Honolulu Essential Facilities Risk Assessment (HEFRA) Project Report January 29, 2010

Transcription

1 Honolulu Essential Facilities Risk Assessment (HEFRA) Project Report January 29, 2010 Prepared For Department of Homeland Security Federal Emergency Management Agency EMR-2003-CO-0046 / Task Orders 016 and 019 Prepared by: RMTC / URS JV 2024 North King Street, Suite 200 Honolulu Hawaii 96819

2 Acknowledgments The work that provided the basis for this publication was supported by funding from the Federal Emergency Management Agency (FEMA) of the Department of Homeland Security under a contract with RMTC / URS, a Joint Venture. The substance and findings of that work are dedicated to the public. RMTC / URS was responsible for project management, technical support, and report review. RM Towill was the overall team leader, coordinator, and responsible for making Task Progress Reports and submission of the Final Project Report to FEMA. MRC LLC was responsible for the flood scenario definitions and flood scenario analyses. Martin & Chock, Inc. was responsible for interpreting the structural characteristics of furnished essential facility building inventory data, and performed the earthquake and wind scenario analyses. The project team prepared this report. The Federal Emergency Management Agency acknowledges and appreciates the contributions of the following individuals and organizations to the development of this report: Project Sponsor FEMA-Region IX Mitigation Division 1111 Broadway, Ste 1200 Oakland, CA Eric Simmons Project Manager RM Towill Corporation 2024 North King Street Honolulu, Hawaii James Yamamoto, P.E. Upgrade of Essential Facility Data and Earthquake, Flood and Wind Analysis MRC LLC Water Resources Engineering N. 78th Way Scottsdale, AZ Massoud Rezakhani, CFM &Martin & Chock, Inc. Structural Engineers 1132 Bishop Street, Suite 1550 Honolulu, Hawaii Gary Chock, SE Dewberry & Davis LLC Project Reviewer 8401 Arlington Boulevard Fairfax, VA Stephanie Routh and Ken Logsdon ii

3 Executive Summary The State of Hawaii consists of eight major islands (Kauai, Niihau, Oahu, Maui, Molokai, Lanai, and Kahoolawe, Hawaii) and 124 small islands, reefs, and shoals (referred to as the Northwest Hawaiian Islands). The City and County of Honolulu consists primarily of the Island of Oahu but also includes the Northwest Hawaiian Islands, with the exception of Midway Atoll, which is administered by the U.S. Fish and Wildlife Service. Consequently this planning document focuses on the Island of Oahu. Oahu s resident population is approximately 952,640 accounting for about 70% of the state s population of 1.3 million. The population has grown by 3.3% since the 2000 census which is slower than the statewide growth rate of 6.3%. The average de-facto population including tourists in 2008 is estimated at 986,785. The average number of tourists on the island in 2008 was estimated at 81,751. The island is much more densely populated than the rest of the state with a density of 1,460 people per square mile compared to a state average of 189. Table ES-1. Population Distribution Region Population 2000 Population 2010 Primary Urban Center 47.9% 46.3% Ewa 7.8% 10.2% Central Oahu 16.9% 17.1% East Honolulu 5.3% 5.5% Koolaupoko 13.5% 12.6% Koolauloa 1.7% 1.6% North Shore 2.1% 2.0% Waianae 4.8% 4.7% Total 100% 100% Total Population 876, ,640 Figure ES-1. Geographic areas represented by the regional Development Plans iii

4 The damage to and destruction of the built environment caused by natural disasters, particularly to public infrastructure, often represents enormous economic, social, and general functional costs to a community, while also impeding emergency response and recovery activities. Essential facilities include those that provide emergency services to the community, i.e. police and fire stations, hospitals, the emergency operations center, and shelters (primarily school buildings), and other facilities providing services to the public that are necessary to preserve public welfare. Essential facilities are the assets for which loss would have the greatest impact during a hazard event. These may be temporarily disrupted during disaster, but would have priority for initial recovery efforts. The Multi-Hazard Pre-Disaster Hazard Mitigation Plan of the City & County of Honolulu recently undertook an overall economic risk analysis based on historical and probabilistic natural hazards. Using Average Annualized Loss as an objective measure of future losses averaged on an annual basis, the severity of the major natural hazards of severe wind events, earthquake, and flood were found to be significant threats. It should be noted that further improvements of the data set for the essential facilities may substantially impact the annual loss result for the flood analysis. Table ES-2 Hazard Severity to the City and County of Honolulu Based on Average Annual Loss Estimates (Multi-Hazard Pre-Disaster Hazard Mitigation Plan of the City & County of Honolulu, 2010) Winds Earthquakes Floods $216 Million / Year $21 Million / Year $13 Million / Year Thus, understanding the potential impacts of severe wind events, earthquakes, and floods on the county s essential facilities and the populace is an important element of good hazard mitigation planning. To support this understanding, the Federal Emergency Management Agency (FEMA) sponsored this project to perform a risk assessment of essential facilities using its HAZUS MH (HAZards U.S., Multi-Hazard) software. A May 2009 pilot project for California, the Orange County Essential Facilities Risk Assessment (OCEFRA), served as a guideline methodology for implementing updated essential facility data in the HAZUS MH program in order to perform this improved risk assessment. A principal difference in this Honolulu study is the additional risk assessment for high wind using the HAZUS MH Hurricane Model. Default data provided with the HAZUS MH software allows a user to run a simplified or Level 1 analysis without collecting additional data. In many cases, however, the quality of default national data delivered with the software is less than optimal; it may originate from agencies other than FEMA, or was collected for applications other than loss estimation. Accordingly, the accuracy of HAZUS MH results can be greatly improved with the input of various user supplied data on either the hazard or the affected assets or both. Such an enhanced analysis is usually referred to as a Level 2 analysis. HAZUS MH produces estimates of damage to regional building stocks, lifelines and essential facilities, economic loss, and social impacts. Local, state and federal government officials use HAZUS MH for mitigation, emergency response, and recovery planning. Default data built into HAZUS MH MR3 includes regional building inventory databases representing building stock iv

5 conditions in the year 2006, proxied from 2000 census data (e.g., square footage of residential structures is estimated from census data on housing unit counts) and commercially-available data on employment and businesses. These data are aggregated data, i.e., the database tabulates attributes such as the total building square footage and dollar exposure by census block (flood) or tract (earthquake), rather than on a building-by-building basis. In contrast to the general building stock, HAZUS MH estimates damage and functionality of essential facilities as well as transportation and utility lifelines, on a building or facility specific basis. In addition to developing enhanced regional building inventory data, the Honolulu study also generated significantly improved data sets for essential facilities, required for emergency response, community resilience and rapid recovery. Within HAZUS MH, Essential Facilities include hospitals, fire stations, police stations, emergency operations centers (EOCs), and schools, including both grade schools and colleges and universities. These improved HAZUS MH -compatible inventory databases have been provided for future use in additional HAZUS MH risk assessments, on-going maintenance, and further enhancement. The goal of this project is to: A. Gather and interpret information for Honolulu essential facilities (police, fire, EOC s, hospitals, University of Hawaii essential facilities, and school emergency shelter buildings). B. Model earthquake, wind, and flood scenarios appropriate with hazard probabilities for the island of Oahu. C. Utilize this specific building data in HAZUS-MH (MR-3) to produce improved loss estimate results for earthquakes, wind, and floods in order to develop risk and vulnerability assessments and priorities for Honolulu Essential Facilities. Default HAZUS Data The default Essential Facilities dataset of 291 buildings included: 3 Fire Department Administrative Building Locations but no fire stations 11 Police Stations and 6 other support and administrative facilities, but no individual building information The Emergency Operations Center of the State Civil Defense and the EOC of the City, plus the administrative site of the City Emergency Services Department, but no individual building information 14 Hospital Sites, but no individual building information 253 Public and Private School campuses, but no individual building information Upgrade of the Essential Facility Inventory Data for Use in HAZUS MH MR-3 This task consisted primarily of implementing county dataset improvements, Hawaii construction costs, design vintage, specific building type, and facility information parameters relevant to HAZUS MH. v

6 Enhanced Data for Essential Facility Buildings For the schools data set only public school buildings designated as tropical cyclone shelters and 57 core buildings on the UH Manoa Campus were included in the essential facilities list. Each known building of each hospital and medical care facility was included in the health care facilities data set. The police and fire station data sets contain all known stations as does the emergency response center data set. The most accurate geo-coordinates of each facility were selected by comparing its location given within the default HAZUS MH database, data from the City and County of Honolulu 2010 Hazard Mitigation plan, and aerial earth imagery. Essential Facility Data of 985 buildings has been assembled for: 43 Fire Stations 14 Police Stations 7 Emergency Operations Center facility sites of the State and County 80 Hospital Buildings 784 Public School Buildings including those identified by the State Civil Defense for use as emergency shelters 57 essential buildings of the University of Hawaii at Manoa Essential Facilities Data was reviewed and incorporated: Data was extracted, interpreted and corrected as necessary, and the representative information databases were used as input into a customized HAZUS MH region for the island of Oahu. The model now includes approximately three times as many essential facilities than did the default data, and includes individual buildings, rather than just the sites of essential facilities. Table ES-3. Comparison of Default and Improved Essential Facility (EF) Essential Facility Type HAZUS MH MR3 - Default No. of Buildings (EF) Fire Station 0 43 EOC 1 7 Police Station Hospitals School Buildings University of Hawaii Buildings 1 57 Improved Honolulu Inventory Data - No. of Buildings (EF) Risk Assessment Analysis of HAZUS MH Modeled Inventory Analysis was performed using the HAZUS MH model with the default data and then with the customized data parameters. Wind Scenario Preparation involved the specification and documentation of a tropical cyclone track data scenario appropriate for HAZUS MH analysis of the City and County of Honolulu, representing year recurrence interval events. This scenario was provided by the Central Pacific Hurricane Center. It is intended that the two analyses reflect a similar probabilistic hazard, so that comparisons of losses are interpretable as a relative- vi

7 risk level. (Flood Analyses performed for a 500-year recurrence would then be approximately compatible for a comparison of relative risk.) Earthquake Scenario Preparation: For loss estimation and building vulnerability ranking a magnitude 6.8 earthquake scenario with an epicenter near the Island of Lanai was analyzed within the HAZUS MH model. Shake maps prepared by USGS for peak ground acceleration, velocity, and spectral accelerations were imported into the model for this study. This is a deep lithospheric earthquake with a similar seismogenic mechanism as the Kiholo Bay earthquake, i.e., plate flexural failure. Maximum peak ground accelerations on Oahu were about 12% gravity at the southeastern most point of the island, with values elsewhere of between 2% to 10%. Flood Scenario Preparation: The risk assessment on the City and County of Honolulu examined the impacts of three different floods on essential facilities and general building stock in the county a 100-year flood with the existing certified levee system in the county intact, a 100-year flood without consideration of these levees, and a 500-year (0.2% chance per year) flood. Depth grids, that were derived from DFIRMs, for all three scenarios were imported into HAZUS MH model for analysis. Scenario Analysis and Risk Assessment included essential facility functionality, loss estimates, and regional losses from General Building Stock and other impacts that place demand on essential facilities. Risk assessments of the essential facilities were ranked by expected damage losses and by functionality losses. Thus, the higher (vulnerability) priority facilities are identified. The HAZUS MH Earthquake Module estimates damage state probabilities (i.e., the probability that a facility will be in each of five damage states; None, Slight, Moderate, Extensive, or Complete) and functionality (i.e., estimates of facility functionality, in percent, at Day 1, 3, 7, 10, 14, 30 and 90). Economic losses are not explicitly generated for essential facilities, but mean damage estimates were computed outside the HAZUS MH program for this study. In the HAZUS MH Wind and Flood Modules, essential facilities functionality and mean damage (in terms of percent of replacement cost) are computed directly. For the flood risk assessment, HAZUS MH MR4 was used to estimate losses since improvements to the general data bases internal to the program with respect to structure flood characteristics would result in more accurate estimates. Risk Analysis Results The risk assessment results are documented in this report. Analysis by this HAZUS MH modeling technique indicates that wind risk to Oahu essential facilities and the general building stock are much higher than earthquake risk. The analysis were performed for a return period of years. Earthquake losses totaled only $3 million for the essential facilities and $75 million for the general building stock, while wind losses of the essential facilities totaled over $637 million with $26.2 billion in losses to the general building stock. Flood Losses for essential facilities totaled to $31.2 million, $32.6 million, and $39.2 million, while the losses to the general building stock were $2.3 billion, $3 billion, $4.4 billion for the 100-year with levees, 100-year without levees, and 500-year with levees scenarios, respectively. vii

8 Table ES-4 Total Losses Based On HAZUS MH Default Data* Hurricane Event Total Losses Essential Facilities $44,499,695 Hurricane Event Total Losses General Building Stock $26,234,352,000 Earthquake Event Total Losses Essential Facilities $705,497 Earthquake Event Total Losses General Building Stock $75,000,000 Flood Event Total Losses 100 with Levees Essential Facilities $31,169,000 Flood Event Total Losses 100 with Levees General Building Stock $2,296,600,000 Flood Event Total Losses 100 without Levees Essential Facilities $32,569,000 Flood Event Total Losses 100 without Levees General Building Stock $3,037,820,000 Flood Event Total Losses 500 with Levees Essential Facilities $39,203,000 Flood Event Total Losses 500 with Levees General Building Stock $4,442,940,000 *Flood losses estimated using HAZUS MH MR4 Table ES-5 Total Losses Based on Updated HAZUS MH Essential Facility Data* Hurricane Event Total Losses Essential Facilities $637,495,287 Hurricane Event Total Losses General Building Stock $26,234,352,000 Earthquake Event Total Losses Essential Facilities $3,082,997 Earthquake Event Total Losses General Building Stock $75,000,000 Flood Event Total Losses 100 with Levees Essential Facilities $16,339,000 Flood Event Total Losses 100 with Levees General Building Stock $2,296,600,000 Flood Event Total Losses 100 without Levees Essential Facilities $21,321,000 Flood Event Total Losses 100 without Levees General Building Stock $3,037,820,000 Flood Event Total Losses 500 with Levees Essential Facilities $34,186,000 Flood Event Total Losses 500 with Levees General Building Stock $4,442,940,000 *Flood losses estimated using HAZUS MH MR4 For wind hazard, medical facilities and school buildings used as tropical cyclone shelters are indicated to be at highest risk of the individual facilities modeled. Basically all essential facilities are expected to lose functionality for some period of time in the event of a Category 2 hurricane similar to the modeled event. Average time of inoperability may range from 3-4 months. Of the general building stock nearly 50,000 structures are expected to be severly damaged or completely destroyed during the event, which will displace nearly 77,000 households and require around 18,000 people to seek temporary shelter. On the other hand, it is expected that nearly all essential facilities will maintain functionality in the event of an earthquake with a similar magnitude to that modeled. It is possible however, that an isolated facility will experience a degree of damage that may render it inoperable for a short time, perhaps 1-2 weeks maximum. Of the general building stock it is predicted that moderate damage will occur to only 33 buildings on Oahu. This may result in a very limited number of injuries (less than 10) that may require medical attention without hospitalization. Risk assessment results from the scenario analyses will help government officials better understand the distribution of risk within the County. This risk information should prove useful for developing effective disaster mitigation plans and hazard mitigation grant applications, as well as for designing emergency response exercises. With the updated county inventory viii

9 databases and the HAZUS MH tool, city and county officials will be able to model additional disaster scenarios, obtaining more accurate estimates of the potential effects on the County for disaster mitigation planning. The risk assessment has identified the essential facility buildings potentially at highest risk to economic loss or loss of functionality during a disaster. This provides a prioritization of facilities for possible detailed investigation and potential retrofit to improve their resilience to natural diasters. This report thus furnishes the initial prioritization of facilities most likely to require such detailed investigation. Follow-up detailed evaluations of these high priority buildings may result in revisions to the risk rankings, but more importantly, will identify specific mitigation measures for each to reduce vulnerabilities and improve expected building performance during earthquakes, winds, and floods. ix

10 Table of Contents ACKNOWLEDGMENTS... II EXECUTIVE SUMMARY... III DEFAULT HAZUS DATA... V ENHANCED DATA FOR ESSENTIAL FACILITY BUILDINGS... VI FIGURE 3-5. HAZUS MODELED PEAK GROUND ACCELERATIONS ON OAHU FOR LANI EARTHQUAKE XII FIGURE 3-8. CONTOURS SHOW NUMBER OF TIMES A TROPICAL CYCLONE XII 1 INTRODUCTION PROJECT OVERVIEW ANALYSIS APPROACH COMMUNITY PARTICIPATION OVERVIEW OF HONOLULU NATURAL HAZARDS Strong Winds Earthquakes Floods ASSESSMENT OF RELATIVE RISKS OF MULTIPLE HAZARDS DEFAULT HAZUS MH DATA UPGRADE OF THE ESSENTIAL FACILITY INVENTORY DATA FOR USE IN HAZUS MH Enhanced Data for Essential Facility Buildings Essential Facility Data of buildings has been assembled for: RISK ASSESSMENT ANALYSIS OF HAZUS MH MODELED INVENTORY UPGRADE OF THE ESSENTIAL FACILITY INVENTORY DATA FOR USE IN HAZUS-MH MR DEFAULT HAZUS MH DATA GENERAL BUILDING STOCK ESSENTIAL FACILITIES DATA COLLECTION CORRECTING COORDINATE SYSTEM ERRORS AND DETERMINING/VALIDATING ESSENTIAL FACILITY BUILDING GEOCODING BUILDING CONSTRUCTION CLASSIFICATION AND REPLACEMENT VALUES GENERAL AND SPECIFIC BUILDING TYPES Specific Building Types for the HAZUS MH Earthquake Module Honolulu Seismic Design Levels Specific Building Types for the HAZUS MH Hurricane Module Honolulu Wind Design Level General Building Types for the HAZUS MH Flood Module Honolulu Flood Design Level (FIRM or Pre-FIRM) ENHANCED HONOLULU DATA FOR ESSENTIAL FACILITY BUILDINGS COMPILED HONOLULU MULTI-HAZARD ESSENTIAL FACILITY INVENTORY NATURAL HAZARDS SEISMIC HAZARD Historic Record of Earthquake Intensities Probabilistic Seismic Hazard Earthquake Scenario Analysis Soil Condition Modeling HIGH WINDS Historic Record Probabilistic Wind Hazard Wind Scenario Analysis x

11 3.3 FLOODS Historic Record Flood Scenario Analysis ANALYSIS OF HAZUS MH MODELED INVENTORY ANALYSIS METHODOLOGY Earthquake Analyses Using HAZUS MH MR Wind Analyses Using HAZUS MH MR Flood Analyses Using HAZUS MH MR RESULTS OF RISK ASSESSMENTS Default Data Risk Assessment Regional Impacts Identifying the Highest Risk Facilities due to Multiple Hazards and Multiple Effects Default Essential Facilities Data Risk Assessment Enhanced Data Risk Assessment Enhanced Essential Facilities Risk and Vulnerability Ranking CONCLUSIONS REFERENCES APPENDIX A HAZUS-MH: EARTHQUAKE EVENT REPORT... 1 APPENDIX B HAZUS-MH: WIND EVENT REPORT... 1 APPENDIX C HAZUS-MH: FLOOD EVENT REPORTS... 1 APPENDIX D HAZUS-MH: EARTHQUAKE AAL SUMMARY REPORT... 1 APPENDIX E HAZUS-MH: HURRICANE AAL SUMMARY REPORT... 1 APPENDIX F HONOLULU COMMUNITY EXECUTIVE COMMITTEE... 1 APPENDIX G DATA TABLES... 1 xi

12 FIGURES Figure2-1. Map Of Police Station Locations In Updated Dataset Figure2.2. Map of Emergency Response Facility Locations In Updated Dataset Figure2-3. Map Of Healthcare Facility Locations In Updated Dataset Figure 2-4. Map of Fire Department Station Locations with Emergency Shelters In Updated Dataset Figure 2-5. Map of School Campus Locations with Emergency Shelters in Updated Dataset Figure 3-1. Distribution Of Epicenters Of Historic Earthquakes Felt On The Island Of Oahu Figure 3-2. Peak Ground Acceleration Hazard Figure 3-3. Lanai 1871 Earthquake Figure 3-4. Shakemap of Event Used for Earthquake Vulnerability Ranking Figure 3-5. Hazus Modeled Peak Group Accelerations On Oahu for Lani Earthquake Figure 3.6 Site Classification for Essential Figure 3-7. Site Classifications For General Building Stock By Census Tract Figure 3-8. Countours Show Number of Times a Tropical Cyclone Figure3-9. The latest wind hazard curve for Hawaii, from the ASCE 7-10 Standard Figure3-10. HAZUS MH severe wind tropical cyclone scenario Figure Honolulu County, 100-Year Floodplain (With Levees) and Depth Grid Figure Honolulu County, 100 Year Floodplain (Without Levees) and Depth Grid Figure Honolulu County, 500 Year Floodplain and Depth Grid Figure 4-1. HAZUS MH Earthquake Loss Estimation Model Figure 4-2. HAZUS MH Hurricane Loss Estimation Model Figure 4-3. HAZUS MH Flood Loss Estimation Methodology Figure 4-4. Residential Earthquake Losses Per Census Tract For Modeled Event Figure 4-5. Residential Wind Losses Per Census Tract For Modeled Event Figure 4-6. Flood Building Losses Per Census Tract for 100-Year Flood with Levees Figure 4-7. Flood Building Losses Per Census Tract for 100-Year Flood without Levees Figure 4-8. Flood Building Losses Per Census Tract for 500-year Flood with Levees Figure 4-9. Total Direct Economic Loss on Oahu Resulting from a M6.8 Scenario Earthquake Figure Estimated Functionality of Oahu Fire Stations in a M6.8 Lanai Earthquake Scenario Figure Estimated Functionality of Oahu Schools and University of Hawaii at Manoa In a M6.8 Lanai Earthquake Scenario Figure Estimated Functionality of Oahu Hospitals in a M6.8 Lanai Earthquake Scenario Figure Estimated Functionality of Oahu EOC s in a M6.8 Lanai Earthquake Scenario Figure Estimated Functionality of Oahu Police Stations in a M6.8 Lanai Earthquake Scenario Figure Total Direct Economic Loss on Oahu Resulting from a Category 2 Scenario Figure Estimated Functionality of Oahu Fire Stations in a Category 2 Hurricane Scenario Figure Estimated Functionality of Oahu Schools and University of Hawaii at Manoa Hurricane Scenario Figure Estimated Functionality of Oahu Hospitals in a Category 2 Hurricane Scenario Figure Estimated Functionality of Oahu EOC s in a Category 2 Hurricane Scenario Figure Estimated Functionality of Oahu Police Stations in a Category 2 Hurricane Scenario Figure Total Direct Economic Loss in Honolulu County Resulting from a 100-Year Flood (Levees intact) Figure Honolulu County Fire Station Functionality Following a 100-Year Flood (Levees Intact) Figure Honolulu County EOCs Functionality Following a 100-Year Flood (Levees Intact) Figure Honolulu Police Facilities Functionality Following a 100-Year Flood (Levees Intact) Figure Honolulu County School Districts Functionality Following a 100-Year Flood (Levees Intact) Figure Honolulu County Hospital Functionality Following a 100-Year Flood (Levees Intact) Figure Total Direct Economic Loss in Honolulu County Resulting From a 100-Year Flood without Levees.. 84 Figure Honolulu County Fire Station Functionality Following a 100-Year flood without Levees xii

13 Figure Honolulu County EOCs Functionality Following a 100-Year Flood Without Levees Figure Honolulu Police Facilities Functionality Following a 100-Year Flood Without Levees Figure Honolulu County School Districts functionality Following a 100-Year Flood without Levees Figure Honolulu County Hospital Functionality Following a 100-Year Flood without Levees Figure Total Direct Economic Loss in Honolulu County Resulting from a 500-Year Flood (Levees Intact) Figure Honolulu County Fire Station Functionality Following a 500-Year Flood (Levees Intact) Figure Honolulu County EOCs Functionality Following a 500-Year Flood (Levees Intact) Figure Honolulu Police Facilities Functionality Following a 500-Year Flood (Levees Intact) Figure Honolulu County School Districts Functionality Following a 500-Year Flood (Levees Intact) Figure Honolulu county Hospital Functionality Following a 500-Year Flood (Levees Intact) xiii

14 TABLES Table 1-1. Hurricane Annual Odds of Occurrence by Saffir Simpson Category... 3 Table 1-2. A Summary of Historic Earthquake Events Felt on Oahu... 4 Table 1-3. Major Floods Affecting Oahu and Associated Damage, Table 1-4. Hazard Severity to the City & County of Honolulu Based on Average Annual Loss Estimates... 6 Table 2-1. Default General Building Stock Inventory Exposure for Oahu... 9 Table 2-2. Feature Classes and Locations of HAZUS MH Program Files Table 2-3. Occupancy Class Floor Areas (Default and Hawaii Typical Floor Areas) Table 2-4. Building Replacement Value Table 2-5. HAZUS MH General Building Types Table 2-6. FEMA 310 Benchmark UBC Building Dates Table 2-7. Historic Seismic Force Comparisons for Oahu Table 2-8. Seismic Design Level Per UBC Code Vintage Table 2-9. Specific Building Types in the HAZUS MH Hurricane Model Table Design Wind Pressures per UBC Code Years Table 3-1. Historic Hawaiian EQ with Honolulu Modified Mercalli Intensities of V and Greater Table 3-2. Reference of Seismic Maps Used for HAZUS Analysis Table 3-3. Determination of Seismicity Region for Oahu Table 3-4. Significant Hawaiian Tropical Cyclones of the 20 th Century Table 3-5. Input Data for HAZUS Wind Scenario Table 3-6. Major Floods Affecting Oahu and Associated Damage, Table 4-1. General Building Stock Economic Losses Per Occupancy Due to Earthquake Scenario Table 4-2. General Building Stock Economic Losses Per Occupancy Due to Wind Scenario Table 4-3. General Building Stock Economic Losses Per Occupancy Due to Flood Scenario (100-year with Levees) Table 4-4. General Building Stock Economic Losses Per Occupancy Due to Flood Scenario (100-year without Table 4-5. Levees) General Building Stock Economic Losses Per Occupancy Due to Flood Scenario (500-Year with Levees) Table 4-6. Illustrated Guide to the Organization of the Comprehensive Essential Facility Priority Table 4-7. Total Losses Based on HAZUS Default Data Table 4-8. Essential Facility Ranking Based on HAZUS Default Data Table 4-9. Summary of HAZUS MH Estimated Impacts for Honolulu Due to a M6.8 Scenario Earthquake in the Lanai Seismic Source Area Table Honolulu Essential Facility Loss Estimates M6.8 Lanai Scenario Earthquake Table Estimated Impacts on Oahu Fire Stations in a M6.8 Lanai Earthquake Scenario Table Estimated Impacts on Oahu Schools and University of Hawaii at Manoa In a M6.8 Lanai Earthquake Scenario Table Estimated Impacts on Oahu Hospitals in a M6.8 Lanai Earthquake Scenario Table Summary of HAZUS MH Estimated Impacts for Honolulu Due to a Category 2 Scenario Landfalling Hurricane Table Honolulu Essential Facility Loss Estimates Category 2 Scenario Hurricane Table Estimated Impacts on Oahu Fire Stations in Category 2 Hurricane Scenario Table Estimated Impacts on Oahu Schools and University of Hawaii at Manoa In a Category 2 Hurricane Scenario Table Estimated Impacts on Oahu Hospitals in a Category 2 Hurricane Scenario Table Summary of HAZUS MH Estimated Impacts for Honolulu County Due to a 100-Year Flood (Levees Intact) Table Honolulu County Essential Facility Loss Estimates 100-Year Flood (Levees Intact) xiv

15 Table Estimated Impacts On Honolulu County Fire Stations in a 100-Year Flood (Levees Intact) Table Estimated Impacts On Honolulu County EOCs in a 100-Year Flood (Levees Intact) Table Estimated Impacts On Honolulu County Police Facilities in a 100-Year Flood (Levees Intact) Table Estimated Impacts on Honolulu School Districts in a 100-Year Flood (Levees Intact) Table Estimated Impacts on Honolulu County Hospitals in a 100-Year Flood (Levees Intact) Table Summary of HAZUS Estimated Impacts for Honolulu County due to a 100-YearFlood without Levees Table Honolulu County Essential Facility Loss Estimates, 100-Year Flood Without Levees Table Estimated Impacts on Honolulu County Fire Stations in a 100-Year Flood Without Levees Table Estimated Impacts on Honolulu County EOCs in a 100-Year Flood Without Levees Table Estimated Impacts on Honolulu County Police Facilities in a 100-Year Flood without Levees Table Estimated Impacts on Honolulu School Districts in a 100-Year Flood Without Levees Table Estimated Impacts on Honolulu County Hospitals in a 100-Year Flood Without Levees Table Summary of HAZUS Estimated Impacts for Honolulu County due to a 500-Year Flood (Levees Intact) Table Honolulu County Essential Facility Loss Estimates-500-Year Flood (Levees Intact) Table Estimated Impacts on Honolulu County Fire Stations in a 500-Year Flood (Levees Intact) Table Estimated Impacts on Honolulu County EOCs in a 500-Year Flood (Levees Intact) Table Estimated Impacts on Honolulu County Police Facilities in a 500-Year Flood (Levees Intact) Table Estimated Impacts on Honolulu School Districts in a 500-Year Flood (Levees Intact) Table Estimated Impacts on Honolulu County Hospitals in a 500-Year Flood (Levees Intact) Table Total Losses Based On Updated HAZUS Essential Facility Data Table Summarized Vulnerability List Of Highest Risk Facilities By Hazard Table Essential Facility Risk Ranking Based On Enhanced Dataset for Hurricane and Earthquake Table Essential Facility Risk Ranking Based on Enhanced Dataset for Flood xv

16 1 Introduction 1.1 Project Overview The City and County of Honolulu consists primarily of the Island of Oahu but also includes the Northwest Hawaiian Islands, with the exception of Midway Atoll, which is administered by the U.S. Fish and Wildlife Service. Consequently this planning document focuses on the Island of Oahu. Oahu s resident population is approximately 952,640 accounting for about 70% of the state s population of 1.3 million. The damage to and destruction of the built environment caused by natural disasters, particularly to public infrastructure, often represents enormous economic, social, and general functional costs to a community, while also impeding emergency response and recovery activities. Essential facilities include facilities that provide emergency services to the community, i.e. police and fire stations, hospitals, the emergency operations center, and shelters (primarily school buildings), and other facilities providing services to the public that are necessary to preserve public welfare. Essential facilities are the assets for which loss would have the greatest impact during a hazard event. These may be temporarily disrupted during disaster, but would have priority for initial recovery efforts. The Multi-Hazard Pre-Disaster Hazard Mitigation Plan of the City & County of Honolulu recently undertook an overall economic risk analysis based on historical and probabilistic natural hazards. Using Average Annualized Loss as an objective measure of future losses averaged on an annual basis, the severity of the major natural hazards of severe wind events, earthquake, and flood were found to be significant threats. Thus, understanding the potential impacts of severe wind events, earthquakes, and floods on the county s essential facilities and the populace is an important element of good hazard mitigation planning. To support this understanding, the Federal Emergency Management Agency (FEMA) sponsored this project to perform a risk assessment of essential facilities using its HAZUS MH (HAZards U.S., Multi-Hazard) software. Default data provided with the HAZUS MH software allows a user to run a simplified or Level 1 analysis without collecting additional data. In many cases, however, the quality of default national data delivered with the software is less than optimal; it may originate from agencies other than FEMA, or was collected for applications other than loss estimation.. HAZUS MH produces estimates of damage to regional building stocks, lifelines and essential facilities, economic loss, and social impacts. Local, state and federal government officials use HAZUS MH for mitigation, emergency response, and recovery planning. Default data built into HAZUS MH MR3 includes regional building inventory databases representing building stock conditions in the year 2006, proxied from 2000 census data (e.g., square footage of residential structures is estimated from census data on housing unit counts) and commercially-available data on employment and businesses. These data are aggregated data, i.e., the database tabulates attributes such as the total building square footage and dollar exposure by census block (flood) or tract (earthquake), rather than on a building-by-building basis. In contrast to the general building stock, HAZUS MH estimates damage and functionality of essential facilities as well as transportation and utility lifelines, on a building or facility specific 1

17 basis. In addition to developing enhanced regional building inventory data, the Honolulu study also generated significantly improved data sets for essential facilities, required for emergency response, community resilience and rapid recovery. Accordingly, the accuracy of HAZUS MH results was greatly improved with the input of various user supplied data on either the hazard or the affected assets or both. Such an enhanced analysis is usually referred to as a Level 2 analysis Within HAZUS MH, Essential Facilities include hospitals, fire stations, police stations, emergency operations centers (EOCs), and schools, including both grade schools and colleges and universities. These improved HAZUS MH -compatible inventory databases have been provided for future use in additional HAZUS MH risk assessments, on-going maintenance, and further enhancement. The goal of this project is to: A. Gather and interpret information for Honolulu essential facilities (police, fire, EOC s, hospitals, University of Hawaii essential facilities, and school emergency shelter buildings). B. Model earthquake, wind, and flood scenarios appropriate with hazard probabilities for the island of Oahu. C. Utilize the specific building data in HAZUS-MH (MR-3) to produce improved loss estimate results for earthquakes, wind, and floods in order to develop risk and vulnerability assessments and priorities for Honolulu Essential Facilities. 1.2 Analysis Approach The Honolulu Essential Facilities Risk Assessment (HEFRA) Study examined the risks to the county s essential facilities and general building stock from earthquakes, hurricane, and floods impacting the county. The project involved eleven tasks, which are listed below, along with a reference to the relevant section in this report.. 1. Community Participation (Section 1.3) 2. Essential Facilities Data Collection (Section 2.3) 3. Essential Facilities Data Processing / HAZUS MH Compatible-Database (Section 2) 4. Earthquake Hazard Scenario Selection (Section 3.1) 5. Earthquake Risk Assessment (Section 4.2) 6. Wind hazard Scenario Selection (Section 3.2) 7. Wind Risk Assessment (Section 4.2) 8. Flood Hazard Data Collection (Section 2) 9. Flood Hazard Data Processing (Section 2) 10. Flood Risk Assessment (Section 4.2) 11. Risk Assessment Report 1.3 Community Participation The City & County of Honolulu Department of Emergency Management and State of Hawaii Civil Defense assisted the project team by identifying data sources and data providers, facilitating data requests, and providing raw data primarily from State of Hawaii inventory lists. 2

18 To ensure that the HEFRA study products would be useful to the user communities, and to facilitate data collection and outreach, a Community Executive Committee (CEC) was initially recommended. Participants from State, County, and City agencies, as well as regional essential services providers (e.g., hospitals, school districts) were invited to participate. The City and County of Honolulu declined to participate because it preferred the community to take a leading role. 1.4 Overview of Honolulu Natural Hazards Detailed information is given in these sections on previous occurrences of natural hazard events and available analysis of probabilities of future events. A very brief synopsis of each follows, taken from the Multi-Hazard Pre-Disaster Hazard Mitigation Plan for the City & County of Honolulu (2010): The Multi-Hazard Pre-Disaster Hazard Mitigation Plan of the City & County of Honolulu recently undertook an overall economic risk analysis based on historical and probabilistic natural hazards. Using Average Annualized Loss as an objective measure of future losses averaged on an annual basis, the severity of the major natural hazards of severe wind events, earthquake, and flood were found to be significant threats Strong Winds High winds from trade winds, which blow 70% of the time, Kona winds 30% of the time, and winds from tropical cyclones and tropical storms passing through Hawaiian waters all affect the island of Oahu. Tradewinds predominate from the northeast and generally range from miles per hour, although occasional extreme events reach miles per hour when the subtropical high pressure cell north of the islands intensifies. Damaging Kona winds have reached velocities of 50 miles per hour for several days on end. Kona storms generally form in the region bounded by 15 o - 35 o N and 175 o E 140 o W and move erratically, though with a slow tendency toward the west. These seasonal winds are typically not severely damaging, although winter storms may produce flooding that periodically rises to the level of a declared disaster. One of the most damaging and potentially catastrophic events that occur in the Hawaii is a tropical cyclone. A tropical cyclone is defined as a large circulating windstorm covering hundreds of miles that forms over warm ocean water. To be officially classified as a hurricane, the sustained wind speeds must exceed 74 miles per hour. Table 1-1 Hurricane Annual Odds of Occurrence by Saffir Simpson Category Incorporating NASA and HHRF Sponsored Research Hurricane Anywhere Sustained Wind 3-sec. Peak Gust Oahu Only Category in Hawaii 1 74 to 94 mph 82 to 108 mph 1 in 25 1 in to 110 mph 108 to 130 mph 1 in 50 1 in or to 155 mph 130 to 191 mph 1 in 75 1 in 400 Any Hurricane Greater than 74 mph Greater than 82 mph 1 in 15 1 in 55 Terrain or topographic amplification of wind speed has been a significant additional contributing factor in the past wind loss experiences of Hawaii. In a NOAA and NASA funded investigation (Peterka 2002; Chock 2008), 1:6000 scale physical models of selected developed portions of Oahu were constructed based on a 10-meter digital elevation model, and tested in a boundary 3

19 layer wind tunnel to determine wind velocity accelerations (or decelerations) for various terrain conditions. Most of the existing residential structures on Oahu are under-designed for high wind, depending on their construction type and topographic location. High expected wind losses on Oahu make tropical cyclones the hazard of greatest risk Earthquakes Earthquakes in the vicinity of Oahu are caused by the long-term accumulation and release of lithospheric flexural stresses generated in the crust and mantle by the weight of the volcanic rock that composes the islands. The deeper mantle earthquakes, at typically 30 to 40 km depth, result from flexural fracture of the underlying lithosphere in long-term geologic response to the load of the island mass. Past examples of such mantle earthquakes include the 1973 M6.2 Honomu (on the northeast coast of the island), the 1938 M7 Maui, and the 1871 M7 Lana i earthquakes and most recently the 2006 M6.7 Kiholo Bay earthquake. Seismic hazard on Oahu was historically underestimated. In the late 1980 s, Oahu was recognized to be in a region of moderate seismic hazard, and building standards were improved in 1990 based on work conducted by members of the Hawaii State Earthquake Advisory Committee of State Civil Defense. The most current seismic design code available is the International Building Code (IBC). These provisions incorporate state of the art seismic hazard mapping of Hawaii developed by the U.S. Geological Survey (USGS) and the Hawaii State Earthquake Advisory Committee. Based on an analysis incorporating soil site factor mapping and Hawaii construction cost data, projected earthquake average annual loss is about $19 million on Oahu. Table 1-2 A Summary of Historic Earthquake Events Felt on Oahu Event Epicenter Richter Magnitude Honolulu Intensity Date Latitude Longitude M Modified Mercalli Intensity Ave Feb Jun Jan Apr Mar Dec 8 Oahu vicinity Dec 5 Molokai-Lanai vicinity Floods Flooding in Hawaii can be frequent and extensive. In the City & County of Honolulu, from about 1915 to 2008, floods caused by rainstorms, tsunamis, and hurricanes have claimed more than 140 lives and inflicted more than $200 million dollars of direct and indirect damage. The cost of damage from significant floods is listed in Table 1-3. This table shows that in recent times there has been a consistent increase in economic impacts of flooding. The major flooding events in Hawaii are caused by storms, storm surge, high surf and tsunamis. Some of the largest rainfall counts and most severe flooding events have occurred in the last several years. 4

20 Table 1-3 Major Floods Affecting Oahu and Associated Damage, Date Lives Lost Location 1998 $ Cause Statewide Cloudburst 11/17/ Statewide $ 1,000,000 Heavy rains Statewide Heavy rains 1/16/ Honolulu $ 500,000 Heavy rains Statewide Heavy rains Statewide Heavy rains Statewide Heavy rains Statewide Heavy rains ll/3/ Kalihi, Moanalua, Halawa valleys, Oahu Heavy rains Statewide Rainstorm 2/27/ Oahu $ 1,000,000 Severe rainstorm Statewide Severe rainstorm 1/4-5/ Hawaii, Maui, Oahu $ 2,200,000 High seas l/23-26/ Hawaii, Maui, Oahu $ 250,000 Strong winds and rainstorm 1/15-17/ Kauai, Oahu $ 550,000 Intense Kona storm 3/26-27/ Oahu $ 1,303,000 Heavy rains and strong winds 1/21/ Oahu $ 500,000 Heavy rains and strong winds 11/27-28/1954 Kauai, Oahu $ 810,000 Heavy rains 12/19-21/ Statewide Kona storm 1/24-25/ Wailua, Kauai, Oahu, Hawaii $ 700,000 Heavy rains 2/25/1956 Sunset Beach, Oahu $ 250,000 Flash flood 2/7/ Honolulu, Waimanalo, Aina Haina, Oahu $ 400,000 Flash flood 12/1/1957 Kauai, Oahu, Maui,Hawaii $ 1,056,000 Hurricane Della total damage 3/5/1958 Oahu $ 500,000 Heavy rain 8/6-7/ Oahu, Maui, Hawaii $ 552,000 Heavy rain, strong wind, high seas 1/17-18/1959 Oahu, Molokai, Maui, Hawaii $ 1,393,000 Heavy rain, strong wind, high seas 8/4/ Kauai, Oahu, Maui, Hawaii $ 11,524,000 Hurricane Dot total damage 5/12-13/1960 Oahu, Maui $ 250,000 Kona storm 10/27/ Oahu, Maui, Hawaii $ 2,045,731 Heavy rain, strong wind, high seas 11/15-17/ Statewide $ 790,000 Heavy rains, strong winds 5/14/1963 Pearl City, Oahu $ 300,000 Heavy rains 12/19-23/ Statewide $ 439,000 Heavy rains, strong winds, high seas 2/4/ Oahu, Molokai, Maui $ 593,000 Heavy rains 5/3/l965 Kahaluu, Oahu $ 711,300 Heavy rains 11/10-15/ Oahu $ 500,000 Heavy rains, strong winds Statewide Heavy rains 12/17-18/ Kauai, Oahu $ 1,355,000 Heavy rain, high seas, tornado 1/5/1968 Pearl City, Oahu $ 1,243,000 Heavy rains 2/1/1969 Keapuka, Oahu $ 705,100 Heavy rains 4/19/ Kauai, Oahu, Maui $ 3,868,300 Heavy rains l/3o-2/l/l975 Kauai, Oahu $ 566,000 Heavy rains 2/5-7/1976 Oahu $ 802,000 Heavy rain, high seas, strong winds 1/6-7/ Oahu $ 270,000 Heavy rain and strong wind Statewide Rainstorm 1/6-14/1980 Statewide $ 42,578,000 Heavy rains, high seas, strong winds 10/28/1981 Walawa Stream, Oahu $ 786,350 Heavy rains 11/23/ Statewide $ 307,859,000 Hurricane Iwa total damage 12/31/1987-1/1/1988 Oahu $ 35,000,000 Heavy rains 7/21-23/1993 Statewide Heavy rains, remnants of hurricane 8/3-4/2004 Statewide Heavy rains, remnants of hurricane 10/30/2004 Manoa, Oahu $ 85,000,000 Heavy rains, Manoa Stream overflow 2/19-4/2/2006 Statewide $ 50,000,000 Sustained rainfall, Kauai dam break 12/4-11/2007 Statewide $ 3,400,000 Heavy rains, high winds 5

21 1.5 Assessment of Relative Risks of Multiple Hazards Risk is defined as the potential losses associated with a hazard, defined in terms of expected annual loss, resulting from the probability of occurrence, severity, asset exposure and vulnerability, and consequences. Total losses linked directly to a hazard event include all damages, deaths and injuries, loss of habitation, shelter demand and employment losses due to the closure of damaged facilities. This includes physical destruction of buildings, transportation and utility systems, crops, and natural resources and employment losses due directly to the closure of damaged facilities, including the cost of post-disaster cleanup. Unquantifiable losses include environmental consequences, non-financial losses such as loss of historical resources, and psychological-social effects suffered by persons involved in a disaster. In this report, when loss figures are presented they include losses attributed to property damage only, which includes buildings, contents, and inventory. There is a method for objectively evaluating economic risks associated with specific hazards. Average Annualized Loss (AAL) is an objective measure of future losses averaged on an annual basis, calculated as the sum of the expected loss for each event (i.e., sum of the products of the estimated loss from each event and that event s rate of occurrence). In cases where there is insufficient confidence in the probability estimates of rare events and where sufficient past data is available, the average annualized loss is based on annualized historical losses. This information is used in assessing the relative contributors to total natural hazard losses and determining the priorities for hazard mitigation measures. Formula Expression: AAL = Li x Pi Li = Estimated Loss for Event i Pi = Annual Probability of Event I Table 1-4 Hazard Severity to the City and County of Honolulu Based on Average Annual Loss Estimates (Honolulu Hazard Mitigation Plan, 2010) Winds $216 Million / Year Earthquakes Floods $21 Million / Year $13 Million / Year Thus, understanding the potential impacts of severe wind events, earthquakes, and floods on the county s essential facilities and the populace is an important element of good hazard mitigation planning. To support this understanding, the Federal Emergency Management Agency (FEMA) sponsored this project to perform a risk assessment of essential facilities using its HAZUS MH (HAZards U.S., Multi-Hazard) software. A May 2009 pilot project for California, the Orange County Essential Facilities Risk Assessment (OCEFRA), served as a guideline methodology for implementing updated essential facility data in the HAZUS MH program in order to perform this improved risk assessment. 6

22 1.6 Default HAZUS MH Data The default Essential Facilities dataset of 291 buildings included: 3 Fire Department Administrative Building Locations but no fire stations 11 Police Stations and 6 other support and administrative facilities, but no individual building information The Emergency Operations Center of State Civil Defense and the EOC of the City, plus the administrative site of the City Emergency Services Department, but no individual building information 14 Hospital Sites but no individual building information 253 Public and Private School campuses, but no individual building information 1.7 Upgrade of the Essential Facility Inventory Data for Use in HAZUS MH This task consisted primarily of implementing county dataset improvements, Hawaii construction costs, design vintage, specific building type, and facility information parameters relevant to HAZUS MH. A summary of the Data Sources utilized to enhance the default HAZUS MH inventories for this study include: City & County of Honolulu Inventory of Police, Fire, and Emergency Operations facilities (2008) State of Hawaii Inventory of Hospitals (2008) State of Hawaii Department of Education Property Listing Inventory (2006) This property listing was of all DOE buildings. The State Civil Defense master of list of emergency shelters was used to select only those qualifying as essential facilities (i.e., shelters) State Civil Defense master of list of emergency shelters (2007) State of Hawaii Department of Accounting and General Services property inventory schedule 2007 University of Hawaii System-Wide Hazard Mitigation Plan 2008 RLB Quarterly Construction Cost Reports (2009) Multi-Hazard Pre-Disaster Hazard Mitigation Plan of the City & County of Honolulu (2010) Enhanced Data for Essential Facility Buildings For the schools data set only public school buildings designated as storm shelters and 57 core buildings on the UH Manoa Campus were included in the essential facilities list. Each known building of each hospital and medical care facility was included in the health care facilities data set. The police and fire station data sets contain all known stations as does the emergency response center data set. The most accurate geo-coordinates of each facility was selected by comparing its location given within the default HAZUS MH database, data from the City and County of Honolulu 2010Hazard Mitigation plan, and aerial earth imagery. 7

23 1.7.2 Essential Facility Data of buildings has been assembled for: 43 Fire Stations 14 Police Stations 7 Emergency Operations Center facility sites of the State and County 80 Hospital Buildings 784 Public School Buildings including those identified by the State Civil Defense for use as emergency shelters 57 essential buildings of the University of Hawaii at Manoa Essential Facilities Data was reviewed and incorporated: Data was extracted, interpreted and corrected as necessary, and the representative information databases were used as input into a customized HAZUS MH region for the island of Oahu. The model now includes approximately three times as many essential facilities than did the default data, and includes individual buildings, rather than just the sites of essential facilities. 1.8 Risk Assessment Analysis of HAZUS MH Modeled Inventory Analysis was performed using the HAZUS MH model with the default data and then with the customized data parameters. Hurricane Scenario Preparation involved the specification and documentation of a tropical cyclone track data scenario appropriate for HAZUS MH analysis of the City and County of Honolulu, representing 500-year recurrence interval events. This scenario was provided by the Central Pacific Hurricane Center. Earthquake Scenario Preparation: For loss estimation and building vulnerability ranking a magnitude 6.8 earthquake scenario with an epicenter near the Island of Lanai was analyzed within the HAZUS MH model. This scenario was developed with the assistance of Dr. Paul Okubo of the USGS Hawaii Volcano Observatory. Shake maps prepared by Dr. David Wald of USGS for peak ground acceleration, velocity, and spectral accelerations were imported into the model for this study. This is a deep lithospheric earthquake with a similar seismogenic mechanism as the Kiholo Bay earthquake, i.e., plate flexural failure. Maximum peak ground accelerations on Oahu were about 12% gravity at the southeastern most point of the island, with values elsewhere of between 2% to 10%. Flood Scenario Preparation: The risk assessment on the City and County of Honolulu examined the impacts of three different floods on essential facilities and general building stock in the county a 100-year flood with the existing certified levee system in the county intact, a 100-year flood without consideration of these levees, and a 500-year (0.2% chance per year) flood. Depth grids, derived from DFIRMs, for all three scenarios were imported into HAZUS MH model for analysis. 8

24 2 Upgrade of the Essential Facility Inventory Data for Use in HAZUS-MH MR Default HAZUS MH Data The default Essential Facilities dataset of 291 buildings included: 3 Fire Department Administrative Building Locations but no fire stations 11 Police Stations and 6 other support and administrative facilities, but no individual building information The Emergency Operations Center of State Civil Defense and the EOC of the City, plus the administrative site of the City Emergency Services Department, but no individual building information 14 Hospital Sites but no individual building information 253 Public and Private School campuses, but no individual building information 2.2 General Building Stock Table 2-1 presents the building exposure statistics by occupancy for the Island of Oahu. Note that this is the default data provided by the HAZUS MH software, and more accurate statistics could be developed by analysis of the tax appraisers records. Population statistics for communities on Oahu are given in Appendix G, Table G-1. Table 2-1 Default General Building Stock Inventory Exposure for Oahu Occupancy Exposure ($1000) Percent of Total Residential 65,267, % Commercial 10,628, % Industrial 1,318, % Agricultural 281, % Religious 885, % Government 578, % Education 756, % Total 79,716, % 2.3 Essential Facilities Data Collection The specific information required by HAZUS MH to characterize essential facilities for earthquake and flood analysis is described in detail in the HAZUS MH MR3 Earthquake Model, Wind Module, and Flood Model Technical Manuals. The general approach for essential facilities data collection entailed the following basic steps. 1. Review the HAZUS MH default essential facilities data. 2. Acquiring available GIS data from participating state or county agencies. 3. Generating a data collection spreadsheet (and ArcGIS geodatabase) containing available data. 9

25 4. Providing the data collection spreadsheet and instructions to participating county and city agencies and representatives. Facility-specific data requested includes facility location (if not already included), capacity (e.g. number of fire engines or student enrollment), and available construction data, such as structural type, foundation type, year built, number of stories, square footage, and replacement values. The Data Sources utilized to enhance the default HAZUS MH inventories for this study include: City & County of Honolulu Inventory of Police, Fire, and Emergency Operations facilities (2008) State of Hawaii Inventory of Hospitals (2008) State of Hawaii Department of Education Property Listing Inventory (2006) State of Hawaii Department of Accounting and General Services property inventory schedule 2007 University of Hawaii System-Wide Hazard Mitigation Plan 2008 RLB Quarterly Construction Cost Reports (2009) Multi-Hazard Pre-Disaster Hazard Mitigation Plan of the City & County of Honolulu (2010) Data processing to develop the enhanced building inventory to include HAZUS MH building parameters specific for Honolulu is summarized by essential facility type in the following sections. 2.4 Correcting Coordinate System Errors and Determining/Validating Essential Facility Building Geocoding We found that the HAZUS MH default datasets had projection errors relative to the use of imported Old Hawaii projected data registered instead to the HAZUS default assignment of NAD83. As a result all HAZUS MH features class projections (DVD data) were redefined from NAD83 to Old Hawaii and then re-projected to NAD83. Hawaii features in systate, sytract, and sycounty, inside syboundary dataset, were re-projected as well. The projection of Hawaii features for the following shape files and features classes under the HAZUS-MH program Data folder were also corrected (Table 2-2). (These projection corrections were made permanent in HAZUS MH with the release of the new MR-4 version.) Table 2-2 Feature Classes and Locations of HAZUS MH Program Files Requiring Coordinate System Corrections Workspace Feature Class/ Shape File Module C:\Program Files\HAZUS-MH\DATA\EQ\USGS.mdb\USGS USGS EQ C:\Program Files\HAZUS-MH\DATA\HU hustates.shp hucounties.shp HU C:\Program Files\HAZUS- MH\DATA\FL\Hydro\FlAnCoastInput.mdb Shoreline TIGER_Land For the schools data set, only public school buildings designated as tropical cyclone shelters and 57 core buildings on the University of Hawaii-Manoa campus were included in the essential facilities list. Each known building of each hospital and medical care facility was included in the FL 10

26 health care facilities data set. The police and fire station data sets contain all known stations as does the emergency response center data set. The most accurate geo-coordinates of each facility was selected by comparing its location given within the default HAZUS MH database, data from the City and County of Honolulu 2010 Hazard Mitigation plan, and aerial earth imagery. 2.5 Building Construction Classification and Replacement Values Information was provided in the current databases regarding the actual construction types of the modeled essential facilities. For approximately half of the facilities some indication of the construction material was given, while for the remaining facilities this information was based on judgment of the type of construction typical in Hawaii for the facility being considered based on historical practices. Specific building types were determined based upon typical Hawaii design practice the general construction type, number of stories, and type of facility. The gross floor area of the facilities was given for some buildings. The area of the buildings lacking this information was assumed to be a default value typical to the facility type in Hawaii as shown in Table 2-3. However if the building area was unknown and a building value was provided it was assumed that this replacement value was correct, rather than a replacement value upon an assumed area. Table 2-3 Occupancy Class Floor Areas (Default and Hawaii Typical Floor Areas) Occupancy Class HAZUS MH Default (ft 2 ) Hawaii (ft 2 ) RES1 Single family dwelling 1,500 1,250 RES2 Single-wall construction 1,000 1,000 RES3 Multi-family dwelling 16,000 21,750 RES4 Temporary lodging 50,000 15,250 RES5 Institutional dormitory 30,000 5,500 RES6 Nursing Home 45,000 19,500 COM1 Retail Trade 14,000 12,250 COM2 Wholesale Trade 35,000 9,750 COM3 Personal and Repair Services 12,000 3,250 COM4 Professional/Technical Services 35,000 5,500 COM5 Banks/Financial Institutions 22,000 7,500 COM6 Hospital 95,000 12,750 COM7 Medical Office/Clinic 12,000 6,500 COM8 Entertainment and Recreation 13,000 5,750 COM9 Theaters 17,000 10,750 COM10 Parking 9,000 27,000 IND1 Heavy Industrial 50,000 11,500 IND2 Light Industrial 20,000 3,750 IND3 Food/Drugs/Chemical 21,000 10,000 IND4 Metals/Minerals/Processing 16,000 n/a IND5 High Technology 17,000 n/a IND6 Construction 19,000 n/a AGR Agriculture 14,000 5,000 REL1 Church/Membership Organization 15,000 3,750 GOV1 General Services 25,000 3,000 GOV2 Emergency Response 10,000 1,750 EDU1 Schools/Libraries 20,000 5,000 EDU2 Colleges / Universities 25,000 25,000 11

27 Building replacement costs were determined using a fill in value appropriate for the State of Hawaii based on the square footage in most cases. These replacement costs were derived from past studies for Hawaii and Maui Counties and the University of Hawaii. Typical Hawaii replacement values used are in the range of $175/ft 2 for wood construction and $300/ft 2 for all other construction types and are comparable to the City of San Francisco. Table 2-4 Building Replacement Value Occupancy HAZUS Default Building Value ($/SF) Hawaii Building Value ($/SF) RES1 $ $ RES2 $ $ RES3A $ $ RES3B $ $ RES3C $ $ RES3D $ $ RES3E $ $ RES3F $ $ RES4 $ $ RES5 $ $ RES6 $ $ COM1 $ $ COM2 $ $ COM3 $ $ COM4 $ $ COM5 $ $ COM6 $ $ COM7 $ $ COM8 $ $ COM9 $ $ COM10 $ $ IND1 $ $ IND2 $ $ IND3 $ $ IND4 $ $ IND5 $ $ IND6 $ $ AGR1 $ $ REL1 $ $ GOV1 $ $ GOV2 $ $ EDU1 $ $ EDU2 $ $

28 2.6 General and Specific Building Types General Building Types are common amongst the three HAZUS modules. Table 2-5 HAZUS MH General Building Types General Building Type Description Wood Wood frame construction Masonry Reinforced or unreinforced masonry construction Steel Steel frame construction Concrete Cast-in-place or pre-cast reinforced concrete construction Manufactured Homes Factory-built residential construction However, in order to capture the specific vulnerability factors appropriate for each hazard, the Specific Building Types are classified differently in each of the three HAZUS modules (Earthquake, Hurricane, and Flood). Using the General Building Types (GBTs) in Table 2-5 as a point of departure, additional hazard-specific attributes have been added to the building classification scheme to provide a richer level of construction detail that is needed to accurately estimate damage and losses. Thus, each property needed to be classified for each hazardspecific prototype of structural system Specific Building Types for the HAZUS MH Earthquake Module The basic definitions for the building types utilized by the HAZUS MH earthquake module in representing the building inventory are: W1: Wood Light Frames W1A: Multi-Story, Multi-Unit Residential Wood Frames W2: Wood Frames, Commercial and Industrial S1: Steel Moment Frames with Stiff Diaphragms S1A: Steel Moment Frames with Flexible Diaphragms S2: Steel Braced Frames with Stiff Diaphragms S2A: Steel Braced Frames with Flexible Diaphragms S3: Steel Light Frames S4: Steel Frames with Concrete Shear Walls S5: Steel Frames with Infill Masonry Shear Walls and Stiff Diaphragms S5A: Steel Frames with Infill Masonry Shear Walls and Flexible Diaphragms C1: Concrete Moment Frames C2: Concrete Shear Wall Buildings with Stiff Diaphragms C2A: Concrete Shear Wall Buildings with Flexible Diaphragms C3: Concrete Frames with Infill Masonry Shear Walls and Stiff Diaphragms C3A: Concrete Frames with Infill Masonry Shear Walls and Flexible Diaphragms PC1: Precast/Tilt-up Concrete Shear Wall Buildings with Flexible Diaphragms PC1A: Precast/Tilt-up Concrete Shear Wall Buildings with Stiff Diaphragms PC2: Precast Concrete Frames with Shear Walls PC2A: Precast Concrete Frames without Shear Walls 13

29 RM1: RM2: URMA: Reinforced Masonry Bearing Wall Buildings with Flexible Diaphragms Reinforced Masonry Bearing Wall Buildings with Stiff Diaphragms Unreinforced Masonry Bearing Wall Buildings with Stiff Diaphragms Honolulu Seismic Design Levels Vulnerability within each building type can also vary in accordance with the key code provision dates applicable to structural system design: Table 2-6. FEMA 310 Benchmark UBC Building Dates Building Seismic Design Provisions Building Type 1 UBC Wood Frame, Wood Shear Panels(TypeW1&W2) 1976 Wood Frame, Wood Shear Panels (Type W1A) 1976 Steel Moment Resisting Frame (Type Sl & SlA) Steel Braced Frame (Type S2 & S2A) 1988 Light Metal Frame (Type S3) * Steel Frame w/ Concrete Shear Walls (Type S4) 1976 Reinforced Concrete Moment Resisting Frame (Type C1) 1976 Reinforced Concrete Shear Walls(TypeC2& C2A) 1976 Steel Frame with URM Infill (Type S5, S5A) * Concrete Frame with URM Infill (Type C3 & C3A) * Tilt-up Concrete (Type PC1 & PCIA) 1997 Precast Concrete Frame (Type PC2 & PC2A) * Reinforced Masonry (Type RM1) 1997 Reinforced Masonry (Type RM2) 1976 Unreinforced Masonry (Type URM) Unreinforced Masonry (Type URMA) * 1 Building Type refers to one of the Common Building Types defined in FEMA Steel Moment-Resisting Frames shall comply with the 1994 UBC Emergency Provisions. 3 Refers to the UCBC Section of the UBC. * No benchmark year UBC - International Conference of Building Officials, Uniform Building Code. Note that the seismic hazard was under-estimated in the code until the 1990 adoption of a local amendment for Zone 2A. The reference for the historic criteria used for seismic design of buildings is A Brief History of Seismic Zonation for the Hawaiian Islands, by the Hawaii State Earthquake Advisory Committee (HSEAC, 1991), from State Civil Defense. 14

30 Table 2-7. Historic Seismic Force Comparisons for Oahu (100% = Current USGS & International Building Code Seismic Hazard on Rock Sites) Approximate Height CODE 25 ft. 75 ft. 180 ft Structural Period (seconds) Pre-1973 UBC 41% 38% - 51% 43% - 71% 1973 UBC 41% 51% 71% FEMA 310 Benchmark Cutoff UBC 43% - 51% 57% - 85% 72% - 107% Oahu Zone Change to 2A UBC 99% 120% - 165% 133% - 200% 1997 UBC 90% - 132% 120% - 219% 106% - 226% 1998 Hawaii State Seismic Hazard Mapping by USGS/HSEAC IBC 100% - 130% 100% -210% 100% -186% The seismic design level was accordingly determined based on the year built and building code adoption dates on the Island of Oahu. Table 2-8. Seismic Design Level Per UBC Code Vintage Effective Date Code Seismic Zonation July 1, 1956 UBC November 25, 1959 UBC March 20, 1964 UBC (UBC-61 continued) UBC January 1, 1969 UBC December 23, 1971 UBC May 5, 1975 UBC January 1, 1978 UBC December 5, 1980 UBC September 17, 1984 UBC March 1, 1987 UBC October 1, 1990 UBC A January 12, 1994 UBC A August 14, 1997 UBC A June 28, 2000 UBC A June 20, 2007 IBC 2003 Probabilistic map values of S s and S 1 HAZUS Design Levels for Typical Buildings PC PC PC PC PC PC PC LC LC LC LC LS LS LS LS LS 15

31 For all buildings with a known year of construction the following rules applied: For typical building types Pre-Seismic Code: (Before 1978) PC Low Seismic Code: ( ) LC Low Special Seismic Code (1991 present) LS Exceptions: Unreinforced Masonry Structures: Use for URML and URMM Pre-Seismic Code: (all years) PC Steel Moment Frame: Use for S1L, S1M, and S1H Benchmark year = 1994 UBC (Code adopted August of 1997) Pre-Seismic Code: (Up to1997) PC Low Special Seismic Code (1998 present) LS Steel Braced Frame: Use for S2L, S2M, and S2H Benchmark year = 1988 UBC (Code adopted October 1990) Pre-Seismic Code: (Up to1990) PC Low Special Seismic Code (1991 present) LS Reinforced Masonry Structures: Use for RM1L, RM1M Benchmark year = 1997 (Code adopted June of 2000) Pre-Seismic Code: (Up to 2000) PC Low Special Seismic Code: (2001- present) LS Tilt-Up Concrete Construction: Use for PC1 structures Benchmark year = 1997 (Code adopted June of 2000) Pre-Seismic Code: (Up to 2000) PC Low Special Seismic Code: (2001- present) LS However, State Government buildings would have been required to comply with DAGS DPW Directive for Seismic Zone 3 Structural Design, Calendar Years of Design Accordingly, as an exception, state buildings designed during that policy timeframe were assigned a Design Level of High Code. For buildings lacking the construction date, the design level was assumed to be pre-code (PC), or low-code (LC) if some background knowledge of the building indicated a slightly higher design level. 16

32 2.6.3 Specific Building Types for the HAZUS MH Hurricane Module Table 2-9. Specific Building Types in the HAZUS MH Hurricane Model Descriptions of HAZUS MH Hurricane Model Building Types Wood, Single Family, One Story (WSF1) The WSF1 model building is a wood-framed, single-story, single-family house. See Section 6.4 of the Technical Manual for a detailed description of the building geometry and the component resistance values. 17

33 Wood, Single Family, Two or More Stories (WSF2) The WSF2 model building is a wood-framed, two-story, single-family house. See Section 6.4 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Wood, Multi-Unit Housing, One Story (WMUH1) The WMUH1 model building is a wood-framed, single-story, marginally engineered or nonengineered, multi-family dwelling or hotel/motel. See Section 6.9 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Wood, Multi-Unit Housing, Two Stories (WMUH2) The WMUH2 model building is a wood-framed, two-story, marginally engineered or nonengineered, multi-family dwelling or hotel/motel. See Section 6.9 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Wood, Multi-Unit Housing, Three or More Stories (WMUH3) The WMUH3 model building is a wood-framed, three-story, marginally engineered or nonengineered, multi-family dwelling or hotel/motel. See Section 6.9 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Single Family, One Story (MSF1) The MSF1 model building is a masonry wall, single-story, single-family house. The masonry walls can be either reinforced or unreinforced. See Section 6.4 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Single Family, Two or More Stories (MSF2) The MSF2 model building is a masonry wall, two-story, single-family house. The masonry walls can be either reinforced or unreinforced. See Section 6.4 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Multi-Unit Housing, One Story (MMUH1) The MMUH1 model building is a masonry wall, single-story, marginally engineered or nonengineered, multi-family dwelling or hotel/motel. The masonry walls can be either reinforced or unreinforced. See Section 6.9 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Multi-Unit Housing, Two Stories (MMUH2) The MMUH2 model building is a masonry wall, single-story, marginally engineered or nonengineered, multi-family dwelling or hotel/motel. The masonry walls can be either reinforced or unreinforced. See Section 6.9 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Multi-Unit Housing, Three or More Stories (MMUH3) The MMUH3 model building is a masonry wall, single-story, marginally engineered or nonengineered, multi-family dwelling or hotel/motel. The masonry walls can be either reinforced or unreinforced. See Section 6.9 of the Technical Manual for a detailed description of the building geometry and the component resistance values. 18

34 Masonry, Low-Rise Strip Mall, Up to 15 Feet (MLRM1) The MLRM1 model building is a masonry wall, low-rise strip mall building, up to 15 feet in height. The masonry walls can be either reinforced or unreinforced. See Section 6.10 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Low-Rise Strip Mall, More than 15 Feet (MLRM2) The MLRM2 model building is a masonry wall, low-rise strip mall building, more than 15 feet in height. The masonry walls can be either reinforced or unreinforced. See Section 6.10 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Low-Rise Industrial/Warehouse/Factory Buildings (MLRI) The MLRI model building is a 240,000 square foot, masonry wall, industrial building or warehouse. The masonry walls can be either reinforced or unreinforced. See Section 6.13 of the Technical Manual for a detailed description of the building geometry and the component resistance values Masonry, Engineered Residential Building, Low-Rise (MERBL) The MERBL model building is a two-story, engineered, reinforced masonry wall, residential building with a compartmented floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Engineered Residential Building, Mid-Rise (MERBM) The MERBM model building is a five-story, engineered, reinforced masonry wall, residential building with a compartmented floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Engineered Residential Building, High-Rise (MERBH) The MERBH model building is an eight-story, engineered, reinforced masonry wall, residential building with a compartmented floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Engineered Commercial Building, Low-Rise (MECBL) The MERBL model building is a two-story, engineered, reinforced masonry wall, commercial building with an open floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Engineered Commercial Building, Mid-Rise (MECBM) The MERBL model building is a five-story, engineered, reinforced masonry wall, commercial building with an open floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Masonry, Engineered Commercial Building, High-Rise (MECBH) The MERBL model building is an eight-story, engineered, reinforced masonry wall, commercial building with an open floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. 19

35 Concrete, Engineered Residential Building, Low-Rise (CERBL) The CERBL model building is a two-story, engineered, reinforced concrete, residential building with a compartmented floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Concrete, Engineered Residential Building, Mid-Rise (CERBM) The CERBM model building is a five-story, engineered, reinforced concrete, residential building with a compartmented floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Concrete, Engineered Residential Building, High-Rise (CERBH) The CERBH model building is an eight-story, engineered, reinforced concrete, residential building with a compartmented floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Concrete, Engineered Commercial Building, Low-Rise (CECBL) The CERBL model building is a two-story, engineered, reinforced concrete, commercial building with an open floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Concrete, Engineered Commercial Building, Mid-Rise (CECBM) The CERBL model building is a five-story, engineered, reinforced concrete, commercial building with an open floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Concrete, Engineered Commercial Building, High-Rise (CECBH) The CERBL model building is an eight-story, engineered, reinforced concrete, commercial building with an open floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Steel, Pre-Engineered Metal Building, Small (SPMBS) The SPMBS model building is a 4,000 square foot, pre-engineered, steel frame, metal clad building. See Section 6.11 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Steel, Pre-Engineered Metal Building, Medium (SPMBM) The SPMBS model building is a 50,000 square foot, pre-engineered, steel frame, metal clad building. See Section 6.11 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Steel, Pre-Engineered Metal Building, Large (SPMBL) The SPMBS model building is a 500,000 square foot, pre-engineered, steel frame, metal clad building. See Section 6.11 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Steel, Engineered Residential Building, Low-Rise (SERBL) The SERBL model building is a two-story, engineered, steel frame, residential building with a compartmented floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. 20

36 Steel, Engineered Residential Building, Mid-Rise (SERBM) The SERBM model building is a five-story, engineered, steel frame, residential building with a compartmented floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Steel, Engineered Residential Building, High-Rise (SERBH) The SERBH model building is an eight-story, engineered, steel frame, residential building with a compartmented floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Steel, Engineered Commercial Building, Low-Rise (SECBL) The SERBL model building is a two-story, engineered, steel frame, commercial building with an open floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Steel, Engineered Commercial Building, Mid-Rise (SECBM) The SERBM model building is a five-story, engineered, steel frame, commercial building with an open floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Steel, Engineered Commercial Building, High-Rise (SECBH) The SERBH model building is an eight-story, engineered, steel frame, commercial building with an open floor plan. See Section 6.12 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Manufactured Home, Pre-HUD (MHPHUD) The MHPHUD model building is a manufactured home built prior to the 1976 HUD standard. The home can be either tied-down or unrestrained. See Section 6.5 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Manufactured Home, 1976 HUD (MH76HUD) The MHPHUD model building is a manufactured home built to the 1976 HUD standard. The home can be either tied-down or unrestrained. See Section 6.5 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Manufactured Home, 1994 HUD Region I (MH94HUD-I) The MHPHUD model building is a manufactured home built to the 1994 HUD standard for Wind Zone I. The home can be either tied-down or unrestrained. See Section 6.5 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Manufactured Home, 1994 HUD Region II (MH94HUD-II) The MHPHUD model building is a manufactured home built to the 1994 HUD standard for Wind Zone II. The home can be either tied-down or unrestrained. See Section 6.5 of the Technical Manual for a detailed description of the building geometry and the component resistance values. Manufactured Home, 1994 HUD Region III (MH94HUD-III) The MHPHUD model building is a manufactured home built to the 1994 HUD standard for Wind Zone III. The home can be either tied-down or unrestrained. See Section 6.5 of the Technical Manual for a detailed description of the building geometry and the component resistance values. 21

37 2.6.4 Honolulu Wind Design Level Hawaii design wind pressures have changed over the years in the Uniform Building Code (UBC). The UBC wind loadings have historically lagged the ASCE 7 standard with respect to wind hazard. Table Design Wind Pressures Per UBC Code Years UBC Code Years Design Wind Pressure at 10M height 1991 to psf 1982 to psf 1958 to psf The critical benchmark year identifying structures previously designed to an inadequate wind pressure is 1984, the date of Oahu s adoption of the 1982 UBC edition General Building Types for the HAZUS MH Flood Module The Flood Module General Building Types are more simply classified by material of construction and height, so the more detailed earthquake and hurricane SBT Specific Building Type classifications were used to assign the flood module building types. This is because while all the modules use a different building type classification system, all of them at the very least are organized by material of construction (Steel, Concrete, Masonry, Wood) and height. The data has the building construction date, from which the FIRM and Pre-FIRM assignments can be based using the criterion date of 1981 when Honolulu started participating in NFIP (exact date was September 30, 1980) Honolulu Flood Design Level (FIRM or Pre-FIRM) The data has the building construction date, from which the FIRM and Pre-FIRM assignments can be based using the criterion date of 1981 when Honolulu started participating in NFIP (exact date was September 30, 1980). 2.7 Enhanced Honolulu Data for Essential Facility Buildings For the schools data set only public school buildings designated as tropical cyclone shelters and 57 core buildings on the UH Manoa Campus were included in the essential facilities list. Each known building of each hospital and medical care facility was included in the health care facilities data set. The hospital data is now building specific with 80 individual buildings with the earthquake and hurricane relevant characteristics assigned. The default HAZUS data is just for the aggregated facility location. The police and fire station data sets contain all known stations as does the emergency response center data set. The most accurate geo-coordinates of each facility was selected by comparing its location given within the default HAZUS MH database, data from the City and County of Honolulu 2010 Hazard Mitigation plan, and aerial earth imagery. The upgraded dataset of 985 buildings included: 22

38 43 Fire Stations 14 Police Stations 7 Emergency Operations Center facility sites 80 Hospital Buildings 784 Public School Buildings including those used as shelters 57 University of Hawaii at Manoa essential buildings 2.8 Compiled Honolulu Multi-Hazard Essential Facility Inventory Maps indicating the locations of all modeled facilities and tables detailing specific building inventory data are included in Figures 2-1 through 2-5, Table 2.10 and Appendix G, Table G-2 through Table G-7. 23

39 Figure 2-1 Map of police station locations in updated dataset 24

40 Figure 2-2 Map of emergency response facility locations in updated dataset 25

41 Figure 2-3 Map of healthcare facility locations in updated dataset 26

42 Figure 2-4 Map of fire department station locations in updated dataset 27

43 Figure 2-5 Map of school campus locations with emergency shelters in updated dataset 28

44 3 Natural Hazards 3.1 Seismic Hazard Historic Record of Earthquake Intensities Previous lists of earthquakes either restricted to or identifying those felt on Oahu, and the contemporary accounts of those earthquakes comprise a total of 113 natural earthquakes definitely felt on Oahu, the earliest of which occurred in 1859 (Cox, 1986). The Honolulu intensity of each of these earthquakes was estimated from the contemporary descriptions of its effects found in the newspapers and elsewhere using a continuous equivalent of the MM scale chosen so that its values, if rounded to the nearest integer, were identical to those of the conventional discrete-valued scale. The historic earthquake with the generally highest Oahu intensities was found to have been one that occurred on February 19, (Cox, 1985) From the geographic distribution of its effects, its Richter magnitude was estimated at about 7 and its epicenter near the south coast of the island of Lanai. The earthquake with the second highest intensity at Honolulu was found to have been one that occurred on June 28, (Cox, 1986) Although several seismographs were then in operations in Hawaii, neither the magnitude nor the epicenter of the earthquake had been determined from seismographic information. From the geographic distribution of its effects, its Richter magnitude was estimated in the study at only about 4.6, but its epicenter was estimated to have been only a few miles south of Honolulu, where its MMI intensity was estimated at 6. Data pertinent to these two earthquakes and others with Honolulu intensities of V or greater are summarized in Table 3-1 and Figure 6. Table 3-1. Historic Hawaiian Earthquakes With Honolulu Modified Mercalli Intensities of V and Greater Event Epicenter Depth Richter Honolulu Magnitude Intensity Date Latitude Longitude Km M MMI Ave Feb Jun Jan Apr Mar Dec 8 Oahu vicinity Dec 5 Molokai-Lanai vicinity

45 Figure 3-1 shows the epicentral locations for the earthquakes in the record for which such locations have either been determined from seismographic evidence or estimated from the distribution of reported effects. Figure 3-1. Distribution of epicenters of historic earthquakes felt on the Island of Oahu and their Modified Mercalli Intensities on Oahu Documentation on a historic Hawaii earthquake catalog of 1823 to 1959 is given in Klein and Wright, USGS Professional Paper 1623, available at Probabilistic Seismic Hazard For the International Building Code (IBC), two maps are used indicating 2/3 of spectral acceleration ordinates at a 2% exceedance in 50-year probability level within each seismic source zone, capped by a deterministic maximum considered magnitude in each seismic source zone. Due to distance, earthquakes on the Big Island do not govern the maximum considered earthquake affecting the island of Oahu. Table 3-2. Reference to Seismic Maps Used for HAZUS Analysis State-of-the-art Maps used for the International Building Code, the FEMA NEHRP Seismic Provisions for New and Existing Buildings, and ground motion hazard curve basis for the HAZUS Annualized Average Loss analysis Documentation for current hazard maps (Seismic Hazard in Hawaii: High Rate of Large Earthquakes and Probabilistic Ground-Motion Maps, by Fred W. Klein, Arthur D. Frankel, Charles S. Mueller, Robert L. Wesson, and Paul G. Okubo, Bulletin of the Seismological Society of America, Vol. 91, No. 3, pp June, 2001); USGS report 2724 published at 30

46 Table 3-3. Determination of Seismicity Region for Oahu Determination of Region of Moderate Seismicity for Oahu (per FEMA 310) Region of Seismicity 1 S DS S DI Oahu S DS Oahu S DI Low < 0.167g < 0.067g Moderate < 0.500g < 0.200g 0.41 g 0.12 g > 0.167g > 0.067g High > 0.500g > 0.200g The highest region of seismicity defined by S DS or S DI shall govern. where: S DS = 2/3 F a S s = design short-period spectral response acceleration parameter; S DI = 2/3 F v S 1 = design spectral response acceleration parameter at a one second period; F v, F a = site coefficients; S s S 1 = Maximum Considered Earthquake (MCE) short-period spectral response acceleration parameter; = MCE spectral response acceleration parameter at a one second period; The values of S s and S 1 represent an earthquake with a 2% probability of exceedance in 50 years with deterministic-based maximum values near known fault sources. Figure 3-2. Peak Ground Acceleration Hazard Curve (for Honolulu International Airport) 31

47 3.1.3 Earthquake Scenario Analysis For loss estimation and building vulnerability ranking a magnitude 6.8 earthquake scenario with an epicenter near the Island of Lanai was analyzed within the HAZUS MH model. The event is analogous to the 1871 Lanai earthquake discussed previously and is utilized for earthquake planning purposes by State Civil Defense s Hawaii State Earthquake Advisory Committee and the Pacific Disaster Center. This is a deep lithospheric earthquake with a similar seismogenic mechanism as the 2006 Kiholo Bay earthquake, i.e., plate flexural failure, with: Magnitude 6.8, Lat N Long -157 W Depth ~35 km Dip ~4 degrees Equivalent "Rupture" ~35 km Figure 3-3. Lanai 1871 earthquake; comparable in magnitude to the Maximum Considered Earthquake in the Maui seismic source region. Dr. Paul Okubo of the Hawaii Volcano Observatory (USGS) helped develop the refined source location indicated above. Subsequently, shake maps prepared by Dr. David Wald of USGS for peak ground acceleration, velocity, and spectral accelerations were imported into the HAZUS model for this study. Maximum peak ground accelerations on Oahu were about 12% gravity at the southeastern most point of the island, with values elsewhere of between 2% to 10%. 32

48 Figure 3-4. Shakemap of event used for earthquake vulnerability ranking Figure 3-5. HAZUS modeled peak ground accelerations on Oahu for Lani Earthquake scenario 33

49 3.1.4 Soil Condition Modeling Actual ground motion can be significantly increased by softer soil conditions. This would indicate areas of greater potential hazard, and site seismic classification should also be considered in individual building assessments. To determine the most likely seismic site classifications, existing GIS data on soil surveys were used. The SSURGO database consists of digital geo-referenced spatial data, attribute data, and Metadata. Geo-referenced spatial data are spatial objects: polygons, lines, points, and nodes whose coordinates represent reallocations on the Earth s surface in one of several coordinate systems. The data consist of: Soil survey area boundaries Water boundaries Soil boundaries Conventional and special soil features The SSURGO database provides the most detailed level of information. Using NCSS mapping standards, soil type maps in the SSURGO database are made using field methods. Data for each major layer of soil include: particle size distribution soil reaction bulk density salinity available water capacity organic matter Data on each soil include: flooding water table depth depth to bedrock soil subsidence Figure 3-6. Site Classifications for Essential Facilities 34

50 Figure 3-7. Site Classifications for General Building Stock by Census Tract 35

51 3.2 High Winds Historic Record One of the most damaging and potentially deadly wind events that occur in the Hawaii is a tropical cyclone. A tropical cyclone is defined as a large circulating windstorm covering hundreds of miles that forms over warm ocean water. To be officially classified as a hurricane, the sustained wind speeds must exceed 74 miles per hour. The maximum winds in a tropical cyclone occur near the perimeter of a calm eye and diminish with distance from the eye. High winds, marine overwash, storm surge and small scale wind bursts may damage or destroy homes, businesses, public buildings and infrastructure. Termed microbursts and mini-swirls, these localized winds may reach wind speeds in excess of 200 miles per hour. During Hurricane Iniki, damage patterns and debris indicated that there were more than 26 mircobursts (sudden intense downdrafts) and two mini-swirls (a violent whirlwind, not tornado) had occurred on Kauai (Fletcher 1994). In addition to severe winds, tropical cyclones have several other characteristics. Barometric pressure is very low, for example, usually 29 inches of mercury or less. Tropical cyclone winds are directly related to the lowest barometric pressure reading at the center of the storm. Tropical cyclone winds are strongest near the Radius of Maximum Winds, the area within the storm path near the lowest central pressure. The larger the radius, the larger the area of maximum destruction. The strongest winds are usually on the right side of the eye, as one faces the direction the storm is moving. Wind speeds decrease as the distance away from the radius of maximum winds increase. Table 3-4 Significant Hawaiian Tropical Cyclones of the 20 th Century Name Date Damage (1990 Dollars) Deaths Mokapu Cyclone Aug. 19, 1938 Unknown Unknown Hiki Aug. 15, 1950 Unknown Unknown Nina Dec., 2, 1957 $900,000 4 Dot Aug. 6, 1959 $28,000,000 0 Iwa Nov. 23, 1982 $394,000,000 1 Iniki Sept. 11, 1992 $1,800,000,000 4 Nevertheless, not all of storms intersect Hawaii, and actual tropical cyclone strikes on the Hawaiian Islands are relatively rare in the modern record (Schroeder, 1993). More commonly, near misses that generate large swell and moderately high winds causing varying degrees of damage are the hallmark of tropical cyclones passing close to the islands. Impacts from these can be severe and lead to beach erosion, large waves, high winds, and marine overwash despite the fact that the tropical cyclone may have missed the island. Communities on the Waianae coast of Oahu suffered severe damage from tropical cyclones Iwa and Iniki, yet neither of these storms actually hit Oahu. 36

52 3.2.2 Probabilistic Wind Hazard Windspeed hazard curves have been derived by two separate investigations (ARA 2001, CPP 2001), both utilizing Monte Carlo simulations of storm tracking and updated regional windfield models. Due to the rarity of tropical cyclone occurrence at a specific location, the prediction of design wind speeds must frequently be obtained by statistical means, such as a Monte Carlo simulation. These simulations are based on tropical cyclone track statistics in portions of the Eastern and Western Pacific basins, which are used to generate hundreds of thousands of simulated tropical storms and cyclones in these regions. A well-evaluated windfield model is then used to predict the wind speeds at a given location for each storm. The current analysis does not include any potential effects of long-term climatic change, but a simulation could be performed for postulated future conditions. The analysis implicitly includes the historical frequency of ENSO events. The directional probabilities of windspeed are approximately uniform. Figure 3-8. Contours show number of times a tropical cyclone (intensity >64 knots) passes within 75 Nmi per 10 years. (Peterka, 2002) 37

53 TABLE C6-2 APPROXIMATE RELATIONSHIP BETWEEN WIND SPEEDS IN ASCE 7 10 AND SAFFIR/SIMPSON HURRICANE SCALE Saffir/Simpson Sustained Wind Gust Wind Speed Over Gust Wind Speed Hurricane Speed Over Water a Water b Over Land c Category Mph (m/s) mph (m/s) mph (m/s) > 155 > 69 >181 >81.0 >171 >76 a 1-minute average wind speed at 33 ft (10 m) above open water b 3-second gust wind speed at 33 ft (10 m) above open water c 3-second gust wind speed at 33 ft (10 m) above open ground in Exposure Category C. This column has the same basis (averaging time, height, and exposure) as the basic wind speed from Fig Figure 3-9 The latest wind hazard curve for Hawaii, from the ASCE 7-10 Standard 38

54 3.2.3 Wind Scenario Analysis To evaluate the potential performance the essential facility buildings on Oahu when subjected to high winds, another scenario based event was run in the HAZUS MH model. The hurricane scenario used was selected to generate the forward quarter of the storm on the south coast of Oahu. The storm track was selected and given to us and State Civil Defense by the Central Pacific Hurricane Center of NOAA. The intensity is similar to the maximum intensities of storms that have landfalled or been close to landfalling in the Hawaiian region, and is consistent with the assumptions given in the Hurricane Flood Insurance Study. Therefore, we believe that the use of this scenario is consistent with that intent, given that one scenario was to be used for this project. Consistent with the parameters used under Task Order 13, this event was a strong category 2 tropical cyclone land falling the southern and western shores of Oahu. It is a storm track aligned with that developed by the Central Pacific Hurricane Center for the 2009 Makani Pahili tropical cyclone exercise conducted by State Civil Defense, but modified to a peak gust windspeed intensity of 129 mph, equivalent to a 700-year return period. Input parameters for HAZUS MH include specifying the storm s track over time and thus it s translational velocity, the Radius to Maximum Winds (RMW), and the Maximum Wind Gust (3-second gust at 10 meters). Table 3-5 Input Data for HAZUS Wind Scenario Position Day Hour (UTC) Latitude (N) Longitude (W) Central Pressure (mb) Max Wind Gust (mph) RMW (miles)

55 Figure HAZUS MH severe wind tropical cyclone scenario track and peak wind gusts per census tract 3.3 Floods Historic Record Flooding in Hawaii can be frequent and extensive. In the City & County of Honolulu, from about 1915 to 2008, floods caused by rainstorms, tsunamis, and hurricanes have claimed more than 140 lives and inflicted more than $200 million dollars of direct and indirect damage. The cost of damage from significant floods is listed in Table 1-3. This table shows that in recent times there has been a consistent increase in economic impacts of flooding. The major flooding events in Hawaii are caused by storms, storm surge, high surf and tsunamis. Some of the largest rainfall counts and most severe flooding events have occurred in the last several years. 40

56 Table 3-6. Major Floods Affecting Oahu and Associated Damage, Date Lives Lost Location 1998 $ Cause Statewide Cloudburst 11/17/ Statewide $ 1,000,000 Heavy rains Statewide Heavy rains 1/16/ Honolulu $ 500,000 Heavy rains Statewide Heavy rains Statewide Heavy rains Statewide Heavy rains Statewide Heavy rains ll/3/ Kalihi, Moanalua, Halawa valleys, Oahu Heavy rains Statewide Rainstorm 2/27/ Oahu $ 1,000,000 Severe rainstorm Statewide Severe rainstorm 1/4-5/ Hawaii, Maui, Oahu $ 2,200,000 High seas l/23-26/ Hawaii, Maui, Oahu $ 250,000 Strong winds and rainstorm 1/15-17/ Kauai, Oahu $ 550,000 Intense Kona storm 3/26-27/ Oahu $ 1,303,000 Heavy rains and strong winds 1/21/ Oahu $ 500,000 Heavy rains and strong winds 11/27-28/1954 Kauai, Oahu $ 810,000 Heavy rains 12/19-21/ Statewide Kona storm 1/24-25/ Wailua, Kauai, Oahu, Hawaii $ 700,000 Heavy rains 2/25/1956 Sunset Beach, Oahu $ 250,000 Flash flood 2/7/ Honolulu, Waimanalo, Aina Haina, Oahu $ 400,000 Flash flood 12/1/1957 Kauai, Oahu, Maui,Hawaii $ 1,056,000 Hurricane Della total damage 3/5/1958 Oahu $ 500,000 Heavy rain 8/6-7/ Oahu, Maui, Hawaii $ 552,000 Heavy rain, strong wind, high seas 1/17-18/1959 Oahu, Molokai, Maui, Hawaii $ 1,393,000 Heavy rain, strong wind, high seas 8/4/ Kauai, Oahu, Maui, Hawaii $ 11,524,000 Hurricane Dot total damage 5/12-13/1960 Oahu, Maui $ 250,000 Kona storm 10/27/ Oahu, Maui, Hawaii $ 2,045,731 Heavy rain, strong wind, high seas 11/15-17/ Statewide $ 790,000 Heavy rains, strong winds 5/14/1963 Pearl City, Oahu $ 300,000 Heavy rains 12/19-23/ Statewide $ 439,000 Heavy rains, strong winds, high seas 2/4/ Oahu, Molokai, Maui $ 593,000 Heavy rains 5/3/l965 Kahaluu, Oahu $ 711,300 Heavy rains 11/10-15/ Oahu $ 500,000 Heavy rains, strong winds Statewide Heavy rains 12/17-18/ Kauai, Oahu $ 1,355,000 Heavy rain, high seas, tornado 1/5/1968 Pearl City, Oahu $ 1,243,000 Heavy rains 2/1/1969 Keapuka, Oahu $ 705,100 Heavy rains 4/19/ Kauai, Oahu, Maui $ 3,868,300 Heavy rains l/3o-2/l/l975 Kauai, Oahu $ 566,000 Heavy rains 2/5-7/1976 Oahu $ 802,000 Heavy rain, high seas, strong winds 1/6-7/ Oahu $ 270,000 Heavy rain and strong wind Statewide Rainstorm 1/6-14/1980 Statewide $ 42,578,000 Heavy rains, high seas, strong winds 10/28/1981 Walawa Stream, Oahu $ 786,350 Heavy rains 11/23/ Statewide $ 307,859,000 Hurricane Iwa total damage 12/31/1987-1/1/1988 Oahu $ 35,000,000 Heavy rains 7/21-23/1993 Statewide Heavy rains, remnants of hurricane 8/3-4/2004 Statewide Heavy rains, remnants of hurricane 10/30/2004 Manoa, Oahu $ 85,000,000 Heavy rains, Manoa Stream overflow 2/19-4/2/2006 Statewide $ 50,000,000 Sustained rainfall, Kauai dam break 12/4-11/2007 Statewide $ 3,400,000 Heavy rains, high winds 41

57 3.3.2 Flood Scenario Analysis In performing the riverine flood analysis for Honolulu County, it is assumed that flooding is completely correlated. That is, all the streams, tributaries, and rivers modeled in the county experience the flood hazard of interest simultaneously. For example, in the 500-year flood scenario, the entire stream network in the county experiences 500-year flooding at the same time. In reality, only portions of the county stream network will experience this level of flooding at a given time. In the without levees flood scenario, it is assumed that all the levees fail during the flooding. This is unlikely and will lead to an overstatement of the flood hazard as well as an overestimate of the resulting losses. Finally, no credit is given for emergency management measures taken to mitigate the flood hazard. Unlike earthquakes, communities typically have some forewarning of an impending flood and can take some measures (e.g., sandbagging) to protect structures from flooding. In this pilot study, such emergency measures are not considered. The Honolulu Essential Facility risk assessment examined the impacts of three different floods on the essential facilities and general building stock in the county a 100-year flood with the existing certified levee system in the county intact, a 100-year flood without consideration of these levees, and a 500-year (0.2% chance per year) flood Year Flood, with Levees The 100-year flood (1% chance of occurrence per year) with levee was chosen as it represents the primary basis for FEMA Flood Insurance Rate Maps (FIRMs) and is often the flood hazard used for city and county planning, and floodplain management purposes. Figure 3-11 shows the 100- year flood depth grid and floodplain for Honolulu County. For a 100-year flood with levees intact, the floodplain is typically a few hundred feet wide (perpendicular to the stream centerline) but may be as much as 1 mile wide in some locations in the southeastern portion of the county. The depth of the water along most river reaches ranges from 6 to 20 feet; the largest flood depths are over 60 feet in the southeastern portion of the county. The Digital Flood Insurance Rate Map (DFIRM) with 100-year flood information used to create the flood hazard data incorporated into HAZUS MH is available from the FEMA Map Service Center ( 42

58 Figure 3-11 Honolulu County, 100-Year Floodplain (with Levees) and Depth Grid Year Flood, without Levees The 100-year flood without levee was modeled to show the impact of flooding should the levees fail and to demonstrate the importance of certifying/maintaining the levee system. The difference between the estimated county losses with and without levees can be used to support a benefit-cost analysis of the levee system and possibly other flood prevention and mitigation measures. Figure 3-12 shows the area in Honolulu County impacted by the 100-year flood with failed levees. In this case, the floodplain again is typically a few hundred feet wide along most river reaches, but extends almost 2 miles across in select locations where the levee system is assumed to have failed. The flood depth in most areas ranges from 6 to 20 feet. However, the deepest flooding occurs in the southeast sector of the county with depths of 60 feet. The Digital Flood Insurance Rate Map (DFIRM) with 100-year flood information used to create the flood hazard data incorporated into HAZUS MH is available from the FEMA Map Service Center ( 43

59 Figure 3-12 Honolulu County, 100-Year Floodplain (without Levees) and Depth Grid Year Flood, with Levees The 500-year flood was selected to represent a more catastrophic flood event. Since levee systems are not always designed to contain such a flood, analysis of this flood event will provide information on severity of damages in an unlikely, but large scale flood that overwhelms typically planned flood control measures. The 500-year floodplain and depth grid for Honolulu County is shown in Figure With the levees assumed intact, the largest width of the floodplain is about 1.5 miles in the southeast portion of the county. The flood depth typically ranges from 6 25 feet along most river reaches, with the deepest flood depths of 60 feet occurring in the southeast sector of the county. The Digital Flood Insurance Rate Map (DFIRM) with 500-year flood information used to create the flood hazard data incorporated into HAZUS MH is available from the FEMA Map Service Center ( 44

60 Figure 3-13 Honolulu County, 500-Year Floodplain and Depth Grid 45

61 4 Analysis of HAZUS MH Modeled Inventory 4.1 Analysis Methodology Earthquake Analyses Using HAZUS MH MR3 The HEFRA regional earthquake risk assessments were conducted using HAZUS MH MR3 (with Patch 2 installed) and HAZUS MH MR4 for the flood risk. HAZUS MH study regions for Honolulu were created using the HEFRA enhanced essential facilities database and improved general building stock data. The USGS ShakeMap, converted to HAZUS MH-compatible geodatabase format, were incorporated into HAZUS MH as usersupplied hazard data for scenario analysis. All analyses were conducted utilizing default damage functions, default restoration functions and default parameter settings. The general process HAZUS MH uses to estimate earthquake losses is illustrated in Figure 4-1. Figure 4-1. HAZUS MH Earthquake Loss Estimation Model For completeness, the HAZUS MH analysis modules for transportation and utility systems were included in the analyses, although these assessments rely on existing HAZUS MH default data. HAZUS MH results from these modules are not included in this report. It should be noted that the Fire Following Earthquake (FFE) module has also been run, but the results should be used with caution as the HAZUS MH software developers are currently revising this code module. The improved FFE module is scheduled for release within HAZUS MH MR4. Risk assessment results were generated using the following HAZUS MH analysis options: General Buildings o Ground Motion o Damage State Probabilities o Damage o Direct Economic Loss Essential Facilities o Medical Care o Police Stations 46

62 o Fire Stations o Emergency Response o Schools Transportation Systems o Highways o Railways o Light Rail o Bus System o Port and Harbor o Ferry System o Airport Transportation Utility Systems o Potable Water o Waste Water o Oil o Natural Gas o Electric Power o Communication Induced Physical Damage o Fire following o Debris Direct Social Losses o Casualties o Shelter Wind Analyses Using HAZUS MH MR3 The HEFRA hurricane risk assessments were conducted using HAZUS MH MR3 (with Patch 2 installed). HAZUS MH study regions for Honolulu were created using the HEFRA enhanced essential facilities database and improved general building stock. The scenario storm track and intensity parameters were manually input using the deterministic scenario wizard. The general process HAZUS MH uses to estimate wind losses is illustrated in Figure 4-2. Figure 4-2. HAZUS MH Hurricane Loss Estimation Model (from Peter Vickery, et al, ASCE Natural Hazards Review Journal, May 2006) 47

63 There are four basic classes of analysis functions used in the Hurricane Model: Building damage functions. Building and contents loss functions. Building loss of use functions. Building debris functions. These functions have been developed for all of the model building types in the Hurricane Model using the methodologies described in the Technical Manual. The resulting functions cannot be modified. Direct economic losses begin with the cost of repair and replacement of damaged or destroyed buildings. However, building damage will result in a number of consequential losses that, in HAZUS, are defined as direct. Thus, building-related direct economic losses (which are all expressed in dollars) comprise two groups. The first group consists of losses that are directly derived from building damage: Cost of repair and replacement of damaged and destroyed buildings Costs of damage to building contents Losses of building inventory (contents related to business activities) The second group consists of losses that are related to the length of time the facility is non-operational (or the immediate economic consequences of damage): Relocation expenses (for businesses and institutions) Capital-related income losses (a measure of the loss of productivity, services or sales) Wage losses (consistent with income loss) Rental income losses (to building owners The shelter module provides two estimates: The total number of displaced households (due to loss of habitability) The number of people requiring short-term shelter Loss of habitability is calculated directly from damage to the residential occupancy inventory and from loss of water and power. The methodology for calculating short-term shelter requirements recognizes that only a portion of those displaced from their homes will seek public shelter, and some will seek shelter even though their residence may have little, if any, damage Flood Analyses Using HAZUS MH MR4 The HEFRA regional flood risk assessments were conducted using HAZUS MH MR4. HAZUS MH study regions for Honolulu were created using the HEFRA enhanced essential facilities database and improved general building stock. FEMA Digital Flood Insurance Rate Maps (DFIRMs), converted to HAZUS MH-compatible geodatabase format, were incorporated into HAZUS MH as user-supplied hazard data12 for each scenario analysis. All analyses were conducted utilizing default damage functions, default restoration functions and default parameter settings. The general process HAZUS MH uses to estimate flood losses is illustrated in Figure

64 Figure 4-3. HAZUS MH Flood Loss Estimation Methodology For completeness, the HAZUS MH analysis modules for transportation and utility systems were included in the analyses, although these assessments rely on existing HAZUS MH default data. HAZUS MH results from these modules are not included in this report. Risk assessment results were generated using the following HAZUS MH analysis options: General Building Stock Damage and Loss o Building and Content Damage (%) o Direct Economic Loss ($) (Bldg, Cont, Inv) o Damage Building Count o Depreciated Building and Content Loss ($) Essential Facilities o Medical Care o Police Stations o Fire Stations o Emergency Centers o Schools Transportation Systems o Highways o Railways o Light Rail o Bus System o Port and Harbor o Ferry System o Airport Transportation Utility Systems o Potable Water o Wastewater o Oil o Natural Gas o Electric Power Facilities o Communication Facilities Vehicles Debris Direct Social Loss o Shelter 49

65 4.2 Results of Risk Assessments Default Data Risk Assessment Regional Impacts First, the results of analyses of the default HAZUS MH dataset are presented for baseline reference: Estimated Earthquake Losses to the Default Inventory The effects of this earthquake on the essential facilities data set of the Island of Oahu were, in general, low. Overall direct losses to general building stock (property losses only) were estimated to be $75 Million. A breakdown of these losses per occupancy type and type of loss is included in Table 4-1. Losses are about two-thirds in the residential occupancy sector and a third in the commercial/industrial occupancy sector. Table 4-1. General Building Stock Economic Losses Per Occupancy Due To Earthquake Scenario Occupancy - losses in thousands of dollars Property Damage Residential Commercial Industrial Others Total Structural 1, ,740 Non Structural 28,670 12,720 2,100 2,650 46,150 Content 12,820 9,340 1,420 2,070 25,660 Inventory Subtotal 43,240 23,010 3,850 4,900 75,000 Business Interruption Loss Wage Capital-Related Rental Relocation Subtotal ,820 Total 4,367 2, ,980 76,820 50

66 Figure 4-4. Residential earthquake losses per census tract for modeled event Estimated Wind Losses to the Default Inventory The scenario produced maximum peak wind gusts of around 138 mph with slightly lower velocities at locations further from the radius of maximum winds, together with some first order adjustments for topographic effects. Overall direct losses to general building stock were estimated to be $26.2 Billion. A breakdown of this total by occupancy is presented in Table 4-2. Wind scenario losses are thus more than 2 orders of magnitude greater than the earthquake scenario. The residential sector is a particularly predominant source of the high losses. Table 4-2. General Building Stock Economic Losses Per Occupancy Due To Wind Scenario Occupancy - losses in thousands of dollars Property Damage Residential Commercial Industrial Others Total Building 16,977,766 1,352, , ,684 18,846,305 Content 6,044, , , ,071 7,344,916 Inventory 0 16,796 24,117 2,218 43,131 Subtotal 23,022,433 2,281, , ,973 26,234,352 Business Interruption Loss Income 16, ,746 2,381 3, ,347 Relocation 1,312, ,874 10,709 52,400 1,571,502 Rental 594, ,294 1,781 8, ,123 Wage 37, ,378 4,004 12, ,671 Subtotal 1,960, ,292 18,876 76,632 2,808,643 Total 24,983,277 3,033, , ,605 29,042,995 51

67 Figure 4-5. Residential wind losses per census tract for modeled event 52

68 Estimated Flood Losses to the Default Inventory The 100-year flood (with levees intact) scenario will primarily impact the south/southeastern communities and infrastructure of Honolulu County and will also communities in the northern region of the county. A breakdown of this total by occupancy is presented in Table 4-3. The residential sector is a particularly predominant source of the high losses. Table 4-3 General Building Stock Economic Losses Per Occupancy Due To Flood Scenario (100-Year with Levees) Occupancy - losses in thousands of dollars Property Damage Residential Commercial Industrial Others Total Building 924, ,000 18,260 15,300 1,086,170 Content 697, ,720 38,710 78,120 1,178,640 Inventory 0 6,860 5, ,530 Subtotal 1,621, ,570 62,790 94,270 2,278,330 Business Interruption Loss Income 510 3, ,800 Relocation 1, ,470 Rental 1, ,420 Wage 1,210 3, ,400 9,640 Subtotal 5,280 7, ,620 18,320 Total 1,626, ,980 62,810 99,890 2,296,660 Figure 4-6 Flood building losses per census tract for 100-Year Flood with Levees 53

69 The 100-year flood (with levees failed) scenario will primarily impact the south/southeastern communities and infrastructure of Honolulu County and will also communities in the northern region of the county. A breakdown of this total by occupancy is presented in Table 4-4. The residential sector is a particularly predominant source of the high losses. Table 4-4 General Building Stock Economic Losses Per Occupancy Due To Flood Scenario (100- Year without Levees) Occupancy - losses in thousands of dollars Property Damage Residential Commercial Industrial Others Total Building 1,270, ,540 21,660 18,650 1,476,910 Content 929, ,280 45,410 95,470 1,544,180 Inventory 0 9,240 6, ,730 Subtotal 2,199, ,060 73, ,900 3,037,820 Business Interruption Loss Income 570 4, ,850 Relocation 1,870 1, ,970 Rental 2, ,120 Wage 1,380 3, ,940 12,100 Subtotal 6,170 9, ,200 23,040 Total 2,205, ,710 73, ,100 3,060,850 Figure 4-7 Flood building losses per census tract for 100-Year Flood without Levees 54

70 The 500-year flood (with levees intact) scenario will primarily impact the south/southeastern communities and infrastructure of Honolulu County and will also communities in the northern region of the county. A breakdown of this total by occupancy is presented in Table The residential sector is a particularly predominant source of the high losses. Table 4-5 General Building Stock Economic Losses Per Occupancy Due To Flood Scenario (500- Year with Levees) Occupancy - losses in thousands of dollars Property Damage Residential Commercial Industrial Others Total Building 1,081, ,140 17,160 22,980 1,240,70 Content 774, ,900 37, ,010 1,239,020 Inventory 0 4,630 5,330 1,020 10,980 Subtotal 1,856, ,660 59, ,020 2,490,700 Business Interruption Loss Income 150 2, ,910 Relocation 1, ,350 Rental 1, ,670 Wage 370 2, ,430 8,300 Subtotal 3,520 6, ,680 15,230 Total 1,859, ,680 59, ,700 2,505,920 Figure 4-8 Flood building losses per census tract for 500-Year Flood with Levees 55

71 4.2.2 Identifying the Highest Risk Facilities due to Multiple Hazards and Multiple Effects With nearly a thousand essential facility buildings evaluated in this study, a prioritization of the most vulnerable buildings was performed in order to identify which buildings are estimated to be at highest risk of economic loss or loss of functionality. With multiple hazards affecting each building differently depending on its construction characteristics, and economic loss and loss of functionality being the critical vulnerability parameters, a tabular format was chosen to provide an overarching look-up to identify not only which buildings are a high priority, but the hazard(s) that is causative of the risk. Economic loss alone would be a biased indicator of risk towards larger buildings. Therefore, loss of functionality was also included as a risk indicator, since essential facilities are expected to remain operational during a natural disaster. The following Table 4-6 summarizes the essential facility risk (EF) results, by hazard type, for the five types of essential facilities as defined in HAZUS. For each essential facility type, the hazard is described as the primary, secondary, or tertiary natural hazard risk for this EF type. Only the 500 year flood risk results were used in making the comparisons. The comparisons are only made based on economic risk only, since the functional risk results are estimated using different metrics for each hazard.. Tables 4-7 for the default inventory and later Table 4-40 for the enhanced inventory summarize the General Building Stock and EF economic risks. In most cases, an essential facility is not at highest risk simultaneously from multiple hazards. This allows the most important information on the buildings at highest risk to be examined without the need to have access to the HAZUS MH model for Honolulu. Table 4-7 would indicate general building stock is at highest economic Risk for hurricanes, followed by floods. Table 4-8 lists high risk essential facilities, per hazard type, based on economic risk and based on loss of functionality risk. With this table, a user can identify specific EFs that have high economic or functional loss risk in the event of a hurricane, earthquake, or large flood as modeled in this study. They can also identify EFs that may have high risks for two or more natural hazards, thus helping make a rational evaluation for how to best harden/protect critical facilities with a multi-hazard strategy. 56

72 Table 4-6. Illustrated Guide to the Organization of the Comprehensive Essential Facility Priority Rankings Shown in Tables 4-7 and 4-8 Type of Risk Governing Essential Facilities Considered Hazard Hospitals Schools EOC s Police Fire Economic Loss due to: Economic Loss to the UHM Core (in Table 4-12 only) Stations Stations Earthquake Tertiary Tertiary Secondary Tertiary Tertiary Risk Risk Risk Risk Risk Wind Primary Primary Primary Primary Primary Risk Risk Risk Risk Risk Flood Secondary Secondary Tertiary Secondary Secondary Risk Risk Risk Risk Risk Earthquake NA Secondary NA NA NA Risk Wind NA Primary NA NA NA Risk Flood NA NA NA NA NA Note: The University of Hawaii at Manoa (UHM) Core essential facility buildings do not appear in Table 4-7 because the default HAZUS MH data does not have any information on specific buildings at any schools or university campuses. 57

73 4.2.3 Default Essential Facilities Data Risk Assessment Table 4-7. Total Losses Based On HAZUS Default Data Hurricane Event Total Losses Essential Facilities $44,499,695 Hurricane Event Total Losses General Building Stock $26,234,352,000 Earthquake Event Total Losses Essential Facilities $705,497 Earthquake Event Total Losses General Building Stock $75,000,000 Flood Event Total Losses 100 with Levees Essential Facilities $31,169,000 Flood Event Total Losses 100 with Levees General Building Stock $2,296,600,000 Flood Event Total Losses 100 without Levees Essential Facilities $32,569,000 Flood Event Total Losses 100 without Levees General Building Stock $3,037,820,000 Flood Event Total Losses 500 with Levees Essential Facilities $39,203,000 Flood Event Total Losses 500 with Levees General Building Stock $4,442,940,000 The following table is the risk-assessment summary of essential facilities in the baseline default HAZUS model analysis of 985 buildings for earthquake and wind hazards, ranked by $ losses and loss of functionality. For final rankings based on the enhanced data developed in this project, see Section

74 High Loss of Functionality Hurricane Earthquake High Modeled Losses Hurricane Table 4-8. Essential Facility Ranking Based On HAZUS Default Data HAZUS Default Honolulu County Essential Facilities - Vulnerability List Total Number of Modeled Buildings = Description 291 Category 2 - Ewa Hurricane Event Vulnerability Lanai Earthquake Scenario Vulnerability Facility Year EQ Bldg Design Soil Wind Building Modeled Loss of Functionality Modeled Loss of Functionality Building Classification Built Type Level Type Type Building $ Loss $ Loss Rank (Num. of Days) Building $ Loss $ Loss Rank (Num. of Days) QUEEN'S MEDICAL CENTER CareFlty -- W2 MC D -- $ 2,604, $ 1, TRIPLER ARMY MEDICAL CENTER CareFlty -- W2 MC D -- $ 2,604, $ 1, KAISER FOUNDATION HOSPITAL CareFlty -- W2 MC D -- $ 2,560, $ ST FRANCIS MEDICAL CENTER CareFlty -- W2 MC D -- $ 1,952, $ 1, LEAHI HOSPITAL CareFlty -- W2 MC D -- $ 1,542, $ 1, KAPIOLANI MED CTR FOR WOMEN CareFlty -- W2 MC D -- $ 1,428, $ 1, CASTLE MEDICAL CENTER CareFlty -- W2 MC D -- $ 1,406, $ 1, HAWAII STATE HOSPITAL CareFlty -- W2 MC D -- $ 1,351, $ 1, STRAUB CLINIC AND HOSPITAL CareFlty -- W2 MC D -- $ 1,302, $ WAHIAWA GENERAL HOSPITAL CareFlty -- W2 MC D -- $ 1,104, $ REHAB HOSPITAL OF THE PACIFIC CareFlty -- W2 MC D -- $ 840, $ KUAKINI MEDICAL CENTER CareFlty -- W2 MC D -- $ 840, $ KAHUKU HOSPITAL CareFlty -- W2 MC D -- $ 702, $ SHRINERS HOSPS FOR CHILDREN CareFlty -- W2 MC D -- $ 368, $ Honolulu Police Dept Police Station -- W1 MC D -- $ 329, $ 33, Honolulu Emergency Svc Dept EmergencyCtr -- W1 MC D -- $ 175, $ 36, Waianae City Police Station Police Station -- W1 MC D -- $ 203, $ 33, Pearl City Police Station Police Station -- W1 MC D -- $ 215, $ 33, Kalihi City Police Station Police Station -- W1 MC D -- $ 112, $ 33, Wahiawa City Police Station Police Station -- W1 MC D -- $ 97, $ 33, Honolulu Police Dept-Telecomms Police Station -- W1 MC D -- $ 162, $ 33, Kahuku Police Sta Police Station -- W1 MC D -- $ 275, $ 33, Honolulu Police Training Acad Police Station -- W1 MC D -- $ 159, $ 33, Honolulu Police Commission Police Station -- W1 MC D -- $ 171, $ 33, Sheriffs Division-Public Sfty Police Station -- W1 MC D -- $ 171, $ 33, THE KAMEHAMEHA SCHOOLS School -- W1 MC D -- $ 196, $ RED HILL ELEMENTARY SCHOOL School -- W1 MC D -- $ 193, $ MANOA ELEMENTARY SCHOOL School -- W1 MC D -- $ 166, $ HONGWANJI MISSION SCHOOL School -- W1 MC D -- $ 160, $ KAWANANAKAO MIDDLE SCHOOL School -- W1 MC D -- $ 160, $ PAUOA ELEMENTARY SCHOOL School -- W1 MC D -- $ 159, $ LINCOLN ELEMENTARY SCHOOL School -- W1 MC D -- $ 159, $ SHAFTER ELEMENTARY SCHOOL School -- W1 MC D -- $ 157, $ NUUANU ELEMENTARY SCHOOL School -- W1 MC D -- $ 144, $ PALOLO ELEMENTARY SCHOOL School -- W1 MC D -- $ 143, $ ANUENUE SCHOOL School -- W1 MC D -- $ 143, $ KAIULANI ELEMENTARY SCHOOL School -- W1 MC D -- $ 138, $ STAR OF THE SEA ELEM SCHOOL School -- W1 MC D -- $ 133, $ STAR OF THE SEA EARLY LRNG CTR School -- W1 MC D -- $ 133, $ MAUKA LANI ELEMENTARY SCHOOL School -- W1 MC D -- $ 130, $

75 4.2.4 Enhanced Data Risk Assessment Regional Earthquake Impacts A M6.8 Lanai scenario earthquake will impact the island of Oahu. A summary of regional impacts is provided in Table 4-9. These impact are tabulated in greater detail in the HAZUS MH Global Summary Report for the scenario earthquake (provided in Appendix A). Table 4-9 Summary of HAZUS MH Estimated Impacts for Honolulu Due to a M6.8 Scenario Earthquake in the Lanai Seismic Source Area HAZUS Estimated Impact (Earthquake): M6.8 Impact Category 1871 Lanai EQ Economic Loss due to Building Damage $75.0 M Total Building-related Direct Economic Loss $76.82 M # of Buildings in Complete Damage State 0 Debris Generated (million tons) 0 Displaced Households 0 People Needing Short-Term Shelter 0 Fatalities (2 am, 2 pm, 5 pm) 0,0,0 Total Injuries (2 am, 2 pm, 5 pm) 3,4,3 % of Households without Water 0 # Highway Bridges w/ at least Moderate Damage (Potentially Closed) 0 Fire Following Earthquake Ignitions, area burned, $ loss 5, 0.04 sq. mi, $7 M In a M6.8 Lanai earthquake, dollar losses related to shaking-induced building damage are estimated to reach $75 million, while total direct economic losses are expected to reach $77 million. No buildings reach the Extensive or Complete damage state. Less than three dozen are expected to reach the Moderate damage state. Accordingly, debris generated is almost negligible. Within HAZUS MH, total direct economic losses include building and content losses, as well as inventory loss and income losses (which include relocation costs, income losses, wage losses and rental income losses). The geographic distribution of total direct economic loss is mapped in Figure

76 Figure 4-9 Total Direct Economic Loss on Oahu Resulting from a M6.8 Scenario Earthquake in the Lanai Seismic Source Area Enhanced Essential Facilities Earthquake Impacts Table 4-10 provides an overview of essential facility performance in the Lanai Scenario Earthquake. The table lists the number of essential facility sites and buildings (these numbers will differ for multi-building campuses, such as schools and hospitals). The table also provided the total number of buildings and their building replacement value. As can be seen in the table, replacement cost data for hospitals was generally not available, unlike most other essential facility types; in these cases the replacement values were estimated based on building area multiplied by unit cost per square foot. Estimated seismic losses to all essential facilities combined were only about $3.5 million. 61

77 Table 4-10 Honolulu Essential Facility Loss Estimates M6.8 Lanai Scenario Earthquake Essential Facility Category No. of Facilities/ Sites No. of Buildings No. of Beds Replacement Cost ($1,000) Fill in used for unknown Values Buildings w/ Actual replacement cost data M Lanai EQ Scenario Functionality Day 1 (%) Mean Damage Economic Loss ($1,000) Small 73 1,431 $ 315, % 0.32% $ 1, Hospital Medium $ 24, % 0.02% $ 5.46 Large 5 2,251 $ 82, % 0.56% $ Schools K $ 2,063, % 0.05% $ UH Manoa $ 1,491, % 0.07% $ 1, EOC's 7 7 $ 6, % 0.01% $ 0.56 Police Stations $ 42, % 0.03% $ Fire Stations $ 30, % 0.02% $ 4.64 TOTALS ,925 $ 4,057, $ 3, Tables 4-11 through 4-13 provide additional detail for fire stations, schools and university buildings, and hospitals, respectively. Figures 4-11 through 4-13 provide maps of the functionality of Fire Stations, School and University Buildings, and Hospitals overlain onto maps of earthquake ground motion. Figures 4-13 and 4-14 indicated the functionality of EOC s and Police Stations. Damage levels to the individual buildings were slight to none (typical damage conditions may include damaged ceiling tiles, wall finishes, or other non-structural acceleration sensitive components), resulting in a maximum loss of functionality of up to 7 days with many buildings experiencing no loss of functionality. Table 4-11 Estimated Impacts on Oahu Fire Stations in a M6.8 Lanai Earthquake Scenario Category District Name No. of Facilities/S ites No. of Buildings Replacement Cost ($1,000) Fill in used for unknown Values Buildings w/ Actual replacement cost data M Lanai EQ Scenario Functionality Day 1 (%) Mean Damage Economic Loss ($1,000) KOOLAUPOKO 6 6 $ 10, % $ 2.35 EWA $ 8, % $ 0.73 HONOLULU $ 8, % $ 1.44 Fire Station WAHIAWA 1 1 $ % $ 0.00 KOOLAULOA 4 4 $ 2, % $ 0.10 WAIANAE 2 2 $ % $ 0.02 WAIALUA 1 1 $ % $ 0.00 TOTALS 43 $ 30,514 3 $

78 Figure 4-10 Estimated Functionality of Oahu Fire Stations in a M6.8 Lanai Earthquake Scenario Table 4-12 Estimated Impacts on Oahu Schools and University of Hawaii at Manoa In a M6.8 Lanai Earthquake Scenario Category District Name No. of Facilities/S ites No. of Buildings Replacement Cost ($1,000) Fill in used for unknown Values Buildings w/ Actual replacement cost data M Lanai EQ Scenario Functionality Day 1 (%) Mean Damage Economic Loss ($1,000) KOOLAUPOKO $ 295, % $ EWA $ 659, % $ HONOLULU $ 820, % $ K-12 WAHIAWA $ 120, % $ KOOLAULOA $ 34, % $ 5.33 WAIANAE $ 104, % $ WAIALUA $ 29, % $ 0.98 UH Manoa HONOLULU $ 1,491, % $ 1, TOTALS $ 3,554, $ 2,

79 Figure 4-11 Estimated Functionality of Oahu Schools and University of Hawaii at Manoa Table 4-13 Estimated Impacts on Oahu Hospitals in a M6.8 Lanai Earthquake Scenario Category District Name No. of Facilities/S ites No. of Buildings Replacement Cost ($1,000) Fill in used for unknown Values Buildings w/ Actual replacement cost data M Lanai EQ Scenario Functionality Day 1 (%) Mean Damage Economic Loss ($1,000) KOOLAUPOKO 8 $ 57, % $ EWA 24 $ 99, % $ HONOLULU 37 $ 207, % $ 1, Hospital WAHIAWA 2 $ 20, % $ 9.70 KOOLAULOA 7 $ 29, % $ WAIANAE 2 $ 8, % $ 0.12 WAIALUA 0 $ - 0 TOTALS 80 $ 422,700 0 $ 1,

80 Figure 4-12 Estimated Functionality of Oahu Hospitals in a M6.8 Lanai Earthquake Scenario 65

81 Figure 4-13 Estimated Functionality of Oahu EOC s in a M6.8 Lanai Earthquake Scenario 66

82 Figure 4-14 Estimated Functionality of Oahu Police Stations in a M6.8 Lanai Earthquake Scenario 67

83 Regional Wind Impacts A landfalling Category 2 scenario hurricane will impact the island of Oahu. A summary of regional impacts is provided in Table These impact are tabulated in greater detail in the HAZUS MH Global Summary Report for the scenario hurricane (provided in Appendix B). Table 4-14 Summary of HAZUS MH Estimated Impacts for Honolulu Due to a Category 2 Scenario Landfalling Hurricane Impact Category HAZUS Estimated Impact (Severe Wind): Category 2 Ewa Beach Landfall Economic Loss due to Building Damage $26.23 B Total Building-related Direct Economic Loss $29.04 B # of Buildings in Complete Damage State 27,415 Debris Generated (million tons) Displaced Households 76,958 People Needing Short-Term Shelter 17,947 Fatalities (2 am, 2 pm, 5 pm) n/a Total Injuries (2 am, 2 pm, 5 pm) n/a % of Households without Water n/a # Highway Bridges w/ at least Moderate Damage (Potentially Closed) n/a Fire Following Earthquake Ignitions, area burned, $ loss n/a In a landfalling Category 2 hurricane, dollar losses related to shaking-induced building damage are estimated to reach $26.2 billion, while total direct economic losses are expected to reach $29.0 billion. Over 27,000 buildings, nearly all of which are residential, reach the Complete damage state. Almost 23,000 buildings, of which 21,400 are residential, reach the Severe damage state. Just over 42,000 buildings, of which 40,167 are residential, reach the Moderate damage state. Accordingly, debris generated is 2.4 million tons. Within HAZUS MH, total direct economic losses include building and content losses, as well as inventory loss and income losses (which include relocation costs, income losses, wage losses and rental income losses). The geographic distribution of total direct economic loss is mapped in Figure

84 Figure 4-15 Total Direct Economic Loss on Oahu Resulting from a Category 2 Scenario Landfalling Hurricane Enhanced Essential Facilities Wind Impacts Table 4-15 provides an overview of essential facility performance in the Category 2 Scenario Hurricane. The table lists the number of essential facility sites and buildings (these numbers will differ for multi-building campuses, such as schools and hospitals). The table also provided the total number of buildings and their building replacement value. As can be seen in the table, replacement cost data for hospitals was generally not available, unlike most other essential facility types; in these cases the replacement values were estimated based on building area multiplied by unit cost per square foot. Estimated wind losses to all essential facilities combined reach $640 million. 69

85 Table 4-15 Honolulu Essential Facility Loss Estimates Category 2 Scenario Hurricane Essential Facility Category No. of Replacement Buildings w/ Actual Cat. 2 Ewa Beach Hurricane No. of Facilities/ No. of Beds Cost ($1,000) Fill replacement cost Mean Loss of Mean Economic Buildings in used for unknown Sites data Use (Days) Damage Loss ($1,000) Values Small 73 1,431 $ 315, % $ 56,044 Hospital Medium $ 24, % $ 2,860 Large 5 2,251 $ 82, % $ 15,441 Schools K $ 2,063, % $ 316,988 UH Manoa $ 1,491, % $ 228,666 EOC's 7 7 $ 6, % $ 1,404 Police Stations $ 42, % $ 5,402 Fire Stations $ 30, % $ 12,756 TOTALS ,925 $ 4,057, $ 639,563 Tables 4-16 through 4-18 provide additional detail for fire stations, schools and university buildings,, and hospitals, respectively. Figures 4-16 through 4-18 provide maps of the functionality of Fire Stations, School and University Buildings, and Hospitals overlain onto maps of hurricane wind speed. Figures 4-19 and 4-20 indicated the functionality of EOC s and Police Stations. Estimated damage to the essential facilities was quite extensive with combined total losses of over $639 million. The model results indicate that with a storm of this magnitude there is a high probability that many of the essential facility buildings on Oahu will experience severe damage with several completely destroyed. With these degrees of damage long periods of inoperability can be expected, reconstruction times may vary, but model estimates are as high as 18 months. An average loss of around 17% of the building value can be expected in all essential facilities, this would result in average loss of functionality of just over 3 months. Table 4-16 Estimated Impacts on Oahu Fire Stations in Category 2 Hurricane Scenario Category District Name No. of Facilities/S ites No. of Buildings Replacement Cost ($1,000) Fill in used for unknown Values Buildings w/ Actual replacement cost data Cat. 2 Ewa Beach Hurricane Mean Loss of Use (Days) Mean Damage Economic Loss ($1,000) $ $ $ $ $ $ $ $ KOOLAUPOKO 6 6 $ 10, % 2, EWA $ 8, % 4, HONOLULU $ 8, % 3, Fire Station WAHIAWA 1 1 $ % KOOLAULOA 4 4 $ 2, % 1, WAIANAE 2 2 $ % WAIALUA 1 1 $ TOTALS 43 $ 30, ,756 70

86 Figure 4-16 Estimated Functionality of Oahu Fire Stations in a Category 2 Hurricane Scenario Table 4-17 Estimated Impacts on Oahu Schools and University of Hawaii at Manoa In a Category 2 Hurricane Scenario No. of Replacement Buildings w/ Cat. 2 Ewa Beach Hurricane No. of Category District Name Facilities/S Cost ($1,000) Fill Actual Mean Loss of Mean Economic Buildings in used for unknown ites replacement Use (Days) Damage Loss ($1,000) Values KOOLAUPOKO $ 295,023 cost 122 data % $ 27, EWA $ 659, % $ 113, HONOLULU $ 820, % $ 125, K-12 WAHIAWA $ 120, % $ 21, KOOLAULOA $ 34, % $ 7, WAIANAE $ 104, % $ 14, WAIALUA $ 29, % $ 5, UH Manoa HONOLULU $ 1,491, % $ 228, TOTALS $ 3,554, $ 545,654 71

87 Figure 4-17 Estimated Functionality of Oahu Schools and University of Hawaii at Manoa In a Category 2 Hurricane Scenario Table 4-18 Estimated Impacts on Oahu Hospitals in a Category 2 Hurricane Scenario Category District Name No. of Facilities/S ites No. of Buildings Replacement Cost ($1,000) Fill in used for unknown Values Buildings w/ Actual replacement cost data Cat. 2 Ewa Beach Hurricane Mean Loss of Use (Days) Mean Damage Economic Loss ($1,000) $ $ $ $ $ $ KOOLAUPOKO 8 $ 57, % 5, EWA 24 $ 99, % 21, HONOLULU 37 $ 207, % 38, Hospital WAHIAWA 2 $ 20, % 1, KOOLAULOA 7 $ 29, % 5, WAIANAE 2 $ 8, % 1, WAIALUA 0 $ - 0 TOTALS 80 $ 422,700 0 $ 74,346 72

88 Figure 4-18 Estimated Functionality of Oahu Hospitals in a Category 2 Hurricane Scenario 73

89 Figure 4-19 Estimated Functionality of Oahu EOC s in a Category 2 Hurricane Scenario 74

90 Figure 4-20 Estimated Functionality of Oahu Police Stations in a Category 2 Hurricane Scenario 75

91 Enhanced Essential Facilities Flood Losses Year Flood with Levees Scenario The 100-year flood (with levees intact) scenario will primarily impact the south/south-eastern communities and infrastructure of Honolulu County and will also impact communities in the northern region of the county. A summary of regional flood impacts is provided in Table The impacts are described below and are tabulated in greater detail in the HAZUS MH Global Summary Report for this scenario flood (provided in Appendix C). Table 4-19 Summary of HAZUS MH -estimated Impacts for Honolulu County due to a 100-Year Flood (Levees Intact) Impact Category HAZUS MH -Estimated Impact Economic Loss due to Building Damage $1.5 B Total Building-related Direct Economic Loss $3.1 B # Buildings in Complete Damage State 242 Debris Generated (million tons) 0.76 Displaced Households N/A People Needing Short-term Shelter N/A # Highway Bridges w/ at least Moderate 0 Damage (potentially closed) In a 100-year flood in the county, direct economic losses due to building damage are estimated to reach $1.5 billion and total building direct economic losses are expected to reach $3.1 billion. The geographic distribution of total direct economic loss is mapped in Figure

92 Figure 4-21 Total Direct Economic Loss in Honolulu County resulting from a 100-Year Flood (Levees Intact) Of the approximately 211,000 buildings modeled within the general building stock for Orange County, less than 0.1% (242) are expected to suffer Complete damage in the 100-Year flood scenario. These building would be considered red-tagged or unsafe for continued occupancy. Approximately 6,152 buildings (3%) are expected to suffer more than 20% damage or more, while about 2,475 buildings are estimated to suffer flood damage of less than 20%. As much as 0.76 million tons of debris may result from these damaged buildings 20% is expected to be heavy debris (concrete and steel), requiring heavy equipment to break down and remove, while 80% is expected to be light debris (wood, brick, drywall and other debris). While 1 bridge in the county s transportation system are expected to suffer minor flood damage, the bridge is expected to remain functional. Table 4-20 provides an overview of essential facility performance in the 100-year flood with levees scenario. The table lists the number of essential facility sites and buildings (these numbers will differ for multi-building campuses, such as schools and hospitals). The table also provides the total building replacement value, and the number of buildings for which value data was available. As can be seen in the table, replacement cost data for hospitals was generally not available, unlike most other essential facility types. Expected building damage in this flooding event ranges from as little as 0% damage for numerous essential facility types with some, but minimal, flooding, to as much as 36% damage for hospitals. Total economic loss for essential facilities has been estimated to reach about $16 million, almost three-fourths of which ($12 million) will occur in schools, and a fourth of which ($3 million) will occur in hospitals. 77

93 78 Table 4-20 Honolulu County Essential Facility Loss Estimates 100-Year Flood (Levees Intact) Essential Facility Category No. of Facilities/ Sites No. of Buildings No. of Beds Replacement Cost ($1,000) # Buildings w/ replacement cost data # Non- Functional Buildings Time to Restore (Days) Economic Loss ($1,000) Small 73 1,431 $315,320 Medium $24,780 Hospital Large 5 2,251 $82, $3,047 K $2,063, $12,771 Schools UH-Manoa $1,491, $0 EOCs 7 7 $6, $0 Police Stations $42, $304 Fire Stations $30, $217 TOTALS ,925 $4,057, $16,339

94 Number of Buildings Replacement Cost ($1,000) # Buildings w/ replacement cost data No. Non- Functional Buildings Restoration Time (Days) Mean Building Damage Economic Loss ($1,000) Tables 4-21 through 4-25 provide additional detail for fire stations, EOCs, police facilities, schools, and hospitals, respectively. Figures 4-22 through 4-26 provide maps of Fire Station, EOC, Police Facility, School and Hospital functionality, overlain onto a map of the 100-year county floodplain/depth grid. As shown in the tables and displayed on the maps, the expected impact to individual agencies and structures may vary considerably across the County. In general, essential facilities in the more flood prone south/south-eastern portion of the county are more likely to experience flood damage. Table 4-21 Estimated Impacts on Honolulu County Fire Stations in a 100-Year Flood (Levees Intact) Agency Honolulu County 43 $30, % $217 Figure 4-22 Honolulu County Fire Station Functionality Following a 100-Year Flood (Levees Intact) 79

95 Table 4-22 Estimated Impacts on Honolulu County EOCs in a 100-Year Flood (Levees Intact) County No. of Buildings Replacement Cost ($1,000) No. Non- Functional Buildings Restoration Time (Days) Mean Damage Economic Loss ($1,000) Honolulu 7 $6, % $0 Figure 4-23 Honolulu County EOCs Functionality Following a 100-Year Flood (Levees Intact) Table 4-23 Estimated Impacts on Honolulu County Police Facilities in a 100-Year Flood (Levees Intact) # Non- Time to Economic Number of Replacement Mean County Functional Restore Loss Buildings Cost ($1,000) Damage Buildings (Days) ($1,000) Honolulu 14 $42, % $304 80

96 Number of Facilities/ Sites* No. of Buildings Replacement Cost ($1,000) # Buildings w/ replacement cost data # Non-Functional Buildings Restoration Time (Days) Mean Damage Economic Loss ($1,000) Figure 4-24 Honolulu Police Facilities Functionality Following a 100-Year Flood (Levees Intact) Table 4-24 Estimated Impacts on Honolulu School Districts in a 100-Year Flood (Levees Intact) Schools K $2,063, % $12,771 UH-Manoa $1,491, % $0 TOTALS $3,554, % $12,771 81

97 Figure 4-25 Honolulu County School Districts Functionality Following a 100-Year Flood (Levees Intact) 82

98 No. of Hospital Sites Number of Buildings Number of Licensed Beds Replacement Cost ($1,000) No. Buildings w/ replacement cost data # Non-Functional Buildings Restoration Time (Days) Mean Damage Economic Loss ($1,000) Table 4-25 Estimated Impacts on Honolulu County Hospitals in a 100-Year Flood (Levees Intact) County Honolulu 80 3,925 $4,057, % $3,047 Figure 4-26 Honolulu County Hospital Functionality Following a 100-Year Flood (Levees Intact) Year Flood without Levees Scenario The 100-year flood (with levees failed) scenario will primarily impact the south/south-eastern communities and infrastructure of Honolulu County. A summary of regional flood impacts is provided in Table The impacts are described below and are tabulated in greater detail in the HAZUS MH Global Summary Report for this scenario flood (provided in Appendix C). 83

99 Table 4-26 Summary of HAZUS MH -estimated Impacts for Honolulu County due to a 100-Year Flood without Levees Impact Category HAZUS MH -Estimated Impact Economic Loss due to Building Damage Total Building-related Direct Economic Loss $1.5 B $3.2 B # Buildings in Complete Damage State 242 Debris Generated (million tons) 0.77 Displaced Households People Needing Short-term Shelter N/A N/A # Highway Bridges w/ at least Moderate 0 Damage (potentially closed) In a 100-year flood in the county, direct economic losses due to flood building damage are estimated to reach $1.5 billion and total building direct economic losses are expected to reach $3.2 billion. The geographic distribution of total direct economic loss is mapped in Figure Figure 4-27 Total Direct Economic Loss in Honolulu County resulting from a 100-Year Flood without Levees Of the approximately 211,000 buildings modeled within the general building stock for Honolulu County, about 0.1% (242) are expected to suffer Complete damage in the 100-Year without levee flood scenario. These building would be considered red-tagged or unsafe for continued occupancy. Approximately 6,571 buildings (3%) are expected to suffer more than 20% damage or more while about 3,105 buildings are estimated to suffer flood damage of less than 20%. As much as 0.77 million tons of debris may result from these damaged buildings 20% is expected 84

100 to be heavy debris (concrete and steel), requiring heavy equipment to break down and remove, while 80% is expected to be light debris (wood, brick, drywall and other debris). While 2 bridges in the county s transportation system are expected to suffer minor flood damage, the bridges are expected to remain functional. Table 4-27 provides an overview of essential facility performance in the 100-year flood without levees scenario. The table lists the number of essential facility sites and buildings (these numbers will differ for multi-building campuses, such as schools and hospitals). The table also provides the total building replacement value, and the number of buildings for which value data was available. As can be seen in the table, replacement cost data for hospitals was generally not available, unlike most other essential facility types. Expected building damage in this flooding event ranges from as little as 0% damage for numerous essential facility types with some, but minimal, flooding to as much as 18% for hospitals. Total economic loss for essential facilities has been estimated to reach about $21 million, about 71% of which ($15 million) will occur in schools and 24% of which ($5.2 million) will occur in hospitals. 85

101 86 Table 4-27 Honolulu County Essential Facility Loss Estimates 100-Year Flood without Levees Essential Facility Category No. of Facilities/ Sites No. of Buildings No. of Beds Replacement Cost ($1,000) # Buildings w/ replacement cost data # Non- Functional Buildings Time to Restore (Days) Economic Loss ($1,000) Small 73 1,431 $315,320 Medium $24,780 Hospital Large 5 2,251 $82, $5,199 K $2,063, $14,921 Schools UH-Manoa $1,491, $0 EOCs 7 7 $6, $0 Police Stations $42, $644 Fire Stations $30, $557 TOTALS ,925 $4,057, $21,321

102 Number of Buildings Replacement Cost ($1,000) # Buildings w/ replacement cost data No. Non- Functional Buildings Restoration Time (Days) Mean Building Damage Economic Loss ($1,000) Tables 4-28 through 4-32 provide additional detail for fire stations, EOCs, police facilities, schools, and hospitals, respectively. Figures 4-28 through 4-32 provide maps of Fire Station, EOC, Police Facility and School functionality, overlain onto a map of the 100-year county floodplain/depth grid. As shown in the tables and displayed on the maps, the expected impact to individual agencies and structures may vary considerably across the County. In general, essential facilities in the more flood prone southeast portion of the county normally protected by the levee system are more likely to experience flood damage. Table 4-28 Estimated Impacts on Honolulu County Fire Stations in a 100-Year Flood without Levees Agency Honolulu County 43 $30, % $557 Figure 4-28 Honolulu County Fire Station Functionality Following a 100-Year Flood without Levees 87

103 Table 4-29 Estimated Impacts on Honolulu County EOCs in a 100-Year Flood without Levees County No. of Buildings Replacement Cost ($1,000) No. Non- Functional Buildings Restoration Time (Days) Mean Damage Economic Loss ($1,000) Honolulu 7 $6, % $0 Figure 4-29 Honolulu County EOCs Functionality Following a 100-Year Flood without Levees Table 4-30 Estimated Impacts on Honolulu County Police Facilities in a 100-Year Flood without Levees # Non- Time to Economic Number of Replacement Mean County Functional Restore Loss Buildings Cost ($1,000) Damage Buildings (Days) ($1,000) Honolulu 14 $42, % $644 88

104 Figure 4-30 Honolulu Police Facilities Functionality Following a 100-Year Flood without Levees 89

105 Number of Facilities/ Sites* No. of Buildings Replacement Cost ($1,000) # Buildings w/ replacement cost data # Non-Functional Buildings Restoration Time (Days) Mean Damage Economic Loss ($1,000) Table 4-31 Estimated Impacts on Honolulu School Districts in a 100-Year Flood without Levees Schools K $2,063, % $14,921 UH-Manoa $1,491, % $0 TOTALS $3,554, % $14,921 Figure 4-31 Honolulu County School Districts Functionality Following a 100-Year Flood without Levees 90

106 No. of Hospital Sites Number of Buildings Number of Licensed Beds Replacement Cost ($1,000) No. Buildings w/ replacement cost data # Non-Functional Buildings Restoration Time (Days) Mean Damage Economic Loss ($1,000) Table 4-32 Estimated Impacts on Honolulu County Hospitals in a 100-Year Flood without Levees County Honolulu 80 3,925 $4,057, % $5,199 Figure 4-32 Honolulu County Hospital Functionality Following a 100-Year Flood without Levees Year Flood with Levees Scenario The 500-year flood (with levees intact) scenario will primarily impact the south/south-eastern communities and infrastructure of Honolulu County. A summary of regional flood impacts is provided in Table The impacts are described below and are tabulated in greater detail in the HAZUS MH Global Summary Report for this scenario flood (provided in Appendix C). 91

107 Table 4-33 Summary of HAZUS MH -estimated Impacts for Honolulu County due to a 500-Year Flood (Levees Intact) Impact Category HAZUS MH -Estimated Impact Economic Loss due to Building Damage Total Building-related Direct Economic Loss $2.2 B $4.5 B # Buildings in Complete Damage State 488 Debris Generated (million tons) 1.2 Displaced Households People Needing Short-term Shelter N/A N/A # Highway Bridges w/ at least Moderate 0 Damage (potentially closed) In a 500-year flood in the county, direct economic losses due to flood building damage are estimated to reach $2.2 billion and total building direct economic losses are expected to reach $4.5 billion. The geographic distribution of total direct economic loss is mapped in Figure Figure Total Direct Economic Loss in Honolulu County resulting from a 500-Year Flood (Levees Intact) Of the approximately 211,000 buildings modeled within the general building stock for Honolulu County, about 0.2% (488) are expected to suffer Complete damage in the 500-Year flood scenario. These building would be considered red-tagged or unsafe for continued occupancy. Approximately 10,000 buildings (5%) are expected to suffer more than 20% damage or more while about 3,500 buildings are estimated to suffer flood damage of less than 20%. As much as 1.2 million tons of debris may result from these damaged buildings 21% is expected to be heavy 92

108 debris (concrete and steel), requiring heavy equipment to break down and remove, while 79% is expected to be light debris (wood, brick, drywall and other debris). While 2 bridges in the county s transportation system are expected to suffer minor flood damage, the bridges are expected to remain functional. Table 4-34 provides an overview of essential facility performance in the 500-year flood (with levees) scenario. The table lists the number of essential facility sites and buildings (these numbers will differ for multi-building campuses, such as schools and hospitals). The table also provides the total building replacement value, and the number of buildings for which value data was available. As can be seen in the table, replacement cost data for hospitals was generally not available, unlike most other essential facility types. Expected building damage in this flooding event ranges from as little as less than 0% damage for numerous essential facility types with some, but minimal, flooding, to as much as 24% damage for hospitals. Total economic loss for essential facilities has been estimated to reach about $34 million, almost 70% of which ($24 million) will occur in schools and 27% of which will occur in hospitals ($9 million). 93

109 94 Table 4-34 Honolulu County Essential Facility Loss Estimates 500-Year Flood (Levees Intact) Essential Facility Category No. of Facilities/ Sites No. of Buildings No. of Beds Replacement Cost ($1,000) # Buildings w/ replacement cost data # Non- Functional Buildings Time to Restore (Days) Economic Loss ($1,000) Small 73 1,431 $315,320 Medium $24,780 Hospital Large 5 2,251 $82, $8,938 K $2,063, $23,717 Schools UH-Manoa $1,491, $0 EOCs 7 7 $6, $0 Police Stations $42, $796 Fire Stations $30, $735 TOTALS ,925 $4,057, $34,186

110 Number of Buildings Replacement Cost ($1,000) # Buildings w/ replacement cost data No. Non- Functional Buildings Restoration Time (Days) Mean Building Damage Economic Loss ($1,000) Tables 4-35 through 4-39 provide additional detail for fire stations, EOCs, police facilities, schools, and hospitals, respectively. Figures 4-34 through 4-38 provide maps of Fire Station, EOC, Police Facility and School functionality, overlain onto a map of the 500-year county floodplain/depth grid. As shown in the tables and displayed on the maps, the expected impact to individual agencies and structures may vary considerably across the County. In general, essential facilities in the more flood prone west/northwest portion of the county are more likely to experience flood damage. Table 4-35 Estimated Impacts on Honolulu County Fire Stations in a 500-Year Flood (Levees Intact) Agency Honolulu County 43 $30, % $735 Figure 4-34 Honolulu County Fire Station Functionality Following a 500-Year Flood (Levees Intact) 95

111 Table 4-36 Estimated Impacts on Honolulu County EOCs in a 500-Year Flood (Levees Intact) County No. of Buildings Replacement Cost ($1,000) No. Non- Functional Buildings Restoration Time (Days) Mean Damage Economic Loss ($1,000) Honolulu 7 $6, % $0 Figure 4-35 Honolulu County EOCs Functionality Following a 500-Year Flood (Levees Intact) Table 4-37 Estimated Impacts on Honolulu County Police Facilities in a 500-Year Flood (Levees Intact) # Non- Time to Economic Number of Replacement Mean County Functional Restore Loss Buildings Cost ($1,000) Damage Buildings (Days) ($1,000) Honolulu 14 $42, % $796 96

112 Figure 4-36 Honolulu Police Facilities Functionality Following a 500-Year Flood (Levees Intact) 97

113 Number of Facilities/ Sites* No. of Buildings Replacement Cost ($1,000) # Buildings w/ replacement cost data # Non-Functional Buildings Restoration Time (Days) Mean Damage Economic Loss ($1,000) Table 4-38 Estimated Impacts on Honolulu School Districts in a 500-Year Flood (Levees Intact) Schools K $2,063, % $23,717 UH-Manoa $1,491, % $0 TOTALS $3,554, % $23,717 Figure 4-37 Honolulu County School Districts Functionality Following a 500-Year Flood (Levees Intact) 98

114 No. of Hospital Sites Number of Buildings Number of Licensed Beds Replacement Cost ($1,000) No. Buildings w/ replacement cost data # Non-Functional Buildings Restoration Time (Days) Mean Damage Economic Loss ($1,000) Table 4-39 Estimated Impacts on Honolulu County Hospitals in a 500-Year Flood (Levees Intact) County Honolulu 80 3,925 $4,057, % $8,938 Figure 4-38 Honolulu County Hospital Functionality Following a 500-Year Flood (Levees Intact) 99

115 Enhanced Essential Facilities Summary Reports Global summary reports of both the earthquake, wind, and flood scenarios are included in Appendix A, B, and C, respectively. These reports provide an overall description of the building inventory, modeled scenario, damage to the general building stock, functionality of the essential facilities, injuries/casualties caused by the event, and economic losses. Economic losses to the general building stock reported from the earthquake scenario total close to $75 Million, while much higher losses in the order of $26.2 Billion in property damage were recorded for the wind event. For each of the flood events, economic losses to the general building stock reported $2.3 Billion, $3 Billion, and $4.4 Billion in property damage for the 100-Year with Levees, 100-Year without Levees, and 500-Year with Levees scenarios, respectively. Table 4-40 is the comprehensive risk assessment summary of essential facilities in the improved model analysis of 985 buildings for earthquake and wind hazards. Table Total Losses Based on Updated HAZUS Essential Facility Data Hurricane Event Total Losses Essential Facilities $637,495,287 Hurricane Event Total Losses General Building Stock $26,234,352,000 Earthquake Event Total Losses Essential Facilities $3,082,997 Earthquake Event Total Losses General Building Stock $75,000,000 Flood Event Total Losses 100 with Levees Essential Facilities $16,339,000 Flood Event Total Losses 100 with Levees General Building Stock $2,296,600,000 Flood Event Total Losses 100 without Levees Essential Facilities $21,321,000 Flood Event Total Losses 100 without Levees General Building Stock $3,037,820,000 Flood Event Total Losses 500 with Levees Essential Facilities $34,186,000 Flood Event Total Losses 500 with Levees General Building Stock $4,442,940, Enhanced Essential Facilities Risk and Vulnerability Ranking As discussed previously in Section 4.2.2, Table 4-41 identifies the essential facilities that the county can focus on first in order to reduce their overall risk most efficiently ranked by economic losses and loss of functionality. Health care and emergency shelters are at highest risk. Tables 4-42 and 4-43 provides further details on the facility and the expected losses that lead to its risk ranking. The $ loss rank value is the rank of the losses of an individual building compared to the losses of all other essential facilities. 100

116 Table 4-41 Summarized Vulnerability List of Highest Risk Facilities by Hazard Type of Risk Considered Hazard List of the Most Vulnerable Buildings for each hazard and for each type of risk, in order of risk Economic Loss due to Functionality Loss due to Wind Earthquake Flood Wind Earthquake Flood Stevenson Middle - Bldg A Queens Medical Center Tripler Army Medical Center St. Francis Medical Center Maluhia Elderly Care Lanakila Health Center Leahi Hospital Solomon - Bldg B Hawaii State Hospital Straub Kapolei Family Health Kaiser Kapolei Clinic Roosevelt High - Bldg A Castle Medical Center Campbell High - Bldg D Puuhale - Bldg A Straub Clinic & Hospital Kapiolani Medical Center Kaiser High - Bldg H Kuakini Medical Center Kaiser Honolulu Clinic Kaiser High - Bldg L Kaiser High - Bldg A Wahiawa General Hospital Kamiloiki - Bldg C Kamiloiki - Bldg A Kaiser Kahuku Clinic Kahuku High & Intermediate Bldg W Straub Hawaii Kai Family Health Kalani High Bldg C Kahuku High & Intermediate Bldg V Kaiser Kailua Clinic Kaiser Kailua Clinic Kaiser Kailua Clinic Kaiser Kailua Clinic Straub Kailua Family Health Center Red Hill - Bldg A Solomon - Bldg P21 Solomon - Bldg P22 Solomon - Bldg P23 Kawananakoa Middle - Bldg H Kawananakoa Middle - Bldg F Kawananakoa Middle - Bldg G Shafter - Bldg B Manoa - Bldg E Makakilo - Bldg K Kawananakoa Middle - Bldg D Stevenson Middle - Bldg C Pauoa - Bldg E Shafter - Bldg C Kaiulani - Bldg F Straub Hawaii Kai Family Health Kaiser High - Bldg B Kamiloiki - Bldg E Koko Head - Bldg P3 Koko Head - Bldg P4 Koko Head - Bldg P5 Koko Head - Bldg P6 Kaiser Kahuku Clinic Kahuku High & Intermediate Bldg W Straub Hawaii Kai Family Health Kalani High Bldg C Kahuku High & Intermediate Bldg V 101

117 Kaiser Kailua Clinic Kaiser Kailua Clinic Kaiser Kailua Clinic Kaiser Kailua Clinic Straub Kailua Family Health Center 102

118 High Loss of Functionality - UH Manoa Earthquake Hurricane High Modeled Losses - UH Manoa Earthquake Hurricane Earthquake High Loss of Functionality Hurricane Earthquake High Modeled Losses Hurricane Table Essential Facility Risk Ranking Based On Enhanced Dataset For Hurricane And Earthquake Honolulu County Essential Facilities - Vulnerability List Total Number of Modeled Buildings = Description 985 Category 2 - Ewa Hurricane Event Vulnerability Lanai Earthquake Scenario Vulnerability Building Name Facility Classification Year Built EQ Bldg Type Design Level Soil Type Modeled Building $ Loss $ Loss Rank* Modeled Building $ Loss $ Loss Rank Stevenson Middle - Bldg A School 1951 W1 PC D WSF2 $ 5,106, $ 5, Queens Medical Center CareFlty UNK C2H PC B CERBH $ 4,291, $ 241, Tripler Army Medical Center CareFlty 1945 C2H PC C CERBH $ 3,956, $ 66, St. Francis Medical Center CareFlty UNK C2H PC C CERBH $ 3,036, $ 66, Maluhia Elderly Care CareFlty 1931 W2 PC D WSF1 $ 2,310, $ 2, Lanakila Health Center CareFlty UNK W2 PC D WSF1 $ 2,310, $ 2, Leahi Hospital CareFlty UNK C2M PC B CERBM $ 2,204, $ 81, Solomon - Bldg B School 1969 W1 PC B WSF2 $ 2,074, $ Hawaii State Hospital CareFlty UNK W2 PC D WSF1 $ 1,952, $ 2, Straub Kapolei Family Health CareFlty 1999 W2 LS C WSF2 $ 1,787, $ Kaiser Kapolei Clinic CareFlty 1999 W2 LS B WSF2 $ 1,735, $ Roosevelt High - Bldg A School 1932 W1 PC D WMUH3 $ 1,704, $ 8, Castle Medical Center CareFlty 2002 C2L LS B CERBL $ 1,611, $ 1, Campbell High - Bldg D School 1975 RM1L PC C MERBL $ 1,585, $ 3, Puuhale - Bldg A School 1972 W1 PC C WSF2 $ 1,583, $ 3, Straub Clinic & Hospital CareFlty 1962 C2H PC D CERBM $ 652, $ 60, Kapiolani Medical Center CareFlty 1976 C2H PC D WSF2 $ 670, $ 60, Kaiser High - Bldg H School 1973 RM1L PC C MERBL $ 651, $ 34, Kuakini Medical Center CareFlty 1968 C2M PC D CERBH $ 463, $ 20, Kaiser Honolulu Clinic CareFlty UNK C2M PC D CERBM $ 514, $ 20, Kaiser High - Bldg L School 1974 RM1L PC C MERBL $ 199, $ 10, Kaiser High - Bldg A School 1971 RM1L PC C MERBL $ 189, $ 10, Wahiawa General Hospital CareFlty UNK RM1L PC C MERBL $ 1,345, $ 9, Kamiloiki - Bldg C School 1971 RM1L PC C MERBL $ 318, $ 8, Kamiloiki - Bldg A School 1973 RM1L PC C MERBL $ 308, $ 8, Red Hill - Bldg A School 1974 W1 PC C WSF2 $ 1,031, $ Solomon - Bldg P21 School 1994 W1 HC B WSF1 $ 87, $ Solomon - Bldg P22 School 1994 W1 HC B WSF1 $ 87, $ Solomon - Bldg P23 School 1994 W1 HC B WSF1 $ 87, $ Kawananakoa Middle - Bldg H School 1939 W1 PC D WSF2 $ 1,272, $ 1, Kawananakoa Middle - Bldg F School 1960 W1 PC D WSF2 $ 611, $ Kawananakoa Middle - Bldg G School 1960 W1 PC D WSF2 $ 582, $ Shafter - Bldg B School 1966 W1 PC C WSF2 $ 1,057, $ Manoa - Bldg E School 1952 W1 PC D WSF1 $ 565, $ Makakilo - Bldg K School 1969 W1 PC B WSF1 $ 488, $ Kawananakoa Middle - Bldg D School 1962 W1 PC D WSF1 $ 657, $ Stevenson Middle - Bldg C School 1954 W1 PC D WSF1 $ 311, $ Pauoa - Bldg E School 1969 W1 PC C WSF1 $ 600, $ Shafter - Bldg C School 1968 W1 PC C WSF1 $ 354, $ Kaiulani - Bldg F School 1970 W1 PC C WSF2 $ 526, $ Straub Hawaii Kai Family Health CareFlty UNK W2 PC D WSF1 $ 155, $ 7, Kaiser High - Bldg B School 1971 W1 PC C WSF1 $ 49, $ 1, Kamiloiki - Bldg E School 1975 W1 PC C WSF1 $ 92, $ 1, Koko Head - Bldg P3 School 1967 W1 PC C WSF1 $ 25, $ Koko Head - Bldg P4 School 1967 W1 PC C WSF1 $ 21, $ Koko Head - Bldg P5 School 1967 W1 PC C WSF1 $ 21, $ Koko Head - Bldg P6 School 1967 W1 PC C WSF1 $ 21, $ Hamilton Library School - UH Manoa 1968 C2M PC D CERBM $ 21,712, $ 168, Pacific Ocean Science & Technology (POST) School - UH Manoa 1995 C2H HC D CERBH $ 16,791, $ 23, Biomedical Sciences Building School - UH Manoa 1972 C2H LC D CERBH $ 13,776, $ 82, St. John Laboratory Complex School - UH Manoa 1969 C2M PC D CERBM $ 9,445, $ 73, Stan Sheriff Center School - UH Manoa 1994 C1L HC B CERBL $ 9,442, $ 5, Agricultural Science Facility School - UH Manoa 1995 C2M HC D CERBM $ 8,318, $ 15, Marine Sciences Building School - UH Manoa 1984 C2M HC D CERBM $ 8,246, $ 14, Art Building School - UH Manoa 1974 C2L LC D CERBL $ 7,825, $ 15, Holmes Hall School - UH Manoa 1972 C2M LC D CERBM $ 6,648, $ 9, Saunders Hall School - UH Manoa 1973 C2M LC B CERBM $ 6,566, $ 9, Snyder Hall School - UH Manoa 1962 C1M PC D CERBM $ 4,507, $ 73, Sinclair Library School - UH Manoa 1956 C1L PC D CERBL $ 6,146, $ 70, Gartley Hall School - UH Manoa 1921 URMM PC D MMUH3 $ 752, $ 48, Hawaii Institute of Geophysics (Geophysics Institute Building) School - UH Manoa 1963 C2M PC D CERBM $ 5,708, $ 44, Moore Hall School - UH Manoa 1969 C2M PC D CERBM $ 4,998, $ 38, Kuykendall Hall School - UH Manoa 1964 C2M PC D CERBM $ 4,934, $ 38, Dean Hall School - UH Manoa 1929 URMM PC D MMUH3 $ 576, $ 37, Keller Hall School - UH Manoa 1959 C2L PC D CERBL $ 4,070, $ 23, Auxiliary Services School - UH Manoa 1962 C1L PC D CERBL $ 2,015, $ 23, Bilger Hall School - UH Manoa 1952 C2L PC D CERBL $ 3,722, $ 21, HECO Substation School - UH Manoa 1998 RM2L HC B MSF2 $ 498, $ Miller Hall School - UH Manoa 1939 RM1L PC D MMUH3 $ 592, $ 4, Maintenance Warehouse School - UH Manoa 1963 S1L PC D SPMBS $ 1,120, $ Hawaii Hall School - UH Manoa 1912 S2L PC D SERBL $ 1,828, $ 8, Kennedy Theatre School - UH Manoa 1963 RM2L PC D MERBL $ 2,137, $ 18, Bachman Hall School - UH Manoa 1949 RM2L PC D MERBL $ 1,389, $ 11, University Health Services School - UH Manoa 1963 RM1L PC D MERBL $ 489, $ 2, Physical Plant Building School - UH Manoa 1963 RM1L PC D MMUH1 $ 77, $ Auxiliary Services School - UH Manoa 1962 C1L PC D CERBL $ 2,015, $ 23, University High School #3 School - UH Manoa 1957 C1L PC D CERBL $ 963, $ 15, Webster Hall School - UH Manoa 1961 C2M PC D CERBM $ 2,683, $ 20, Edmundson Hall School - UH Manoa 1963 C2M PC D CERBM $ 1,958, $ 15, Spalding Hall School - UH Manoa 1961 C2M PC D CERBM $ 1,487, $ 11, Wind Building Type Loss of Functionality (Num. of Days) Loss of Functionality (Num. of Days) 103

119 The University of Hawaii at Manoa essential buildings are those indicated by the University to be essential core operational buildings. The University of Hawaii essential facilities are the 57 core buildings identified by UHM as being essential to maintaining operation of the entire campus of nearly a thousand buildings. The University of Hawaii system has a Hazard Mitigation Plan of its own, separate from the Honolulu Hazard Mitigation Plan. Therefore, the priorities for the UHM campus are separately identified. Table Essential Facility Risk Ranking Based On Enhanced Dataset For Flood 104