience capacities: anticipation, adaptation,
restoration, coping and absorption
 The level of achievement within each capacity index is measured with resilience indexes which are
partly also calculated as aggregated indexes

Resilience indicators for measuring
 A.1. Awareness of potential hazards
 A.2. Quality/extent of mitigating features
 A.3. Quality of disturbance planning/response
 A.4. Communication Systems / Information sharing
 A.5. Learnability/Training

A.1. Awareness of potential hazards:
 Awareness of the community or awareness of the owners and operators of critical infrastructures
about potential hazards that could endanger their infrastructure is an important factor of
comprehensive resilience.

A.2. Quality/extent of mitigating features:
o Assessing the quality and extent of features associated with an infrastructure that can mitigate the
consequences of disturbance or shock is an important a-priori resilience indicator.
o Mitigating features add to the robustness of the infrastructure, and an early assessment of their
quality and extent can be useful in improving these features where the necessity exists. Mitigating
features will be speciﬁc both to the type of infrastructure and the nature of disturbance the
infrastructure is likely to be subject to.

A.3. Quality of disturbance planning/response:
 Technical assessments of infrastructure are perhaps the most obvious when considering resilience,
yet considering organisational planning for preparedness and response are also important.
 Assessing the value of pre-determined policies that increase or maintain the quality and
functionality of infrastructure can be a useful indicator of resilience.
 In addition, the nature and availability of repair facilities, resources or personnel can also increase
the speed of recovery.

A.4. Communication Systems / Information sharing:
 The quality and nature of crisis communication structures, and organisational information sharing
between managers of CI and government agencies can be a useful indicator of CI resilience.
 Where crisis communication methodologies and technologies are of high quality, their deployment at
times of disturbance or shock may limit loss of functionality, and speed up the recovery of
infrastructure function.
 Making either qualitative or quantitative assessments of information sharing processes and practices
can be particularly good indicators of the strength of relationships of the managers of infrastructure
systems that are characterised by signiﬁcant interdependencies.

A.5. Learnability/Training
 Learnability is the ability of an organisation to use the lessons of their own and others’ experiences
to better manage the prevailing circumstances, including using lessons in real time as they
emerge.

Absorptive capacity
 B.1. Systems failure (integrity of the CI affected
 B.2. Severity of failure (services of the CI affected)
 B.3. Resistance
 B.4. Robustness and redundancy

Absorptive capacity
B.1. Systems failure (integrity of the CI affected):
 Observing an actual failure in an infrastructure can provide a clear indication of its resilience, and
speciﬁcally what characteristic of the infrastructure, or its relationship to the disturbance, may have
led to the failure.
 Many factors may inﬂuence the likelihood that a system fails completely, such as
interdependencies, lack of security, inadequate emergency planning, poor communication, etc.
 Systems failure can be measured in a binary fashion: fail, or not fail.

Absorptive capacity
B.2. Severity of failure (services of the CI affected):
 For instance, old or poorly maintained infrastructures are likely to fail such that they lose
functionality completely following a disturbance, and consequently require a complete rebuild
during recovery.
 By contrast, well-managed, newer infrastructure that is designed to cope with disturbances is likely
to suffer less as a result of a disturbance, and some functionality may persist.

Absorptive capacity
B.3. Resistance:
 Resistance is focused on providing protection. The objective is to prevent damage or disruption by providing
the strength or protection to resist the hazard or its primary impact.
 Probability of failure is an estimation of the expected impact and degradation of an infrastructure following a
disturbance or shock. This probability will vary depending on the nature of the disturbance or shock, but also
on the nature of the critical infrastructure itself.
 Performance of a CI is inﬂuenced by design, materials, age, service life, and the quality of management and
maintenance. Infrastructures with lower quality are likely to be less operable after disturbance.
 Resistance has significant weaknesses as protection is often developed against the kind of events that have
been previously experienced, or those predicted to occur based on historic records, which may not be
suitable for climate change.

Absorptive capacity
B.4. Robustness and redundancy:
 The robustness component of resilience is the ability to maintain critical operations and functions in the face of
a crisis. It is directly related to the ability of the system to absorb the impacts of a hazard and to avoid or
decrease the impact of the event.
 Robustness is reflected in physical building and infrastructure design (office buildings, power generation and
distribution structures, bridges, dams, levees), or in system redundancy and substitution (transportation,
power grid, communications networks).
 Redundancy is concerned with the availability of backup installations or spare capacity that can allow
operations to be switched or diverted to alternative parts of the network in the event of disruptions to ensure
continuity of services.
 Substitutability is an aspect of a CI system’s redundancy, and a key characteristic associated with resilience in
infrastructure. Substitutability reﬂects the possibility that the functional aspects of an infrastructure or
infrastructure system can be replaced by back-up infrastructure or by other components in the system.

Coping capacity
 C.1. Response
 C.2. Economics of response
 C.3. Interoperability with public sector

Coping capacity
C.1. Response:
 Response aims to enable a fast and effective response to disruptive events.
 The effectiveness of this element is determined by the thoroughness of efforts to plan, prepare and
run drills/exercises in advance of events.
 It is related to the ability to respond quickly to restore services.

Coping capacity
C.2. Economics of response:
 The cost of returning infrastructure to pre-event functionality can be used as an indirect measure of
an infrastructure’s resilience.
 These costs include response costs and backup costs.

Coping capacity
C.3. Interoperability with public sector:
 Interoperability is the ability to cooperate at all levels with neighbouring cities/states and other
levels of government of critical systems and procedures.
 Interoperability needs to be assessed at multiple levels.

 D.1. Post-event damage assessment
 D.2. Recovery time
 D.3. Economics of restoration

Resilience indicators for Restorative
capacity
D.1. Post-event damage assessment:
 Measuring functionality of an infrastructure following a disturbance or shock, and comparing this
level to the pre event assessment of functionality will provide an excellent indication of CI
resilience.
 The closer the level of post-event functionality to the assessed pre-event functionality, the more
likely the infrastructure is to be resilient (in relation to a consequential disturbance).
 Geographic information systems (GIS) and remote sensing technologies can, and have been used
in post disaster damage assessments. Such technologies can be used to yield quantitative
measures of damage to many forms of infrastructure, and therefore give a direct idea of the
robustness of infrastructure affected by the disturbance.

D.2. Recovery time:
 Possibly the most well-known indicator of resilience in CI, the recovery time post-event is a
measure of the amount of time it takes for an infrastructure to be brought back to its pre-event level
of functionality.

D.3. Economics of restoration:
 Economics of restoration can also be used as a measure of an infrastructure’s resilience.
 This measure assumes that a greater expense (relative to the value of the infrastructure alone, not
the value of the service the infrastructure provides to society) equates to more damage, and
therefore lower resilience of the infrastructure.

Adaptive capacity
 E.1. Adaptability and flexibility
 E.2. Impact/Consequences reducing availability
 E.3. Economic of adaptation

Adaptive capacity
E.1. Adaptability and flexibility:
 Adaptability and flexibility are the abilities to change while maintaining or improving functionality,
adopting alternative strategies quickly, responding to changing conditions in time, designing open
and flexible structures.

Adaptive capacity
E.2. Impact/Consequences reducing availability:
 Impact reducing availability is availability of adaptive processes that reduce the impacts of climate
change, e.g. re-allocation of facilities, building new facilities according to climate-ready standards,
protection of existing critical infrastructures, etc.
 Consequences reducing availability is availability of adaptive processes that reduce consequences
of climate change, e.g. re-routing transportation flows, developing flexibility of networks, etc.

Adaptive capacity
E.3. Economics of adaptation:
 Local communities are interested in ensuring they develop and maintain a vibrant and thriving
economy, even amid hazard events.
 Factors that might affect a community‘s economic sustainability after hazard events include the
degree to which the local economy depends on a single industry.

Resilience indexes
 Resilience index R is calculated from Resilience sub-indexes as:
Sum of weighted values of Resilience sub-indexes
Weights are calculated based on the end-user’s prioritisation of each Category (Rank order
approach)
 Capacity and Overall indexes are calculated in the same way as Resilience index

Resilience indicators aggregation methods
Aggregation level Aggregation method Elicitation of weights
IV
From i to I
Calculating Category index I
Average value
or
Sum of all simple weighted sum
Without weights (for average)
or alternatively
Predefined weight and priority
(without end user input)
III
From I to R
Calculating Resilience index R
Sum of all simple weighted sum End user prioritisation input
based on own experience or
simple pair comparison (see
RAT).
Weight based on rank order –
rank sum
II
From R to C
Calculating Capacity index C
I
From C to ORI
Calculating Overall resilience index
ORI

Weight coefficients
 Weight table of Sum of all
simple weighted sum
aggregation method

Resilience Metrics
 In principle, the strategy for measuring resilience is to quantify the difference between the
ability of a critical infrastructure to provide services prior to the occurrence of an event and
the expected ability of that infrastructure to perform after an event
 Good metrics are comprehensive, understandable, practical, non-redundant and minimal
 The above create defensible, transparent and repeatable metrics

Category metrics
 Category metrics can be:
Binary: a) without subcategories
b) with subcategories
Quantitative
 Each category is expressed with Resilience sub-index (I = from 0 to 10)

Binary (yes/no) Category metrics
 With subcategories:
Not directly measurable
If answer is no, than Resilience sub-index I = 0
If answer is yes, than we go to subcategory:
Each subcategory has its own value from 0 to 10
Resilience sub-index I is then calculated as the Average value

Binary (yes/no) Category metrics
 Without subcategories:
Directly measurable:
If answer is no, Resilience sub-index I = 0
If answer is yes, Resilience sub-index I = 10

Quantitative Category metrics
 Directly measurable with two simple formulas:
I = (x/y)*10 - for bigger is better
I = (1-(x/y))*10 - for smaller is better
 Indirectly measurable: derived from other formulas, coefficients, etc.
 Inputs are from end-user using the end-user questionnaire or using EU-CIRCLE’s Critical
Infrastructure Resilience Platform (CIRP)

Connection with CIRP
 For the resilience assessment, a large number of data must be provided – a large part of this data
will be provided by end-users through completion of the end-user questionnaire and the other part
of the data will be drawn directly from CIRP
 There are a total of 139 questions for asset analysis, and 156 questions for network or
network of network analysis. However, the data that is not difficult to gather by end-users. 70-80%
of the requested data are easily understood by operators / owners of critical infrastructures, so
additional effort should be made to collect those remaining 20-30%.
 The values of the Resilience Indexes represent variables based on which to evaluate the
opportunities and make decisions on the necessary adaptation measures and ensure business
continuity.

Section 6 Resilience Assessment
Tool (RAT)

Resilience Assessment Tool – Excel
version

RAT – step 1: End user questionnaire

RAT – Resilience indicators with metrics
 Separate Excel file
 Containing some
explanation that helps
end-user to define
appropriate values

RAT – step 2: Definition of weights

RAT - Overall resilience index

Resilience Assessment Tool – Web version
 Logic and steps
of assessment
are the same as
in Excel version
 Online version
has a database
giving the
possibility of
processing more
than one asset
 You can access
the online tool at:
rat.eucircle.eu

References
[1] Thayaparan, M., Ingirige, B.I., Pathirage, C.P., Kulatunga, U., Fernando, T. (2016). A Resilience Framework for Critical Infrastructure.
Proceeding of 12th International Conference of the International Institute for infrastructure Resilience and Reconstruction(I3R2), Kandi –
Sri Lanka, 5-7 August 2016
[2] National Institute of Standards and Technology (2015) NIST Special Publication 1190: Community Resilience Planning Guide for
Buildings and Infrastructure Systems Volume2.
[3] National Institute of Standards and Technology (2015) NIST Special Publication 1190: Community Resilience Planning Guide for
Buildings and Infrastructure Systems Volume1.
[4] EU-CIRCLE (2016). D4.1: Resilience framework (initial version). EU-CIRCLE Project (Grant Agreement n° 653824).
[5] IBM and AECOM (2015) UNISDR Disaster Resilience Scorecard for Cities.
[6] Chang, S.E. (2014). Infrastructure resilience to disasters. The Bridge, 44(3).

References
[7] Sandia National Laboratories (2014) Annual Report, Laboratory Directed Research and Development.
[8] Ellis, J. (2014). Climate Resilience Indicator, Literature Review. Prepared as part of “Using Columbia Basin State of the Basin Indicators
to Measure Climate Adaptation”.
[9] Prior, T. (2014). Measuring Critical Infrastructure Resilience: Possible Indicators, Risk and Resilience, Report 9. Center for Security
Studies, ETH Zürich.
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Energy Review Technical Workshop. Infrastructure Assurance Center.
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Management 25(2): 6.

References
[13] Cabinet Office (2011). Keeping the Country Running: Natural Hazards and Infrastructure. A Guide to improving the
resilience of critical infrastructure and essential services. Whitehall, London.
[14] Watson, J.P., Guttromson, R., Silva-Monroy, C., Jeffers, R., Jones, K., Ellison, J., Rath, C., Gearhart, J., Jones, D., Corbet,
T. (2014). Conceptual Framework for Developing Resilience Metrics for the Electricity, Oil, and Gas Sectors in the United States.
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[17] IEA (2015). Making the energy sector more resilient to climate change. International Energy Agency, Paris.

References
[18] UNISDR, 2004, Terminology: Basic terms of disaster risk reduction [online], available from http://www.unisdr.org/2004/wcdr-dialogue/
terminology.htm [accessed 8 Nov 2015].
[19] RAMSES (2016). D2.1: Synthesis review on resilient architecture and infrastructure indicators. RAMSES Project (Grant Agreement n°
308497).
[20] Barami, B. (2013). Infrastructure Resiliency: A Risk-Based Framework. John A. Volpe National Transportation Systems Center,
Cambridge, MA.
[21] Petrović, N., Stranjik, A., Peternel, R. (2018) Generic Resilience Indicators of Critical Infrastructures; Ann. Disaster Risk Sci. 2018, 1,
p.97-103
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[23] EU-CIRCLE (2017). D4.5: CI Resilience indicators. EU-CIRCLE Project (Grant Agreement n° 653824).

References
[24] Sfetsos, A., Katopodis, T., Eleftheriadou, A., Eftychidis, G., Gkotsis, I., Leventakis, G., Hedel, R., Hamman, S., Shakou,
L.M., Varianou Mikellidou, C., Boustras, G., Freissinet, C., Lecroart, J., Million, M., Hisham, T., Pathirage, C., Petrovic, N.,
Stranjik, A. (2017): How interconnected critical infrastructures can support societal resilience under future climate: The EU-
CIRCLE approach, in RESILIENCE, The 2nd International Workshop on Modelling of Physical, Economic and Social Systems
for Resilience Assessment, 14-16 December 2017, Ispra, Publications Oﬃce of the European Union, p.161-172

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