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Sea Level Rise: Infrastructure Analysis Tools and Impact Assessment. David Judi, Los Alamos National Laboratory Workshop on Sea Level Rise: Science, Prediction, and Stakeholder Planning May 17-18, 2010 San Diego, CA. Energy & Infrastructure Analysis. - PowerPoint PPT Presentation
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U N C L A S S I F I E D
LA-UR 10-03268
Operated by the Los Alamos National Security, LLC for the DOE/NNSA
Sea Level Rise: Infrastructure Analysis Tools and Impact
Assessment
David Judi, Los Alamos National Laboratory
Workshop on Sea Level Rise: Science, Prediction, and Stakeholder Planning
May 17-18, 2010
San Diego, CA
U N C L A S S I F I E D
U N C L A S S I F I E D
Operated by the Los Alamos National Security, LLC for the DOE/NNSA
Slide 2
Energy & Infrastructure Analysis
• Infrastructure Interdependency Modeling and Simulation– Examines how infrastructure systems interact with one another
and how disruptions in one infrastructure can propagate among infrastructures
– Natural and terroristic events– Tools developed for varying levels of fidelity
U N C L A S S I F I E D
U N C L A S S I F I E D
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Slide 3
Multi-Hazard Infrastructure Impact Assessment (MHIIA)
• Flood Hazard Models– One-dimensional models– Two-dimensional models– Cellular Automata (CA)
– Step up from “Naïve”
• Existing inundation maps– E.g., FEMA, NOAA/NWS
HazardEvents/Modeling
• IND
• Earthquake
• Flood
• Chem/Bio
• Etc.
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Slide 4
HazardEvents/Modeling
Direct Effects(Fragility)
• IND
• Earthquake
• Flood
• Chem/Bio
• Etc.
• Infrastructure databases
• Fragility curves
Secondary Effects(Infrastructure Models)
• Electric power
• Water
• Economy
• Telecomm
• Public health
• Etc.
Multi-Hazard Infrastructure Impact Assessment (MHIIA)
Extraction of assets from many sectors
and mapping of damage probability
very quick
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5
Interdependency Environment for Infrastructure Simulation Systems (IEISS)-
A Flexible & Extendible Software Framework designed for:
ModelingModeling
SimulatingSimulating AnalyzingAnalyzingMultipleInterdependentInfrastructures
• Objective – – iidentify and understand interdependencies• Importance – s – study complex, emergent, cascading behaviors• Value – understanding system behavior; capturing cascading effects; analyzing “what-
if” scenarios
Infrastructure Secondary Impact Analysis
U N C L A S S I F I E D
U N C L A S S I F I E D
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Case Study: Bay Area Sea Level Rise
• Inundation Event• USGS inundation map (Knowles 2008, used in Heberger et al. 2009)
• Sea level rise at 0, 50, and 100 centimeters using MSL and 100-yr event
• Infrastructure Impact Assessment• Infrastructure Identification
• MHIIA (Electric power, hospitals, wastewater facilities)
• Cascading Impact
• IEISS (Electric power only)
• Questions:• How many substations are inundated and what are the impacts (e.g.,
outage area and population)?
• How many hospitals and wastewater facilities are inundated and what are their capacities?
Slide 6
U N C L A S S I F I E D
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Slide 7
Case Study: Electric Power Infrastructure Impacts
Mean Sea Level
• Current condition
100-yr Flood Event
• 69 Substations inundated
• Concentration along SW side of bay
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Slide 8
Mean Sea Level
• 8 substations
100-yr Flood Event
• 95 substations inundated (26 additional)
• Concentration remains along SW side of bay
• Some along east side
Case Study: Electric Power Infrastructure Impacts
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Slide 9
Case Study: Electric Power Infrastructure Impacts
Mean Sea Level
• 20 substations
• Mostly along SW side of bay (dense population)
100-yr Flood Event
• 128 substations inundated (59 additional compare to no SLR)
• Concentration remains along SW side of bay
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Slide 10
Mean Sea Level
Scenario Substations Population in Outage Area
No Sea Level Rise - -
50 cm Sea Level Rise 8 185,000
100 cm Sea Level Rise 20 542,000
100-Year Flood Event
Scenario Substations Population in Outage Area
No Sea Level Rise 69 993,000
50 cm Sea Level Rise 95 1,408,000
100 cm Sea Level Rise 128 1,642,000
Case Study: Electric Power Infrastructure Impacts
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Case Study: Wastewater and Hospital Impacts
Slide 11
Mean Sea Level
• Current condition
100-yr Flood Event
• 1 hospital
• 10 wastewater facilities
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Case Study: Wastewater and Hospital Impacts
Slide 12
Mean Sea Level
• No hospitals
• 1 wastewater facility
100-yr Flood Event
• 1 hospital (no change)
• 14 wastewater facilities (4 additional)
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Case Study: Wastewater and Hospital Impacts
Slide 13
Mean Sea Level
• No hospitals
• 2 wastewater facilities
100-yr Flood Event
• 1 hospital (no change)
• 19 wastewater facilities (9 more than no SLR)
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Case Study: Wastewater and Hospital Impacts
Slide 14
100-year Flood Event
Scenario Hospitals Beds Wastewater Treatment Facilities
Combined Capacity(mgd)
No Sea Level Rise 1 213 10 254
50 cm Sea Level Rise 1 213 14 272
100 cm Sea Level Rise 1 213 19 405
Mean Sea Level
Scenario Hospitals Beds Wastewater Treatment Facilities
Combined Capacity(mgd)
No Sea Level Rise - - - -
50 cm Sea Level Rise 0 0 1 14
100 cm Sea Level Rise 0 0 2 19
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Operated by the Los Alamos National Security, LLC for the DOE/NNSA
Conclusions
• Inundation related infrastructure impacts from sea level rise alone are minimal– Flood events on top of sea level rise must be considered– Upstream tributary impacts should be investigated– Accountancy of changing morphology due to sea level rise
induced erosion
• Framework can be used in planning– Many scenarios quickly for many sectors– Local to regional scale
Slide 15
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Contact Information
David JudiLos Alamos National [email protected]
Tim McphersonLos Alamos National [email protected]
Jim DoyleLos Alamos National [email protected]
