1. 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

2. 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 1 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

3. 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 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 Hazard Events/Modeling IND Earthquake Flood Chem/Bio Etc.

4. 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 3 Hazard Events/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

5. U N C L A S S I F I E D Operated by the Los Alamos National Security, LLC for the DOE/NNSA 4 Interdependency Environment for Infrastructure Simulation Systems (IEISS)- A Flexible & Extendible Software Framework designed for: Modeling Simulating Analyzing Multiple Interdependent Infrastructures – i Objective – identify and understand interdependencies – s Importance – study complex, emergent, cascading behaviors Value – understanding system behavior; capturing cascading effects; analyzing “what- if” scenarios Infrastructure Secondary Impact Analysis

6. U N C L A S S I F I E D Operated by the Los Alamos National Security, LLC for the DOE/NNSA 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 5

7. 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 6 Case Study: Electric Power Infrastructure Impacts Mean Sea Level Current condition 100-yr Flood Event 69 Substations inundated Concentration along SW side of bay

8. 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 7 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

9. 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 8 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

10. 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 9 Mean Sea Level ScenarioSubstationsPopulation in Outage Area No Sea Level Rise-- 50 cm Sea Level Rise8185,000 100 cm Sea Level Rise20542,000 100-Year Flood Event ScenarioSubstationsPopulation in Outage Area No Sea Level Rise69993,000 50 cm Sea Level Rise951,408,000 100 cm Sea Level Rise1281,642,000 Case Study: Electric Power Infrastructure Impacts

11. U N C L A S S I F I E D Operated by the Los Alamos National Security, LLC for the DOE/NNSA Case Study: Wastewater and Hospital Impacts Slide 10 Mean Sea Level Current condition 100-yr Flood Event 1 hospital 10 wastewater facilities

12. U N C L A S S I F I E D Operated by the Los Alamos National Security, LLC for the DOE/NNSA Case Study: Wastewater and Hospital Impacts Slide 11 Mean Sea Level No hospitals 1 wastewater facility 100-yr Flood Event 1 hospital (no change) 14 wastewater facilities (4 additional)

13. U N C L A S S I F I E D Operated by the Los Alamos National Security, LLC for the DOE/NNSA Case Study: Wastewater and Hospital Impacts Slide 12 Mean Sea Level No hospitals 2 wastewater facilities 100-yr Flood Event 1 hospital (no change) 19 wastewater facilities (9 more than no SLR)

14. U N C L A S S I F I E D Operated by the Los Alamos National Security, LLC for the DOE/NNSA Case Study: Wastewater and Hospital Impacts Slide 13 100-year Flood Event ScenarioHospitalsBedsWastewater Treatment Facilities Combined Capacity (mgd) No Sea Level Rise121310254 50 cm Sea Level Rise121314272 100 cm Sea Level Rise121319405 Mean Sea Level ScenarioHospitalsBedsWastewater Treatment Facilities Combined Capacity (mgd) No Sea Level Rise---- 50 cm Sea Level Rise00114 100 cm Sea Level Rise00219

15. U N C L A S S I F I E D 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 14

16. U N C L A S S I F I E D Operated by the Los Alamos National Security, LLC for the DOE/NNSA 15 Contact Information David Judi Los Alamos National Laboratory djudi@lanl.gov Tim Mcpherson Los Alamos National Laboratory tmac@lanl.gov tmac@lanl.gov Jim Doyle Los Alamos National Laboratory jcd@lanl.gov