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Estimating Losses from Future Earthquakes (1989)

Chapter: WORKING PAPERS

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Suggested Citation:"WORKING PAPERS." National Research Council. 1989. Estimating Losses from Future Earthquakes. Washington, DC: The National Academies Press. doi: 10.17226/1361.
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Working Paper A Types and Examples of Loss Estimation Studies Potential users of loss estunates have different objectives, and a loss estimate study can only be called successful when it meets the purposes for which it is intended. Loss estunate studies can be categorized according to: type of losses estimated, kinds of facilities encompassed, certainty and detail, time span, and geographic scope. These considerations can be combined in a variety of ways in a particular study, and it would be impossible to discuss all of them. The categorization scheme depicted in Figure A-1 is only one way of structuring this subject matter. Other ways of categorizing and ana- lyzing earthquake loss estimation methods may be found in reviews of the field conducted from the 1930s to the present by Freeman (1932), McClure (1973), Boissonade and Shah (1982), Steinbrugge (1982, 1986), Reitherman (1985), Scawthorn (1986), and Whitman (1986~. Table A-1 divides earthquake loss estimation methods into five basic types, which can be characterized in terms of the combination of aspects presented in Figure A-1. Type I: General Type IT: Hazard Reduction Type IlI: Emergency Planning Type IV: Financial Risk ~ Type V: Economic Impact The methods presented in Figure A-1 all have a low degree of 85

86 TYPE OF LOSS Monetary cost of damage Casualties Homeless Functionality of essential facilities Safety problems of potentially high hazard facilities Economic impact National security KINDS OF FACILITIES Selected facilities (e.g., occupancy, ownership, construction) Essential facilities Lifeli nes Large potential for loss All buildings or structures CERTAINTY DETAI L high low high low TIME SPAN Hypothesized (scenario) Cumulative set of Predicted Actual earthquake earthquakes to earthquake earthquake occur in time span , ~ , G EGG RAPH IC SCALE Local Regional/state National FIGURE A-1 Aspects of earthquake loss estimation studies. certainty, which reflects the inherent uncertainty in the field of earth- quake loss estimation and is not necessarily indicative of method- ological errors or weaknesses in any particular method. In many engineering applications, the term accurate connotes a method that can reliably produce estimates that do not deviate much, say no more than perhaps 10 percent, from the actual results. Earthquake loss estimation methods that ace reliably of such accuracy (even in the case of facility-specific studies with high levels of effort) do not exist. Earthquake loss estimates that might prove to be in error by a factor of 3* are often considered accurate in this field. The word certainty is used here to describe the degree of confidence in a Toss estimate; an estimate with low certainty will have a large range of uncertainty *See footnote 2 in Chapter 4.

87 TABLE A-1 Purposes, Users, and Examples of Types of Lose Estimation Studies Type of Study Purpose Users Examples I: General Identify the general scope General public J. H. Wiggins of the earthquake problem as well as Company and to establish a basis for all other Engineering planning, prioritizing, users listed Geologists, and funding earthquake below Inc.1979; risk reduction efforts Algermissen et al., 1972 II: Hazard Guide hazard reduction Legislative, Alfors et al., reduction actions to reduce regulatory 1973; Ward, physical damage bodies; 1986; Office government of State officials Architect, and staffs; 1982; Los utilities and Angeles City corporations Planning Department, 1980 III: Emergency Facilitate more efficient Emergency Algerminsen planning emergency response response et al., 1972; agencies; D avis et al., utilities 1982a,b and corporations IV: Financial Rate earthquake risks of Insurance, Freeman, 1932; individual properties or mortgage California collective risk of lending, and Department of portfolios investment Insurance, industries 1985; Working Group Earth- quake Hazard Reduction, 1978 V: Economic Estimate economic losses National Applied impact (including indirect, security Technology long-term economic agencies and Council, 1985 impacts) national or regional planners about the best estimate, and conversely one with high certainty will have a small range of uncertainty. Specific examples of loss studies follow. TYPE I: GENERAL An example of this broadest type of loss study is the research

88 funded by the National Science Foundation (NSF) that produced property loss estimates for earthquakes as well as floods, expansive soil, landslides, hurricanes, and tornadoes Hi. H. Wiggins Company and Engineering Geology Consultants, Inc., 1979) for cumulative property losses during the years 1970 to 2000. Life loss was also estimated to some degree as well as the reduction in losses that could be expected by application of hazard reduction actions. The scope of such a study is very broad both geographically and in terms of considering more than one hazard. Although the results are more aggregated and less certain than those from studies focus- ing on an individual region and only one hazard, such comprehensive estimates are needed. Comparisons among hazards, between the con- tinuation of policies or the initiation of certain preventive actions and between the losses that would likely occur In the near term versus the Tong term, can be useful decision-making tools, especially at the national policymaking level. This type of study also enables compar- isons between the relative degree of risk faced by different states in relation to fixed analytical benchmarks, in contrast to comparisons of Tosses resulting from scenario events that vary in likelihood from one study to another. General studies are necessary if the intended application, such as selecting among policy options and evaluating the effectiveness of loss reduction programs, requires statements that say, for exam- ple: "Unless significant new steps are taken, the costs of replacing or repairing buildings destroyed and damaged by the nine natural hazards studied, during a typical year, are likely to increase more than 85 percent in the Midyear period between 1970 and 2000" Hi. H. Wiggins Company and Engineering Geologists, Inc., 1979~. Figure A-2 illustrates the characteristics combined in Type national-scale Toss estunation study using the above-mentioned study as the example. The types of losses estunated by such a study may vary, but two basic components are direct monetary cost of damage and casualties. The time variable is defined In terms of the cumulative losses estimated to occur in a given time span, in this case 197(}2000. The scope in terms of the kinds of facilities extends to all buildings, and both certainty and detail are relatively low. This study could also qualify as a Type T! (hazard reduction) study, which illustrates the overlap between categories. Regional Type ~ studies have fulfilled a variety of purposes, perhaps their most frequent use being as an emergency planning resource. The first of the studies (AIgermissen et al., 1972) sponsored

89 TYPE OF LOSS · Monetary cost of damage · Casualties Homeless Functionality of essential facilities Safety problems of potentially high hazard facilities Economic impact National security KINDS OF FACILITIES Selected facilities (e.g., occupancy, ownership, construction) Essential facilities Lifelines Large potential for loss · All buildings or structures CERTAINTY DETAIL · high low high low TIME SPAN Hypothesized (scenario) earthquake · Cumulative set of Predicted Actual earthquakes to earthquake earthquake occur in time span l GEOGRAPHIC SCALE Local Regional/state · National FIGURE A-2 Aspects of a Type I, national-scale loss estimation study, using the example of J. H. Wiggins and Engineering Geology Consultants, Inc. (1979~. Key: · = aspects that pertain to this type of study. by the National Oceanic and Atmospheric Administration (NOAA) is a typical example of a Type ~ regional-scale study. This study of the San Francisco area projects a broad range of losses. Later NOAA and U.S. Geological Survey (USGS) studies are quite similar in their broad scope. (~n the mid-1970s, earthquake loss estimation projects and staff were shifted from NOAA to USGS with no significant change in the type of studies undertaken nor the methods used.) Casualties were estimated by time of day, by county, and according to hazard sources, that is, casualties that would occur within hospitals, schools, or dwellings are differentiated from other injuries and fatalities. Outages of utility services, transportation routes, and other types of functional losses suffered by lifelines were estimated. Property lodes involved only single-family dwellings. An updating loss study (Steinbrugge et al., 1981) also estimated property

go losses for commercial and most other building types. Figure A-3 shows the table of contents from the first NOAA study in order to indicate its scope, which is sunilar to later NOAA-USGS studies. Type ~ studies are often the first type of study to be conducted in a region. They are essential tools of seismic safety advocacy. As public policy, earthquake hazard reduction, or emergency planning activities develop, other studies with narrower foci may be conducted to support more specialized risk reduction efforts. Type ~ study elements are often adapted for use in other kinds of studies, and in some cases a Type ~ study can serve some of the more specific purposes requiring Type Il. Ill, IV, or V studies (Figure Add. The regional-scale study ~ much finer in detail than a national study, but at the cost of a smaller geographic scope. This trade-off between covering a larger area at a shallower level versus a smaller area in-depth is an inescapable constraint on all earthquake loss estimation studies. Figure A-4 categorizes a Type ~ regional study as including all but the overall econorn~c Trip act and national security types of losses; it may include the entire range of kinds of facilities. Its Toss statements have usually been predicated upon scenario events, and the certainty and especially its detail are greater than in the case of national-scale studies. In most cases, it is unportant that the study area boundaries or subarea boundaries match political boundaries demarcating cities or counties. TYPE II: HAZARD REDUCTION Type IT studies primarily support hazard reduction efforts, and the primary user is government agencies which adopt building codes regulating new construction or retroactive ordinances pertaining to existing hazardous facilities, land-use plans, and other laws and poli- cies. Type ~ studies are often used for this purpose, but Type IT studies emphasize this hazard reduction purpose with more specific reference to the codes, ordinances, voluntary standards, or other concrete policy options under consideration, and limit their scope to the specific physical hazards, resources, or jurisdictions of interest. On a state scale, cumulative losses over future time spans have been estimated in studies of California (Alfors et al., 1973) and Utah (Ward, 1986~. These two studies fit the pattern shown in Figure A-5, with the scope of the California study extending to all buildings and the Utah study focusing on particular types of facilities, such as schools and hospitals. By using a multidecade time

91 Table of Contents PART A: ISOSEISMAL STUDIES. PART B: CASUALTIES AND DA\lAG E Section 1: Introduction Section 2: Bases for Analysi s Section 3: Effects on Local Medical Resources Major Hospitals Health Manpower. Medical Supplies . Bloodbanks Hospital Reserve Disaster Inventory (HRDI) Modules . Packaged Disaster Hospitals . Clinical Laboratories . . . . . . . . Ambulance Services . Nursing Homes Section 4: Demands on Medical Resources . Deaths and Inj uric s, Ex eluding Dam s Dams . . · · ~ Section 5: Effects on Immediate and Vital Public Needs Public Structures . Communications Transportation. Public Utilities. . Schools . . . . . . . . . c ~ . Mercantile, Industrial ~ and Warehousing . Homeless . ~ . . Fire Following Earthquake Selected Bibliography . . . 1 8 34 34 55 61 68 76 80 87 93 102 108 108 126 · · ~ 133 133 146 153 172 i88 194 200 208 215 FIGURE A-3 Table of contents of the first of the joint National Oceanic and Atmospheric Administration and U.S. Geological Survey studies. Source: Algermissen et al. (1972~.

92 TYPE OF LOSS Monetary cost of damage · Casualties · Homeless · Functionality of essential facilities Safety problems of potentially high hazard facilities Economic impact National security r '~ KINDS OF FACILITIES Selected facilities (e.g., occupancy, ownership, construction) Essential facilities Lifeli nes Large potential for loss · All buildings or structures CERTAINTY DETAIL · ~ high low high low TIME SPAN · Hypothesized (scenario) Cumulative set of Predicted Actual earthquake earthquakes to earthquake earthquake occur in time span . . GEOGRAPHIC SCALE Local · Regional/state National FIGURE A-4 Aspects of a Type I, regional-scale loss estimation study, using the example of Algermmsen et al. (1972~. Key: · = aspects that pertain to this type of study. span and estimating cumulative losses, these studies provide a way for policymakers to develop long-term risk reduction strategies. The study of 229 hospitals having 1,077 buildings in six southern California counties (Office of State Architect, 1982) is a Type IT study of a large urban region within one state, with the scope limited to one kind of occupancy. Vuinerabilities were rated without regard to scenario or cumulative losses. On a broader geographic scale, limited also to one kind of facility, a survey of 800 major buildings on University of California campuses was conducted (McClure, 1984~. Losses in this case were estimated in terms of the relative risks faced by building occupants, assuming the buildings were subjected to the same strong level of shaking. These last two examples of studies indicate that for some hazard reduction purposes, relative

93 TYPE OF LOSS · Monetary cost of damage Casualties Homeless Functionality of essential facilities Safety problems of potentially high hazard facilities Economic impact National security KINDS OF FACILITIES Selected facilities (e.g., occupancy, ownership, construction) Essential facilities Lifeli nes Large potential for loss · All buildings or structures _ CERTAINTY DETAI L · ~ high low high low TIME SPAN Hypothesized (scenario) earthquake · Cumulative set of Predicted Actual earthquakes to earthquake earthquake occur in time span GEOGRAPHIC SCALE Local · Regional/state National E`IGURE A-5 Aspects of a Type II, state-scale loss estimation study, using the examples of Alfors et al. (1973) and Ward (1986~. Key: · = aspects that pertain to this type of study. risk ratings rather than estimated numbers of casualties In a given scenario earthquake may be the appropriate goal of the analysis. An example of a local-scale hazard reduction study is the en- vironmental impact report accompanying an ordinance that went into effect in Los Angeles in 1981 requiring the hazards of about 8,000 unreinforced masonry buildings to be reduced (Los Angeles City Planning Department, 19803. In this study, only one kind of structure was studied, only life losses were of concern, the time span was in terms of a future scenario earthquake, and the certainty and detail were higher than with typical Type ~ studies (Figure A-6. This Toss estimate study was calibrated with the earlier NOAA study of losses estimated for a broader area and without an explicit breakdown of casualties related to classes of construction (AIgermis- sen et al., 1973~. The 1980 L08 Angeles study provided the conclusion

94 TYPE OF LOSS Monetary cost of damage ·Casualties Homeless Functionality of essential facilities Safety problems of potentially high hazard facilities Economic impact National security Kl N DS OF FACI LITI ES · Selected facilities (e.g., occupancy, ownership, construction) Essential facilities Lifeli nes Large potential for loss All buildings or structures CERTAINTY DETAIL · ~ high low high low TIME SPAN · Hypothesized (scenario) Cumulative set of Predicted Actual earthquake earthquakes to earthquake earthquake occur in time span _ . GEOGRAPHIC SCALE I · Local Regional/state National FIGURE A-6 Aspects of a Type II, local-scale lose estimation study, using the example of Los Angeles City Planning Department (1980~. Key: ~ = aspects that pertain to this type of study. that in a great earthquake (the same scenario earthquake used in the 1973 NOAA study), the number of fatalities within the city would de- cTine from 8,500 to 1,500 if the retroactive standards for unreinforced brick buildings were implemented. TYPE m EMERGENCY PLANNING The NOAA-USGS study (Type I) also fits this category, but another example is the work done by the California Division of Mines and Geology to identify functional losses to lifelines in the urban areas of Los Angeles (California Division of Mines and Geology, in progress; Davis et al., 1982a) San Francisco (Davis et al., 1982b; Steinbrugge et al., in progress), and San Diego (ReichIe et al., in progress). The characteristics of this type of study, at the regional scale, are shown

95 TYPE OF LOSS Monetary cost of damage Casualties Homeless · Functionality of essential facilities Safety problems of potentially high hazard facilities Economic impact National security KINDS OF FACILITIES Selected facilities (e.g., occupancy, ownership, construction) Essential facilities · Lifelines Large potential for loss All buildings or structures CERTAINTY DETAIL high low high low Tl M E SPAN · Hypothesized (scenario) Cumulative set of Predicted Actual earthquake earthquakes to earthquake earthquake occur in time span rim ~ GEOGRAPHIC SCALE Local · Regional/state National FIGURE A-7 Aspects of a Type III, regional-scale loss estimation study, using the examples of Davis et al. (1982 a,b). Key: ~ = aspects that pertain to this type of study. in Figure A-7. When such a study is devoted to a smaller geographic area, the detail of the results increases, as shown by the finer scale of the maps used to portray the results. The fire department of Orange County, California has extended the detail of one type of emergency planning study concerning transportation routes to the level of the neighborhood surrounding each fire station, looking at each roadway route that leads from the station to the outside area and considering potential route blockages such as collapsing bridges or building debris (C. Nicola, Orange County, California, Fire Department, personal communication, 1986~. This might be called the "street map" scale of Type ITI studies.

96 TYPE IV: FINANCE RISK This type of study is distinguished by its focus on direct prop- erty loss and the fact that its prunary user for many decades has been the insurance industry, and to a lesser extent the mortgage lending and investment industries. Several examples are provided in an earlier, widely published work in the field of earthquake loss es- timation, Earthquake Damage and Earthquake Insurance (Freeman, 1932~. Freeman produced regional-scale property loss estimates for all areas of the United States; the nature of this study is diagrammed in Figure A-8. Another study that fits this pattern of a state- or regional-scale financial study is the annually updated report issued by the Department of Insurance in California, which estimates aggre- gate losses in each of the various regional-scale zones of the state for properties covered by earthquake insurance (California Department of Insurance, 1985~. In these two cases, the rating of the risk of experiencing prop- erty damage or insurance losses extends essentially to Al buildings, and the intended user is broadly defined as the property insurance industry or government regulators having industry-wide insurance concerns. Some Type IV studies conducted for a given company, however, limit themmeIves to a smaller scope those facilities that are contained in that particular company's portfolio of insured, fi- nanced, or owned properties. An appendix to a comprehensive report by the Office of Science and Technology Policy (OSTP) discussed one particular aspect of the subject matter that falls under the heading of Type IV studies: the risk faced by various sectors of the financial industry during certain possible earthquake prediction situations (Working Group on Earthquake Hazards Reduction, 1978~. This analysis pointed out the need to divide a financial sector, such as mortgage lending, into smaller categories when analyzing earthquake risk, because of the different characteristics in terms of assets, liabilities, income, and expenses of institutions such as commercial banks, savings and loans establishments, and life insurance companies. This type of study is an exception to the rule that financial risk studies generally focus on the monetary cost of damage as the type of loss of concern. TYPE V: ECONOMIC IMPACT Type V studies deal with the decrease in the economy's pro- duction of goods and services that might result months after the

97 TYPE OF LOSS Monetary cost of damage Casualties Homeless Functionality of essential facilities Safety problems of potentially high hazard facilities Economic impact National security KINDS OF FACILITIES Selected facilities (e.g., occupancy, ownership, construction) Essential facilities Lifelines Large potential for loss · All buildings or structures _ , CERTAINTY DETAI L high low high low T TIME SPAN · Hypothesized (scenario) ~ Cumulative set of Predicted Actual earthquake earthquakes to earthquake earthquake occur in time span GEOGRAPHIC SCALE Local · Regional/state National FIGURE A-8 Aspects of a Type IV, regional-scale loss estimation study, using the example of Freeman tl932~. Key: ~ = aspects that pertain to this type of study. earthquake, rather than just the unmediate damage. The most re- cent effort of this type has been initiated by the Federal Emergency Management Agency (FEMA). The ATC-13 study is the engineering component of the overall FEMA method that will use the ATC-13 estimates of initial damage and decrease in functionality to forecast the effects on local, regional, and national economies and national security. Therefore, the ATC-13 method may also be thought of as a Type I, general-purpose loss estunation technique. The primary motivation for the ATC-13 study was concern over the ability of de- fense industries to supply militarily essential products after a major C)aTifornia earthquake, and it was requested by the National Security Council (NSC). Figure A-9 illustrates the basic characteristics of this proposed type of study (which has to date been implemented only In pilot projects). The ATC-13 or earthquake engineering portion of

98 TYPE OF LOSS · Monetary cost of damage ·Casualties · Homeless Functionality of essential facilities Safety problems of potentially high hazard facilities · Economic impact · National security KINDS OF FACILITIES Selected facilities (e.g., occupancy, ownership, construction) Essential facilities Lifeli nes Large potential for loss · All buildings or structures CERTAINTY DETAI L high low high low TIME SPAN · Hypothesized (scenario) Cumulative set of Predicted Actual earthquake earthquakes to earthquake earthquake occur in time span GEOGRAPHIC SCALE l · Local · Regional/state ·National FIGURE A-9 Aspects of a Type V, regional-scale loss estimation study, using the example of FEMA Fedloss Method and its ATC-13 engineering component (Applied Technology Council, 1985~. Key: · = aspects that pertain to this type of study. this overall economic loss modeling method could also be applied to other purposes and diagrammed differently, but is outlined here in the context of its original purpose. ATC-13 as of this date has not been used to produce a complete, published loss study. Much detail exists with the FEMA/ATC-13 type of study be- cause its aim was to clevelop an inventory of almost every facility according to about 500 econorn~c sectors for most of the state of California. It makes precise statements about the amount of damage and the functional loss that could be suffered in each facility. It includes industrial tanks, tunnels, and other nonbuilding structures in greater detail than other methods. The AT~13 method devel- ops losses on the scale of each individual factory, for exan~ple, first estimating damage and then determining the number of days after

99 the earthquake before 30 percent, 60 percent, and 100 percent of pre-earthquake functioning is restored. Because hard data or relatively accurate field-acquired informa- tion describing the construction characteristics of all buildings in a region do not exist, and because of few data on the connection between building damage and loss of function, the ATC-13 method provides inferences for constructing an inventory from readily avail- able socioeconomic data bases. Expert opinion was used to develop damage and loss relationships for a large number of types of facilities. The ATC-13 example is a reminder that when great detail is sought on a large scale requiring that the loss estimation method answer a number of difficult questions in a detailed, quantitative way—certainty must be sacrificed. Widely accepted, easily applied, and objective ways of rating the certainty of loss estimate methods do not exist, and the issue of what constitutes acceptable certainty or acceptable detail can be decided only by reference to the fitness of the study for its intended purpose. This again brings up the important subject of the users and uses of loss estimation studies, a theme throughout this report.

Working Paper B User Needs IDENTIFICATION OF THE USER CO~IUNITY Early in the panel's deliberations it became clear that one of the most important considerations in exarn~ning the different methods of estimating earthquake losses would be the users' needs. This required defining who the users were so that their particular needs could be reflected in the panel's assessment of different loss estimation methods. Many different groups and sectors potentially could have been included as users. A subpanel developed several sampling strate- gies, as well as research designs for a comprehensive study of user groups. For example, the panel could have considered the needs of such diverse elements as federal, state, and local adrn~nistrators and officials, insurance companies, bonding companies, social scientists, the engineering and scientific communities, public information insti- tutes, and other groups. Indeed, the different user groups in each of these sectors pose very complicated sampling and design problems. After considerable discussion with FEMA and USGS representatives, the user group was defined to include only state, county, and local public officials. Several factors led to this simple definition of users: ~ The scale of a study that would include all potential groups would be large. 100

101 o The time frame of the pane} was relatively short, prohibiting a large-scare study. Funding for such a large-scale study was not possible within the panel's budgetary constraints. ~ The funding agency's major clientele were public sector enti- ties invested with protecting the public health, safety, and welfare. Given this user group the panel's goal was to determine needs and to evaluate different methods in terms of meeting the users' requirements. It was believed that the better such studies met the requirements and needs of the user community the more likely the studies would be utilized in planning for, responding to, mitigating the effects of, and recovering from a major damaging earthquake. Even with this limited definition of the user community, the selection of state and local officials for inclusion in the study presented some significant problems that limit the extent to which the subpanel's recommendations may be generalized and that warrant discussion. Options for obtaining the views of users included a questionnaire survey based on a scientific national sample, a similar survey with a smaller sample, in-depth discussions with some very experienced users, and a workshop. The workshop option was selected primarily on the basis of time and budget. The results of opinions solicited in the workshop, presented later in this paper, should not be construed to be statistically valid as a representation of state and local users. The Method for Selecting Users The first step was to obtain a list of users that could be used in constructing an appropriate sample. After extensive consultation with USGS, FEMA, and the COSMOS Corporation, consultant to the panel, a user was defined to be an appointed or elected public official who could be involved in developing data for use in loss esti- mation studies or in making decisions, based on those studies, which resulted in a lowered risk to the community. This definition, although limited, included officials in such functional positions as mayors, city managers, planners, directors of public works departments, building code officios, county commissioners and managers, and emergency service personnel at the local and state level. The geographic scope of the list was limited to approximately a dozen higher seismic risk areas of the United States (Table B-1~. The panel could not develop what it considered an adequate list.

102 TABLE B-1 Participants in the Workshop, by Area and Level of Government Level of Government Area City County/Regional State California 3 emergency 1 regional earthquake 1 state earthquake services program manager program manager officials 2 building code officers 1 city manager 1 planner Central 1 county commissioner 1 state emergency United States services official Northeast 3 emergency 1 state emergency services services official officals . Puget Sound, 1 city council Washington member 1 emergency services official Utah 1 mayor 1 county residential 2 state emergency supervisor services officials Alaska 1 planner 1 state emergency services official Hawaii 1 state emergency services official South Carolina 1 state emergency services official Puerto Rico 1 state emergency services official Total 14 3 9 Eventually the list of local government users included some plan- ners, building code officials, and a few council members, mayors, and managers (Table B-1~. The state list of users was overrepresented by emergency service managers. Finally, the list was overly representa- tive of California users, which is not surprising given the fact that over a dozen loss studies have been conducted there. The workshop invitees were selected from lists of potential users supplied by federal agencies, and very few actual users are present in this pool at this time; there was a limited representation of the functional positions at the state and local levels, and geographic affi~- iations were not nationally representative. All of these factors make it necessary to address briefly the limitations of the data collected.

103 Data Sources and [mutations The pane! has relied on the results of the survey, the small group discussions, and the presentations by technical and user community members to suggest the users' needs. This information has been uti- lized to broaden the perspective of the panel in its deliberations. The workshop provided the key instruments for gathering data, and a few factors require discussion. The pane! fully recognizes the Irritations of these data sources and the fact that generalizing solely on the basis of the workshop cannot be done with much certainty. The major goal of the workshop held September 22, 1986 was not to train or even educate the participants in loss estunation studies. Rather, participants were invited to educate members of the pane] about the requirements and needs of the community which would or potentially could utilize loss studies once they were completed. The workshop was designed to provide several different approaches and methods by which panel members could determine user needs. The survey instrument administered to participants was designed to gain insight into participants' needs and familiarity with loss stud- ies. The instrument was administered twice during the workshop, but not to deterrn~ne the effectiveness of the workshop. The pane! was far more interested in the responses to the first questionnaire prior to participant exposure to the speakers, because of the focus on determining what state and local users (or potential users) of loss studies believed they needed to utilize such studies. Hence, the find- ings below focus almost entirely on the users' responses to the first questionnaire. Finally, small group discussions addressed four questions, three of which were common to all groups. The questions reflected issues briefly covered in the questionnaire but requiring additional atten- tion. These data sources are utilized in this working paper and are suggestive and informative. The pane! makes no claim that the findings can be generalized to the larger user community. If INDINGS The discussion in this section is based on findings about user needs from the three data sources discussed earlier.

104 Usefulness of Prior [ose Studies A major concern of the panel and the federal agencies focused on the widespread belief that previous loss studies were not being adequately utilized by the user community. Many of the pane} mem- bers who had been involved in some of these loss studies indicated their disappointment over the lack of use. As a result, workshop participants were asked about their exposure to such studies and the usefulness to their agencies and units of government. Twelve of the 26 workshop participants indicated either that they had never seen the results of a loss study or that the study in which they had participated was not yet completed. The remaining 14 participants were asked how useful the results of the studies were for a variety of activities: mitigation efforts, planning and preparedness efforts, response and recovery planning, land-use planning, building code design, and efforts to educate the public and elected officials. Participants did not indicate that the results were very useful for any one activity, but a majority of participants found these studies useful (either very or somewhat useful) for the spectrum of activities. The most important use of these studies, according to small group discussions and questionnaire results, was their use in educating elected officials and the public about the seriousness of seismic threat and the need to take action. There was clear agreement that such studies have been and should be used to advocate the unportance of seisrn~c programs in order to obtain greater emphasis on actions that reduce the ef- fects of an earthquake. Additional uses that received strong support among participants were public awareness and education programs and emergency response planning. General Barriers to Utilization Participants were asked why they believed loss studies were not utilized in developing public policy. Most important, and a general theme in the utilization issue, was the lack of involvement by state and local officials and policymakers in the entire study process. Par- ticipants indicated that too often the "experts" conducting the loss studies proceeded without regard to whether the users would under- stand what the results addressed or meant. In addition, some users indicated that the conflicts and disagreements among professional and technical experts had seriously undermined any efforts to utilize such studies. Workshop participants also stated that some reports

105 were completed in an untimely fashion and, when delivered, were written too technically. All of these factors seem to contribute to the final barrier to using these studies the lack of support among elected officials for taking action and making policy. If the above-identified barriers were removed it would not ensure greater support from policymakers, but it would help. If these loss studies are to be used, in part by advocates of seismic planning and policy, then officials must be involved in the loss estunation study process and the reports must be understandable, less technically presented, and timely. Defining the Seimn;c Hazard: The Earthquake Scenario An issue that has emerged in many loss studies emphasizes how helpful it Is to policymakers and planners to have a loss study based on the most damaging historical earthquake. Participants in the workshop strongly indicated their desire to have studies focus on major but likely earthquakes. In addition, participants (about two- thirds) believed it was either very or somewhat important to have different estimates of loss for different seasons of the year. Finally, all of the participants believed it important that losses be estimated for earthquakes occurring at different times of the day. In short, if the users' needs are to be met, loss studies should include these features: most likely earthquake to cause significant damage, seasonal estimates of loss, and estimates for the event occurring at different times of the day. Geographic Focus of Study Users at the state, region, county, and local level have differ- ent needs and requirements. In addition, recent research indicates that the key actors' functional positions influence their support for seismic planning and policy (Mushkatel and Nigg, 1987~. Nowhere are these different needs more manifest than in the data addressing the geographic focus of the studies. The small group discussions strongly indicated that the level of government one is employed by influences the desired geographic focus. Hence state participants wanted the loss studies to be for either states or regions, whereas local government officials desired a local focus. Local government participants used several examples of studies that were of such large geographic focus that they were of little value

106 to localities, particularly when the loss estimates and data could not be disaggregated to the local level. In addition, for individuals in some functional positions the most valuable ciata and Toss estimates would be site specific, which may be impossible or at a minimum very costly. Workshop participants also discussed some elements of the inven- tory data used in loss studies. There was agreement that a multitude of data from both public and private sources should be utilized in such studies. Yet there was also the belief that too frequently the data utilized were not maintained or accessible to the users and that in new studies firms or governmental entities had to recollect or re- discover much of the same data. Thus the users urged those doing Toss studies to take steps to standardize the process for collection, maintenance, and dissemination of inventory data. Types of Formation m [ose Studies Loss studies have produced much information about projected losses for different types of structures serving various purposes. Par- ticipants at the workshop were asked to rank the importance of loss estimates to 19 different structures and facilities along a four-point ordinal scale from very important to not at all ~rnportant. Over 90 percent of the participants indicated that estimates regarding emer- gency public facilities (96 percent) and hospitals (92 percent) were very important. Almost as vital were loss estimates for water dis- tribution systems (88 percent), electric power systems (80 percent), hazardous materials storage sites (80 percent), and highway systems (76 percent). The least important information concerning losses ac- cording to workshop participants were port facilities (14 percent) and government buildings (32 percent). These rankings are relative, and tests of statistical significance are inappropriate given the data base and sample. They suggest, however, that the participants seemed to focus on the response and preparedness components of the disaster and the ability of authorities to estimate losses to facilities critical for emergency response. This focus may be a function of the makeup of the participants (functional position) or of the fact that most loss estimate utilization has been identified somewhat with emergency response and preparedness. Specificity, Accuracy, and Credibility of [ose Estimates An issue discussed at length by the pane! is the importance of

107 accuracy In loss estimates and the trade-offs between accuracy (cer- tainty) and specificity. To the user community an important point is the credibility of the estimates. A consistent theme was that the earthquake scenario and the estimates of losses had to be generated from a recognized and credible source and, most important, be plau- sible. Small group discussions indicated that some estimates were based on extreme events with such high loss estimates that they had not been taken seriously. In some instances, public actors viewing the expected losses were so overwhelmed they felt local and state action would not be feasible or would not make any difference because the problems were intractable in light of the estimates. Given the amount of error loss studies potentially contain, steps must be taken to ensure the greatest amount of credibility to loss studies. The greater involvement of state and local authorities throughout the loss estimate study process will increase the like- lihood such estimates are taken seriously. Ideally, these Toss estimates could be both certain (estimation of total Tosses) and specific or detailed (Iosses to specific locations or sites). When participants were asked to select between specificity and certainty, a majority chose specificity (60 percent) as the more important to them for utilizing the information. This is especially important for hazard reduction programs. This desire for specificity is not surprising but may cause some difficulty because of the state of the art in loss estunates. Even more disturbing was the fact that of those state and local users at the workshop who had some familiarity with loss estimates, only 17 percent were very confident of the loss predictions. Obviously this lack of confidence contributes negatively to the credibility issue discussed above. One frequently mentioned problem was that the ranges of predicted losses in life and property were too great to be very useful for planning purposes. Finally, participants were asked on the survey to indicate how reliable different loss estimates must be for utilization. The results are difficult to interpret since state and local users might be willing to forego some information reliability if the type of structure or its purpose is sufficiently important. Keeping this potential trade- o~ in mind, participants indicated that it was most important to have very reliable information for dams (48 percent), electric power systems (44 percent), natural gas and water distribution systems (40 percent), and highway systems (36 percent). Participants indicated it was least important to have very reliable information about airports

108 (4 percent), radio and television facilities (8 percent), government buildings (12 percent), and residential structures (16 percent). Obviously state and local officials want as much specific and cred- ible information as possible. Yet these requirements, as reasonable as they seem, involve real costs. It is in this light that the infor- mation collected on users' ~nIlingness to spend takes on additional · · - slgnmcance. Cost, Willingness, and Ability to Spend The issue of the willingness and ability to spend scarce fiscal resources on loss studies by the state and local user community has several important dimensions. First, the proposed sharing of costs between FEMA and state and local governments for other programs may in the near future include the monies used to finance loss studies. lIence, the pane! determined it would be appropriate to investigate not only the needs of users, but also their willingness and ability to spend monies to obtain loss estimates. Furthermore, it is often thought that if a government spends some of its own resources for a study it is more likely to use the results. One of the questions included in the survey requested workshop participants to indicate what amount their office or agency would be willing to spend for an earthquake loss study. The most frequent response category selected was less than $75,000. Because of the way the question was worded it is impossible to deterrn~ne how many of the 71 percent who indicated they would spend $75,000 or less would spend nothing for such a study. Almost 20 percent of the participants did not answer the question at all, and only 10 percent indicated they would spend $225,000 or more. In short, state and local users perceive a lack of willingness or ability for their agencies and offices to expend monies for such studies. In addition, more than 80 percent of the state and local users indicated that their current budgets did not contain adequate funds for such a study. Questions about future budgets were not asked. Finally, despite this apparent inability or unwillingness to fund loss studies, users expressed support for sharing costs. When asked what percentage their governmental units should be responsible for, 59 percent of the participants indicated between 41 and 50 percent, 16 percent signified less than 10 percent, and 11 percent noted more than 50 percent.

109 Workshop ciata reveal support among state and local users for cost sharing, but they also show that current budgets are not suf- ficient to assume these costs. The last constraint on willingness to spend involves the total cost of the studies. Workshop participants (71 percent) indicated they would only spend less than $75,000 for a loss study. Hence, there seems to be a strong desire to hold down costs because current budgets are inadequate to finance the studies. The [ose Study Report and its Dilation One explanation for the lack of willingness and/or ability to spend is the users' lack of satisfaction with such studies. The survey data cannot test this explanation, but a consistent viewpoint that emerged at the workshop was that current loss studies are understood only with great difficulty by the user community. A major problem is the results are not presented in a way that makes clear their implications for seismic planning and policy development. Users at the workshop also criticized the presentation of the re- sults, most often citing them as being too technical. They supported the presentation of technical materials in an appendix, rather than in the body of the report. In addition, the problem associates} with inventory and other data bases reemerged. Users want the data to be accessible to them after the report is finished. Such accessibility would permit Aggregation to lower units of government or to a smaller geographic area. The participants often shared the perception that once such studies had been completed they were not disseminated adequately. Too little attention was paid to disseminating the findings to the potentially large community of users. Participants believed that more attention should be given to dissemination in the loss study process, and suggested that either state or local government agencies be responsible for the dissemination of findings to the users. As previously emphasized in this paper, participants strongly believed that to ensure the clarity and dissemination of study results for the largest possible user community, state and local representatives should be involved in the loss study process from its inception. CONCLUSIONS AND RECOMMENDATIONS The user needs subpane} concluded that some previous loss stud- ies may not have sufficiently taken into account state and local users.

110 This lack of attention and focus has manifested itself in studies hav- ing a geographic focus and an inventory data base that do not easily permit utilization at the local level. ~ addition, reports have been too technical to be readily understood by users. The earthquake scenario on occasion has produced loss estimates that lacked credi- bility and hence were not useful for planners or policymakers. Too often it seems the producers of loss studies have incorrectly identi- fied other producers of loss studies as being the users of their studies. Too often users have neither received the types of information they thought they were to obtain, nor have they received reports they could understand and disseminate easily. Data assembled from workshop discussions and the survey form the base on which the pane} has based its recommendations. It is important to reiterate that these data may not reflect the needs of the larger state and local government user communities. The pane! believes, however, they are suggestive of those needs. Within the methodological limitations discussed earlier, the following recom- mendations are offered. 1. Producers of loss estimation studies should involve their state and local clientele (the users) in the entire loss estimate study process. Loss estimation should and can be a vehicle of understanding the risk and potential losses from earthquakes. Therefore, the process by which such studies are conducted becomes more important than the actual results. The involvement of state and local users in the entire process of loss estimating will increase the likelihood that these important actors come to understand not only the manner in which the study is carried out but also the nature and extent of the seismic problem. Their involvement will facilitate the utilization and dissemination of the findings as well as the use of such studies for the purpose of advocating greater emphasis on seismic policy. 2. Loss estimate studies should clearly indicate the level of po- tential error In the estimates as well as the confidence of the producers of the estimates for the various components of loss estimates. A consistent workshop theme among users was the desire for credible loss estimates. The state of the art in such studies is not well advanced, and predictions of loss may be in error by a factor of 10. The user community needs to understand where error in prediction is most likely. In addition, it is important for the user community to be able to specify where the most accurate information is needed and to

111 know what accuracy is possible. When additional expenditures may result in Tower error factors, this information should be presented. It is also relevant when deciding if the Formation is sufficiently valuable to warrant additional resources. 3. Producers of studies should build an inventory base for loss estimates that can be d~saggregated to the smallest political and geographical unit. State or regional loss studies must present sufficient information for local planning, preparedness, and mitigation activities. By com- piling inventory data so that they can be d~saggregated and accessed by local units, producers win provide the opportunity for smaller units to use their studies. Furthermore, the computerization of data would permit updating and multiple use. For example, if a loss study identifies "suspects buildings in a regional area, each locale could be provided a list of these buildings and their locations to determine if local action is warranted. 4. Loss estunate studies should contain a scenario earthquake that is relatively probable and yet large enough to cause serious losses. Loss estunates should be provided for different seasons and times of the day. This recommendation is consistent with findings from workshop discussions and survey instrument results. About 70 percent of the users indicated these types of information are essential for planning purposes. The producers of loss studies should determune the impor- tance to users of the estimates of loss to different types of structures and functions. In addition, the importance of the certainty and re- liability of the different estimates to the users should be identified, and the studies should be oriented toward these needs. The users at the workshop ranked the importance of 19 differ- ent structures and functions and indicated how reliable loss estimate predictions should be for each structure and function. It is impor- tant to remember, however, that these rankings are only suggestive. IdeaDy, state and local decision makers who are involved in the loss study from its inception can provide producers with more refined definitions of their needs. 6. The dissemination of loss study findings should have greater

112 emphasis. State and local users of such studies should be responsible for dissemination to relevant agencies and the public. Previous dissemination of studies appears to have been unsatis- factory, and there is some indication that the dissemination process has been a barrier to utilization. To increase the likelihood of access and use the reports should be as nontechnical as possible. Method- ologica] discussions should be included in appendixes. More emphasis should be placed on the implications of the findings for set c plan- ning and policy adoption. The loss study reports must be aimed at the audience of users and not other producers. Methodological appendixes wid provide the information necessary for replication and validity checks. But the thrust of the report must be concentrated on those who wiD apply the findings the users.

Working Paper C Characterization of Earthquake Hazards for Loss Studies Technically, earthquake hazard or seismic hazard refers to the di- rect impact of an earthquake on the earth, including ground shaking, ground failures (liquefaction, surface faulting, landslides, and settle- ment), and the water-related phenomena of tsunamis and seiches. In this usage, the characterization of earthquake or seismic hazard does not include effects on the humanly constructed environment. Thus, threats such as collapsing buildings, overturning shelving, or breaking gas lines which in common language are often caned earth- quake hazards, or which are encompassed in the National Earthquake Hazards Reduction Program, are not topics in this working paper. This paper describes earthquake hazards and how they can be quantified, reviews current practice in the specification of hazards for loss studies, and describes a range of hazard specifications that might be used ~ future loss studies. TYPES OF EARTHQUAKE HAZARDS The primary and most pervasive hazard associated with earth- quakes is the shaking of the ground. This causes direct damage to structures as well as physical phenomena (seiches, liquefaction, and landslides) that can result in significant damage and loss. Ground shaking is generally caused by the release of crustal energy by rup- ture along a fault surface. Sometimes the rupture reaches the earth's 113

114 surface and is evident after the event, but often the rupture is buried beneath surficial sediments and rocks. Voicanic earthquakes are less common, tend to be limited to moderate magnitudes, and are pri- mariTy caused by thermal rather than mechanical action. The energy released by a rupture propagates in the form of com- pressional waves and shear waves. The character of ground motion from these waves is a function of the source characteristics of energy release, the attenuation (clamping) characteristics of the earth's crust along the wave travel path, the near-surface geologic characteristics that may modify the frequency content of the motion (amplifying certain frequencies and damping others), and the interaction of the body waves with the earth's surface to form surface waves. Collateral earthquake hazards caused by ground shaking include seiches, liquefaction, and landslides. These hazards can lead to com- plete destruction of structures. For example, the Niigata earthquake of 1964 led to the liquefaction of soil in a large area, causing the loss of foundation strength for many apartment buildings. As a result, buildings tilted by as much as 70 degrees. A recent report of the National Research Council (1986) summarizes the state of the art of estimating the hazard from liquefaction. Landslides constitute a similar, shaking-induced hazard. In the 1964 Alaska earthquake, landslides in Anchorage caused the destruction and total loss of many residences and buildings. Landslides into bodies of water, or on the bottom of harbors and bays, can produce water waves that may cause very serious losses. Another hazard associated with earthquakes is rupture of the earth's surface caused by displacement of a fault. In the United States this phenomenon is generally observed only in the western states and Alaska. The fault movements associated with great earthquakes may be on the order of 5-10 meters. Such deformations are difficult or impossible to design for, and the best policy may be to avoid fault locations entirely. For some civil engineering works (e.g., pipelines, transmission lines, highways, railroacis, and aqueducts) it is not possible to avoid fault crossings. In these cases the hazard to the facility can be identified and quantified, and the eject on the system's function can be evaluated. If the system damage and its probability of occurrence are not acceptable, alternative system designs are usually possible to alleviate damage to components crossing faults (e.g., designing redundant links in the system, designing the fault crossing to be easily

115 repairable, or devising an earthquake response plan that reduces the functional loss). Still another earthquake hazard is a tsunami, which is a wave generated in the open ocean as a result of tectonic movement of the floor of the ocean. Where such waves come ashore, they can rise to significant heights and cause considerable damage. Tsunamis are a potentially severe problem for Alaska, and tsunamis generated by Alaskan earthquakes have also caused damage to the West Coast states. Tsunamis generated both in Alaska and Chile have caused great destruction and fatalities in Hawaii. Apparently tsunamis are not a problem along the Atlantic and Gulf coasts, but may be a threat in Puerto Rico and the Virgin Islands. SCOPE OF EARTHQUAKE HAZARD ASSESSMENT The purpose of assessing earthquake hazards is to identify and quantify the severity of the various hazards in the geographic area of interest for the loss estimation study, given a scenario earthquake. In most cases an estimate of the frequency in tune (or probability of occurrence over a given period of time) of the hazard is also necessary. The results of the hazard assessment are combined with the ground- motion and damage relationships and the inventory of facilities in the study region to produce estimates of losses. Assessing earthquake hazards and specifying the other inputs to a loss study are related but independent activities that can be undertaken by different investigators at different times. One advan- tage of this independence is that various parts of the analysis can be updated (e.g., more recent data from a U.S. census can be incorpo- rated) without having to reinvestigate other inputs to the analysis. Also, studies of facility inventories and vulnerability relations can be locally or regionally undertaken, while nationally developed seismic hazard data (e.g., studies by the U.S. Geological Survey) can be pro- duced separately. The converse division of labor is also possible, as when national inventory data (e.g., census data on housing) is com- bined with seisrn~c hazard studies locally undertaken by state or local government geological agencies or local geotechnical consultants. Earthquake hazards and other inputs to loss estimation are re- lated in that the hazard must be specified in terms that are meaning- ful to the vulnerability analysis. For example, if the seismic hazard is specified in terms of the peak acceleration during the earthquake,

116 the vulnerability functions cannot be given using a qualitative inten- sity scale such as MMI. If either the hazard or vulnerability analyses must be translated to make it compatible with the other, care must be taken in the translation, and the conversions used must be fully documented. Simple empirical correlations based on observed statistics often lead to incorrect results in particular applications. Simple repre- sentations of the shaking hazard, for example, those using peak acceleration or Modified Mercalli Intensity (MMI), are attractive be- cause hazard analyses are frequently available for these parameters, and vulnerability functions are available to estimate losses for them for many types of structures. The price for this simplicity is a wide range of uncertainty in the damage and loss, because simple rep- resentations of seismic shaking or earthquake-caused ground failure cannot capture the details of the underlying phenomena. More complex representations of ground shaking, for example, through a filtered "effective peak motion, a single-degree-of-freedom linear response spectrum, a nonlinear spectrum, a time history of motion, and the duration of strong shaking, have the ability to be more accurate predictors of damage and loss. There is less agreement, however, on how to estimate these functions for a future earthquake, how to quantify the single- or multidimensional hazard associated with them, and how to derive an accurate predictor of damage from them. CHARACTERIZATION OF GROUND SHAKING For historical and pragmatic reasons, MMI has been used as the ground-shaking measure in most earthquake loss studies conducted in the past, and likely will remam the standard for studies in the near future. This procedure was popular in early loss studies because multiple, instrumental records of ground shaking were not available to correlate motion levels to damage. Even today, records of strong shaking at the site of buildings damaged during earthquakes are rare, whereas assessments of the MMI level at that site can always be made by an experienced investigator. The MM! assessment denotes the severity of earthquake shaking at a particular location in terms of the effects on people, on construction, and on the earth's natural features. The MMI level depends on seismic, geologic, engineering, and human factors. The assigned MM! value for a particular earthquake and

117 location is a qualitative measure of the integrated response of the natural and man-made environments to earthquake energy. As Richter (1958) also notes, at the higher intensity levels (MMI _ X, XT, XIT) the scale refers primarily to ground failure rather than directly to ground vibration. The primary fault trace phenomena and secondary ground effects depend on the type of faulting motion (vertical versus horizontals, the duration of the faulting movement, and the nature of the ground in the immediate vicinity of the fault. Ground failures such as liquefaction, faulting, and landslides are not good measures of ground shaking since they can occur at low as well as high levels and durations of ground motion. Contrary to conventional seismological practice and to previous applications in the loss estunation field (e.g., ATC-13), it is desirable to use MMI intensity as follows: First, ground failure phenomena should be treated separately from ground shaking, and second, only intensities below MMI X! should be used to describe the severity of ground vibration. This does not unply that quantitative measures of ground vibration (e.g., peak ground acceleration or velocity) are limited to a maximum value that would correspond, according to one of the various MMI-acceleration or MMI-velocity relationships proposed, to MM! X. In other words, MMI X is not necessarily the maximum severity of ground shaking that could occur on earth. As a general rule, the estimation of MM} can rarely be refined beyond a 1-unit range. When making loss estimates, the ejects of soil conditions on intensity of shaking must be considered. One means of accomplishing this, if ground motion is used as an intermediate variable to estimate losses, is to modify the estimates of ground motion (e.g., MMI) to reflect the expected effects of soils at locations in the region from the hypothesized earthquakes. Table C-1 presents one set of correction factors that has been proposed for southern California and that attempts to account for both the type of rock that might underlie a site, ~d the depth to the water table (Evernden and Thomson, 1985~. Other correlations may have equal or greater justification, depending on the data base and the region of study. The use of MMI in loss estimates is a gross simplification that is justifiable only if more precise methods are not available. It is known, for example, that modifications of earthquake ground motions by soils are frequency dependent. Therefore, an accurate modification of ground motion should consider the frequency characteristics of the structures for which losses are to be estunated. Similarly, explicit

118 TABLE C-1 Ground-Motion Correction Factors for Southern California Geologic Condition Change in Intensity Quaternary alluvium (water table > 100 ft) Quaternary alluvium (water table 30-100 ft) Quaternary alluvium (water table < 30 ft) Sedimentry rock Volcanic, granitic, and metamorphic rock 0.0 +1.0 +1.5 0.0 to -1.6 -1.7 to 2.0 SOURCE: E,rernden and Thomson (1985~. quantification of the effects of earthquake magnitude, distance, and duration are ignored when MMI is used. For example, an MMI VII observed at the epicenter of a magnitude 5 earthquake does not unply the same ground motion as an MMI VII observed (for the same soil conditions) 100 km from a magnitude 7 (Murphy and O'Brien, 1977~. For these reasons, use of MMI (and similar intensity scales) should be recognized as a less-than-perfect representation of earthquake ground shaking to be used only until more precise parameters and methods are available. HAZARD AND LOSS ESTIMATION PROCEDURES Scenario earthquakes have been deterrn~ned following rationales that in different ways express the need to compromise between the likelihood or credibility of the event and its destructive potential. Once the scenario event has been selected, all existing large-scale loss estunation procedures use deterministic relationships to calculate the level of ground motion at each site, the resulting damage, and the losses. Occasionally, some of the relationships (most notably the rela- tionship between ground-motion intensity and damage) include un- certainty, but in no study has uncertainty been propagated through the analysis to produce probabilistic estimates of loss. For the treat- ment of uncertainty, one can therefore regard all previous large-scale, general-purpose loss est~rnation methods as Deterministic proce- dures under scenario earthquakes. This type of analysis reflects

119 TABLE C-2 Applications of Loss Estimation Methods Applications Appropriate Methods Advocacy Response planning Preparedness planning Mitigation strategies Relocation/reco~rery Risk evaluation Economic impact analysis Insurance National security A,B A,B,D A,8 A,B,C B,C B A,B,C,D,E B,C,D . KEY: Current practice: A = extrapolation from historical data; and B = scenario analyses and accuracy estimates. Emerging methods: C = lose-frequency analysis; and D = simulation of actual events with variability. E = cumulative over time. the heritage of early loss estimation efforts. Resistance to change has resulted from the difficulty of more complete representations of uncertainty and by computational constraints. Deterministic scenario-type analyses are easy to interpret and will likely remain the basic type of earthquake loss calculation in the near future. However, they are not ideal for all purposes because they are not capable of fully representing uncertainty and because of the lack of a clear rationale for selecting scenario earthquakes. For cer- tain uses, deterministic scenario analyses are actuaby inappropriate, and alternative methods, not yet fully available, must be developed. A listing and brief description of loss estunation procedures (some existing, others in need of development) and an indication of their potential uses follow. Appropriate applications of each are shown in Table C-2. Extrapolation from Historic Losses Loss information from historical events in the region of inter- est can be adjusted to reflect recent changes in the inventory and differences between characteristics of the scenario earthquakes and those of the historic events. This analysis is simple and inexpensive, but typically less accurate and less general than analyses based on models of ground motion, damage, and loss. Such a technique is

120 appropriate when a historic event, not much different from the sce- nario earthquake of interest, has occurred in the recent past, as in the case of the largest of the six scenario earthquakes used in the National Oceanic and Atmospheric Adm~nistration's San Francisco study (AIgermissen et al., 1972~. This condition, however, seldom applies. Selecting a historic event as the basis for a loss stiffly does not avoid the problem of uncertainty, although the nontechnical audience is less likely to bring up the issue of uncertainty because of the intuitively convincing nature of events that have happened before. Results of analyses of this type are illustrated in Figure C-la. Scenario Analysis with a Statement of Accuracy This type of analysis is most often used today, although often without the accompanying statement of accuracy. One or more earth- quakes are selected, based on criteria reviewed earlier herein, and single-value estimates of the resulting losses are produced. Accom- panying these estimates with even sunple but objective statements of certainty would prove useful to the users. For example, one might use sensitivity analysis: each major input parameter or relationship is modified in turn and the analysis is repeated to calculate the effect of the change on the calculated losses. The amount by which each input parameter is modified should reflect the degree of uncertainty on that parameter. The results of such an analysis are similar to the "type A" seismic hazard analysis (Figure C-la), but a description of uncertainty in the estimates for the scenario event may be included. Historic Maximum E:arthqu~ce Historic earthquakes, when judged to be suitable and perhaps with adjusted magnitude, intensity distribution, or location, can be used in loss estimation studies. These earthquakes are convincing to both the users and the general public. Recurrence Bate Earthquake This can be an appropriate selection technique when a known seismic source zone or fault dominates the problem at hand, for ex- ample, the Was atch Fault at Salt Lake City, Utah. In such a case, an earthquake magnitude may be selected on the basis of its recurrence rate, that is, from the magnitude-frequency law flog N = a - bM). N

121 L = Best estimate loss (a) HISTORIC LOSSES OR SCENARIO EARTHQUAKE 100% ,'_ m Cl: m o a: J ~ m LL' -1 ~ ~ 10 m an O ~ a: Cal Q ~ 10-2 ~ X Z 1 0-3 0% L = Loss (b) PROBABILISTIC 1W _ ~ ,. \ Existing Hazard - With Hazard ~ Reduction L= Loss (c) LOSS-FREQUENCY ANALYSIS FIGURE C-1 Form of results of different loss estimation techniques.

122 is the number per unit tune of earthquakes exceeding magnitude M, and a and b are coefficients typically estimated by statistical analy- sis. For example, the magnitude of earthquake expected to occur on the average once in every 100 or perhaps 500 years or more Knight be selected. The location of the earthquake can be defined to maximize damage or loss. This method is more difficult to apply In an area of diffuse seismicity in that the locationts) of the seismogenic tectonic structures are not well constrained, as in much of the eastern United States. However, even in those areas, it is possible that the recurrence rate method could be a viable approach for some problems. Geologically Defined Characteristics This method is also most applicable to regions where the tec- tonic regime and the seismogenic tectonic structures are well known. Earthquake magnitude and location are determined on the basis of geologic and seismologic parameters that have been specifically asso- ciated with a given fault or area, for example, slip rate, stress drop, and typical fracture directions and lengths. Locations where this criterion might be applied are Pallet Creek and Anza, California, because of the ability of geologists to define the characteristic fault behavior at these places. Forecasting Based on past seism~city as well as relevant physical premonitory considerations, specific earthquake forecasts can sometimes be made. Such forecasted events (earthquake predictions) might then be used as scenario earthquakes. Regions of the United States where earth- quake prediction efforts are under way include the Aleutian Islands and central California (Parkfield). Maximum Credible Earthquake This and similar undefined criteria have sometimes been used in the past, but such concepts are vague and should be avoided in favor of more objective criteria. [os~Erequency Analysis This Toss estimation procedure is very different from the previous two methods (extrapolation of historical losses and scenario analysis).

123 Its objective is not to estimate earthquake losses under a single postulated event, but to calculate the frequency with which various levels of loss are exceeded in the region of study. It is important to realize that a particular loss may result from earthquakes of different characteristics, for example, from a nearby earthquake of moderate size or from a distant earthquake of larger magnitude. This procedure sums up the contributions to the frequency with which any given loss is exceeded from all possible earthquakes, large and small, near and far away. The final result is a plot of the annual probability of exceedance versus loss (Ioss-frequency curve), as shown in Figure C-lc. From an operational point of view, the analysis proceeds as follows: discrete ranges of possible magnitudes and locations are se- lected and a frequency of occurrence is assigned to each magnitude- location combination. The loss produced by each combination is then estimated using a procedure signaler to scenario-earthquake analysis and the results of all such loss calculations are summa- rized through the loss-frequency curve. (A mathematical formu- lation of this method is given later.) The major departure from existing scenario-type analyses is that, in loss-frequency calculation, one would typically regard the loss from a given magnitude-Iocation combination as a random variable, due to the uncertainties of pre- dicting ground-motion intensity, physical damage, and economic and human losses. The mathematical procedure for this type of analysis follows closely the method of probabilistic seismic hazard analysis described in a report authored by the Committee on Seismology, National Research Council (1987~. Described here is the specific application of these probabilistic concepts to derive estimates of losses and their frequencies of occurrence for a region or metropolitan area. Procedures are well established for estimating the probabilities of seismic ground motion at a point. Three types of input are required: (~) a designation of faults or sources that generate earthquakes and the distribution of earthquake locations on the faults or sources, (2) a description of the distributions of earthquake sizes (magnitude*) and tones of occurrence for each fault or source, and (3) a function that estimates the intensity of ground motion at the site, for earthquakes of specified magnitudes and locations on the faults or sources. With *It is essential to be clear as to which magnitude scale is used.

124 these three inputs, probabilities that a specified amplitude of ground motion a wiD be exceeded at the site per unit time can be calculated. The total probability theorem is used for this calculation: PI`A > a)`Gime ~ As, Hi / ~ PtA > Am, is fM,Rtm, r`J&m~r. (~) ~ m r in equation 1, Pt.] indicates probability, the vertical bar (~) indicates conditions, f(.) is probability density, the summation is over all sources, i, that might produce ground motions affecting the site, pi represents the expected number of earthquakes per unit time in source i, and m and r are general descriptors of earthquake size (e.g., magnitude) and location tenth respect to the site (e.g., distance). The approximation in equation ~ results from using the expected number of earthquakes rather than calculating probabilities of multiple occurrences and from neglecting the effects of multiple exceedances of amplitude a. For the usual annual probabilities of interest this approximation is very accurate. The formulation of seismic hazard considers (and integrates over) all earthquakes that can affect the site. The resulting annual probability is calculated, in effect, by weighting all these earthquakes by the ground motion that they may produce at the site. Practical applications of seismic hazard analysis are accom- plished in several steps, which lead to the calculation of equation 1. An illustration ~ given in Figure C-2. First, earthquake faults or zones of seismicity must be delineated; from these, the distribu- tion of distance fR(r) between earthquakes and the site is obtained. Next the probability distribution of earthquake magnitudes fat (m) is derived for each source or fault, often by analysis of historical earth- quakes that are spatially associated with that feature. The product of these two distributions is fM,R(m,r) in equation 1. The third specification concerns the ground motion occurring at a site, which is a distribution of ground-motion levels conditional on earthquake magnitude, distance, and local geology. This distribution allows calculation of the probability PEA > a~m,r] in equation I. The equation that calculates a mean or median ground-motion level as a function of m and ~ is often termed an attenuation equation. The final step in the process consists of integrating over all earthquake magnitudes and distances, in the manner of equation 1, to calculate hazard results for various ground-motion amplitudes, as illustrated in Figure C-2d by a typical hazard curve.

A. Seismic Source i (Earthquake locations in space lead to a distribution of epicentral distances fR (rl m) - / fR(r~ m) ,' RuDture _,_ Site a L. I Distance r C. Ground motion estimation: Alm,r~ cut cut c' a, a - Fault i m =~\ GA|m,r( Distance (log scale) 125 B. Magnitude distribution and rate of occurrence for Source i: f M (m), Hi f M (m) Lo, mO mmax Magnitude m D. Probability analysis: P[ A ~ a in time t] /t ~ Zi V! !|GA~mr(a*) f M (m) f R (r ~ m) dmdr - a, c' 0 ce a, 0 _ CL At_ , ok\ \  Ground Motion Level a. (log scale) FIGURE C-2 Graphs indicating probabilistic seismic hazard analysis steps. Source: McGuire (1987~.

126 A similar procedure can be applied to calculate annual prob- abilities of earthquake losses from earthquake ground shaking in a region, but additional information is needed. First, a scalar variable needs to be chosen to represent the potential losses (e.g., dollar loss or number of deaths). Second, the correlation of ground motion at different sites must be taken into account. This correlation results because separate sites may be affected simultaneously by the same earthquake, by similar focusing effects of the source, by similar travel paths, and by similar geologic conditions at the site. Just as the un- certainty in ground motion is important in site hazard calculations, PtA > a~m,r] in equation 1, correlation of ground motion at multiple sites is important to regional risk estunates. The estimation of an- nual probability of exceeding a loss $' for the region can then proceed by an enumeration of all earthquakes that might affect the region: P[$ > $ ~ ~ Eui / ,/ Pt$ > $'m' r] fM,R(m, r`)dmdr, {~2~) m r which is similar to equation 1 except that the summation is over all earthquakes that may affect the region of interest, and R represents earthquake location (without reference to a particular site). The conditional probability in equation 2 is evaluated as: P[$ > $' ~ m,r] = Pt(~$j~xj,yj)) > $' ~ m,r), (3) .j where $j (I, y, ) is the loss at location I, yj and the summation is over all locations in the region. The correlation of ground motion enters into this calculation of total loss over all locations in the region for an earthquake of specified size and location. In practice the region is divided into convenient units (e.g., census tracts, statistical areas, or blocks) for this enumeration. The available format for the facility inventory or census information obviously plays a role in choosing the appropriate size of subdivisions for estimating total losses. Several simplifying assumptions are usually made in applying equation 2 to estimate earthquake losses. Often the uncertainty in earthquake losses during a hypothesized earthquake is ignored, leading to a great simplification of equation 3. These uncertainties may result from variabilities in the ground motion generated at the site (whether or not this is used as an intermediate variable), the effect of local geology on ground motion, the loss that might be generated in specified facilities for a given ground motion, and the

127 number and type of facilities at a given location (e.g., uncertainty in the facility inventory). Ignoring these uncertainties constitutes a simplification that may be justified if, for example, only a best estimate of losses versus annual probability Is desired, but in this case the statistical mean of all relations (rather than, for example, the median) should be usecI. Even then the results only approximate the mean loss, and they are likely to underestimate it, perhaps substantially. Other sunplifying approximations are appropriate under certain conditions. If the region considered for the loss estunate Is rather small (several tens of square kilometers), the integration over loca- tions in the region can be avoided by assuming that the entire region is subjected to the same ground motion. Then, an accurate hazard analysis can be performed for one point (e.g., the geographical center of the region), and the seismic hazard results can be translated to loss estimates. In effect, this assumes that the region Is small enough that the same ground motion occurs over its entirety. In some parts of the United States, the earthquake hazard re- sults from specific fault zones or sources that are small relative to the size of the area that could be affected, for example, the New Madrid fault zone. In these cases the earthquakes occur in an area that is small relative to the region that may be examined for loss calculations, for example, the Mississippi Valley. The loss (more specifically, the range of losses) calculated for a specific magnitude earthquake occurring in the fault zone can then be associated with the annual probability of that event, using the recurrence relation for earthquake magnitudes in that source. In erect, one avoids the integration over location in equation 2; the 1,000~year earthquake is used to estimate the 1,00~year loss. Note that this circumstance does not by itself justify ignoring uncertainty in the resulting losses; as a minimum, mean values (rather than medians) should be used in aD relations to calculate the resulting losses. Simulation of Actual Events In this typical analysis, all of the uncertain input parameters, ex- cept possibly for earthquake magnitude and location, are numerically simulated. Hence, for each given earthquake magnitude and location, different loss scenarios are generated in different simulations. The results are patterns of damage and Toss, which are more realistic

128 than those produced by bes~estimate scenario analysis. Figure C-lb illustrates results of this type. Cumulative [ose Over Time For applications that depend on the total loss that may be ex- pected in a certain geographical region over a given time period, one should sum losses due to future earthquake occurrences in the region. One use of this result would be to compare earthquake risks with risks from other natural phenomena. For certain uses, one may need only the expected (actualized) cumulative loss, whereas for others it may be important to calculate the entire probability distribution of the cumulative loss. SU~RY This description of loss estimation methods is neither exhaus- tive nor exclusive, meaning that certain applications may require the development of specialized procedures not included in the present list or the combined use of several methods. Generally speaking, deterministic scenario analyses can be made at a level of detail and spatial resolution that is ~rnpractical in probabilistic risk calcula- tions, because of the large number of calculations required by the latter methods. Hence, deterministic analyses (methods A and B as described in Table C-2) might be ideal tools for use in disaster exercises and for the detailed evaluation and improvement of loss reduction strategies. On the other hand, public safety policies (such as the selection of suitable building code provisions) and economic decisions would be best made considering the integrated results of risk studies (method C). The usefulness of scenario type analyses may vary geographically. For example, in regions where events of size close to the magnum possible magnitude occur frequently, a single-event analysis using one such event may be all one needs to make informed decisions. By contrast, in regions where seismicity is low and the maximum earthquake size is unknown, the earthquake threat may be dominated by events in an intermediate magnitude range. ~ the latter case, one should make decisions based on the projected loss from a variety of earthquakes, considering the frequency with which each type of event occurs in the area. For many uses, a fully probabilistic risk calculation by method C is the ideal type of analysis. For example, knowledge of the risk curve

129 would allow quantitative assessments of public safety with respect to earthquakes and comparisons with other risk sources. Insurance and financial institutions would find risk curves appropriate for the evaluation of expected (Iong-term average) profits as well as for the evaluation of the frequency of catastrophic losses. Another example is the comparison of risk reduction options: different risk reduction or preventive actions might have different effects depending on the earthquake size and the amount of damage. The effectiveness of each proposed action could then be represented in terms of the downward shift that a particular action produces on the original risk function, as shown by the dotted curve of Figure C-Ic. Method D (repeated simulation) is perhaps most appropriate to plan emergency response, when one needs to evaluate the adequacy of response strategies in the context of certain damage and loss scenarios.

Working Paper D Inventory of Facilities This paper addresses the inventory problem. It limits the term inventory to the task of listing man-made facilities and their at- tributes, rather than the parallel task of producing an inventory of the attributes of different soil types or other geologic data, which is a seismic hazard analysis task. Structures other than buildings, such as lifeline facilities, can be inventoried similarly as for buildings, al- though the information sources and data collection techniques vary. Most major lifeline facilities are already inventoried to some extent by their owners, and it is the more difficult problem of conducting an inventory of buildings that is the focus of this paper. The number of buildings and other structures in the study area of most large-scale loss estimation studies is great. The earthquakes selected as the planning basis for large-scale loss est~rnation studies can be strong enough to shake 5,000 or more square miles, and the study area of most interest often contains a population of several million. Pre-existing files or data bases do not contain the amount or quality of information that is desired for the purpose of estimating earthquake losses. Inventories used for earthquake loss estimation purposes must be developed in a highly selective manner because this is the most time-consuming and costly step in the loss estimation process. Thus, the inventory task is often a matter of using the data that can be collected and organized within the budget allotted, rather than developing the ideal inventory. 130

131 The losses of concern may be facilities damaged or rendered dys- functional, dollar losses to facilities or dollar value of lost production, casualties, or homelessness. The kind of loss information sought is a determinant of the kinds of inventory information needed in the analysis. Hence, the types of loss to be estimated must be specifically defined prior to selecting an inventory method. Theoretically speaking, a unique and all-purpose inventory might be created, but its contents would include so many descriptors and other items of information that it would not be feasible to assemble. Moreover, given the lack of understanding about motion and damage or ground failure and damage relationships and the prospect that this understanding will improve in tune, the chances of anticipating all relevant inventory data today for some future use are, indeed, slim. Efforts to create an exhaustive inventory of information about facilities would be a misguided, ineffective effort. HIERARCHY OF DATA Based on recent loss estimations prepared by different methods and people, the best hierarchy of data items seems to be: ~ Facility location (addresses are preferred for buildings and structures, but they are often listed only by zip code or census tract; the census tract or other appropriate zone is used for linear or area- wide facilities); Type of structure; Materialts) of construction (for the load-carry~ng system); Height (for buildings); Floor area (for buildings); Date constructed; Value (market or replacement value adjusted to a selected base year); Use of facility (occupancy or social function); and · Number of people in facility at different times of day and season. Many other data might be added that, based on present knowI- edge of earthquake effects, could improve the accuracy of loss esti- mates. Among these (not necessarily in order of unportance) are: Type of foundation system; Configuration of facility (in plan and in elevation or section); Special-damage control features of facility;

132 Code under which facility was constructed; and ~ Nonstructural features or contents with special fire or haz- ardous materials characteristics. Nevertheless, no loss estimates are possible without certain ba- sic information about facilities. Further, some kinds of inventory information are common for all loss estunation methods, that is, fa- cility location, construction classification, occupancy data (number of occupants and type of occupancy or use), and facility property value. According to current procedures, this information is assem- bled (inventoried) by (a) field observation or sampling, (b) review of other previously assembled records for a given community, or (c) extrapolation from conveniently available records to the end-form construction data desired, such as by inferring floor area from num- ber of employees or land-use acreage figures, degree of earthquake resistance incorporated in the design from date of construction, or value from floor area. When other economic losses are to be estimated, additional in- ventory information is needed, especially the facility's economic use, or "social function" in the terminology of ATC-13 (Applied Tech- nology Council, 1985), and facility contents. Economic relationships that are not a part of the inventory also must be modeled. Essential inventory information can be assembled in several ways, and no single inventory method can be recoin-mended. However, two major alternatives discussed in this paper are (~) the NOAA- USGS method of field observation, coupled with input from local building experts, lancI-use patterns, and census data, and (2) the FEMA/ATC-13 method, which would use existing detailed construc- tion class inventories where available but in practice would generally rely on extrapolations from economic data to impute almost all con- struction characteristics. The most important attributes of facilities other than buildings seem to be unique to the type of facility and are not addressed herein. For example, while underground pipelines can be treated in a parallel manner to buildings in classification systems, the general headings have very different meanings. The size of a pipeline would probably mean the diameter of a pipe, while for a building it would mean the square footage or height. The types of materials used for pipes are also different from buildings.

133 DISCUSSION OF ESSENTIAL DATA The following subsections discuss three aspects of the data re- quired for essentially every study. Construction CIasees The most frequently used approach to developing an inven- tory of building construction characteristics Is the construction class method. Once the facilities are described in terms of their location and construction class, and after construction classes are tied to motion-damage-Ioss relationships, this overall vulnerability analysis can be combined with the seismic hazard analysis to predict damage. Table 3-1 presented an example of a typical construction class system (see Chapter 33. Developed by the Insurance Services Office (ISO), this scheme has been widely used for insurance as well as noninsurance loss estimation purposes. Once the difficulties of prop- erly counting buildings and assigning them to the appropriate class are overcome, relationships between shaking intensity and resultant damage are used to project damage (see Working Paper E). The degree of approximation present in this approach Is typical of earthquake loss estimation studies. It is very expensive to col- lect precise data about construction characteristics, and these data are not already tabulated in inventories prepared for nonseismic purposes. Although this scheme may seem to categorize the building stock rather coarsely, it is usually more than precise enough to match the accuracy of the inventory work. The extreme case of what might be called a detailed inventory is the information an engineer collects concerning materials properties and geometric data on each structural member and connection in a building for the purposes of new design or an evaluation of a build- ing's earthquake vulnerability. This "inventory" is then subjected to detailed load and capacity calculations to design an adequately strong and stiff structure or to see if the existing building is ade- quately earthquake resistant. Even when an inventory of this detail is collected for a single building, the estimation of earthquake damage that would result from a specified earthquake is still an approxima- tion. Thus, while it is true that the better the inventory the better the accuracy of the resulting loss estimates, it is also true that even with a perfect inventory there would still be a large amount of am proclamation inherent in the process of estimating the losses that might occur in future earthquakes.

134 A discussion of the extent of building stock inventory information already available for earthquake loss estimation purposes will be found In work conducted at Cornell University (Jones et al., 1986) and by the Association of Bay Area Governments (ABAG) (Perkins et al., 1986~. A rough estimate of the field work required in the ABAG project to survey commercial or industrial areas is that about five census tracts per day can be Windshields surveyed from a slowly moving auto with a two-person team. The study by Gauchat and Schodek (1984) is innovative for its use of aerial photo analysis, although it restricted itself to housing be- cause the construction characteristics of housing are easier to observe in this way; commercial and industrial building construction charac- teristics are more varied and less easily observed from the exterior. In a study of Los Angeles County earthquake losses by Scawthorn and Gates (1983), except for construction data on high-r~se and unre- inforced masonry buildings, inferences were used to convert land-use maps showing acreage of various uses into 13 construction classes and into building areas. A committee of engineers, building officials, and realtors was relied on for these extrapolations. The NOAA-USGS studies also capitalized on existing files con- cerning high-rise or other special categories of buildings, used census data to inventory most of the housing, and relied on field sampling of commercial-industrial areas coupled with land-use maps and local engineering knowledge of typical construction patterns. Occupancy When life safety impacts of an earthquake are to be estimated, as is almost always the case except for insurance or other property loss studies, the number of occupants in buildings must be estimated. Once the damage to a class of construction is estimated, the per- centage of occupants or passersby who would be slightly or seriously injured, or killed, is estimated. This allows for the number of persons to be multiplied by this ratio to produce estimated casualties. An- other approach used instead of or in combination with this method is to apply a casualty ratio to the overall population of an urban area. The number of people who would be outside of buildings must be estimated because for some classes of construction, notably un- reinforced brick buildings, the collapse of at least some brickwork off the outside the building to the sidewalk or other exterior area is more likely than complete collapse.

135 The time of day must be taken into account. In many areas of the United States, people work, shop, and engage in other daytime activities in buildings that are on average more hazardous than the residences where they spend the night. E~tunating losses for different tunes of day is typical of loss studies for this reason. Fortunately, census data, planning department studies or economic data, and reliable inferences relating the number of occupants to land-use or building area data (Jones, et al., 1986) are usually available. This is not as difficult an inventory task or as prone to error as the listing of buildings according to construction classes. Another aspect of occupancy or use that must be collected for some studies is the type of occupancy or function of the building. For estimating the ability of emergency response agencies to experience an earthquake and yet be able to provide essential services, most loss studies pay particular attention to hospitab. In terms of the overall medical system in the area, the medical roles of other facili- ties, including ambulance garages, wholesale pharmaceutical supply locations, ~d blood banks, must also be properly inventoried. For estunat~ng economic losses, an estunate of the economic activity occurring in buildings must be made. The designation of type of use for facilities with essential emer- gency response functions (e.g., fire stations and hospitals) is almost always easily available from government agencies or other sources. Since these more essential facilities can be listed quickly, it is possi- ble to segregate them and address their inventory and analysis tasks differently. Detailed, facility-specific techniques are more costly, but relatively few essential facilities exist (and in some cases only the most essential among this small population need detailed attention). The greater cost is also justifiable on the grounds that the vuInera- bility analyses for these buildings should be more accurate because these facilities are more important for emergency planning and to some extent for hazard reduction purposes. In California, for example, there are (in about 1985) 520 hospi- tals, 433 essential communications facilities or emergency operating centers, and 441 police or sheriff stations (Office of Emergency Ser- vices, 1986~. There is a greater number of fire stations (3,155), but many of these are small in size or significance and are generally one of the easiest of the essential emergency function buildings to field survey. ~ the set c safety study for the general plan of the cities of El Cerrito, Richmond, and San Pablo in the San Francisco Bay Area (Cities of El Cerrito. Richmond, and San Pablo, 1973), every

136 fire station in the three cities was enumerated according to address and location on a seismic hazard map, and the type of framing of walls and floor or roof was noted; this was a minor aspect of the overall project and only a small effort was devoted to it. These different types of inventory data that relate to the con- struction class and the various occupancy-related information items are not centrally collected by any agency or organization, and their availability can vary from one local jurisdiction or region to the next. Skiff inventory development is largely a matter of carefully ex- tracting the useful but inexpensive data from pre-existing sources, such as local planning or assessor's departments, or from field survey work and then moving on to a completely different source to obtain other information to fill gaps. Facility Location Typically seismic hazard maps of ground failure or ground shak- ing are only available on a relatively coarse scale. Either census tracts or zip codes often provide a more detailed scale than is required to match the detail of the seismic hazard mapping. Where detailed geo- logic maps showing the distribution of soft soil or high ground-water areas are not available, and where the seismic sources are relatively distant rather than located within the study area, facilities some- tunes need not be located more accurately than by general district of a city, or even by city, for the purposes of that particular study. Because refinements in the geologic data base or changes in the analysis of seismic sources may occur and because the inventory may be useful for nonseismic purposes, it is always desirable to locate facilities according to a scale at least as fine as zip codes or census tracts, unless especialRy rapid and inexpensive studies are to be at- tempted. Since Bureau of the Census data include an enumeration of one- to four-family dwellings, dwelling lomes are generally esti- mated from an inventory that is already conveniently broken down into census tracts, block groups, and blocks. Census tract boundaries are redrawn periodically by the Bureau of the Census, and zip codes are also rearranged by the Post Office, which create an updating problem. While not a major problem, census tract, zip code, and political jurisdiction boundaries must also be reconciled; a census tract, for example, may extend into more than one municipality. Disaggregating the inventory down to a small geographic level is

137 a goal sought by users, but they also face problems of confidential- ity or controversy if specific facilities are identified. In the seismic safety study for San Francisco's general plan (UEtS/Blume and As- sociates, 1974), a building-specific inventory of the larger seismically hazardous or suspicious buildings of the city and county was pro- duced, based on a rapid technique using county assessors' data and a walk-by of each major building by an experienced engineer. This de- tailed and potentially very useful information—the detail that users often request was also very controversial and never made public. According to the engineer in charge of the study and the head of the planning department, the information was withheld at the direc- tion of the city government out of fear of lawsuits. The head of the building department at that tune advised in a memo that publicizing the list would do no good and would cause "panic, accusations, etc." (Finefrock, 1980~. On the other hand, failing to disclose information about hazards may increase liability exposure, so this issue of the specificity of an inventory should be considered with legal advice. It ~ also true that earthquake hazard inventories required by state or local law, as distinct from inventories compiled in loss estimation studies, have withstood legal tests over more than a decade. Another approach to defining location is to use an arbitrary grid or rectangular cell system. The I-hectare cell (about 2.5 acres) system used by ABAG in a recent earthquake loss inventory project was found to be generally adequate. In Japan, a grid is often used to map both seismic hazards and building inventories using similar small-scale ceils. Where local government assessors' files contain construction- related or other useful information, the assessor's parcel can be used as the basic mapping unit. Assessor's parcels conform to land owner- ship patterns, which are usually much finer-scaled in urban areas than zip codes or census tracts, or even census blocks. Census tract, zip code, arbitrary grid, and assessor's parcel boundaries are unrelated to each other, although with extra cost they can be cross-referenced. Geographic information systems using digitized maps provide several advantages once their initial cost is paid and funding for their maintenance is assuredly. Changes in seismic hazard zones or contours can be easily accommodated. Changes in the facility inventory, once the new information is collected, can be included inexpensively in new calculations of loss. In addition, the mathematical manipulation of units within geographic areas (such as calculating the number

138 of dwellings located where the intensity is estimated at a certain level) can be easily accommodated. A recent conference devoted to geographic information systems indicates the range of possible natural hazard as well as other applications (American Society for Photogrammetry and Remote Sensing, 1987~. Another great advantage of computerized approaches is in deal- ing with problems where various combinations of layers of informa- tion on the map must be compared. A study of regional southern California earthquake response issues (Haney, in progress) is digitiz- ing pre-existing information, some of which is related to lifelines, from a California Division of Mines and Geology (CDMG) report (Davis et al., 1982a). Broadcast coverage areas for Emergency Broadcast System stations can be compared with the CDMG study's projection of intensities and with the languages of residents as determined from census data, for example. No files on building structures are being added to the data base, although there are plans to use the AT~13 method in its present form for this purpose. Two disadvantages of computerized systems are the initial costs of establishing the system and the costs of maintaining the system. The first-year cost of establishing a Regional Information Manage- ment System in southern California using the earthquake loss esti- mation method applied to a pilot project area in San Bernardino County was estunated at about $1 million (Schulz et al., 1983), although other nonseism~c benefits were postulated. The work in southern California that is jointly funded by FEMA and the state of California (Haney, in progress) and three recent projects illustrate this evolving approach: digitizing of several dif- ferent types of seismic hazard and facility data for Sugar House quadrangle in Utah by the USGS Rocky Mountain Mapping Center (Alexander, 1987~; digitizing of seismic hazard maps for San Mateo County, California (Brabb, 1985~; and digitizing of a small study area in San Bernardino County, California (Schulz et al., 1983~. None of these projects deal very specifically with the problem of enumerating buildings in terms of construction characteristics, which is by far the single biggest inventory problem in the earthquake loss estimation field. This is not what computerized approaches do best. Manipula- tion of already collected information, rather than data collection, is the strong point of the computer-aided inventory approach. Portions of the USGS map system for the United States, the familiar topography maps produced at scales as fine as 1:24,000, are now digitized and the remainder of the USGS maps will eventually

139 be converted to this format, allowing for various types of digitized data to be related directly without having to convert via paper maps. The U.S. Bureau of the Census will digitize the results of the 1990 census (Marx, 1986~; future earthquake loss studies that tie into a geocoded information system may benefit more than at present. Many local organizations, such as utility companies, planning depart- ments, emergency services departments, and others are investigating the potential of combining resources to produce multipurpose maps. SUGGESTED SOURC1:S OF INVENTORY INFORMATION Guidelines are suggested here for preparing rapidly an inventory of facilities when the preferred ideal inventory cannot be done for an earthquake loss estimation study. A number of ways have been used or proposed. These have typically been uniquely tailored for a particular type of loss study in a particular area. The techniques suggested or followed in preparing such inventories have been shaped not only by the kinds of data needed for the particular study, but also by the kinds of information readily available in the particular area. An additional element of expert judgment from persons familiar with the study locality has been an important part of these inventory techniques, because it typically has been necessary to infer needed end-form data from other types of information. Inventories that are less than the ideal type have advantages as well as limitations that must be recognized In the beginning. Foremost among the advantages are: in general, they are less costly to prepare, and they typically can be completed in less tune than an ideal inventory would take. Foremost among the disadvantages are: more sophisticated ex- pert knowledge must be employed in extrapolating essential data from available raw data, and they are less accurate than more de- ta~led inventories and these inaccuracies carry over to the loss esti- mates. Poor-quality input information leads to poor output results. Rarely have earthquake loss estimation studies quantified their un- certainties, so a study with less accurate inventory, and thus less accurate loss estimates, may appear to be as valid as a more accurate study, but this is not the case. Owing to the diverse types and forms of readily available data about facilities in a study area, a ste~by-step procedure cannot be suggested for preparing an inventory, nor can it be suggested that

140 one source of data is better than another. The process to be followed depends on several factors, among them: Financial resources available for the study; ~ Type of loss study, which establishes the type of end-data needed for the inventory and which relates to the geographic scale, kinds of facilities and losses, and time frame as discussed earlier; and ~ Kinds of existing data (i.e., what kinds of data have been com- piled on, for example, schools, dwellings, publicly owned buildings, and high-rise buildings). From earthquake loss estimate studies prepared by others and from examination of basic elements of loss estimation methods, some general guidelines for an inventory procedure can be inferred. First, the end-form of the inventory data for the particular loss study must be established, which in most cases consists of: ~ Numbers of facilities of various types that are located in specified zones (e.g., blocks and census tracte), in short, a count of facilities. Classification of facilities according to the classes in the motion-damage relationships to be used in the analysis phase. Value of facilities, normalized to some base year. . Occupancy information, since casualty loss estimates are in- cluded in many studies. E unction or use classification, if economic sector loss estimates are to be prepared and if essential emergency response facilities are to be identified. Second, the inventory must be built at least partly from ex- isting data sources. Inventories created from field observation are much more costly than those based on reuse of existing data. More- over, some of the end-form data can be extrapolated with reasonable accuracy from existing data sources, especially when someone knowI- edgeable about the study area is utilized. The degree of extrapolation that is acceptable is a significant msue In this regard and relates to the required overall accuracy of the result from the user's viewpoint. Following is a brief list, with some discussion of the existing data sources most often used for preparing earthquake loss estimation inventories. 1. For housing: ~ U.S. census information. These data, giving dwelling unit counts, occupancy numbers, and relatively precise locations, are

141 especially useful for rapid inventories of housing, but unfortunately not of help in dealing with the other kinds of structures that often have a greater bearing on total losses (which is unport ant from a hazard] reduction viewpoint) or need for emergency response (which is important for emergency planning purposes). ~ Land-use maps. Most local governments retain reason- ably current maps that indicate the general land-use patterns in a community from which one can infer, although somewhat imprecisely, the general types of facilities In each zone or area. 2. For selected types of facilities, for example, schools, publicly owned buildings, hospitals, university buildings, and state-owned buildings, the following may be useful: ~ Some state or local regulatory or management offices, for example, school district or public health agencies, usually retain an inventory of facilities under their jurisdiction. Sometimes these in- ventories have enough detail on each facility to allow direct recording of end-form data for loss estimation studies. 3. For commercial/industrial facilities: This is the most difficult part of any facility inventory. Unfortunately, most communities do not have data on these types of facilities that fulfill the construction data needs of an earthquake loss study inventory. Whatever information one finds for these types of facilities normally is ~ economic terms, for example, retail or industrial space in an area, employment by type of business, and sales volume. Assessors' records generally do not adequately define construction class, but should be checked. Insurance data that may adequately define the construction class of commercial and industrial facilities are usually proprietary. Sanborn (insurance industry) maps, if they are available for the area and are reasonably up-to-date, should be consulted. 4. For facility property value: Local county assessor records. Use of these records can be a tedious and time-consuming effort, depending on the way in which they are kept. Also, since values estimated for property tax assessment purposes may be artificially related to actual market or replacement property values, adjustments may be required. 5. For facility floor area: ~ Local county assessor records. Building area in square feet often is included in records kept by the assessor. ~ Local building department. Some building departments .

142 retain floor area data on all facilities for which building permits have been issued. . Local chamber of cornrnerce, real estate, or economic development organizations. These offices often compile information on retail, commercial office, and industrial space in an area as one of the tools for promoting economic development. 6. For degree of earthquake resistance incorporated into struc- tures of various vintages: . Local building department and design professionals can usually provide information about the code basis of designs according to year of construction. Year of construction is a datum available for housing from the census and typically is listed in assessors' files. Sanborn maps may also be useful to identify vintages. 7. For nonbuilding facilities, for example, utilities, transporta- tion facilities, large industries, and refineries: . The best (and possibly only) source of information on these types of facilities is the particular industry group, regulatory agency, or owner who usually retains a detailed record of these facil- ities, their locations, and at least some of their construction charac- teristics. The methods and sources for inventory information, whether for an ideal inventory or for one assembled less rigorously and more rapidly, are much the same. The distinguishing feature between the two in many cases is the form and degree of recordkeeping that accompanies the inventory work, which is related to cost. Accord- ingly, the following previously stated position can be reiterated: If an earthquake loss estimate inventory is to be compiled, it is infinitely wiser in the long run to: Establish a systematic form for the needed end-data; Compile the data in a computer-retrievable form: ~ Record systematically the facility data by address or zone location; and Differentiate on the data record between those data that are real (correct or known) and those data that have been inferred. POTENTL\~[Y HIGH-HAZARD OR ESSENTL\L FACILITIES Potentially high-hazard facilities include large dams, nuclear power plants, and liquefied natural gas (LNG) plants. Were such a facility to be severely damaged in an earthquake the resulting loss

143 could be very great. Assessing the likelihood of failure is much more difficult than the initial step of locating such facilities on maps and then estimating the associated exposure areas (such as the ~nunda- tion area for a reservoir). The cost of a properly conducted seismic study of a single critical facility may exceed the cost of a multi- purpose earthquake loss study for an entire region, and frequently quantitative loss est~rnates for critical facilities are beyond the scope of most large-scale loss studies. When critical facilities are excluded, this should be noted In the loss study. Also included in this category of potentially high-hazard facilities are refineries and chern~cal plants, tank farms, semiconductor plants using toxic materials, laboratories, gas transmission lines, and large buildings (high rises, large plan area structures) with hundreds or thousands of occupants. It is possible within the limits of a reasonable loss study budget to inventory facilities of large potential hazard, even if the study stops short of predicting their losses or the likelihood of failures. It is usually possible to obtain inventories of the location, size, age, and approximate construction class of essential facilities such as police and fire stations or hospitals. Because of their unportance, as is the case with potentially high-hazard facilities, these essential facilities must be inventoried and field-rated on an individual basis. Because essential emergency facilities are often individually vis- ited, or an inventory of their construction characteristics is available from drawings or records of regulatory agencies or owners, the in- ventory data are more accurate than for the general population of buildings. This allows for greater accuracy in the results. As noted earlier, however, the accuracy will not be high by comparison with the accuracy available in many other fields of engineering. Even when a structural seismic analysis of an individual building is conducted, costing perhaps one-quarter to one percent of the value of the build- ing, the results will be approximate and uncertain because of the inherent limitations in the state of the art of est~rnating earthquake losses. The issues of the confidentiality or the controversial nature of facility-specific loss estimates and concern over liability are always present in this type of study. For example, the unusually detailed study of about 1,000 hospital buildings in southern California by the Office of State Architect (1982) is publicly available only in aggregate form where the identity of individual structures and their owners is concealed.

144 METHODS FOR l:VA[UATING INDIVIDUAL BUI[D~GS OR FACII ITIES In many cases, the method used for facility-specific analysis is more difficult to describe in detail than the methods used for the general building stock, simply because the estimates of vulnerability are usually based on limited visits by engineers to the facilities or on reviews of drawings or other information. To sunply describe the method as engineering judgment does not precisely define the method since judgments vary among different engineers. Since these facility- specific analyses will usually stop far short of a full set of calculations for loads and capacities, because of the budget limitations of large- scaTe loss studies, reliance on an expert's opinion is the preferred approach. The first of the large-scale, general-purpose studies (AIgermis- sen et al., 1972) included a rapid review of major hospitals, with the method being the judgment of one or more experienced structural engineers who were already familiar with a significant percentage of these buildings. Some field visits and quick reviews of construc- tion drawings were used to supplement pre-existing knowledge about these buildings. Field visits are especially important for assessing the ability of an essential facility's equipment to function after an earthquake. About 800 of the University of California's major buildings, totaling 44 million square feet, have been seisrn~cally evaluated using a rapid rating process that essentially relied on the judgment of two experienced engineers, with a construction class system derived Tom the ISO scheme used as a guide. Two to four days were spent to review drawings, to conduct walk-through surveys at each of the nine campuses, and to divide the buildings into four categories of vulnerability to MMI OX shaking. Then another method (McClure et al., 1979) was used, in a derivation of the ISO construction class scheme, to rate the benefit-cost ratio for each building, with the benefit being the likely savings in lives and the cost being that for strengthening. The U.S. Navy has used a method called rapid analysis to sort buildings and spend more time analyzing the most hazardous struc- tures. Screening proceeds from a consideration of size and functional importance of a building to a rapid calculation of loads and capaci- ties. An application is described by Chelapati et al. (19783. A National Bureau of Standards research effort led to the de- velopment of a technique called the field evaluation method (Culver

145 et al., Igloo. This method was not intended to evaluate essential facilities, but it Is representative of rapid, building-specific rating methods. A structure's characteristics are rated according to a point system: type of vertical elements (11 classes), diaphragm rigidity (4 levels), diaphragm anchorage (4 levels), diaphragm chords (4 levels), symmetry (4 levels), quantity (4 levels), and condition (4 levels). The rating method produces an earthquake resistance point value that is then compared with values for four intensities (MMI V, V1, VIT, and VIlI+), with the result being a four-level (good, fair, poor, very poor) evaluation. Nonstructural components are considered via use of a few overall categories. The inclusion of nonstructural damage in a method is unusual. The general exclusion of nonstructural damage seems to be more attributable to limited budgets rather than a disregard for the im- portance of this type of damage. The field evaluation method is based on a rating of components, rather than overall engineering judgment or overall construction class. Another componen~based method ~ the ISO (1983) Guide for Determination of Earthquake Ciassifications, which differs from the earlier ISO overall construction class method referred to as The ISO methods throughout this paper. In the guide, which describes a point rating system, the following components are defined: framing system (16 categories) with a weighted combination for buildings where more than one framing system is present, exterior walls (12), interior partitions (3), diaphragms (7), area/height (3), ornamenta- tion (S), configuration irregularity (4), equipment (4), design level (5), and quality control (5). The output is a point total that converts to ISO earthquake insurance guideline premium rates, rather than a direct loss estimate. Standard and Poor's Corporation (n.~.) also uses a loss or risk estunation based on components. Local engineers are directed to tabulate a building's construction in terms of: vertical and lateral load-resisting system (27 categories), floor (21), roof (28), exterior wall (17), interior was (13), year built, and stories. Another building-specific, component-based rating system is the FEMA Natural Hazard Vulnerability Surrey (FEMA, 1985a) method. Beginning in 1985, essential emergency response facilities began to be surveyed in different areas of the country. The earth- quake, hurricane and high wind, tornado, and flood portions of the method were applied where geographically applicable according to definitions of threshold risk. The output, in addition to a specific

146 rating of several nonstructural components (e.g., whether the gener- ator is anchored or not), is a five-levl! rating. Uniform Building Code seismic zones are used, along with estimates of the building's period, mass, and other factors, to estimate the load. The construction com- ponents surveyed and numbers of classes for each are: length, width, average floor area, and height; whether designed by architect anchor engineer; year designed; frame (13 categories); shear wall type (10~; total shear wall lineal footage for each axis, per story; diaphragm (73; configuration irregularities (6~; connections (83; condition (3~; seis- mic code (5~; and soil (2~. Geologic hazards that pertain, extracted from available published maps, are converted to a standard severity scale; hazardous appendages are noted; seven nonstructural items are rated resistant or nonresistant; and the existence or absence of an earthquake plan for the occupants of that building ~ noted. A review of literature and development of a detailed component- based method intended for high-technology facilities Is described in the work of EQE, Inc. (1985~. A portion of this approach ~ derived from research on component-based earthquake loss estimation by Kustu et al. (1982~. One of the advantages cited for this approach is the ability to combine the results of experimental work, which is mostly done on the scale of a component rather than a complete building, with more general approaches to loss estimation. Where a given type of construction is of interest, such as un- reinforced masonry, methods particular to this class are sometimes available. An early application of a component-rating system for purposes of rating unreinforced masonry buildings in a local govern- ment seismically hazardous building program (the first In the United States, beginning in the 1950s) was in I,ong Beach, California (City of Long Beach, 1977). This approach, using a concept of balanced risk, was developed by Wiggins and Moran (1971~. As noted in the discussion of lifelines, key individual lifeline structures must be evaluated with a facility-specific method. The reports by the California Division of Mines and Geology are exam- ples of earthquake loss studies where the estimated performance of individual major bridges, highway segments, airport runways, and other specific facilities is evaluated and listed (Davis et al., 1982a,b).

147 PRINCIPAL ELEMENTS OF SEVERAL SPECIFIC METHODS The NOAA-USGS Inventory Method The NOAA-USGS method for estimating losses from earth- quakes actually ~ a general approach that has been used in several studies undertaken over the past 15 years, usually with major roles played by S. T. AIgermissen (USGS) and Karl Ste~nbrugge (con- sulting structural engineer). Its construction classes and motion- damage-Ioss relationships are essentially those of the ISO system and are discussed In Working Paper E. Whether or not these loss studies should be generalized and called a single method is subject to debate, but the general inventory technique is discussed here in reference to two specific applications, the San E`rancisco Bay Area (AIgerm~ssen et al., 1972) and the Salt Lake City Area or Was atch Front (Rogers et al., 1976) studies. Compared with the ATC-13 inventory method, discussed later, which attempts to enumerate every facility within the study area, the NOAA-USGS method is selective in its inventory process. In some cases, such as the Salt Lake City study, a few classes of con- struction, such as unreinforced masonry, can be reliably predicted to account for a large part of the total losses (AIgerm~ssen and Stein- brugge, 1984), and thus the inventory effort is more concentrated on these influential construction classes. The concept of seeking out only the "seismically suspicious" buildings (Arnold and Eiener, 1984) in an area takes this process one step further. If only major emer- gency response unplications of a scenario are needed, one could, for example, avoid inventory of wood-frame dwellings, which are the ma- jority of buildings in most California cities, and instead concentrate the inventory effort on downtown areas where unreinforced masonry, nonductile concrete, or other "seismically suspicious" buildings are most prevalent. (Estimating postearthquake housing problems is an emergency response task that requires dealing with all the dwelling stock.) With respect to the inventory elements of the methods for the two studies, the Wasatch Front study is said to be the more accurate of the two because of the detailed procedures that were followed (AIgermissen and Steinbrugge, 1984~. This Salt Lake City study inventory procedure ~ summarized in that paper as follows: A program supervised by K.V. Steinbrugge for the U.S. Geological Survey was begun in 1974 to develop a detailed inventory of buildings by class of construction in Salt Lake City. For one to four family

148 . dwellings and for population distribution, the best source of data was found to be the United States Census data. The Census provider information of the numbers and geographical distribution of dwellings according to census tract. Census tracts are a convenient unit since the number of one to four family dwellings in each tract seldom exceeds 2000 units in the Salt Lake area. The most accurate cost estimates for housing were obtained from boards of realtors or realtor associa- tions which compile frequent (usually monthly) summaries of actual dwelling sales. Aerial photos and appropriate sampling techniques were used to develop the construction characteristics of dwellings since there is a great difference in vulnerability between wood frame and other types of housing construction. Studies (Steinbrugge and others, 1969) have shown that the number of brick, concrete block and related types of construction used for dwellings in, for example, California is small (less than a few percent). It was found that brick, concrete block and related construction types made up about 60 per- cent of dwellings in the Salt Lake City area. A detailed inventory of buildings by classes of construction other than dwellings was un- dertaken by the H.C. Hugh Company of Salt Lake City for the U.S. Geological Survey. The development of the inventory was supervised by K.V. Steinbrugge. Air photos and drive-by inspection of buildings in-each census tract were conducted. Construction type was noted and the dimensions of the buildings were obtained either from the air photos or from actual measurements. Replacement cost per unit area for the various classes of construction was estimated by a professional building inspector in Salt Lake City with long experience in the re- gion. It is believed that the inventory obtained in Salt Lake City is extremely accurate for the purposes of an earthquake loss study and that the errors in the estimation of ground motion are likely to be much larger than the inventory errors in this particular study. In contrast, the inventory method for the San Etrancmco Bay Area was based on building information extrapolated from census data (dwellings) and modified fire insurance property values (other buildings). AIgermissen and Ste~nbrugge (1984) give the following description of the inventory method in this case. Data on dwellings was obtained in the same manner as described in the Salt Lake City study i.e., from census data and summaries of real estate transactions. For buildings other than dwellings a novel ap- proach was used. Quoting from Steinbrugge and others (1981~: `'The initial data were fire insurance property values by county for north- ern California and an assumed 8.3 magnitude earthquake on the San Andreas fault. These values included dwellings, commercial buildings, manufacturing plants, warehouses, offices, and all other fire-insured properties. These property values were increased to include non- insured private property as well as increased to include under-insured property. Adjustments were made on a judgement basis to include the value of Federal, State of California, and local governments-owned buildings. Intensities from the NOAA report's isoseismal maps were

149 converted into loss {actors, or the percent loss based on an im- personal definition basis. These percentages were multiplied by the property values to obtain the total impersonal 1088 by county in the study area, then summed to obtain the total aggregate loss. In this process, values were adjusted to compensate for inflation to 1980. Building contents for the aforementioned San Andreas earthquake were analyzed in a similar manner to derive the total contents aggre- gate loss. A strong point of this NOAA-USGS inventory approach is its balancing of accuracy versus detail pushing the available data as far as appropriate and then stopping short of making further assump- tions that would be necessary to obtain more detailed estimates. The expertise used in these studies appears to be appropriate to the task: While earthquake engineering experts were employed, the expertise of real estate, building inspection, insurance, or other local sources of knowledge concerning the distribution of classes of construction was also utilized. A weak point in the method is that complete documen- tation of the technique—complete enough for others to replicate or test the technique in an updating study of the same area or to apply it elsewhere—is lacking. Since the experience of a few key individuals has been heavily relied on in these studies, documentation may be inherently difficult, and to some extent it would be more a matter of teaching an art rather than specifying the precise steps that could be mechanically followed. The 1?EMA/ATC-13 Inventory Method The method for estunat~ng losses from earthquakes described in the AT~13 report (Applied Technology Council, 1985) was designed to provide Formation on damage, casualties, and immediate func- tional loss to be combined with an economic model for predicting economic losses, that is, direct building and structure lopes, loss of equipment, production losses, losses to infrastructures such as utilities and transportation systems, and losses due to interrupted business. To serve its original intended purpose, the inventory and loss estimates had to be compatible with the economic sectors to be used in the interindustry input-output model. Accordingly, this method ~ comprehensive in the inventory it seeks. Forty classes of building construction and 38 nonbudding structure ciames are de- fined, and each facility must also be defined In terms of one of 35 occupancies or asocial functions.

150 The broader nature of the ATC-13 inventory makes it only par- tially comparable with the NOAA-USGS method, and only the por- tion of the ATC-13 inventory method that dead with buildings is discussed here. It should be noted that the breadth of the AT~13 method which encompasses lifelines, industrial structures, ground failures, and functional losses in a quantitative manner ~ one of its significant accomplishments. The FEMA/ATC-13 inventory method aims at compiling loca- tions and quantitative measures for ad facilities plus descriptors of the construction that allow classification for use In estimating dam- age. Facility values are also needed, as is information about each facility's economic use for input into an economic mode} that begins with damage and reduction In functional levels and then forecasts longer-term econorn~c impacts. The portion of the loss study that inventories the information and analyzes it to produce estimates of immediate losses is called FEDLOSS by FEMA in its automated form. The portion of the loss study that would employ an economic input-output mode} to est~ate longer-term econorn~c losses ~ called FElMS (FEMA Earthquake hnpacts Modeling System). The AT~13 report states its preferred source of inventory data as pre-existing inventories of facilities containing the required con- struction class detail, but because even less demanding classification systems cannot be supported by data that have already been col- lected, this preference will in most cases be unfulfilled. This hoped for pre-ex~sting inventory is called a Level ~ inventory. A Level 2 inventory, the one necessary in most cases, wiD be described below. A Level 3 inventory ~ sunply a complete synthesis of an inventory based only on overall population data, such as by a~um~ng both the number and construction types of all buildings in a city on the basis of its population. In the Level 2 approach, the location and descriptors of con- struction are obtained by extrapolation from a variety of economic and census data. The sources for these data are discussed in ATC-13, and are described in detail in the FEMA Data Base Catalog (FEMA, 1985b), which lists the many different computer data files acquired by FEMA from other agencies, through marketing or economic anal- ysis services, or in some cases from within the FEMA organization. These data bases have been accumulated and funded primarily as a function of the civil defense program of FEMA and its predecessor agencies and have been used in nuclear war loss estimations. Corre- lations between facility and use classification were developed in the

151 ATC-13 project to allow for the transformation of economic data into construction data. The relationships imputed In the ATC-13 study were developed only in the context of California. ~ some ways, facility classifications of the ATC-13 method are similar to those of the USGS method, but are more detailed. The ATC-13 method has almost two tones as many classes of construc- tion as the NOAA-USGS method (40 versus 2l, comparing building classes only), and each individual facility must also be amigned one of 35 use categories. There are, however, some buildings whose construction would be more precisely defined by the NOAA-USGS inventory (or ISO) scheme, such as a steel moment-resisting (rigid frame, or rigidly connected joints) building with flexible diaphragms (or floors acting to resist lateral forces). Clearly more information is required to construct an inventory for the 40 ATC-13 classes of facilities than for 21 classes. Given any comparable inventory budget, the accuracy of the assignment of a facility to its proper class in the ATC-13 method would usually be less than in the NOAA-USGS method. The greatest advantage of the ATC-13 method ~ that it is very powerful: it can assemble a very large and detailed inventory inex- pensively by using already computerized socioeconomic data. This is also its biggest disadvantage compared to methods that use ac- tual inventory data obtained from or checked by fieldwork with less extrapolation. The large amount of extrapolation and reliance on rules of thumb developed by combining the opinions of earthquake engineering ex- perts can be seen from a typical example of how the inventory method would operate. First, the ATC-13 method would probably start with the number of employees who work at a commercial or industrial business. (For some small number of industrial facilities, the FEMA data bases may contain construction data and thus make the Level 2 extrapolations unnecessary. The number of ones to four-family dwellings can be obtained directly from census data.) One of a few data bases, such as the Census Bureau's Manufacturing Establish- ments by Industry Sequence, would be used in which the known information (excluding economic data on value of goods produced, for example) is simply number of employees and the location by zip code, along with the detailed (four-digit) Standard Industrial CIas- sification (SIC) code that defines the type of economic activity. The precision of the location is sometimes but not usually an issue. For

152 example, the zip code location listed for a supermarket company in a city wall lump Al of the employees at the headquarters' zip code. These data number of employees, type of economic activity, and location- are the only data known directly for the facility in most cases, and the remainder of the necessary data ~ synthetic. As ATC-13 notes, The FEMA Manufacturing Establishment File, the Wholesale Trade Establishment File, and other business establishment/company files do not include either the size, location, or structural characteristics of facilities. This information must be estimated based on economic data such as the number of employees or annual production amounts. . . . Few if any existing facility databases or the inventories synthesized using Level 2 and 3 procedures contain sufficient information to allow the accurate determination of Earthquake Engineering Facility Classifications. The second step in the AT~13 inventory method Is to relate the number of employees to the building size, according to estimat- ing factors for different occupancies. These relationships are gener- ally drawn from transportation studies, especially those of Caltrans (California's highway department). In the ABAG inventory method (Perkins et al., 1986), similar relationships were used to estimate building square footage, using instead Federal Highway Administra- tion data. This extrapolation is more accurate than those of the other steps and is not a major source of error. As noted in the work of Jones et al. (1986), stable and reliable relationships exist for square footage per person estimating factors, although a curious effect of this relationship ~ that an inventory would show buildings swelling and shrinking in size as fluctuations in the economy cause the number of employees in a building to rise or fan. The third step ~ to divide up the buildings, known at this point only in terrors of location and, by extrapolation from number of employees, the size, into construction classes. The height of the approximately 3,000 high rises in California can be known from files specific to high rises assembled by the Council on Tall Buildings of Lehigh University. For the majority of buildings that remain, they can be divided into mid-rise and low-rise categories based on rules of thumb developed by a process of asking earthquake engineering experts their opinions. In this third step of developing a synthetic construction class distribution, the other basic task is to assign a construction class (e.g., reinforced masonry shear wall with moment-resisting frame, reinforced masonry shear wall without moment-resisting frame) to

153 each facility. This was done by obtaining collective expert opin- ion from the engineers involved in the ATC-13 project, assigning a certain percentage of the buildings in each use category to each of the construction classes. In each use category (e.g., s~gle-family dwelling) the fractions for low-r~se wood frame, low-rme reinforced or unreinforced mansonry, and so on sum to 100 percent. The result ~ the end-form data: construction class (and high- , mid-, or low-r~se subclass designation), floor areas, use, and zip codes for ad buildings in the study area. Steps one and two involve relatively noncontroversial extrapolations common to many loss esti- mation methods. It ~ the third step, where the inventory variable of central importance construction class is synthesized on the basis of opinion, that involves untested relationships. Essentially, the con- struction class inventory ~ synthesized knowing only the number of employees, the zip code of the business, and the economic function. Comparison of the NOAA-USGS and FEMA/ATC-13 Inventory Methods A full application of the ATC-13 method has not yet been re- ported in the literature. The NOAA-USGS method is a general method that can be extracted from the reports of its application, for example, the large-scale NOAA-USGS loss study of San Franc~sco. ATC-13 is a report that describes its method very specifically, but there ~ no loss estimation study or actual application to refer to as a concrete case. This makes a comparison of the two inventory methods difficult. Also, the two methods were devised for different purposes. Although the comparative information given in Table D-1 on the type of end-form data implies that inventories would be much the same for both methods, this is not precisely true. Somewhat different characteristics are used for classifying the facilities In the two methods, and this affects the details for each. However, the striking difference in the two methods ~ not the data they seek, but how they assemble them. While both methods use judgment in the inventory process, the ATC-13 method is more reliant on judgment. The application of judgment in the ATC-13 method is, however, generally more apparent, In that it would be easier for other investigators to rely on the published description of the method, reuse it, and replicate the results obtained by others. Descriptors used in the classification process for each method

154 TAl3LE D-1 Comparison of ATC-13 and NOAA-USGS Inventory Data FEMA/ATC-13 NOAA-USGS Seventeen basic building construction classes with subclasses for low, mid-, or high-rise heights, and combinations of systems (such as shear wall and frame); 40 classes total Primary categories Wood frame Light metal Unreinforced masonry Reinforced-concrete shear wall Reinforced-masonry shear wall Braced steel frame Moment-resisting steel frame Moment-resisting concrete frame Precast concrete Long span Tilt-up Mobile home Descriptorsa Structural material Framing system Floor area Height Ductility Economic use, social function Thirty-five classes that are cross- referenced to the broader range of SIC classes; each facility inventoried is assigned a class Nine basic building construction classes, with subclasses for size and degree of earthquake- resistant design; 21 classes total Primary categories Wood frame Light metal Unreinforced masonry Reinforced-concrete shear wall Reinforced-masonry shear wall Steel frame Concrete frame Precast concrete Tilt-up Descriptorea Structural material Framing system Floor area Height Earthquake-resistant design Economic use, social function Collected for some essential facilities (e g., hospitale) but not collected for each building aAll of these descriptors are not necessarily inventoried for all classes. vary in detail in some cases but would be identical for the two meth- ods in other cases, for example, construction material or height. The lists shown in Table D-1 are in a different form than they appear in either method and are organized more generically to allow for comparisons. For example, the NOAA-USGS approach contains a class for mixed construction (different was and diaphragm mate- rial) that includes buildings with wood roof and floors with walls

155 of tilt-up, reinforced masonry (brick or block) or poured-in-place, reinforced-concrete construction. Variations in earthquake-resistant quality ratings can result in these buildings then being assigned to different classes (Insurance Services Office, 1977~. In Table D-l, these variations on the mixed NOAA-USGS class of construction are listed as separate classes to allow for closer comparison with ATC-13. Inventories for the two methods contain much of the same type of information, although the broader purpose of the AT~13 method (economic loss estunation) leads it to develop two additional detailed sets of information, one on economic function and the other on lifelines and nonbuilding structures. The PEPPER Study In~rento~ Method The method for estunating earthquake lodes used ~ the PEP- PER (Pre-Earthquake Planning for Post-Earthquake Rebuilding) study (Spangle, 1984) relied on automated data already collected by the planning department of the City of Los Angeles. No new field surveys were conducted, partly because of budget limitations and partly to try to test the usefuIne" of this large data base, which had been assembled from assessors' tax records and other sources. As partial checks on the accuracy of this comprehensive data base of about ~ million buildings, files containing information specific to building construction characteristics were consulted. An accurate inventory of pre-1934 (preseism~c code) unreinforced masonry build- ings was already in existence because of the city's retroactive seismic ordinance, and the characteristics of high-rme buildings were tabu- lated in a real estate survey. Census data on population and housing from the 1980 census were used, along with a 1974 city study. Buildings were (~) aggregated in planning areas of the city, and (2) classified according to type of construction ~ five classes: steel, concrete, masonry, wood, and special. Use was classified according to four classes: residential (with three subcIames), commercial, in- dustrial, and other. No other details appear in the report to suggest the way in which buildings were allocated to each class. As noted in the study's engineering report, The inventory of structures . . . is probably the least reliable component of the various factors that determine the damage pattern" (Degenkolb, 1984~. The building classification method might be described as an adjusted NOAA-USGS method. The PEPPER method adjusted the basic ISO or NOAA-USGS construction classification system

156 because the available data were not that finely subdivided. This also had implications for the analysis task, because the hybrid or combined construction classes of the PEPPER inventory had to be analyzed using hybrid motion-damage relationships. The beginning form of the data In the city planning department's data base did not differentiate high rises according to their type of enclosure system (e.g., curtain wall, poured-in-place concrete). Inferences based on year of construction (e.g., assuming that post-1960 high rises were predorn~nantly of curtain wall exterior) were used. One point made by this study is that even if a very large com- puterized file of buildings exists, this does not necessarily mean that the data are detailed or accurate. Lack of detail is evident from the fact that all steel buildings, or aD concrete buildings, for example, were lumped together In one class. This level of detail is a common constraint in the use of assessors' or local planning department data. The accuracy of the inventory was also limited and was related to the fact that this data base was assembled for nonseism~c, nonengineer- ing purposes. An example of a major type of inaccuracy concealed in the data bee was that high-rise buildings were sometunes described as having wood-frame structures. Another problem was that this data base was not current because the cost of updating it had been considered too high by the planning department a few years after it had been created. POSTEARTlIQUA1lE STUDIES OF LOSS Related to the pre-earthquake inventory problem ~ the task of postearthquake inventory of damage by class of construction, loca- tion, ground conditions, and intensity or measured ground motion. Although all loss estunation investigators bemoan the fact that there are not more historical loss data available, there are few ongoing ef- forts outside of the insurance industry to collect this type of data after earthquakes occur. As pointed out in the Earthquake Engineering Research Institute's guide to postearthquake investigation (Earth- quake Engineering Research Institute, 1977), und~naged as well as damaged buildings should be tabulated. Statistical techniques pro- vide many tools for analyzing damage data, and these are explained in the guide in a special section. However, most earthquake recon- naissance reports or detailed studies do not comprehensively report damage or loss data, but rather concentrate on the more unique or instructive individual cases of damage.

157 Because the types of pre-earthquake inventory data and con- struction classes that are generally used are known prior to initiating postearthquake investigations, damage data could be collected effi- ciently, on a sampling basis where necessary, to try to fill gaps in historical loss data. Although in theory systematic studies of build- ing damage could result in complete data for estimating purposes, in practice this is not so. Construction innovation will always be ahead of recorded earthquake experience. Earthquakes in Chile and Mexico in 1985 tested the building construction methods in use in these coun- tries of the 1950s, 1960s, and 1970s. There are no data, however, on the performance, under moderate to severe ground motion, of tall welded perimeter tube structures, modern m~d-rme steel-braced frame structures, or large t~vo-story tilt-up concrete structures that are common in many parts of the United States. SUMMARY In theory, a perfect inventory can be created. However, it will never be achieved because of cost and tune constraints. Therefore, ways of obtaining the most useful, imperfect inventory are being studied. The attempt to start from an econorn~cally based inven- tory, as in ATOLL, is not advised. Although the final output is intended to be economic, economic loss can only be estunated on the basis of an estimate of earthquake damage. Earthquake damage can only be estimated accurately when building construction data are directly sought. Converting economic data into construction cIassifi- cation data ~ not recommended because this can greatly reduce the accuracy of the inventory. If the focus is to be on building damage, then the inventory should focus on vulnerable or ~seisrn~ca]ly suspicious" buildings. Pro- cedures that provide an initial screening by low-cost means, leading to a more detailed survey to provide accuracy, make more sense than an attempt to develop a complete inventory from which the hazardous buildings must be selected. Facilities with a potential for large loss, or with essential emer- gency functions, should be inventoried on a case-by-case, field survey basis. The insurance industry, particularly in California, has much in- formation both on building damage and on building inventory. This information is generally unobtainable due to industry's confiden- tiality requirements and competitiveness, although the California

158 Department of insurance obtain this Information, aggregated by geographic zone and clam of construction, on an annual basis. 0~ tanning some of this information would benefit national or regional interests, solve some of the data problems of earthquake damage estimating, and yet-preserve such proprietary information as the industry deems necessary.

Working Paper E Relationships of Ground Motion, Damage, end toss Although in actual practice the steps in a loss estimation study do not necessarily proceed sequentially, the previously discussed tasks of seismic hazard analysis (Working Paper C) and inventory (Work- ing Paper D) are conceptually the two steps that precede the process of relating the ground motion or ground failure to a given construc- tion class to estimate damage. This paper also discusses relating damage to property low, casualties, or functional loss. The discus- sion here is limited to the eEects of ground shaking on buildings and lifelines; the effects of ground failures are treated in Working Paper G. Material presented in the two earlier working papers is directly applicable here. Working Paper C discussed the limitations of the Modified Mercalli Intensity (MMI) scale and other problems in the accurate definition of the ground motion to which the inventory should be subjected in the motion-damage analysis step. Working Paper D explained that the construction classification system is a part of both the inventory process and the motion-damage analysis step because the inventory information must be collected with the same construction classes used in relating the seismic hazard to construction classes through motion-damage relationships. Many methods of relating ground motion, or less commonly ground failures, to damage have been proposed or developed. How- ever, in the context of large-scale, general-purpose loss estimation 159

160 studies the number of basic approaches is relatively small. In this paper, three particular methods are discussed because they bring out different aspects of the possible ways to approach this problem of relating motion, damage, and loss. The loss estimation method referred to here and elsewhere in this report as the NOAA-USGS method is also, in terms of the motion-damage analysis step, essentially the Insurance Services Of- fice (ISO) method. As explained earlier, this method was used In the first large-scale studies produced by the National Oceanic and Atmo- spheric Administration (NOAA) and later, with essentially the same personnel, by the U.S. Geological Survey (USGS) when NOAA's earthquake loss estimation functions were shifted to USGS. This method has been molded by the work of AIgermissen, Stein- brugge, and others. The studies of San Francisco (AIgermissen et al., 1972), Los Angeles (AIgermissen et al., 1973), Puget Sound (Hopper et al., 1975), and Salt Lake City (Rogers et al., 1976) are examples of the use of this method. It is the method that has been applied in most of the urban- or regional-scale studies of the type focused on in this report (studies intended for disaster planning and hazard reduction purposes). It is also the method that has been most widely used in the prop- erty insurance industry. The NOAA-USGS or ISO method produces damage estimates in the form of mean damage ratios for each con- struction class percentages associated with each MMI level indicat- ing the average property loss In terms of cost of repair or replacement divided by replacement cost. In the NOAA-USGS method, lifelines and nonbuilding structures are analyzed by different methods than the mean damage approach applied to buildings. The ATC-13/FEMA approach was produced by the Applied Technology Council and funded by FEMA (Applied Technology Council, 1985~. While it has yet to be carried out in a loss study resulting in a published report of the type produced for several re- gions of the country by the NOAA-USGS method, it is a recent, comprehensive effort that involved many experts and it surveyed and evaluated a broad range of analysis methods and data. The ATC-13 method uses the format of the damage probability matrix to present its damage estimates for each MMI level: the percentage of facilities that wouic] fall into each of seven damage levels is given for each construction class (with these damage levels described verbally, with property damage ratio ranges, and with central damage ratios). For each MMI, the distribution of damage

161 for a construction class can also be converted into an overall damage ratio. In the ATC-13 method, lifelines and nonbuilding structures are essentially handled with damage probability matrices the same way as for buildings. A third basic method to be discussed is the application of fragility curves to the task of estimating regional-scale earthquake losses. The Central U.S.-Six Cities study (ABen and Hoshall et al., 1985) used this approach. The motion-damage portion of this study's method, the development of fragility curves based on a combination of em- pirical or historical data and theoretical calculations, was developed by Jack Benjamun and Associates, Inc. (Kircher and McCann, 1984) and is occasionally referred to as the lBA method later. One fragility curve describes the probability a given construction class will reach or exceed one particular level of damage at various intensities of shaking. A set of curves, to cover all the damage states, is used for each construction class. Fragility curves and damage probability matrices are similar in the information they provide and one can be converted into the other. Fragility curves present the information graphically, while damage probability matrices present the infor- mation in tabular form. In the dBA-Central U.S. study's method, lifelines and nonbuilding structures were treated with fragility curves in a manner parallel to that used for buildings. NOAA-USGS MOTION-DAMAGE RE[ATIONE3HIPS The earliest U.S. attempt at estimating earthquake property loss on a large scale began in 1925 when engineers Harold Engle and Jack Shields gathered data on the damage caused by the Santa Barbara earthquake for use by the insurance industry. This work has con- tinued and has resulted, after several developments and refinements, into the NOAA-USGS method or the similar ISO method. The generic NOAA-USGS motion-damage relationship is shown in Figure Ad. The truncation of the mean damage ratio curve at MMI X-X is due to the fact that intensities above this point have sometimes been assigned to sites in previous earthquakes on the basis of ground failure, not ground shaking. Table ~1 briefly tabulates the construction classes. Each class is described with approximately a paragraph in the Commercial Earthquake Insurance Manual (ISO, 1977). The damage ratio is the percentage damage related to cost of

162 100 a' ILL - co an o J IL] G IL .~. ale....... ..~.............. ,A ~ 2.- - 2..2 - - .. ~ 2 2. . ~ ' Geologic ~ ~= , ~ effects .~............................................................................... Ace . .................. ' ~^ SAC O ~ a.,, . ~ ~~ D 1 1 1 E 1 1 IV V Vl Vll Vlil IX X Xl X11 MODIFIED MERCALLI INTENSITY FIGURE E-1 Relationship of ground failures to ground shaking in the Modified Mercalli Intensity scale. Source: Steinbrugge (1982~. replacement. Mean damage ratios are used because they are aver- age factors for all buildings of given classes. They do not give the distribution of damage, such as how many buildings had little or no damage or how many had moderate damage. The mean damage

163 TABLE E-1 Construction Classes Used in the ISO and NOAA/USGS Methods Building Class Brief Description of Building Subelasses lA-1 Wood-frame and stuccoed frame dwellings regardless of area and height 1A-2 Wood-frame and stuccoed frame buildings, other than dwellings not exceeding three stories in height or 3,000 square feet in ground floor area 1B 2A 2B 3A 3B 3C 4B 1A-3 Wood-frame and stuccoed frame structures not exceeding three stories in height regardless of area Wood-frame and stuccoed frame buildings not qualifying under class 1A One-story, all metal; floor area less than 20,000 square feet All metal buildings not under 2A Steel frame, superior damage control features Steel frame, ordinary damage control features Steel frame, intermediate damage control features (between 3A and 3B) 3D Steel frame, floors and roofs not concrete 4A Reinforced concrete, superior damage control features Reinforced concrete, ordinary damage control features 4C 4D 4E 5A 5B 5C 5D BE 6 Reinforced concrete, intermediate damage control features (between 4A and 4B) Reinforced concrete, precast reinforced concrete, lift slab Reinforced concrete, floors and roofs not concrete Mixed construction, small buildings and dwellings Mixed construction, superior damage control features Mixed construction, ordinary damage control features Mixed construction, intermediate damage control features Mixed construction, unreinforced masonry Buildings specifically designed to be earthquake resistant SOURCE: Algermissen and Steinbrugge, (1984~. For more complete descriptions of each class, see Iso (1977) and McClure et al. (1979~.

164 35 30 25 - a) ~ 20 a) cat a) _' in 1 5 o J 10 5 r - ~5~ /~B 3D 4C 5C / _~, ~ ~ , 3C 4A 5B/ - - /' 3A 2B A/— 1 1 V Vl V11 MM INTENSITY V11 IX FIGURE ~2 Mean damage ratio curves used in the NOAA-USGS method. Source: Algermmsen and Steinbrugge (1984~. ratio directly defines property loss, but does not directly indicate loss of function or number of casualties. Figure ~2 shows some of the mean damage ratio curves used in the NOAA-USGS method. The amount of historic damage data available on some of the classes of construction, particularly wood-frame dwellings, is exten- sive, whereas more judgment and fewer data are employed to develop damage ratios for high-rise buildings or many low-rise commercial- industrial construction classes for which there is less experience. The ISO system generally limits itself to classes of construction for which there are historic data. Single-family wood-frame dwellings are the class of construction

165 having the greatest historical data, with the possible exception of mobile homes. The accuracy of the basic NOAA-USGS method for this class is high as judged by the work of McClure (1967),* whose property loss relationships (based on the 1952 Kern County earthquakes) predicted a total loss of $3.8 million when applied to the 1969 Santa Rosa earthquakes, whereas the actual postearthquake estimated dwelling loss figure was $4 million (Steinbrugge et al., 1970~. Another test of a loss estunation method for single-family dweD- ings is provided in Rinehart et al. (1976) wherein the results of a modified version of the 1969 method by Steinbrugge and others are favorably compared with data from the 1971 San Fernando earth- quake. The 1971 data on all of the approximately 12,000 dwellings in one area of the San Fernando Valley where the shaking was strongest are unusually large and detailed. Often only rough or sem~quanti- tative data on a few dozen buildings of one construction class are available Tom an earthquake, or the reports are selective (typically only noting cases of dramatic damage). ATC-13 MOTION-DAMAGE RELATIONSHIPS The ATC-13 method does not describe its building construction classes in as much detail as in the NOAA-USGS scheme, but includes many structures that are not addressed in the NOAA-USGS method. It has a total of 78 classes of structures, 40 of which are buildings and 38 of which are lifeline-related or equipment classes. These classes are listed in Table ~2. Lacking the major source of hard data in the ISO or NOAA- USGS method, which was proprietary to the insurance industry, ATC-13 relied on the expert opinion of experienced individuals in the earthquake engineering field to produce motion-damage relation- ships. The techniques used for processing the questionnaire answers are described in the AT~13 report. The form in which the ATC-13 motion-damage relationship for each class was solicited from the experts, and the way in which the combined or consensus expert opinion was presented, was the damage probability matrix. This format and idea was originated by Marte} (1964) and independently developed in the Massachusetts Institute * Given the loose definition of aNOAA-USGSn method used here, the McClure work fits this definition.

166 TABLE E-2 Earthquake Engineering Facility Classification Facility Classification Number BUILDINGS Wood frame (low rise) Light metal (low rise) Unreinforced masonry (bearing wall) Low rise (1-3 stories) Medium rise (4-7 stories) Unreinforced masonry (with load-bearing frame) Low rise Medium rise High rise (> 8 stories) Reinforced concrete shear wall (with moment-resisting frame) Low rise Medium rise High rise Reinforced concrete shear wall (without moment-resisting frame) Low rise Medium rise High rise Reinforced masonry shear wall (without moment-resisting frame) Low rise Medium rise High rise Reinforced masonry shear wall (with moment-resisting frame) Low rise Medium rise High rise Braced steel frame Low rise Medium rise High rise Moment-resisting steel frame (perimeter frame) Low rise Medium rise High rise Moment-resisting steel frame (distributed frame) Low rise Medium rise High rise Moment-resisting ductile concrete frame (distributed frame) Low rise Medium rise High rise 2 75 76 78 79 80 3 4 6 7 8 9 10 11 84 85 ~6 12 13 14 15 16 17 72 73 74 18 19 20

167 TABLE E-2 (Continued) Facility Classification Number Moment-resisting nonductile concrete frame (distributed frame) Low rise Medium rise High rise Precast concrete (other than tilt-up) Low rise Medium rise High rise Long-span (low rise) Tilt-up (low rise) Mobile homes BRIDGES Conventional (less than 500-ft spane) Multiple simple spans Continuous/monolithic (includes single-span bridges) Major (greater than 500-ft spans) PIPELINES Underground At grade DAMS Concrete Earthfill and rockfill TUNNELS Alluvium Rock Cut and cover STORAGE TANKS Underground Liquid Solid On ground Liquid Solid Elevated Liquid Solid 87 88 89 81 82 83 91 21 23 24 25 30 31 32 ~5 56 38 39 40 41 42 43 44 45 46

168 TABLE E-2 (Continued) Facility Classification Number ROADWAYS AND PAVEMENTS Railroad Highways Runways CHIMNEYS (high industrial) Masonry Concrete Steel CRANES CONVEYOR SYSTEMS TOWERS Electrical transmission lines Convention (less than 100-ft high) Major (more than 100-ft high) Broadcast Observation Offshore OTHER STRUCTURES Canal Earth-retaining structures (over 20-ft high) Waterfront structures EQUIPMENT Residential Office (e.g., furniture, computers) Electrical Mechanical High technology and laboratory Trains, trucks, airplanes, and other vehicles 47 48 49 50 51 52 53 54 55 56 57 58 59 61 62 63 64 65 66 68 70 90 SOURCE: Applied Technology Council (1985).

169 TABLE E-3 General Form of Damage Probability Matrix as Used in ATC-13 (in percent) D amage Central a Factor Damage Probability of Damage by MMI Range Factor VI VII VIII IX X XI XII 1--None 0 0.0 95.0 49.0 30 14 3 1 0.4 2--Slight 0-1 0.5 3.0 38.0 40 30 10 3 0.6 3--Light 1-10 5.0 1.5 8.0 16 24 30 10 1.0 4--Moderate 10-30 20.0 0.4 2.0 8 16 26 30 3.0 5--Hea~ry 30-60 45.0 0.1 1.5 3 10 18 30 18 6--Major 60-100 80.0 -- 1.0 2 4 10 1 39 7--Destroyed 100 100.0 -- 0.5 1 1 3 8 38 aExample values are listed. NOTE: These definitions are used as a guideline: 1--None: no damage. 2--Slight: limited localized minor damage not requiring repair. 3--Light: significant localized damage of some components generally not . . . requlrlng repair. 4--Moderate: significant localized damage of many components warranting repair. 5--Heavy: extensive damage requiring major repairs. 6--Major: major widespread damage that may result in the facility being razed. 7--Destroyed: total destruction of the majority of the facility. SOURCE: Applied Technology Council (1985~. Of Technology Seismic Design Decision Analysis research program by Whitman et al. (1973~. Table ~3 shows a generic ATC-13 damage probability matrix. MMI XI and XIT are used here to refer to increasingly severe ground motion, beyond the X-X point; this is not a literal interpretation of the scale's reference to ground failure indicators at these highest two intensities. Examples of damage probability matrices produced by expert opinion in the ATC-13 project are shown in Table ~4. Facility class 73 (medium-r~se moment-resisting distributed steel frame) and 74 (same, except high riser are very earthquake resistant. Classes 75 and 76 are low-rise and medium-rise, unreinforced-masonry bearing walls, which are very damageable. At any given intensity, the dis- tribution for the steel frames will be seen to be concentrated at a much lower level of damage than for the unreinforced masonry. In any column, the percentages total to 100. Although these expert opinion matrices show that for any in- tensity the buildings are usually contained within two or three dam- age levels, this is not quite consistent with observations of actual

170 TABLE E-4 Damage Probability Matrices From ATC-13 Central Damage Modified Mercalli Intensity Factor VI VII VIII IX X XI XII Facility Class = 73 0.00 22.4 1.1 *** *** *** *** *** 0.50 51.3 34.0 2.5 *** *** *** *** 5.00 26.3 64.9 95.4 83.1 29.5 9.2 0.2 20.00 *** *** 2.1 16.9 70.5 80.7 50.6 45.00 *** *** *** *** *** 10.1 49.2 80.00 *** *** *** *** *** *** *** 100.00 *** *** *** *** *** *** *** Facility Class = 74 0.00 26.8 0.5 *** *** *** *** *** 0.50 60.0 22.2 2.7 *** *** *** *** 5.00 13.2 77.1 92.3 58.8 14.7 5.9 0.8 20.00 *** 0.2 5.0 41.2 83.0 67.1 42.3 45.00 *** *** *** *** 2.3 26.9 55.7 80.00 *** *** *** *** *** 0.1 1.2 100.00 *** *** *** *** *** *** *** Facility Class = 75 0.00 *** *** *** *** *** *** *** 0.50 9.1 0.6 *** *** *** *** *** 5.00 90.5 55.5 10.9 0.5 *** *** *** 20.00 0.4 43.4 66.0 22.4 2.0 0.1 0.1 45.00 *** 0.5 22.9 65.9 35.0 10.1 3.4 80.00 *** *** 0.2 11.2 62.5 83.1 50.4 100.00 *** *** *** *** 0.5 6.7 46.1 Facility Class = 76 0.00 *** *** *** *** *** *** *** 0.50 4.7 1.5 *** *** *** *** *** 5.00 89.9 49.5 3.7 *** *** *** *** 20.00 5.4 46.4 53.3 7.6 0.9 *** *** 45.00 *** 2.6 42.0 63.4 21.4 5.3 S.1 80.00 *** *** 1.0 29.0 74.7 80.0 43.0 100.00 *** *** *** *** 3.0 14.7 53.9 * * *Very small probability. SOURCE: Applied Technology Council (1985~.

171 earthquake performance. For example, at MM! VITI or ~X, no unreinforced-masonry buildings are predicted to collapse, whereas in areas assigned those intensities in the 1933 Long Beach or 1983 Coalinga earthquakes, collapses of this class of construction did occur 5 percent in 1933 in Long Beach (Wailes and Homer, 1933) and 30 percent in Cowlings In 1983 (Reitherman et al., 1984~. It has been suggested that in the ATC-FEMA method, a larger spread of damage classifications could be attained for any intensity of shaking by averaging the proportions of each central damage factor one or two steps down and one or two steps above the desired MM! intensity. (The matrices apply to "average Californian construction.) For some purposes, the average damage ratio (caBed damage factor in the ATC-FEMA method) ~ not sufficient; instead a ma- tr~x of the distribution of the degree of damage, as provided by the ATC-FEMA method, is needed. This would be important when con- sidering effects of deductibles for earthquake insurance, or calculating the number of homeless, casualties, and so on. Another recent study used a different method for the expression of damage. The Central U.S.-Six Cities study (Allen and Hoshall et al., 1985) presented the relationship of motion to damage In terms of fragility curves. This adaptation of fragility curves to the task of large-scale loss estimation is described in Kircher and McCann (19843. "Fragility curves . . . provide essentially the same information as does a DPM (damage probability matrix), but in graphical rather than tabular forms (Whitman, 1986~. Figure ~3 describes the dam- ageability or fragility of one class of construction. In this case, it ~ a general class of "all wood-frame buildings" which would be applicable where distinctions between above and below standard wood-frame buildings cannot be made. Figure ~3 illustrates that for earthquake intensity MMI ~X, there is a: 0.95 probability of at least nonstructural damage, 0.91 probability of at least slight structural damage, 0.23 probability of at least moderate structural damage, and 0.01 probability of at best severe structural damage, and 0.00 probability of collapse (Kircher and McCann, 1983~. The key to reading fragility curves is to keep in mind that each curve plots a single damage state and the probability that this state will be reached or exceeded with increasing levels of motion, pro- ceeding toward the right side of the graph. Curves with steeper

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173 slopes imply that those who developed the curves think there is less uncertainty in their estimate than for curves of flatter slope. COMPARISONS BETWEEN METHODS Table ~5 compares mean damage ratios for comparable AT~13 and NOAA-USGS construction classes. Considering the various as- sumptions required in relating motion to loss, the different methods used to devise these motion-Ioss relations, and changing trends in construction and design codes, the comparison of the two methods in terms of average damage ratio shows the results to be remark- ably close. For the first 10 darnage ratios shown in Table ~5, the agreement is much better than for the remainder of the construction classes. However, the relatively good agreement of the two methods does not necessarily establish accuracy for either. No method that Is based on prior earthquake experience or expert knowledge of present and past construction practices can keep current with new construction types, changing code requirements, or changing concepts of quality control. Each earthquake tests existing structures, not the structures in design today or in the future. Damage probability matrices can be converter} into fragility curves. In Figure ~4, ATC-13 results for low-rise unreinforced- masonry buildings have been converted into fragility curves, and compared with lBA curves. For the lower damage levels, the two sets of curves are very similar. For the two highest damage lever, although the median values are similar the shapes of the curves are quite different. The steeper slope of the ATC-13 curves implies that the ATC-13 method concluded there was less uncertainty in estimat- ing the probability of severe damage or collapse than did the CUBA method. While damage probability matrices can be converted into fragil- ity curves, there is a difference in the supporting foundations upon which the motion-damage relationships were based in the studies. In the Six Cities study, calculations of structural capacities were made for a given class of construction. These defined the levels of motion (in units of acceleration, not intensity) at which only nonstructural damage would occur followed by, initial yielding, generalized yielding, and collapse. The steps are shown in Table ~6. This theoretical picture of the fragility of the structure was compared with available historical data, and the two analyses were compared and combined.

174 TABLE E-5 Comparison of Certain Building Damage Ratios, USGS as Compared to ATC-13 at MMI IX Damage USGS ATC-13 Name Number Ratio Curare Damage Ratio Comments Wood frame (low) 1 8.8 1A 12 Old community 9 New development Light metal (low) 2 5.6 2A Small 6 2B Large 8 Unreinforced masonry BE 35 Unreinforced Bearing masonry Low (1-3) 75 42 Medium (4-7) 76 52.9 Unreinforced masonry 4B 25 Vertical frame, Vertical frame nonbearing Low (1-3) 78 27.5 walls Medium (4-7) 79 33.1 High (> 8) 80 44.5 Reinforced concrete 3A 10 1/2 Steel moment- resisting frame Shear wall/moment- Concrete moment- resisting frame 4A 13 resisting Low (1-3) 3 7.8 frame (assume Medium (4-7) 4 12.4 ductile) High (> 8) 5 13.4 Reinforced concrete ED 23 Reinforced Shear wallJno frame bearing walls Low (1-3) 6 12.1 Medium (4-7) 7 15.2 High (> 8) 8 22.6 Reinforced masonry ~ SD 23 Reinforced Shear wall/no frame bearing walls Low (1-3) 9 12.2 Medium (4-7) 10 15.8 High (> 8) 11 20.2 Reinforced masonry 3A 10 1/2 Dual-steel Shear wall/moment- 4A 13 Dual-concrete resisting frame (assume Low (1-3) 84 8.7 ductile) Medium (4-7) 85 10.8 High (> 8) 86 13.9 Tilt-up (low) 21 15.8 4D 30

175 TABLE E-5 (Continued3 Damage USGS ATC-13 Name Number Ratio Curve Damage Ratio Comments Braced steel frame 3A 10 1/2 Low (1-3) 12 9.6 Medium (4-73 13 11.3 High (> 8) 14 14.0 Perimeter steel 3A 10 1/2 CIP concrete walls Moment-resisting 3B 17 Curtain walls frame Low (1-3) 15 6.3 Medium (4-7) 16 8.4 High (> 8) 17 13.0 Distributed steel 3A 101/2 CIP concrete walls Moment-resisting 3B 17 Curtain walls frame Low (1-3) 72 5.6 Medium (4-7) 73 6.7 High (> 8) 74 9.1 Concrete ductile 4-A 13 Moment-resisting frame/distributed Low (1-3) 18 8.7 Medium (4-7) 19 10.3 High (> 8) 20 12.5 Nonductile concrete 4E 27 1/2 Moment-resisting 4D SO frame Low (1-3) 87 17.6 Medium (4-7) 88 24.7 High (> 8) 89 23.4 Precast\no tilt-up 4D 30 Precast or Low (1-3) 81 20.1 lift slab Medium (4-7) 82 23.8 High (> 8) 83 28.8 Long span/low rise 91 6.6 Mobile home 23 13.9 KVS (133 Extrapolated SOURCE: Degenkolb (1986).

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177 TABLE E-6 Steps in Development of Fragility Curves Development Using Calculations and Engineering Judgment Building Acceleration Capacity Parameters Step 1: Determine the basic geometry and structural properties of the building. Step 2: Calculate the base shear capacity value for the building based on the working stress design (WSD) level of the code. Step 3: Estimate the true WSD base shear capacity value for the building considering inherent design redundancies, and so on. This value represents the initiation of nonstructural damage. Step 4: Calculate the base shear value for the building corresponding to the initial yield of the lateral-force resisting system. This value represents the initiation of slight structural damage. Step 5 Calculate the base shear value for the building corresponding to the ultimate capacity of the main elements of the lateral-force resisting system. This value represents initiation of the severe structural damage threshold. Step 6: Interpolate between the base shear value at initial yield (Step 4 resulte) and the base shear capacity at ultimate (Step 5 resulte) to determine the base shear value of the building corresponding to the general yielding of the lateral-force resisting system. This value represents the initiation of moderate structural damage. Step 7: Estimate the base shear value for the building corresponding to the ultimate capacity of all lateral-force resisting elements. This value represents building collapse. SOURCE: Kircher and McCann (1984~. In the ATC-13 study, only expert opinion was used to formulate damage probability matrices. In the earlier work of Whitman et al. (1973) and Martel (1964), historical data (from the 1971 San Fernando and 1933 Long Beach earthquakes, respectively) were the basis of damage probability matrices. Thus, while the Six Cities method used fragility curves, it also

178 used the approach of defining a standard or archetypical building for each construction class. (Actually, three archetypes superior, me- dian, and poor were developed for each of the seven building classes and nine nonbudding structures.) Calculations were then made as a basis for estimating realistic structural capacities, defined in terms of initial yielding, generalized yielding, and collapse. Though detailed, these calculations contained approximations because it is difficult in practice to estimate these capacities (Sharpe et al., 1982~. Historic loss data were then assembled to compare with the theoretical re- sults, with the final fragility curves being a compromise between the two. The careful definition of standard structures ideally with a picture and diagram of the actual or hypothetical building that is the standard allows for the framework of the motion-damage debate or solicitation of expert opinion to be well defined. This method is also designed to accommodate a division of labor. As in other studies, the earthquake engineering was prunarily a task accomplished by California structural engineers; then the inventory work was accomplished by local (Memphis) engineers, using the welI-defined standard buildings as their guide to rating earthquake resistance. Another use of carefully defined standard or archetypical build- ings ~ the work of Gauchat and Schodek (1984), where earthquake engineers' opinions were solicited concerning the vulnerability of dwellings that were precisely defined with drawings and descriptions of materials. Figure ~5 shows the level of detail of the description of one construction class (one of six low-rise housing types defined in the study's inventory phase; captions for the construction details, tabular data relating to building codes, and other information are not shown in Figure ~5~. This detailed description of construction classes allows the use of expert opinion to be focused on the same pre- cise question and also allows other investigators to apply or convert the motion-damage relationships with confidence as to the departure point. All three other major methods reviewed here could benefit from this careful documentation of construction class definitions. Malik (1986) argues that in the case of the ATC-13 project, fit is not clear what each expert considered to be the overall characteristics of a given classification of buildings because the questionnaires only defined the classes by -a short name. "blat is impossible to determine how much of the wide variability in the expert opinion is due to differing opinions regarding the overall characteristics of the building

~ r: ~ ~ '`` 1: ~- - ~ / FIGURE ~5 Definition of one construction class (attached three-story row- house). Source: Gauchat and Schodek (1984~. Foundations: A continuous basement wall of brick supports the party and exterior walls. The interior load bearing lines are supported by a main beam resting on brick piers. Footings are made of large fiat rubble stones. (See A, B. C, D.) Exterior Walls: An exterior brick wall wraps the front and rear of the building which is divided into living units by solid brick party walls. The party walls are bonded to the wrapping exterior brick walls by a series of metal ties. Brick walls are finished with wood lath and plater. (See E, F.) Interior Walls: Interior party walls are made of solid masonry. For interior partitions, typical platform framing is used. Interior walls consist of 2" x 4" studs covered with lath and plaster. (See G. H. I, J.) Floors and Roof: Floors are simply supported 2~' x 10~' (full dimension) members sheathed by diagonally laid 1~' x 6~' sheathing and 19' finish flooring. Roofs are 2~' x 8~' members sheathed with diagonally laid 1~' x 6~' sheathing and finish roofing. (See K, L, M, N.)

180 = _ 4.,~ ~ 2"~;10" Joists _~_ be ~ ~: nut ~ -I ~,~1_ ~~ L,c'aI,:~" ~12" 4" 20" A /~ //~ FIGURE ~5 (Continued). ~~, ~ , ~ . 1 . . ~ . ~1 it_ 1 , ~ >4 r L 1 \ Metal Ties Join 'll.~115 2 "a; 1 0 " J o i .s t .s If" :lf~)" ~ MCKAY. . t ~,.O _ __ B 6"xlO" Bean\, j,` \\ \ I ntcr i or Transverse Pa rty ala I I s ( Ma sorry ) Ch imney Stud I'Jalls I need i or Tr3 nsv<-rse St u d lea I I a. Ext~rio, Lon<'itudin31 We 1 ~ (Masonry ~3y \^.'i O^OW D

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182 ~ I I I I I I D U if 1 1 I _ l , ` \ Interior Transverse —Party Wal is (Masonry ) _ 1, ~ , ~ _ I - Interior Transverse Stud Wall ~L''~ Bas even t tNeam L ~ (column stem | ~ . 2 "xlO" Joists @ 18"oc '/ /~ At_ 2"x6' Of to Is ~ ~ ~ oc M l___ FIGURE ~5 (Continued). ~1 \\` \ \ \ \\ :,': L\~\\~' .~

183 stock," as compared to differences of interpretation of the definition of each class or of the MMI levels. The most critical comment applicable to these earthquake loss estunation techniques is really a statement of the limitation of the state of the art rather than a critique of any individual method. A great deal of judgment and approximation are used to make up for the lack of definitive or hard data. The historical data on earthquake damage and losses are quite scarce as compared with the amount of data available in many other fields where lom or risk estimates are produced, such as with floods, fire, automobile accidents, and disease. This is the basic problem faced by all earthquake loss esti- mation methods. As Arnold (1985) notes, earthquake loss estimation methods are cheap but the information required to make them work · ~ IS eXpenSlVe. Every method must face the question of where to limit itself in attempting to produce quantitative estimates how far to push expert opinion, educated guesses based on suggestive but inconclusive data, or relatively untested extrapolations. This relates to the needs of those who will use the study, and while it has been stated in Working Paper B that these user needs should drive the study and determine its scope and methods, it ~ also true that the users must very realistically assess how much they really need to know, how much information they will really put to practical use, and how reliable this information must be. How much should be attempted? There is little doubt that large-scale, multipurpose loss estimates must produce more than property loss estunates (e.g., casualties are very important), and certainly these estimates must extend beyond housing. Property loss estimates for dwellings, at least where the dwelling stock is relatively homogeneous as fir California, are per- haps more a matter of science than art, but beyond this, loss esti- mation becomes much more art than science. Because any method selected must venture beyond the relative shallows of estimating dwelling property losses into deeper waters, this question of how far to venture will always arise. No large-scale application has yet to attempt quantitative, precise earthquake-caused fire or hazardous materials release losses, for example, because there seems to be a consensus among experts presently that quantitative loss estimation for these secondary or ensuing hazards ~ more appropriately kept in the realm of research rather than put before the public ~ credible forecasts upon which to base behavior. Users want detailed forecasts _

184 of every possible effect, and yet they also demand accuracy. Quali- tative statements identifying high-risk areas or high-r~k factors may be a suitable substitute. The ATC-13 method is the most ambitious to date in several key respects: The number of construction classes; The number of use classes; Reliance on structured expert opinion to produce motion- damage and damage-Ioss relationships; and ~ Extrapolation from nonconstruction (socioeconomic) data to synthesize an inventory. Each of these four aspects was largely determined by the orig- inal scope of the study-for example, the need to enumerate every individual facility by construction and use class, because of the re- quirements of the intended econorn~c use and the decision to rely primarily on presently computerized FEMA data. If the method is now to be applied or adapted to different uses, each of these four aspects requires re-evaluation and revision. 1. construction classes. The number of construction classes could be reduced to be closer to that in the NOAA-USGS system, at least for buildings. Fewer lifeline or nonbuild~g structure classes might be warranted as well, although dealing with these classes in a manner parallel to that for buildings is generally valid and is one of the significant contributions of the ATC-13 effort. 2. Use classes. The number of use classes could be greatly reduced, because for most emergency planning and hazard reduction purposes, the fine distinctions between various commercial and in- dustrial economic sectors wiD not be used. In some cases, greater definition of essential emergency services facilities would be desirable, but this relates to facility-specific field surveys that are not discussed in ATC-13. 3. Reliance exclusively on expert opinion. In attempting fewer predictions, less expert opinion would be needed. For example, to forecast the number of days after the earthquake when 30 percent, 60 percent, and 100 percent of pre-earthquake function is restored for each of 60 use categories (an expanded version of the 35 use or social functions is used for this purpose), and for each of six damage states, 1,080 judgmental answers are needed: 3 functional levels x 6 use categories x 6 damage levels = 1,080 judgments.

185 If the method will be used to evaluate the hazards of unreinforced- masonry buildings in local jurisdictions, use of the historic data available and the increasing number of building-specific structural evaluations of such structures in communities with retroactive ordi- nances would seem to be obvious information sources to incorporate into a method. ATC-13's original broad scope does not make it the best method for such specific application. 4. Extrapolation of inventory `data. Although the synthesis of construction data from economic or social data bases is to some extent necessary in any method, AT~13's extensive reliance on this approach, primarily for budgetary reasons, emerges as a limitation. Other large-scale loss estimation studies have afforded the cost of at least some fieldwork to assemble information on key facilities, to sample areas to develop extrapolations that can be relied on as valid for a particular reg~on's inventory of facilities, and to check at least some of the existing file data's accuracy. The above critique has emphasized the weak points of ATC-13, but the project also resulted in some impressive accomplishments. The ATC-13 final report combines in one volume more data, a more comprehensive review of possible methods, and more discussion by experts of the various tasks involved in the earthquake loss estima- tion process than any other single publication. To some extent, the admirable degree to which the ATC-13 project documented each step of its method is the reason why criticism can be so precisely aimed at its weak points—the transparency allows the critic to see its blem- ishes as well as its attractive aspects. In this respect, the ATC-13 method is much superior to the NOAA-USGS and Six Cities studies discussed in this working paper, and allows independent investigators to analyze and evaluate each detail of the method in a very useful way. While the NOAA-USGS literature makes frequent references to the fact that judgment has been used, these references are not so explicit as to allow investigators unconnected with these studies to replicate the results. Historical lo~ data are relied on to a much greater extent than expert opinion. Moreover, no indication is given as to how expert judgment was structured, whereas the ATCi13 method devoted consiclerable effort to an explicit process of struc- turing the opinions of its expert team. Hence, one of the reasons the ATC-13 study was launched was that The body of historical dam- age data for earthquakes was largely proprietary and not publicly available" (Wilson, 1987~.

186 The NOAA-USGS method, were its publications to define as ex- plicitly the numerous judgments needed to interpret data or produce relationships based on expert opinion where data are lacking, would probably be seen to have comparable weaknesses to ATC-13. The NOAA-USGS method does not attempt to provide estimates of the loss of function experienced by many different economic sectors, to estimate equipment damage in buildings, or to analyze lifeline out- ages in a quantitative manner comparable to buildings. Due to its less ambitious scope and less explicit documentation, these NOAA- USGS weaknesses are less apparent. In summary, the ATC-13 expert opinion method documents at least some of its uncertainties, while these are left quantitatively untreated in the NOAA-USGS reports. The fragility curve approach of the Six Cities study also attempts to portray at least some of its uncertainties. Whether damage probability matrices or fragility curves are the best way to represent loss estimates is an issue apart from the point that the explicit accounting for uncertainty must be attempted by all methods. RE[ATIONSEIP OF DAMAGE TO PROPERTY LOSS Steinbrugge (1986) discusses several complications in the prop- erty loss estimation process. Property damage may be repaired by hiring contractors ("impersonal loss" cost basis), or the owners of buildings (especially lightly damaged dwellings) may perform their own work ("personals basest. For the 1971 San Fernando earthquake, his calculated difference between losses on a personal or ~rnpersonal loss basis amounts to $17 million in 1971 dollars. The difference between defining property loss as the cost of rep air or reconstruction divided by replacement cost, or as a percentage of cash value, can also be very large. McClure (1967) found that the actual cash value of dwellings in Bakersfield at the time of the 1952 Kern County earthquakes was only about a third of their replacement cost, and thus losses calculated on a replacement cost basis would have been about three times greater than if calculated on a cash value basis. (With wood-frame dwellings, where the accuracy of loss estimation is generally considered to be well developed, this is a large difference.) The definition of actual cash value, of great interest in some legal proceedings, is also variable. For legal purposes in some states

187 this is defined as the present market value, while in others it is the replacement cost less depreciation. In spite of these difficulties, the translation of damage estimates into property loss estimates is easier than the task of translating damage into either casualty or functional loss estimates. RELATIONSHIP OF DAMAGE TO CASUALTIES Of all the kinds of loss to be estimated by a study, casualties are perhaps the most important to emergency services organizations and agencies. The data on casualty experience In individual buildings are more anecdotal than is the case with property loss. While there has never been a total collapse without an accompanying property loss of nearly 100 percent (depending on the definition of property loss as discussed above), there have been many buildings that have completely Pancaked and yet have not hurt anyone sunply because the earthquake occurred when the building was empty. Even when buildings are fully occupied at the time of the earthquake, the ca- sualty ratios may differ greatly for the same damage level. This suggests that the casualty experience in previous earthquakes in a larger number of buildings must be collected and analyzed than in the case of relating property loss to damage. At this tune, data that relate building damage to casualties are almost nonexistent. Three pages in the ATC-13 report (257-259) provide most of the known information. The casualty-estimation method used In most large-scale studies is to consult overall (city-wide or larger) casualty statistics from previous earthquakes, rather than to relate casualties directly to damage or property loss estimates. The NOAA-USGS studies, for example, generally applied one casualty rate to wood-frame dwellings and one or more other rates to other kinds of construction. While the overall fatality rate in any of the U.S. metropolitan area studies has always been less than ~ percent, the relative differ- ence between 0.1 percent and 0.2 percent, for example, is a doubling of the predicted fatalities. In the NOAA-USGS studies, serious in- juries that would require hospitalization were estimated at four times the number of fatalities, and thus the spread in the number of injuries predicted could fluctuate widely based on a seemingly small fatality ratio difference. Data collected from a larger number of earthquakes, with the type and degree of injury related to the physical Carnage that caused it, may slowly refine this state of the art.

188 RELATIONSHIP OF DAMAGE TO FUNCTIONAL LOSS Of the three basic kinds of loss, functional loss is the most dif- ficult to relate to damage. In the case of lifelines, areawide average outages from past events are often used, adjusted for local condi- tions, to reach a first approximation of the functional loss problem. For losses caused by building darnage, the methods reviewed above attempt to associate a damage level with functional loss, in some cases inexplicitly (NOAA-USGS), in some cases explicitly (ATC-133. As the ATC-13 report notes, data are insufficient to allow for a sta- tistica] approach, so the relationships are based on judgments of how severely affected various occupancies or uses would be by various levels of damage. The same engineers selected for their expertise on predicting damage were used to develop these relationships. Estimates of homelessness are a form of functional loss projec- tion. The NOAA-USGS method assumed that a 50 percent dwelling damage ratio was the indicator that the building could not be oc- cupied, resulting in homelessness and a need for alternative shelter. While the NOAA-USGS method is usually said to be a mean damage ratio method, the estunation of homelessness required a representa- tion of the spread of the building damage lever. This distribution was obtained prunariTy from the distribution pattern of damage for the 1933 Long Beach and ~L971 San Fernando earthquakes. The 1969 study by Steinbruggefet al. on dwelling losses was also used, and this study essentially used a damage probability matrix: for each MMI, and for each damage ratio range, the per- centage of buildings falling in that MMI/damage cell was produced. This indicates that seemingly clear lines of demarcation between different methods become blurred on closer examination and empha- sizes the potential In developing hybrid methods that combine the best elements of different methods. The damage rati~h~torical data (NOAA-USGS), damage probability matrix-expert opinion (ATC- 13), and fragility curve-analysis of archetypes and historical data (JBA) approaches all have their strong and weak points. The property los~oriented studies of housing from past earth- quakes "identify the dollar losses to wood frame dwellings but do not state at what damage level the houses were evacuated. Indeed, there probably was no consistent practice in this regard; in some earthquakes, social needs were sometimes confused with safety re- quirements when it came to buildings condemnations" (AIgermissen et al., 1972~.

189 Gulliver (1986) reviewed the relationships between damage ra- tio and building condemnation by local authorities that had been researched by Whitman (1974), Lee and Eguchi (1977), and the Of- fice of Emergency Services (1979), and informally consulted some earthquake engineers. She concluded that a 20 percent damage ratio (with damage ratio defined in teens of replacement value) was the threshold past which homelessness would result. In addition to homelessness caused by structural damage for both ground shaking and ground failure, Gulliver estunated homelessness caused by utility outage. Temporary homelessness was estimated according to intensity for eight construction classes, and permanent homeless caseload figures, related to irreparably damaged dwellings, were estunated for the higher damage ratios. Evans and Arnold (1986) proposed a triage-based division of housing damage, defined in terms of habitability: habitable, tem- porarily uninhabitable, and permanently uninhabitable. Severe dam- age to a garage, porch, or deck would not affect the habitability of the adjacent single-fam~ly dwelling, and even severe structural damage might be repairable depending on the occupants' ability to finance the cost. Therefore, this classification system does not correlate homelessness with damage ratio or with overall damage level. The bet of indicators assumed to match these three habitability states require dweDing-by-dweDing inspection, and this method is oriented toward postdisaster housing inspection procedures rather than loss estunation. LIFELINES Lifelines, or utilities and infrastructure systems, include rail- road, motor vehicle, water, electricity, sewage, and communications services. The words systems and services are central to the distinc- tion between the loss estimation process for lifelines as compared to buildings. Service outages are almost Sways a prominent concern addressed by lifeline studies. In many cases, the central concern with the estimation of damage to the building stock is to identify life safety or property risks. With some lifeline components, for exam- ple, dams that are part of a water system, life safety may also be a primary concern, but this does not apply to the majority of lifeline components. A lifeline such as a water or electrical utility's facilities and functions must be analyzed as a system rather than as separate, unrelated structures.

190 ~ v ~ ~ Loss estimation studies have seldom incorporated lifelines to the same extent as building losses. Lifeline loss estimation methodology is not an mature. Most lifeline earthquake engineering studies have either concentrated on deterministic evaluations of specific lifeline designs or on research into lifeline network analyses. The techniques used tent} to be too complicated and tune consuming for incorpo- ration into a large geographic area loss estimation study. However, many recent loss estimation studies are attempting to incorporate lifelines into loss estunations. Future loss estunation studies should be encouraged to include lifelines partially for the purpose of aiding in the maturing of lifeline loss estunation. Because the various components of a lifeline system are interre- lated, lifeline loss estimation methods tend to rely on a probabilistic approach bred on the idea of the reliability of networks. The net- work is defined in terms of serial (in-line, nonredundant) and parallel (redundant) components of the system, and the failure implications of individual components are analyzed in this context. Applying a given level of conservatism to the evaluation of a single switchyard, the result of an expert's evaluation may be that a complete outage should be assumed for emergency planning pur- poses. Applying this judgment to all switchyards in an entire region, forecasting a 100 percent outage throughout the system would not necessarily be appropriate. This same expert, if asked to estimate the overall system's postearthquake capacity, would probably take into account that performance wait vary among a large number of fa- cilities, even if seern~ngly identical in construction characteristics and subjected to the same presumed intensity. The systems approach to lifeline loss estimation also can point out instances where the loss to a single facility could have a widespread effect throughout a system, far out of proportion to the size or property value of that one key facility. The estimation of losses to the individual components of a lifeline system the individual bridge, power transmission or radio tower, docks and quaywalIs, and so on—has a led extensive historical loss experience data base than for buildings. The most ambitious attempt at developing classes that include nonbuilding structures ~ AT~13 (Applied Technology Council, 1985), in which 38 of the 78 total construction classes are nonbuilding structures and most of these 38 classes are related to lifelines. Lifeline service outage estimates can be stated in various ways. The simplest form of the estimate is to state, for example, that a

191 certain segment of a highway route should be presumed either closed or open. A more complex statement, requiring more information and analysis to produce valid results, would be to assign a postearthquake traBic flow capacity to highway segments. This latter approach is unusual, but was used in a study of the San Erancisco Bay Area's transportation system (Jones, 1983~. In the first of the urban-scale 1088 studies by NOAA, the essence of the telephone loss estimate was as follows: It is anticipated that 50 percent of the telephone system will be out of service in the counties of San E`rancisco, San Mateo, Santa Clara and Marin for an indefinite period of time due to equipment damage in the event of a magnitude 8.3 shock on the Bad Andreas fault.... Even without damage to the system, the lines will be overloaded and for all practical purposes it will be useless for telephoning in emergency situations. (Algermmsen et al., 1972) A California Division of Mines and Geology study of the same area and scenario earthquake, although with different scenario intensities, was done 10 years later (Davis et al., 1982b) and provided telephone outage statements with greater detail. The geographic breakdown of outage zones was approximately at the county scale, as for the earlier NOAA study, but the outage was estimated in terms of recovery patterns where the percentage of normal service was graphed versus the number of days after the earthquake. One of four different graphs or levels of outage was assigned to each county-s~zed zone. Losses in the level of service provided by the lifeline should take into account a noneng~neering factor that may be difficult to evaluate: the emergency response capability of the lifeline operator or of other emergency response agencies. A utility with an earthquake-resistant radio system, personnel who undergo annual earthquake exercises to test their ability to carry out preassigned tasks, and back-up plans for handling significant damage beyond that occurring in weather- related incidents, should be much more able to contain the impact of earthquake damage than another utility without these attributes. The first of the large-scale loss estunates (AIgermissen et al., 1972) established the basic table of contents followed by most other lose estimate studies. The categories of lifelines used were: com- munications (primarily radio, television, and telephone service, al- though newspaper and post office services were also briefly consid- ered); transportation (railroads, highways, bridges, mass transit, airports, and ports); and public utilities (electricity, natural gas,

192 water, sewage, and petroleum pipelines). There were 15 systems in all. The Central U.S.-Six Cities loss study (Allen and Hoshall et al., 1985) used fragility curves to analyze individual lifeline components. Bridges, for example, were divided into five classes based on type and length of spans. Network analysis was used to relate the performance of individual components to overall performance of the system. Of the large-scale multipurpose low estimation studies, this appears to be the most extensive use of network analysm to date. Network analysis has been more routinely used with one given lifeline system. The probabilistic analysis of the semi risk faced by a gas utility's system in Utah, where 52 different earthquakes was considered, illus- trates an approach that has become increasingly common in the field of lifeline earthquake loss analysis (McDonough and Taylor, 1986~. Reviews of the state of the art of lifeline earthquake analysis are found in the works of Eguchi (1984), Cooper (1984), Smith (1981), Shah and Benjamin (1977), Whitman et al. (1975), and Duke and Moran (1972~. The Applied Technology Council (1985) reviewed the field in the process of developing ways to deal with the problem of estunating lifeline losses, and another broad review of the field from the hazard reduction perspective is provided by the Building Seismic Safety Council (1987~. The fact that the proceedings of the Eighth World Conference on Earthquake Engineering (Earthquake Engineering Research Insti- tute, 1984) contain 14 papers on the topic and the American Society of Civil Engineering Technical Council on Lifeline Earthquake Engi- neering is engaged in numerous ongoing activities are signs of rapid growth in the field. -v ~ - ~~ J ~ SUMMARY As to the question of the accuracy or uncertainty of these meth- ods, some options can be presented, although little is available concerning controlled, statistically valid comparisons of the results produced by different methods with the actual losses produced by earthquakes. However expressed (e.g., curves or matrices), estimates almost always are used as single numbers. This is true for estimates of forces in engineering design ultimately one force number is developed for design purposes. It is also true for estimates of casualties and

193 property loss that are used for planning and earthquake awareness purposes. The uncertainty contained in a loss study's motion-damage or damage-Ioss analysis method should be documented, as well as that of the seismic hazard and inventory components. When ranges of numbers are provided, however, many users will still need to select a s~ngle-value result the best estimate or maximum estimate, for example. Many disaster planning, public education, and hazard reduction program development purposes require a single number on the bottom Ime of the analysis. At present, accuracy Is not great. A prudent claim would be to within a factor of one and one-half for single-family dwellings, a factor of three for commercial, industrial, and institutional buildings, and a factor of ten for areas with no recent earthquake history.* The amount of systematic data for building damage is very small compared to the variety of conditions applying to any future earth- quake. At present, typical estimating techniques relate a single, gross, structural parameter (construction cIa - ) to a single, gross, ground-motion parameter (intensity) to arrive at a damage estimate. The variety of parameters that In fact significantly affect building performance are indicated in Table ~7, for one claw of construc- tion. Clearly, with even a small uncertainty in each parameter, the cumulative uncertainty must be very large. At present however, there is little point in incorporating these additional parameters in estimating methods because matching damage data do not exist. If the expected accuracy noted above is accepted, then a central concern is the relative accuracy of different methods of relating mo- tion to damage cases. Significant improvements in the state of the art should be sought, but the users of loss studies should not expect dramatic improvements in the near future. Comparisons done so far indicate variations between methods to be well within the limits of overall accuracy. As shown in Table ~5, the most extreme discrete ancy between the NOAA-USGS and ATC-13 estimates is for tilt-up structures, where ATC-13 shows a mean damage ratio of 15.8 per- cent, compared to 30 percent in NOAA-USGA. All other structural types show a much closer level of agreement. Attempts to refine methods, such as greatly increasing the range and definition of structural types, will not improve accuracy until *These ranges have not been established on statistical grounds, and repre- sent a consensus of the panel.

194 TABLE E-7 Damage Estimate Based on Simple Estimating Parameters Contrasted to Listing of All Factors That Affect Damage - E)uilding Description Ground Motion Damage Ratio Estimatea 4A Reinforced concrete, superior MMI IX Reality Height, low, medium, high Structural system types Concrete types and quality Building size Design of connection details Irregularity of plan Irregularity of elevation Building age (code) Building period 13 Percent Acceleration Displacement Velocity Duration Frequency content Foundation type Soil type Dispersion as indicated by DPM or fragility curve aExample category from ISO classification. damage information matches those structural types. The same is true for the effects of ground motion. Use of the Modified Mercalli Scale, with all its limitations, still matches the available Carnage information.

Working Paper F Liquefaction and Landslides LIQUEFACTION As applied to seismic problems, liquefaction has become a catch- all word referring to various types of earthquake-caused failures of saturated cohesionless soils. Four different Manifestions of liquefac- tion have been identified (National Research Council, 1985~: 1. Flow slides from slopes. 2. Loss of foundation bearing capacity, leading to large settle- ment author tilting of structures. 3. Lateral spreading, that is, a movement of gradually sloping ground toward low points. 4. Ground oscillation, where ground overlying saturated sand breaks up into jostling "plates. All of these phenomena may be accompanied by sand boils small volcanoe-like mounds or craterlets from which sand and water spurt to the surface. The first two manifestations of liquefaction are dramatic but less common. When they do occur, there is considerable potential for damage and, in the case of flow slides, for loss of life. Flow slides may occur in natural ground, but are also likely in man-made deposits, such as earth dams, mine tailings darns, and fill placed behind waterfront retaining structures. 195

196 The remaining manifestations are less spectacular but much more common. Lateral spreading frequently disrupts pipelines, roads, railways, and canals, and if occurring beneath a structure, can cause extensive damage and even loss of life. Ground oscillation and associated sand boils can present an enormous clean-up problem if they occur in a built-up area. If accompanied by ground settlement, damage and disruption can also occur. All aspects of seismic liquefaction have been reviewed and dis- cussed in a major report (National Research Council, 1986~. It is important, for the subsequent discussion, to distinguish two situa- tions: . Level ground where no shear stresses are required for equilib- rium following an earthquake. . Slopes (which include building foundations) where shear stresses are required for static equilibrium. Ground with a very gentle slope (< 5°) may, depending on the circumstances, fall into either situation. Liquefaction Susceptibility A range of criteria and methods exists for evaluating the sus- ceptibility of a soil to liquefaction as a result of earthquake ground shaking. The simplest method considers just two factors: the geo- logic age of the deposit and the depth to the water table. Table F-1 presents such a set of criteria from Youd et al. (1978~. Other exam- ples appear in ATC-13 (Applied Technology Council, 1985~. These ratings are based on observations and experience during actual earth- quakes, and rate the susceptibility of a soil deposit as a whole. Only portions of a deposit would actually experience liquefaction. In Table F-1, latest Holocene refers to the most recent 1,000 years, with the earlier Holocene extending back to 10,000 years. Experience suggests that deposits older than about 130,000 years will not liquefy. As indicated, the depth of the water table is also a very important factor. The information in Table F-1 is directly useful for preparing liquefaction hazard maps. A procedure for combining this information with the expected ground-shaking hazard is described by Youd and Perkins (1978~. A more quantitative method for assessing liquefaction suscepti- bility makes use of penetration resistance as measured by the Stan- dard Penetration Test (SPT). In Figure F-1, the horizontal axis is the blow count in the SPT, corrected for the depth at which the blow

197 TABLE F-1 Considerations Used in Producing a Map of Liquefaction Susceptibility in the San Fernando Valley Deoth to Groundwater (ft) Age of Deposit 0-10 10-30 < 30 Latest Holocene Earlier Holocene Late Pleistocene High Lowa Nil Moderate Low Nil Low Nil Nil aLatest Holocene deposits in this basin generally are not more than 10-ft thick. Saturated deposits in the 10- to 30-ft intermural are earlier Holocene sediments. SOURCE: Youd et al. (1978~. count is recorded and the energy delivered to the drib rods when per- form~ng the test. The vertical axis is the ratio of the dynamic stress occurring during an earthquake to the vertical elective overburden stress in the soil. The dynamic stress is commonly computed from a simple expression involving the peak acceleration at ground surface and the unit weight of the soil. The data points on the plot represent actual observations during earthquakes, and a curve has been drawn separating cases of liquefaction from those where no liquefaction was observed. If a new situation is represented by a point plotting above this curve, liquefaction is to be expected. The data in Figure F-1 apply for an earthquake with a mag- nitude of 6.5. Corresponding curves have been developed for other magnitudes (see Figure F-2~: the larger the magnitude, the greater the duration of shaking and hence the greater the susceptibility to liquefaction for a given (Nl)60 and Tab/ a'. These figures apply for clean sands; relations for taking into account the influence of fines have also been developed. It is unlikely that a program of penetration tests would be under- taken in connection with a large-scale loss estimation study. However, data from previously drilled borings can be used to evaluate the liq- uefaction susceptibility of deposits in a study area and thus serve as a basis for preparing liquefaction hazard maps. Other and more sophisticated methods for evaluating liquefac- tion susceptibility have also been developed. There are more precise techniques for measuring penetration resistance, such as the Cone Penetration Test (CPT). If very good undisturbed samples can be obtained, various types of laboratory tests can be done. Theoretical

198 06 0.5 0.4 T~V a' 0.3 0.2 0.1 o . _ ~ / · ~ a I'1 1 · ~ I · ~ + a / I o / 0 · ~ a so ~ 0 .~ ~ / He o o , · ~ Pon Time riccn data Jcpanese data Chinese date too Pi N ES CCl~J7E>J ~ 5 5 % Ctl~rese 3ulIding Code (clay ccotent-O) ver-ir.al No L`=efccti~ L-ue~c.'cn Ocuef~:t~on 1 ~ ~ ~ 0 0 0 ! 0 10 20 30 (~1)60 40 50 FIGURE F-1 Relationship between stress ratios causing liquefaction and (N. )60 values for clean sands for magnitude 7.5 earthquakes. Source: Seed et al. (1984~. methods are also available. While these techniques are of value for evaluating specific sites or particular earth structures (e.g., earth dams), they are not appropriate for large-scale loss estimation stud- ies.

05 8 O 04 .o = cr v' Cal — c ° . _ g 5 . _ 0 0 _ _ 0 (,0 c - 't 0 3 b' c `~ 0 2 ~ . _ In ~ O ~ J · _ — _ ~ — lo. — A) ~ o 199 I I I / I / I .' ; ' / I J I l l l l _ _ . _ 1.1 _ ~ I ~', / / / / / ,, 1 1 1 10 , . ~ / 1 ~11 ~ ~ / go/' `\~/ V' ~~ hi/ ' ,' / - 20 30 Modified Penetration Resistance, Nl -blows/ft 40 FIGURE F-2 Chart for evaluation of liquefaction potential of sands for earth- quakes of different magnitudes. Source: Seed and Idriss (1982~. Consequences of Liquefaction Methods for evaluating liquefaction susceptibility are essentially determunistic in nature, and do not indicate directly how likely liquefaction might be during an event of given intensity nor how widespread liquefaction might be over a given deposit. Furthermore, the methods are based heavily on observations as to the occurrence

200 or nonoccurrence of some manifestation of liquefaction, without ref- erence to the severity of the occurrences. Indeed, it is possible, even likely, that liquefaction actually occurred beneath the surface in some of the cases identified as "no liquefaction," but these liquefactions did not appear at the surface of the ground. Ishihara (1985) has shown that the thicknesses of a liquefying layer and of an overlying nonliq- uefiable layer both affect the likelihood that liquefaction is observer! at the surface; Figure F-3 provides initial guidance in this matter. The ATC-13 report gives a ground probability failure matrix, reproduced here as Table F-2, based on expert opinion. The matrix obviously is oriented to situations in California, but for comparable soils should also apply elsewhere. Liso et al. (1988) performed a detailed statistical analysis of the case studies upon which Figure F-1 is based. It was concluded that the boundary curve in Figure F-1 might correspond to about 50 percent probability of liquefac- tion. This study also provided curves for estimating the probability of liquefaction for a point falling at any point of a raV/a' versus (N~60 diagram. However, these several results still do not get at the questions of how widespread and damaging liquefaction may be for a given deposit. In the ATC-13 report, some very scant data are cited to the effect that damage to buildings on poor ground (such as liquefiable sand) is 5 to 10 times greater than damage to buildings on firm ground, for the same intensity of ground motion. Thus, for facilities on the surface, the ATC report proposes to evaluate a mean damage ratio (MDR) as: MDRgrour~d = MDRfirm ground X PtL] X 5, where PtL] is the probability of liquefaction for the deposit of interest. For buried structures (e.g., pipelines), the ATC report proposes using a factor of 10. Youd and Perkins (1987) introduce the concept of a liquefaction severity index (LSI). They relate LSI to the extent and magnitude of movements and other manifestations of liquefaction that can be expected; their descriptions are reproduced in Table F-3. They also propose an equation relating LST to the magnitude and epicentral distance for an earthquake. However, this equation is applicable only for late Holocene floodplains and deltas associated with rivers having channel widths greater than 10 meters and for seismic conditions in California and Alaska. Thus the method is not directly applicable to other parts of the country. In addition, the method still leaves

201 12 1 1 10 Cal I , 8 CO a) Ct ~ _ :D Or ._ o in CO a) 4 By ._ 6 _ s 3 2 1 Max. ace. _ 200 gal ~- c ._ ~ 1 AS c ,o ~ ' 0 a, ~ J _ _ 0 1 - Max. ace. . 300 gal ., / \ I Max. ace. 1 400-500 gal / - - ~/ .. .. . I I I l i I 2 3 4 5 6 7 8 9 Thickness of surface layer, H 1 (m) 10 FIGURE F-3 Proposed boundary curares for site identification of liquefaction- induced damage. Source: Ishihara (1985~. the problem of relating LSI to quantitative measures of damage to facilities e LANDSLIDES Earthquake-~nctuced landslides have caused tens of thousands of

202 TABLE F-2 Ground Failure Probability Matrix for Poor Ground (in percents Zone Type of Deposit Probability of Ground Failure by MMI VI VII VIII IX X XI : XII la Stream channel, tidal channel 5 20 40 60 80 100 100 lb San Francisco Bay mud and fill over bay mud 3 15 30 40 60 80 90 2a Holocene Alluvium, water table shallower than 3 m (10 ft) 2 10 20 30 40 60 80 2b Holocene Alluvium, water table deeper than 3 m ([Oft) 0.5 2 5 7 12 25 40 3 Late Pleistocene Alluvium 0.1 0.5 1 2 4 7 10 aEstimates are based on consensus of the ATC-13 Project Engineering Panel. SOURCE: Applied Technology Council (1985). deaths and billions of doDars of losses worldwide in this century. In many earthquakes the resulting landslides have caused as much or more damage than the other effects of ground shaking. Over half of the damage caused by the 1964 Alaska earthquake was the result of landslicles. In Japan, of the deaths caused by large earthquakes since 1964, more than half have been attributed to landslides. In an earthquake in the Peruvian Andes in 1970, an avalanche was triggered that buried two cities and killed at least 20,000 people. The 1987 earthquake in Ecuador caused landslides that clogged rivers and destroyed sections of the trans-Andean of} pipeline. In 1959, the Hebgen Lake, Montana earthquake set off a mam- moth landslide that dammed the Madison River. Major efforts were made to reduce the possibility of rapid erosion when this natural dam was overtopped, to prevent catastrophic downstream flooding. The 1971 San Fernando earthquake caused very damaging slides in earth dams and structural earthfi~] in the western part of the San Fernando Valley most of which were associated with liquefaction. In addition there were several hundred rockfalIs, soil falls, and de- bris flows that caused considerable damage to highways and roads. Blockage of roads is a common occurrence whenever earthquakes shape steep terrain.

203 TABLE F-3 Qualitative Assessment of Abundance and General Character of Liquefaction Effects as a Function of LSI for Areas with Widespread Liquefiable Deposits LSI Abundance and General Character of Liquefaction Effects 10 30 70 90 5 Very sparsely distributed minor ground effects include sand boils with sand aprons up to 0.5 m (1.5 It) in diameter, minor ground fissures with openings up to 0.1 m wide, ground settlements of up to 25 mm (1 in.~. Effects lie primarily in areas of recent deposition and shallow groundwater table such as exposed stream beds, active flood plains, mud flats, shore lines, and 80 on. Sparsely distributed ground effects include And boils with aprons up to 1 m (3 ft) in diameter, ground fissure with openings up to 0.3 m (1 ft) wide, ground settlements of a few inches over loose deposits such as trenches or channels filled with loose sand. Slumps with up to a few tenths of a meter displacement along steep banks. Effects lie primarily in areas of recent deposition with a groundwater table less than 3 m (10 ft) deep. Generally sparse but locally abundant ground effects include sand boils with aprons up to 2 m (6 ft) diameter, ground fissures up to several tenths of a meter wide, some fences and roadways noticeably offset, sporadic ground settlements of as much 0.3 m (1 ft), slumps with 0.3 m (1 ft) of displacements common along steep stream banks. Larger effects lie primarily in areas of recent deposition with a groundwater table less than 3 m (10 ft) deep. 50 Abundant effects include sand boils with aprons up to 3 m (10 ft) in diameter that commonly coalesce into bands along fissures, fissures with widths up to 1.5 (4.5 ft), fissures generally parallel or curare toward streams or depressions and commonly break in multiple strands, fences and roadways are offset or pulled apart as much as 1.5 m (4.5 ft) in some places, ground settlements of more than 1 ft (0.3 m) occur locally, slumps with a meter of displacement are common in steep stream banks. Abundant effects include many large sand boils (some with aprons exceeding 6 m [20 It] in diameter that commonly coalesce along fissures), long fissures parallel to rivers or shorelines usually in multiple strands with many openings as wide as 2 m (6 ft), many large slumps along streams and other steep banks, some intact masses of ground between fissures displaced 1-2 m down gentle elopes, frequent ground settlements of more than 0.3 m (1 ft). Very abundant ground effects include numerous sand boils with large aprons, 30 percent or more of some areas covered with freshly deposited sand, many long fissures with multiple strands parallel streams and shore lines with openings as wide as 2 or more meters, some intact masses of ground between fissures are horizontally displaced a couple of meters down gentle slopes, large slumps are common in stream and other steep banks, ground settlements of more than 0.3 m (1 ft) are common. SOURCE: Youd and Perkins (1987~.

204 TABLE F-4 Relative Abundances of Earthquake-Induced Landslides in 40 Historical Earthquakes Worldwidea Very abundant (> 100,000~: Rock falls Disrupted soil slides Rock elides Abundant (10,000 to 100,000~: Soil lateral spreads Soil slumps Soil block slides Soil avalanches Moderately common (1,000 to 10,0003: Soil falls Rapid soil flows Rock slumps Uncommon (100 to 1,000~: Subaqueous landslides Slow earth flows Rock block slides Rock avalanches aLandslide type listed in order of decreasing total numbers. SOURCE: Wilson and Keefer (1985~. An excellent, recent summary about earthquake-~duced land- slides and their consequences has been prepared by Wilson and Keefer (1985~. Table F-4 assembles data concerning the relative abundance of different types of landslides, while Table F-5 categorizes different types of earthquake-induced landslides together with their charac- teristics. Likelihood of [an~lides Information relating the occurrence of landslides to characteris- tics of earthquakes has been summarized in ATC-13 (Applied Tech- nology Council, 1985~. Building on a concept proposed by Legg et al. (1982), and utilizing expert opinion, ATC developed the probability matrices reproduced in Table F-6. Each box in this table represents a different degree of inherent stability for a slope, characterized nu- merically by the yield acceleration, ac, at which movement starts. The slope failure states (SFS) relate, in a probabilistic manner, land- slide displacement to shaking intensity as a function of initial slope stability. The matrices are for dry summer conditions in California;

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208 for applying to a wet season it is recommended that the ~fM! be in- creased by one unit. Yield acceleration has been used in conjunction with a Newmark (1965) analysis to prepare a regional map of seismi- cally induced landslide susceptibility as a function of bedrock type, slope steepness, and seasonal groundwater-leve! conditions (Wiec- zorek et al., 1985~. Going a step further, ATC also used expert opinion to relate landslide severity (i.e., SES) to the mean damage ratio (MDR) at affected facilities (see Table F-7~. Thus, the mean damage ratio from landslides is: MDRL,s = As, PtSFS] x CDF~s, SFS where PtSFS] comes from Table F-6, the central damage factor CDF~s is from Table F-7, and the products are summed over all slope stability states. This ATC method is logically sound, but at this stage it involves considerable judgment and has not yet been tested for an actual large-scale study. Mapping Landslide Hazards During the Bay Area Project of the 1970s, a landslide hazard map was developed for the San Francisco Bay Area (Nilsen and Wright, 19793. The indicated hazardous areas were identified on the basis of evidence of past sliding (not necessarily during earthquakes) and topography. Wieczorek et al. (1985) produced a map of earthqual~e-caused landslide susceptibility for one of the San Francisco Bay Area coun- ties. In this approach, the nonseismic data needed are: maps showing the distribution of geologic materials; estunates of the wet and dry strength characteristics of each of the age or stratigraphic cIassifi- cations obtained from the geologic maps; estimates of wet and dry season depths to saturated soil; and maps showing topography, with the contour intervals assigned to one of six percentage slope ranges. These geologic-based susceptibility data are then combined with a consideration of ground motion. Faults capable of producing suffi- cient motion to cause slides are identified. (Because the map was in- tended to serve several purposes rather than being tied to a scenario- based disaster response planning study, the effects of the different earthquakes were not plotted discretely on the final map.) Several

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211 TABLE F-7 Relation Between Landslide Severity and Facility Damage Factora Central Slope Failure State Damage Factor (percent) Light Moderate Heavy Severe Catastrophic o 15 50 80 100 aEstimates are based on consensus of the ATC-13 Project Engineering Panel. SOURCE: Applied Technology Council (1985~. . historic earthquake records are adapted to represent the size of earth- quake assigned to each fault. Simple slope stability analysis is used to determine the yield or critical acceleration, ac, necessary to overcome slope equilibrium. The severity of the slide, in terms of the amount of displacement, is then computed using the method of Newman (1965) as adapted by Wilson and Keefer (1983), which accounts for the way in which suc- cessive accelerations of critical or greater size act over time, against the restraining influence of friction, to move the slide downhill. The results are displayed on a map and divide the study area into high, moderate, low, and very low earthquake-caused landslide hazard zones. Liquefaction was beyond the scope of this method, but liquefaction susceptibility was also plotted on the same map from the work of Youd and Perkins (1985~. The four descriptive landslide sus- ceptibility categories are defined quantitatively in terms of predicted movement, relative to a benchmark amount of displacement of 5 cm (2 in.~. This was considered a conservative estimate of the threshold of movement causing major damage to average building foundation conditions, based on Youd (1980~. The other factor determining the assignment of a site into one of the four zones was the critical acceleration causing the movement. For each of these four levels of susceptibility, an estimate is provided of the percentage of the area of that zone that would fait when the presumed earthquake occurs. This estimate of the extent of failure within each landslide zone is derived from Youd (19803.

212 Figure F-4 shows the maximum distance of several types of landslides ~ a function of magnitude and was assembled by Wil- son and Keefer (1985) U8=g data from California. These authors also used Newmark's sliding block theory to relate the likelihood of slides to the intensity of ground motions, and produced a map (see Figure F-5) giving the probability of coherent slides (in either hilly terram or saturated soils) for a magnitude 6.5 earthquake on the Newport-Inglewood fault. This type of mapping is still in the developmental stage, and does depend heavily on historical data con- cerning earthquake-induced landslides. However, the work points the way to the type of analysts that can be used for mapping landslide hazards.

- - l i I I I I I I I T~ I \ ~ · I \ - e Y \~ ·  \ C \ ~ CO—4% cr. i i ~ ~ 1 1 ~ 1 O O O O O O O LO ~ ~ ~ C~ o o o o .O ~ ~ o L`~ ~ ~ o o SH319W011> Nl 3~0Z 3Unid(18-llOV] WOU] S3Ol1S lN383H00 30 3ON~lSIC WtlWIXVW i ! i 1 _ ~ ~ _ \ \ · ~ _ - \ - \ - V~e \ LL \ - \ J\ ~ ~ ~ . a:N U) o o o o o L£) _ o ln _ . oo _ o oo _ LO — r~ ~ O UJ _ . _ CD Z _ o, LO _ ln _ o .D LO o ~ o a' o, ID co o oo LO r~ o r~ o, LD o o O O O O O ~ ~ — LO ~ o o o SH313W011> Nl'3NOZ 3UnidnU-llf)~] WOU] SllV] H0 S3Ol1S 031dnUSIC J0 33N~lSIC WnWIXVW 213 - - UJ z 6 .= ~ o ~ .. ~ O _ ~ ~ V =_ _ c<3 O ~ U2 ~ 4= ~ U '_ a a) ~ ~ ~ CS, _ s C~ U) ".= " - V ° a2 -D vrY >~. · - ° ~ V 0 _ ~ 0 , . U' _ ~ ~ C~ _= _ ~ ~ - ~ V>^ ~ C, V^¢ CQ bO~ ~ ~ ~ 0 ~ ~ o~ ._ ~ ~ '6 ~ V ~- ~ ~ _ ~ ° tS, Cc~ U) ~ _= ~ ,= ~ ~

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215 A I. 1 1 I. 1 rat ,, M O J A ~ .E: 'ID E Syt R , , ¢. ~ A::;:: A E ~ ~ A ~ 1, ' ~ off I ~ =~9~ ;j~—~5~\ '-iffy SALES _~' ~ ! \ ~ G . . -a - rut ~ , \- ~ ~~ ~ ~~ 3!\ 72- RIVE ,, I"""_", ~-~^ i,^~ 'ii' ~o5~85~ . ~ ~ V~__ _ ~ i; \ °~ , ~1 i , ~^ ~ - R <! - . ~^ 1_ ~ ma, \ ~ ,' ';\ \ i~ - V .\ ,,\~N .,,,..., Am, \NC);~—rl- ' ~~ ~ ~ 4~- ~ F. ,,', _/ .. i; ~ . . . .'! ' i\ . t ~ S ~ ~ A ' '''`...,_,i' -','.~% ",, ',, · 4- ' \, ~'0~ , ,, ~ ~ ,~ ~ ~ ~ '` C A T A r .' N A FIGURE F`-5 Map of the Los Angeles basin and surrounding uplands showing zones of probability for coherent landslides from a hypothetical M 6.5 earthquake on the northern Newport-Inglewood fault zone (straight line in center of map). The outer oval-shaped line is the limit for coherent slides from a M 6.5 earthquake based on worldwide data from historical earthquakes (Keefer, 1984~. Most of the coherent landslides will occur within the 50 percent probability line. Source: Wilson and Keefer (1985~.

Working Paper G Economic Aspects of Earthquake Loss Estimation The economic consequences of an earthquake are presented in most loss studies only as direct property losses, usually estimated as a percentage of replacement cost. While these estimates do provide some indication of the financial resources needed for reconstruction, another reason for often quoting direct losses in dollar terms is one of convenience. For planning, preparedness, and recovery purposes, one could just as easily use only estunates of the numbers and the types of structures with varying qualitative degrees of damage. The study of natural hazards has long been dominated by engi- neers, sociologists, geographers, and social psychologists (Cochrane, 1984~. Few economists have engaged in this field of study, leaving a large gap in knowledge of the overall economic accounting of the consequences of catastrophic earthquakes or other natural hazards. This does not mean, however, that these consequences are insignif- icant. Rather, it reflects the difficulties involved in conducting a comprehensive economic accounting of the effects of an earthquake. The preceding working papers clearly demonstrate the complex- ities surrounding procedures for estimating direct earthquake losses. Efforts to estimate the indirect economic effects can complicate the study procedures significantly, particularly with respect to collecting additional information about structures and identifying the interrela- tionships among sectors in the economy and how they would change after the event. It is unlikely that these extended analyses will soon 216

217 be incorporated into large-scale, general-purpose loss estimate stud- ies. Interest in better understanding the economic consequences of earthquakes, however, led FEMA to sponsor an ambitious study, ATC-13 (Applied Technology Council, 1985), to lay the groundwork for estimating these impacts in a comprehensive fashion. This paper attempts to place a number of ATC-13's procedures in perspective, to discuss the current feasibility of doing such comprehensive eco- nomic analyses, and to outline briefly a research agenda that might enhance the feasibility of future studies. CHARACTE1tIZING ECONOMIC [OSSElS The economic consequences of an earthquake can be classified in several ways, but for purposes here, three types are delineated: (~) direct losses due to damage; (2) losses due to premature death or injury, and (3) indirect losses due to business disruption. Estimates of the direct property losses follow in a straightforward fashion from damage estimates, but the other two types of losses warrant some further discussion. As a first approximation to losses from premature mortality, Sorkin (1982) suggests multiplying the expected number of deaths by the present value of expected future earnings foregone, considering the likely age, sex, and occupational profiles of the victims and their effects on expected future earnings. The indirect costs of injuries are reflected in foregone earnings and medical costs. In extremely severe earthquake events, these economic losses could be substantial and certainly tragic for the victims' families. Estimates of this kind may also be important for insurance purposes or other questions of legal liability. However, the majority of these losses are in the form of foregone future earnings, rather than immediate out-of-pocket costs. For this reason, in addition to the tre~nendous uncertainties surrounding casualty estimates, these losses should not be a major focus of economic loss studies. The public concern should be with the casualties themselves and efforts to reduce them, rather than foregone future earnings. However, the same conclusion cannot be applied to indirect busi- ness losses stemming from physical damage and disruptions clue to the earthquake. These indirect losses are immediate and can persist throughout the recovery effort. They can affect the entire region and spill over to other states and regions of the country. For a variety of reasons, ranging from hazard mitigation and recovery to concerns

218 about national security and increased vulnerability after the event, these indirect losses are potentially of major concern to the local economy and to the federal government. MEASURING INDIRECT ECONOMIC IMPACTS FEMA's ambitious study to identify in a comprehensive fashion the economic consequences of a catastrophic earthquake has two ma- jor components. The first, ATC-13, involves a damage estimation technique that integrates geocoded seismic intensity simulations and inventories of buildings and other facilities with damage functions, relating seismic intensity and construction characteristics to dam- age estimates. The second component is designed to determine the overall economic impact by using the results from the damage evalu- ation methodology in conjunction with recently developed economic interindustry modeling capacities. ATC-13 describes only the first component of FEMA's study design. Its loss estunates are confined to the direct effects of the earthquake (e.g., damage from ground motion and collateral hazards) along with estimates of casualties, property loss (measured as a percentage of replacement cost), and loss of function. From this standpoint, its objectives are not that much different from those of other studies or approaches. However, the procedures by which estimates of these losses are produced differ significantly from what others have done. One major difference is the level of detail attempted in terms of the number of construction classes and the classification of economic and social function. The attempt to add detail to the damage relationships by consulting a number of experts was unique, as was the attempt to generate a comprehensive inventory from socioeconomic data in automated form available from FEMA. The rationale for the inven- tory procedures was in part due to a desire for consistency in studies throughout the country. Shortcomings of FEMA's methodology stem from the large num- ber of construction and use classifications and the fact that the it- erative process used with the experts led to distributions that may underestimate the true variability in damages. The accuracy of infer- ring structural information from the social and economic functions of buildings Is questionable and has not been empirically verified. In terms of the damage relationships, it is probably true that little would be lost by considering a smaller number of separate

219 damage curves or matrices. If this were done and the estunates were not revised through this iterative process, the damage relationships would probably not be too much different from those used in other studies. The real shortcorn~ng of the method is in having to relate economic and social function to structure type at such a disaggregate level at the level of each individual building or other facility. One way that the procedures could be improved ~ to invest more time and money in collecting more detailed information about the use of structures in the inventory. Art alternative might be to conduct some general field research to determine if there is any systematic relationship concerning economic function, geographic location, and age and type of structure. Why was such a high level of disaggregation needed in the ATC- 13 study? The answer derives from FEMA's interest (or that of the National Security Council, which requested the study) in identifying the impact of an earthquake on any one of up to 470 economic sectors identified by the Standard Industrial Classification (SIC) code used by the Bureau of Economic Analysis (Executive Office of the President, 1972~. This motivation ~ probably related more to the national security implications of loss of function to specific defense or related high-technology industries than it is to education, mitigation, and planning efforts. If the first phase of the ATC-13 methodology could be imple- mented at this level of detail, then some initial estunates of loss of function to defense related or other ~critical" industries might be possible. However, these direct damage and loss estimates ignore im- portant secondary effects throughout the economy after catastrophic events. (This is true regardless of the level of disaggregation in the analysis.) These secondary impacts are due to a variety of things. Probably most important is the loss of productive capacity from damage to physical plant and equipment. This reduces the capacity of the economic sectors to produce goods for final consumption as well as for use as intermediate inputs (some of which might have strategic value) in other productive activities. Because of the damage to the area's productive capacity, a larger fraction of the area's continuing demands for goods and services need to be imported from other regions of the country, at least during the recovery period. Employment and income in those sectors damaged by the event are reduced also, and this in turn reduces the demand for goods and services in many of the region's economic sectors. However, recovery

220 activities bring with them an influx of financial resources (e.g., from government recovery and relief efforts, and insurance cIaims) that increases the demand for the output of certain sectors, particularly construction. These new demands are either met by the remaining productive capacity of the area or through interregional imports. The purpose of the second phase of FEMA's study is to attempt estimates of these secondary impacts at the four-digit SIC level. In theory, this is possible by using an interregional interindustry mode! of the U.S. economy. The most complete description of the mode! intended for use In conjunction with ATC-13 ~ In a paper by Wilson (1982~. The methods to be used in this phase of FEMA's study can be described in abbreviated fashion through simple equations. The basic interindustry, input-output (~-O) mode! developed initially by Leontief (1951) is described In numerous economic books and in a summary by Wilson (1982~. The mode} ~ developed essentially from a double-entry bookkeeping description of an area's economy that records purchases and sales of goods from one sector to another, as well as imports and sales to final users (e.g., to final demand). Total sales or output of any sector (e.g., agriculture, manufac- turing, and services) of an e-sector model are recorded along the rows of the transactions table and are expressed as ~Xij+Yi=Xi(i=l' ...), j=1 (1) where xij is the value of the output of sector i purchased by sector j, pi is the final demand for the output of sector i, and xi is the value of the total output of sector i. To complete this set of balance equations, the entries down the columns of the table also add to the value of a sector's output. I` xij + pj = Xj(j = 1, · ~ n)' i=1 (2) where pj is the final payments (purchases of imports and primary factors of production by sector j], Xj is total outlay (purchases) of sector j, and ~ equals Xj for all i= j. From this transactions table, a matrix, A, of direct input re- quirements from sector i (in dollars) per dollar of sector jets output is given by

221 A = As = { $i] } (i, j = 1, . . ., n). (3) Substituting (4) into (~) yields n Xi = ~ aijxj + yi(i = 1, . . ., n), (4) j=1 which may be expressed more compactly as X= AX+Y, where Ax x2 X= . -On - I all al2 a21 a22 · · ~ ... al" a2" , A= . · · a"1 at .·· ann" (s) IY1 - , and Y = An . (6) Rearranging tints set of equations, it is easy to see that gross output minus intermediate use equate the net output or final use of the system X—AX= (I—ALEX= Y. (7) In the econorn~cs literature, much of the policy analysm that uses interindustry models is focused on the fact that this set of equations can be used to estimate the total output in the economic system required to meet any given set of final exogenous demands (e.g., consumer demand, government purchases, and exports). That is, if one knows the specific values for the components of Y. one can solve for required output by X= (I—A`J-iY. (8) In the planned second phase of the economic study, FEMA would make use of the direct damages and loss estimates coming out of the AT~13 method. The first task would be to estimate the interindustry mode} for the geographic area of interest (e.g., estimate the predisaster A matrix). Historically, this has been done either through extensive questioning of a sample of local businesses (Bills and Barr, 1968), or through systematic adjustments to the national

222 interindustry table based on some measure of the region's economic activity in a particular sector to that of the nation (Boisvert and Bills, 1976; Hwang and Maki, 1979; Lofting and Davis, 1973~. To estimate economic losses from natural hazards, these nonsur- vey techniques are the only feasible approach, and FEMA chose to use the procedures developed by Lofting and Davis (1973), which are based on a biproportional matrix-balancing technique (RAS) devel- oped by Stone (referred to in Wilson, 1982 and Boisvert and Bills, 1976~. The procedures by Lofting and Davis, and Hwang and Maki, accommodate the development of integrated interindustry models that account directly for trade flows across more than one region and can trace the impact to other regions in the country. Wilson (1982) discusses this extension of the model. Once the interindustry mode] is in place, on the basis of the initial direct loss estimates, procedures would be developed to estimate new levels of fin e] demand, Y. in the postdisaster situation. This would require establishing estimates of the loss in income due to the event and the projected influx of resources due to recovery efforts, as well as estimates of how these changes affect final demand for each sector's output. Projecting changes in final demand as a result of disruptions in an economy (be they due to economic or other factors) is not an easy task, but it is something that is done frequently in interindustry studies. The third task would be to modify the interindustry tables for the region. That is, in most interindustry studies, it is assumed that the intermediate input requirements, the A matrix, is invariant to the initial change in economic activity. This, of course, could not be assumed after an earthquake because of the damage to plant and equipment and the corresponding reduction in productive capacity. In general, this would mean that many of the components of the matrix A would be reduced indicating that more of a sector's in- termediate input requirements from other sectors would be imported from outside the region. There has been very little, if any, work attempting to modify interindustry models to account for an imme- diate structural change in intermediate input flows caused by a major disaster. SUMMARY AND CONCLUSION Little comprehensive analysis of the overall economic impact of earthquakes on a regional economy exists but an economist's general

223 knowledge of a region's interindustry relations would suggest that the secondary (or indirect) eEects stemming from the initial damage are likely to be substantial. It would be useful to link our estimates of damage to buildings and other facilities with their economic function. This information could assist recovery by helping to set priorities for reconstruction of essential services and perhaps to identify the location of industries that use toxic or other hazardous substances that could be released during the earthquake. The key question is, however, At what cost? Data to imple- ment the procedures do not exist, en c! if the inventory of facilities had to include data on economic function, the costs of this phase would increase substantially (by as much as 40 percent by one esti- mate). furthermore, even if there were reliable estimates of direct losses to structures by economic function, serious problems remain in trying to relate direct losses to changes in final demand and other interindustry relationships. These difficulties can only be resolved through additional research. Regardless of how rapidly some of the research problems are resolved, it is unlikely that comprehensive economic analysis will be viewed in the near future as an integral part of what has been called Type ~ studies (general purpose, large scale) in Working Pa- per A. This does not mean that the procedures used in future loss estunation studies should be insensitive to the data requirements of more complete economic analysis of the consequences of catastrophic earthquakes. At a minimum, researchers should collect inventory information that relates construction class to economic and social function or undertake specific research to establish any systematic relationships that Knight exist. Furthermore, to be useful for hazard reduction, emergency plan- ning, and recovery planning efforts, the level of detail in terms of econorn~c and social function does not need to be fine enough to differentiate all 470 sectors. A reasonable objective would be to look initially at the 25 to 30 major economic classifications defined by the SIC, with the expectation that there might be a Landfill of impor- tant individual industries in any region that could be exaTruned in greater detail. These would depend on the location being studied and the purpose of the study. Major defense contractor plants and military bases could be studied in greater detail if the purpose is defense-related, as In the case of ATC-13.

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