This document summarizes the state of practice in resilience approaches in the USA. It discusses the evolution from risk-based approaches to resilience and provides examples of resilience assessment tools used by different government agencies. It also describes pilot studies conducted by the US Army Corps of Engineers using a resilience matrix approach and network science models to assess resilience. The document outlines weaknesses in existing resilience methods and calls for more integrated cross-disciplinary approaches.

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From Risk to Resilience:
State of Practice in the USA
Igor Linkov, PhD
Risk and Decision Science Focus Area
Lead, USACE, ilinkov@yahoo.com
Adjunct Professor, Carnegie Mellon
University
Visiting Professor Ca Foscari
Known, quantifiable
threats
Risk
Unknown
Uncharacterized
Professor, University of Venice, Italy
Co-Authors:
Cate Fox-Lent, USACE
Steve Flynn, Northeastern University
Low-probability
Events
Resilience
Global Risks
World Econ. Forum
2014
Emerging
Global
Risks
2

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Risk and Resilience: Political Importance and
Challenge
Executive Order:
"resilience" means the ability
to anticipate, prepare for, and
adapt to changing conditions
and withstand, respond to, and
recover rapidly from
disruptions.
Risk-Resilience Integration
Top-Down
Resilience/ Decision &Network
Analysis
Bottom-Up
Risk Assessment
Goal Identification and Problem
Framing Management
-
What are the goals,
alternatives, and
constraints?
Decision Model
-
What are the criteria and
metrics, How do we measure
decision-maker values
Risk Characterization
-
What are the risks relative to a
threshold? How do they compare
to other alternatives?
Physical/Statistical Model
-
What is the hazard?
What is exposure?
g
Modeling
Metrics Generation and
Alternative Scoring
-
How does each alternative
score along our identified
criteria and metrics?
Data Collection
-
What are fundamental
properties/mechanisms
associated with each alternative?
Data
Collection
Linkov et al., 2014

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Outline
 From Risk to Resilience (US Army Corps Case)
► Risk
• Conceptualization
• Risk Assessment Case Studies
•• Problems with Risk-based Approaches
► Resilience
• Conceptualization
• Resilience Matrix Approach and Jamaica Bay Case
• Network Science Approach
 State of Practice in the US
•• Army (Installations and Energy)
• DoD (Cyber)
• Department of Interior (Environment and Infrastructure)
• EPA (Environment)
• DHS (infrastructure)
• NIST (framework and Community)
 Discussion – UK vs US Approach
Risk Assessment Formulation

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Risk Management Challenges
ADD WEB REFERENCE

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Risk Assessment is
one part of Resilience
Risk
Ri k Analysis
Risk
Plan Ada
Critical pt
Functi
onality
System
Resilien
ce
Conseque
nce
Ti
me
After Linkov et al, Nature Climate Change 2014
Importance of Recovery
h e
Risk
Low High
Resilience
Low High
a b
c d
Traditional risk management focuses on planning and reducing
vulnerabilities. Resilience management puts additional emphasis
on speeding recovery and facilitating adaptation.
After Linkov et al, Nature Climate Change 2014

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Country Comparison
UK US
Organization Top-down integrated
approach
Parallel but independent
agency efforts
Scope Detailed national risk Community-level risk and
assessment
y
recovery assessment; agency
performance monitoring
Threats Off-shore natural disasters,
cyber attack, international
terrorism
Flooding, domestic natural
disasters, cyber attack
Tools Planning toolkits for
communities and businesses
Planning toolkits for
communities and assessment
frameworks for local
governments
Focus Critical Infrastructure
vulnerability and cascading
consequences
Critical Infrastructure and
capacity to maintain
Process-based, descriptive Metrics, more prescriptive
DHS Disaster Resilience Index
 Demographic data as indicators of scale of vulnerability and
resilience/ ability to recover quickly.
 Metrics in categories of : social,
economic, institutional,
infrastructure, and community.
 All categories equally weighted.
 Regional assessment,
county level resolution.
 Spatially reported results,
comparative.
 All hazards assessment

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FEMA Disaster Resilience Index
 Community member awareness and vulnerability survey
 Potential hazard severity identification
 Strength of social systems
 Relative importance of community
structures
 Rate general mitigation measures
on level of effectiveness or
feasibility to improve each
community component
 Guidance on developing specific
mitigation actions.
 Supplements: specific hazard
probability, functional loss, and
cost calculator; local all-hazards
risk assessment http://www.dhses.ny.gov/oem/mitigation/documents/fema-local-mitigation-
handbook.pdf
NOAA Community Resilience Index
 Identify past and expected storm
strength for benchmark scenarios.
 Checklist of likely losses to critical
infrastructure and facilities under
each scenario.
 Expected level of recover in 1
week.
 Business recovery,
 Strength of social systems
 Existing plans and agreements
 Rank resilience in each category
as High, Medium, Low.
 No relative weights
 Local Government Use
 Specific to coastal storms
ADD REFERENCE

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Nature Conservancy Coastal
Resilience Mapping Tool
 ESRI powered geospatial analysis
tool
 Pre-loaded map layers of relevant
demographic and ecological data
 4 apps available for decision making
purposes
► Flood and Sea Level Rise (future projections)
► Habitat Explorer (weighing habitat importance)
► Community Planning (current data map layers)
► Future Habitat (projected marsh advancement)
 Local decision-makers and planners
in coastal communities
 Used for land management and
wetland preservation prioritization
http://maps.coastalresilience.org/ct/
Resilience Alliance Social-Ecological
Resilience Management Workbook
 Meant for resource management and
planning stakeholders
 Workbook guides stakeholders through
5 steps of resilience assessment:
► Defining your system
► Identifying alternate states and thresholds
► Evaluating dynamics based on system cycles
► Probing the system’s adaptability
► Planning interventions
 Qualitative resilience assessment helps
to frame current state of system,
identify desirability of possible changes
in system states and functions, and
determine disturbances of concern. http://www.sustentabilidad.uai.
edu.ar/pdf/cs/practitioner_work
book_1.pdf

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Weaknesses of Existing Methods
 Assessments built in ad-hoc manner based on
specific expertise of agency.
 Most agencies efforts are not framed in context of
larger system. These efforts are each components
of the necessary changes.
 Assessments do not explicitly consider uncertainty
 Assume future impacts will reflect past impacts and
that locations of past events will be equally
important in future events.
 Tools largely assess vulnerability through risk
metrics rather than assess resilience through
capabilities to absorb, recover, and adapt.
Learning from Military
A highly networked system is governed by domains of
warfare that organize system components and
establish a basis for measurement.
estab s bas s o easu e e t
Physical: system performance in space and
time.
Information: creation, manipulation and
sharing information.
Cognitive: translating, sharing, and acting
upon information to enable system
management.
Social: interaction, collaboration and self-synchronization
between individuals and
entities.

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Resilience: Matrix Approach
Resilience Matrix:
Analyze the functionality of each domain of the system across each stage
of the event timeline
Prepare Absorb Recover Adapt
Physical
Information
Cognitive
Social
• Uses general metrics for measuring relative system resilience
• Diff Different t from f vulnerability l bilit assessment t – th threats t unknown
k
• Useful for identifying weak areas and prioritizing investment to
improve overall resilience
From Linkov et al, Env. Sci. & Tech 2013
Time
General Form of Resilience Matrix
Adverse Event
Previous Cycle Plan/Prepare Absorb Recover Adapt
Physical
• State and capability of
• Event recognition and
• System changes to
• Changes to improve
equipment and
personnel, network
structure
system performance to
maintain function
recover previous
functionality
system resilience
Information • Data preparation,
presentation, analysis,
and storage
• Real-time assessment
of functionality,
anticipation of
cascading losses and
event closure
• Creation and improvement
of data storage and use
protocols
• Data use to track
recovery progress and
anticipate recovery
scenarios
Cognitive • System design and
operation decisions,
with anticipation of
adverse events
• Contingency protocols
and proactive event
management
• Design of new system
configurations, objectives,
and decision criteria
• Recovery decision-making
and
communication
Social • Social network, social Resourceful and
Teamwork and
Addition of or changes to
capital, institutional and
cultural norms, and
training
• accessible personnel
and social institutions
for event response
• institutions, policies, training
programs, and culture
• knowledge sharing to
enhance system recovery
From Linkov et al, Env. Sci. & Tech 2013

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Ways to Quantify
From Keisler and Linkov, 2014
Assessment using Decision Analysis
Use developed resilience metrics to
comparatively assess the costs and
benefits of different courses of action

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Pilot Study in Jamaica Bay, NY
Test two analyses to calculate present-day resilience
• Tier 1: Resilience Matrix, screening
• Tier 2: Integrated Risk/Resilience
Assessment using Bayesian
probabilistic analyses; appropriate for
design
POC: Julie Rosati, ERDC, CHL
NACCS Planning Reaches
Jamaica Bay
23
Jamaica
Bay, NY
Tier 1 Screening: Resilience Matrix Approach
Jamaica Bay Goal:
Provide baseline assessment for
intercomparing project alternatives
Approach:
• Define extent of system & potential
Good
Moderate
Low
Ecosystem
Health
repare
Resist
ecover
Adapt disturbances
• Identify function(s) to be evaluated; for
Jamaica Bay:
• Ecosystem health
• Housing/shelter
• Assess via expert elicitation* capacity of each
cell in matrix
• Results indicate:
• Gaps in system resilience
Pr
R
Re
A
Physical System
Data & Analysis
Decision Support n/a
Communication
Housing and
Shelter
Prepare
Resist
Recover
Adapt
• Project needs
• Partner roles
 Detailed assessment focused on Housing &
Shelter
*Query experts; review literature; examine historical
record
24
Physical System
Data & Analysis
Decision Support
Communication

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How will it work: Project Evaluation
 Baseline assessment can be used to evaluate proposed
projects Prepare Absorb Recover Adapt
Physical 71 16 60 10
Information 63 45 21 18
Cognitive 90 49 38 27
Social 82 54 12 52
43
Project 1 Project 2
Prepare Absorb Recover Adapt
Physical +10 +18 +9 +32
Information +8 +17
Cognitive
Social
Prepare Absorb Recover Adapt
Physical
Information +5 +15 +22
Cognitive
Social +3 +12 +21
Prepare Absorb Recover Adapt
Physical 81 34 69 42
Information 71 45 38 18
Cognitive 90 49 38 27
Social 82 54 12 52
Prepare Absorb Recover Adapt
Physical 71 6 60 10
Information 63 50 36 40
Cognitive 90 49 38 27
51 47
Social 85 54 24 73
*Projects may have (+) or (-) in other matricies
Future: Network Science
We quantify resilience by using network science approach by considering
the different domains as interdependent multiplex networks.

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Resilience and Network Science
A simple illustration of the model,
in which a city depends on Power,
Mobile Communication and Water
services, the latter of which are in
turn dependent on Electrical
power.
Here:
• Power Plant: supplier
• City: demander
• Cell, Water: both suppliers and
demanders
Country Comparison
UK US
Organization Top-down integrated
approach
Parallel but independent
agency efforts
Scope Detailed national risk Community-level risk and
assessment
y
recovery assessment; agency
performance monitoring
Threats Off-shore natural disasters,
cyber attack, international
terrorism
Flooding, domestic natural
disasters, cyber attack
Tools Planning toolkits for
communities and businesses
Planning toolkits for
communities and assessment
frameworks for local
governments
Focus Critical Infrastructure
vulnerability and cascading
consequences
Critical Infrastructure and
capacity to maintain
Process-based, descriptive Metrics, more prescriptive

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Risk-Resilience Integration
Top-Down
Resilience/ Decision &Network
Analysis
Bottom-Up
Risk Assessment
Goal Identification and Problem
Framing Management
-
What are the goals,
alternatives, and
constraints?
Decision Model
-
What are the criteria and
metrics, How do we measure
decision-maker values
Risk Characterization
-
What are the risks relative to a
threshold? How do they compare
to other alternatives?
Physical/Statistical Model
-
What is the hazard?
What is exposure?
g
Modeling
Metrics Generation and
Alternative Scoring
-
How does each alternative
score along our identified
criteria and metrics?
Data Collection
-
What are fundamental
properties/mechanisms
associated with each alternative?
Data
Collection
Linkov et al., 2014
References
 Linkov, I., Eisenberg, D. A., Bates, M. E., Chang, D., Convertino, M., Allen, J.
H., Flynn, S. E., Seager, T. P. (2013). Managing resilience to meet national
needs. Environmental Science & Technology 47:10108-10110.
 Park, J., Seager, TP, Rao, PCS, Convertino, M., Linkov, I. (2013). Contrasting
risk and resilience approaches to catastrophe management in engineering
systems. Risk Analysis 33: 356–367.
 Linkov, I., Eisenberg, D. A., Plourde, K., Seager, T. P., Allen, J., Kott, A (2014).
Resilience Metrics for Cyber Systems. Environment, Systems and Decisions
33:471-476.
 Roege, P., Collier, Z.A., Mancillas, J., McDonagh, J., Linkov, I. (2014). Metrics
for Energy Resilience. Energy Policy 72:249–256.
 Linkov, I, Kröger, W., Levermann, A., Renn, O. et al. (2014). Changing
Resilience Paradigm. Nature Climate Change 4:407-409.
 Eisenberg, D.A., Linkov, I., Park, J., Chang, D., Bates, M.E., Seager, T., (2014).
Resilience Metrics: Lessons from Military Doctrines. Solutions 5:76-87.
 Keisler, J. and Linkov, I. (2014). Models, Decisions and Environment.
Environment, Systems, Decision 4:369–372.
 Collier, Z., Linkov, I. (2014). Decision Making for Resilience within the Context
of Network Centric Operations. In: Proceedings of the 19th International
Command and Control Research and Technology Symposium.

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Call for Papers: Springer’s
Environment, Systems and Decisions
ESD provides a catalyst for
research and innovation in
cross-disciplinary and trans-disciplinary
methods of
decision analysis, systems
analysis, risk assessment,
risk management, risk
communication, policy
31
analysis, environmental
analysis, economic analysis,
engineering, and the social
sciences.