SESSION: RESILIENT INFRASTRUCTURE A Risk-Based Approach to Resiliency in a Post-Sandy Era

Ayesha Dolasa, P.E., LEEP AP BD+C, Program Manager for BEM Systems, Inc

In the aftermath of Superstorm Sandy, NJ TRANSIT developed a resiliency framework to assess the risk of assets to severe weather impacts. This risk-based approach consists of a semi-quantitative approach to evaluate (i) the criticality of assets based on several criteria and (ii) the vulnerability of assets to impacts such as fluvial flooding, storm surge, high heat, and high wind.

Ayesha Dolasa, P.E., LEEP AP BD+C, is an environmental engineer with 15 years of consulting experience providing environmental services. Post-Sandy, she has been working with NJ TRANSIT to develop a long-term sustainability and resiliency plan. In addition, she has been involved with project to evaluate the effects of sea level rise and develop flood mapping tools. Ms. Dolasa serves as a Program Manager for BEM Systems, Inc., an employee-owned consulting engineering and information management firm providing comprehensive environmental services to federal, state, and local government agencies.

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A Risk-Based Approach to Resiliency in a Post-Sandy Era

_______________________________________________ TRB Resiliency Panel

June 17, 2014

Presented by:Ayesha Dolasa, PE, LEED AP

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Damage by Sandy - Impetus for Developing Resiliency

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What is Resiliency?

“Resiliency is not a single outcome. It is a cradle-to-grave process…

… to meet three high-level performance criteria: efficiency, sustainability, and survivability.”

Volpe (June 2013)

Sparta Mississippi

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Developing an approach to determine resiliency by:

assessing the risk of assets to severe weather impacts and

prioritizing capital spending

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Risk-Based Approach

Federal guidance (FTA, FHWA, Volpe) was used to develop a semi-quantitative risk-based approach

Criticality: how important is an asset to the system

Vulnerability: the degree to which an asset is susceptible to and unable to cope with a severe weather impact

RISK = CRITICALITY X VULNERABILITY

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Criticality Assessment

Enables focus on the most important assets Captures institutional knowledge

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Example Criticality Criteria 1 Total Passengers Serviced/Ridership

3 = number of passengers above 10,000 per day

2 = number of passengers between 4,000 and 10,000 per day

1 = number of passengers below 4,000 per day

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Example Criticality Criteria 2Time to Repair/Replace

3 = Duration is long term – 1 week or more

2 = Duration is medium term – more than 24 hours

1 = Duration is short term – less than 24 hours

Parts not manufactured - replace system

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Asset X scores maximum 75/75

Train Stop

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Vulnerability Assessment

Vulnerability is a function of: Exposure

Sensitivity

Adaptive Capacity

RISK = CRITICALITY X VULNERABILITY

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Exposure: Nature and degree to which a system is exposed to a severe weather event

(FTA, 2011)

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Sensitivity: Extent of damage to the asset or negative effect caused by extreme weather

Adaptive Capacity: Ability of the asset to be protected from a severe weather impacts

Adaptive CapacitySensitivity

Low Moderate High

Low 1 3 4Moderate 1 2 3High 1 1 1

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Exposure Sensitivity Adaptive Capacity Vulnerability Score

Flooding/Storm Surge

Y HExtensive damage experienced due to Sandy

LLittle or no protection in place

4

Vulnerability Score – Asset X

FEMA Flood Maps

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Storm Surge/Flooding Heat Wind Snow/Ice

Asset X 300 225 75 150

Vulnerability Scor

e

HIGH

4 100 120 140 160 180 200 220 240 260 280 300

3 75 90 105 120 135 150 165 180 195 210 225MO

D 2 50 60 70 80 90 100 110 120 130 140 150

LOW 1 25 30 35 40 45 50 55 60 65 70 75

  25 30 35 40 45 50 55 60 65 70 75  LOW MODERATE HIGH

      Criticality Rating  

   High Risk - Evaluate and implement resiliency measures  

   Moderate Risk - Evaluate resiliency measures  

       Low Risk - Watch and evaluate for changes         

Risk Matrix - Asset X

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Lessons Learned

Apply a logical risk-based approach to prioritize assets and help decision-makers focus the resiliency investments.

Every transportation system is different – not one size fits all.

It is important to work with personnel with experience to discuss vulnerabilities and asset importance.

All climate predictions, by nature, are uncertain to varying probabilistic degrees.