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Related Titles

• National Earthquake Resilience: Research, Implementation, and Outreach
• Facing Hazards and Disasters: Understanding Human Dimensions
• Other Related Titles

Hazard forecasting and warning systems	NOAA, USGS, USACE, NASA, USFS, state agencies, private sector	Constant data collection and monitoring	Allows forecasts of potential events and their impacts to be made; when communicated in a timely way, warning systems can save lives	Complex disasters and natural systems, increasing population, and potential longer-term impacts require increased data precision and better forecasting models
Insurance	FEMA, state insurance commissioners, private insurance industry, banks	Policies currently are issued on an annual basis but some consideration is being given to multiyear insurance tied to the property	Risk-based pricing that communicates level of risk to people in hazard-prone areas; vouchers for lower-income owners	Continued public financial assistance to those who do not buy insurance
Catastrophe bonds	Insurers, banks, investors	Typically 1 to 3 years	Risk is transferred to a broad investor base in the event of a catastrophic event; allows access to large fund amounts fairly quickly	Investors lose invested funds if a catastrophic event occurs; insurers pay bond amount with interest if the event does not occur

Note: FEMA = Federal Emergency Management Agency, NASA = National Aeronautics and Space Administration, NIST = National Institute of Standards and Technology, NOAA = National Oceanic and Atmospheric Administration, USACE = U.S. Army Corps of Engineers, USFS = U.S. Forest Service, and USGS = U.S. Geological Survey.

IMPROVING RESILIENCE THROUGH RISK MANAGEMENT

Several themes emerge from disaster risk management, which provide a foundation for increasing the resilience of communities to hazard and disaster risks (Sayers et al., 2012):

1. Risk cannot be eliminated completely, so some residual risk will continue to exist and require management actions. The impacts of past natural disasters, particularly recent ones, are not necessarily a key to the future for several reasons. Society and its support systems have become increasingly interdependent (Chapter 1). In addition, human activity and development have destroyed much of nature’s defenses against natural hazards. This fact, coupled with likely changes in the physical environment due to climate change, suggests that future hazard probability and exposure will rise if no actions are taken. Historic records are short in a geological time frame, and the possibility exists for more severe floods, earthquakes, or other disasters.

2. The nature of risk perceptions and behavioral biases are important to consider in developing risk management strategies. The public and decision makers often underestimate the likelihood of a disaster occurring and hence do not undertake risk-reducing measures beforehand. Short-term strategies may also dominate when deciding what action to take. These behavioral features need to be considered when determining what types of risk management strategies are likely to increase resilience to disasters.

3. A diverse portfolio of disaster risk management measures provides options for decision makers and communities before, during, and after disasters. Such a portfolio can aid in efficient use of resources and more effective risk management. A portfolio with diverse risk management measures provides multiple options for enhancing resilience to a community in case one of the measures should fail. Combining well-enforced building codes and insurance with structural reinforcements or other measures can take on special significance to protect the community or region against physical and financial losses should structural measures (e.g., dams and levees, natural defenses) fail to provide full protection against the hazard. A key balance is that between investment in resources for managing disaster and the likelihood and magnitude of the hazards.

3. The need for science-based objective hazard identification and risk assessments is a critical input into the risk management process. Such input should be easily communicated to the community, with information and data that are transparent and not cloaked in an unpublished model, with all details proprietary. The sole reliance on anecdotal information, past experience, or deterministic scenarios does not provide an adequate or rigorous foundation for determining disaster risk.

5. Reflecting risk in insurance premiums while keeping insurance acquisition affordable to those requiring special treatment can encourage more individuals to purchase insurance policies. When insurance premiums are based on risk they provide signals about the hazards individuals face and can encourage them to adopt cost-effective mitigation measures to decrease their vulnerability to future disaster losses. General public funding, as opposed to insurance premium subsidies, can provide insurance for homeowners currently residing in hazard-prone areas and who may be socially vulnerable but are uninsured or inadequately insured.

6. Communicating risk in ways that are understandable to the public is a critical aspect of the risk management process. Decision makers and the public require accurate information on the risks they face. Risk maps, framing of information, social networking, and educational processes can be employed to communicate information on the risk and on mitigation measures (Sayers et al., 2012; this topic is addressed in detail in Chapter 5).

KNOWLEDGE AND DATA NEEDS

To achieve resilience the federal government has a dominant leadership role in supporting research to improve forecasting, impact-modeling capabilities, as well as the efficacy of risk-reduction strategies for the physical, public health, ecological, and socioeconomic aspects of natural and human-made disasters. Over the last several decades, significant investment by federal and state agencies in both land-based and space-based monitoring and observation networks for natural hazards has greatly increased our ability to forecast the likelihood and characteristics (e.g., magnitude, path) of future event occurrence as well as the intensity of the physical impacts of natural hazard events (e.g., ground-shaking level, wind speed, inundation depth). These data networks provide a quantitative basis for accurate, real-time meteorological forecasting, as well as early warning of flooding and tsunamis. In addition, these hazard monitoring networks provide a multidecadal baseline to help evaluate natural variability as well as the impacts of climate change.

The digital technological revolution made hazard monitoring network data available in real time and, in some cases, permitted rapid computer-automated, preliminary data analysis. The nation relies on a number of essential land-based and space-based hazard monitoring networks for short-term forecasting and early warning, as well as for understanding the physical processes leading to natural disasters and their physical impacts. Both the sensors and the communication networks supporting them require continual maintenance as well as upgrades to take full advantage of technological advances in sensor capabilities and communications. However, resource limitations have prevented many federally run monitoring networks from taking full advantage of the technological advances. The key federal hazard monitoring networks (along with the relevant reviews which include recommendations) are illustrated in Appendix C. Nearly all these networks have been the subject of outside reviews with consistent recommendations for upgrades. While it is beyond the scope of this report to repeat all the recommendations related to hazard monitoring in each of the NRC reports listed in Appendix C, we extend our strongest support for continued and adequate upgrading, expansion of coverage, maintenance, and staffing of the key hazard monitoring networks and observation platforms as outlined above. These data are essential for sustaining the forecasting and modeling capabilities required for national resilience.

Achieving resilience involves monitoring impacts in all the systems and the integration of data. While many hazard monitoring networks are in place, comparable networks for monitoring changes in the human systems as they affect vulnerability and resilience are lacking. Monitoring vulnerability and resilience requires long-term systematic data collection to capture for place-based human and environmental changes. A number of studies have advocated establishing place-based observatory networks on community resilience and vulnerability (Peacock et al., 2008; NRC, 2011c)—observatories that integrate social sciences, natural sciences, and engineering data in monitoring progress toward resilience.

Breakthroughs in hazard and risk assessment will come from better constraints on the key parameters in the models that govern the systems responsible for disaster impacts, such as the role of clouds in climate models, the three-dimensional effects of basins on strong ground shaking in earthquakes, and improved estimates of seasonal and diurnal changes in populations in hazardous areas. Research is also needed on the role and function of natural defenses against natural disasters (e.g., the capacity of coastal wetlands to help absorb storm surge, the role of swamps along rivers for floodwater storage), many of which have been severely compromised by actions of people. Until we fully understand the full ecosystem functions and feedback loops of these natural defenses, it is difficult to meaningfully evaluate whether it would be more cost-effective to restore wetlands or swamps or simply build or continue to raise and strengthen a system of levees downstream.

Research is also scant on the value of disaster mitigation and what factors strongly reduce losses. Targeted research into new materials and new processes for much more resilient construction of new buildings and infrastructure is needed, as well as assessment models of the role of retrofit standards to meet resiliency goals or effective strategies for addressing infrastructure interdependencies, . From a social science perspective, more research is required in modeling social capital within communities. Integration of information and modeling the connections between threats, vulnerability, exposure, sensitivity, and impacts also require more research, especially based on differences in geographic scale or time periods.

One of the key themes in the report is that despite some level of information about disaster risk, individuals, communities, businesses, and political leaders may be reluctant to reduce risk to make the nation more resilient. The question is why? To address that question more research into the social and behavioral biases that affect the processing of risk information, how risk data could be more effectively communicated, and how such risk information translates into the adoption of resilience strategies could be helpful. Research on the next generation of technologies for communicating and sharing location-based risk information would also enhance resilience at all levels.

SUMMARY AND RECOMMENDATIONS

Understanding, managing, and reducing risk is an essential foundation for increasing resilience to hazards and disasters. Risk management is a continuous process, and the choice of strategies requires regular reevaluation in the context of new data, models, and changes in the socioeconomic and demographic characteristics, and environmental setting of a community. The risk management strategy that works best for a community is based on the available information, how it is communicated to the key interested parties, and the perception of risks and rewards for avoiding or mitigating risk.

A variety of tools exists to manage disaster risk. These tools include structural (construction-related) measures such as levees, dams, disaster-resistant construction, and well-enforced building codes, and nonstructural (nonconstruction-related) measures such as natural defenses, insurance, zoning ordinances, and economic incentives. Structural and nonstructural measures are complementary and can be used in conjunction with one another. Risk management is at its foundation a community decision—including not only the immediately affected community, but also local, state, and federal levels of government and the private sector—and the risk management approach and will only be as effective if there is commitment to use risk management tools and measures.

Recommendation: The public and private sectors in a community should work cooperatively to encourage commitment to and investment in a risk management strategy that includes complementary structural and nonstructural risk-reduction and risk-spreading measures or tools. The portfolio of tools should seek equitable balance among the needs and circumstances of individuals, businesses, and government, as well as the community’s economic, social, and environmental resources.

Examples from actual disasters and their aftermaths show that implementation of risk management strategies involves a combination of actors in local, state, and federal governments, NGOs, researchers, the private sector, and individuals in the neighborhood community. Each actor will have different roles and responsibilities in developing the risk management strategy and in characterizing and implementing the measure or tool, whether structural or nonstructural, to be added to the community’s risk management portfolio. Some strategies can be implemented over the short term, while others may take a longer time. Table 2.2 is a potential template for decision makers to consider how to develop and implement risk management strategies and to manage expectations. The roles and responsibilities of the different actors are described in more detail in Chapters 5 and 6.

One underutilized tool is investment in risk reduction through insurance and other financial instruments to enhance resilience. Such measures can improve mitigation of properties and infrastructure, but more importantly, can encourage the relocation of residences, businesses, and infrastructure through more risk-based pricing.

Recommendation: The public and private sectors should encourage investment in risk-based pricing of insurance in which insurance premiums are designed to include multiyear policies tied to the property, with premiums reflecting risk. Such risk-based pricing reduces the need for public subsidies of disaster insurance. Risk-based pricing can serve as an incentive that clearly communicates to those in hazard-prone areas the different levels of risk that they face. Use of risk-based pricing could also reward mitigation through premium reductions and can apply to both privately and publicly funded insurance programs.

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¹ The term “community” throughout the report is used very broadly to incorporate the full range of scales of community organization—from the scale of a neighborhood to that of a city, county, state, multistate region, or the entire nation. Where a specific kind of community is intended, the chapter adds the appropriate descriptor.

² The terms structural and nonstructural as they are applied in this report reflect the use of these terms in the flood, hurricane, tsunami, and to a lesser degree, the earthquake arena. Within the emergency management community, the terms are used interchangeably to describe certain mitigation measures. Although the report is consistent in its use of these terms and not outside the norm, nonstructural mitigation has a very specific meaning in engineering circles (it only refers to contents and other building elements not related to structural strength). For the purposes of this report, the committee uses the terms “structural” and “construction-related” and their opposites interchangeably.

³See http://earthquake.usgs.gov/hazards/.

⁴ https://geohazards.usgs.gov/secure/designmaps/us/

⁵See USGS FAQs: http://earthquake.usgs.gov/learn/faq/?faqID=223.

⁶ http://www.fema.gov/hazus/.

⁷http://damsafety.org/newshttp://damsafety.org/news/?p=412f29c8-3fd8-4529-b5c9-8d47364c1f3e.

⁸ http://ceres.ca.gov/planning/pzd/2000/pzd2000_web/pzd2000_misc19.html.

⁹http://www.usrc.org/.

¹⁰ For more details on the nature of catastrophe bonds and other alternative risk transfer instruments see Kunreuther and Michel-Kerjan (2011, Chapter 8).

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“We lost 31 of those (street) cars. To rebuild those cars cost us $1.2 million per car. That’s not a capital cost you can replace very easily.” —Justin Augustine, CEO of the New Orleans Regional Transit Authority,
January 2011 on losses to the New Orleans transportation system after Hurricane Katrina

3


Making the Case for Resilience Investments: The Scope of the Challenge

INTRODUCTION

The potential benefits of being resilient to hazards and disasters make abundant sense. Few would oppose taking action to reduce the loss of life or property damage. However, increasing the resilience of a community requires large-scale investments of money, human resources, and time. Once risk has been identified and assessed, what actions are sufficient to address the risk? How resilient does the community need to be? How do investments in improving resilience compete with other community investment priorities? What are the benefits? Who pays now? Who pays later?

The available data portraying past disasters show that the scale and scope of disaster losses¹ are enormous and that significant investment is required to mitigate the losses of human life, risks to human health, and economic and social costs. Investments are required for a wide spectrum of community needs such as planning, organizing, training, and equipping first responders to large infrastructure projects. Owners of community assets are primarily responsible for their own resilience investments, yet community leaders from both the public and private sectors recognize that community assets are interconnected and interdependent and that holistic planning, programming, investing, and execution create common and interrelated resilience benefits for the community. Realizing the maximum benefits requires close collaboration among public- and private-sector leaders aided by a shared approach and commitment to investment.

As stewards of community assets the potential benefits of being resilient to hazards and disasters are attractive from governmental, economic, social, and environmental points of view. Although consensus generally exists on the goals for strengthening resilience, making the case for investing in resilience programs, in individual initiatives or projects, and in strengthening weak infrastructure is very challenging, especially in the context of demand for competing resources. Particularly during times of economic hardship, competing demand for many societally relevant resources (education, health, and social services) can be a major barrier to making progress in building resilience in communities. As a prerequisite for making the case, advocates are required to demonstrate that the potential benefits of being resilient to hazards and disasters make conceptual sense. However, such efforts also have to show clearly that community investments in resilience will yield significant and measurable short-and long-term benefits that balance or exceed the costs. This kind of cost-benefit analysis is critical for sustained commitment to increasing resilience, given the rising level of competition for scarce resources at local, state, and federal levels (Rose et al., 2007).

Furthermore, increasing resilience is tied in important ways to economic recovery after a disaster. Specifically, resilience measures can encourage efficient use of existing resources, and thereby lead to as rapid a recovery as possible. Some factors that have been shown to have achieved these ends include rapid business relocation (because of the existence of excess office space), use of inventories and stockpiles, and substitution of inputs or suppliers (Rose and Blomberg, 2010).

One approach that communities can use as they embark on a process of improving resilience is to develop multiyear plans or programs that include compelling initiatives or projects. These projects may include improving weak or underfunded community infrastructure such as schools, clinics, and hospitals, and the services which constitute any community. Involving and empowering individuals and families in developing these programs are important because of the ultimate need for individuals to take a share of responsibility in building resilience. Beyond the essential cost-benefit analysis, the value of each initiative or project also rests on the basis of its life-safety, economic, social, public health, and environmental significance. This kind of valuation can assist community leaders with prioritizing investments, decision making, and developing a schedule for implementing their resilience-building strategies.

Resilience investments challenge traditional approaches to “cost-benefit” analysis because communities have many different kinds of assets which are valued differently. Communities have very-high-value assets that are “essential” to keep operating—for example, hospitals, power plants, water and sewage plants, and transportation and communication networks—that usually have a tangible dollar value attached to them, and the costs of disruptions in these services can usually be directly calculated. The social, cultural, and environmental assets of a community also have high “value” but the value is described in cultural and life-quality terms and is more difficult to quantify in financial terms. Such assets include museums, natural landscapes or areas, protected environmental zones, historical buildings, and a health infrastructure that supports prevention and health maintenance throughout the population. Thus the total value of a community’s assets—both the high-value structural assets and those with high social, cultural, and/or environmental value— necessitates qualitative and quantitative inputs into a decision-making framework for disaster resilience. Such decision making is going to be difficult for community leaders as they try to address the value of multiple community assets in economic, social, cultural, and environmental terms. Access to reliable data is vital in order to support these kinds of decisions. This chapter identifies the data needed and an approach for valuing assets, planning, programming, and investment decision making for resilience. Specifically, the chapter addresses (1) the challenge of decision making for community leaders in developing their priorities in the context of their risk management findings and conclusions (see also Chapter 2); and (2) the scale and scope of the threat and potential losses from disasters. The ways in which communities might be able to develop or adapt measures of their progress toward resilience are developed in Chapter 4.

CHALLENGE OF RESILIENCE DECISION MAKING FOR COMMUNITY LEADERS

High-value assets of a community are those for which continued operation is essential and urgent for the entire community (e.g., water and power utilities, fuel systems, transportation facilities and systems, communication systems, first responder operations centers, and hospitals). These interdependent, high-value assets drive the need for holistic thinking, risk management (Chapter 2), priority setting, and investment timing.

Although substantial investments in some communities are made for contingency preparations to secure essential community services and operations during disasters, the scale of a disaster can nonetheless overwhelm the capacity of the system and its operators to cope, leading to a failure in one or more parts of the system as occurred, for example, with essential utilities in coastal Louisiana during and after hurricane Katrina (NRC, 2011). Proven techniques such as systemwide analyses and scenario planning offer insights for decision makers to see resilience improvement needs and weigh their investment priorities.

Other high-value assets of a community may include its economic foundation (e.g., local industry or business), and its social, cultural, environmental, and educational assets. These may include traditional ethnic neighborhoods, religious centers, parks and preserves, wildlife habitats, art centers and architectural icons, town squares, and schools or other educational institutions. These assets are held dear and are highly valued as distinguishing attributes by the community. Although it is difficult to measure their value in purely monetary terms, their loss may significantly degrade the total ambiance or qualify of life of a community. Although such losses may at first be devastating, the investment priority judgments of community leaders will consider the promise and possibilities embedded in the ingenuity and self-reliance of citizens (see Box 3.1).

Establishing ownership of a community’s assets is also important. Asset owners in a community will vary and include those from public utilities, local businesses and industries, faith-based communities, governmental and nongovernmental organizations, and individual citizens. Owners are primarily responsible for their property and for making appropriate steps including investments in mitigation measures—structural and nonstructural (see Chapter 2)—to prepare and plan for hazards and risks. Community resilience planning and investment programming set goals, strategies, and metrics for the community and guide owners in how best to prioritize and time their investments. However, resilience is also the outcome of interconnected systems (Chapter 1). Decisions about the prioritization and the level of investment require consideration of both quantitative data and qualitative value assessments the community is key in this regard. The next section examines the urgency of the need to consider the scale and scope of disasters and disaster losses as a means to motivate community efforts to identify and prioritize the full extent of a community’s assets.

THE SCALE AND SCOPE OF DISASTERS AND DISASTER LOSSES— AN URGENT PROBLEM

The Economic Value of Mitigation

Understanding the benefits of investing in one or more mitigation strategies in one place may provide some level of guidance that similar measures implemented elsewhere may yield a certain, or potentially greater, level of benefit. One of the landmark studies on the economic value of disaster mitigation is the work of the Multihazard Mitigation Council (2005), a public— private partnership established to reduce the economic and social costs of natural hazards. The study, based on cost-benefit analysis, examined future savings from hazard mitigation related to earthquakes, wind, and floods using two approaches: (1) a purposive sample of communities with mitigation grants funded by the Federal Emergency Management Agency (FEMA) to determine losses avoided through reductions in direct property damage, business interruptions, nonmarket damages, human losses, and costs of emergency response; (2) estimates of future savings from FEMA mitigation expenditures that use a statistically representative sample of FEMA-funded mitigation grants and that was then generalized to all FEMA mitigation grants (Multihazard Mitigation Council, 2005). HAZUS-MH was used to estimate direct property damage from earthquake, flooding, and hurricane wind. The mitigation approaches included both physical measures (elevating or relocating structures, strengthening structures against earthquake or wind hazards) and processes (such as building codes, policies, education). The study results concluded that mitigation saves money with benefits that greatly exceed the costs: for every $1 spent on pre-event mitigation, $4 was saved in post-event damages (see also Chapter 1). In another study that examined physical mitigation measures, Sutter et al. (2009) found that wind-resistant construction costing less than $500 additional per typical single-family home could mitigate future wind damage in tornado-prone regions by 30 percent. Research conducted by the Institute for Business and Home Safety has also demonstrated the economic value of relatively simple and inexpensive home fortification through significant reduction in structural damage and economic losses from strong weather events (Box 3.2).

Patterns of Disaster Losses to Guide Resilience Investments

Examining historic patterns of disaster losses provides some sense of the magnitude of the need to become more disaster resilient. In addition, the geographic patterns of disaster losses—human fatalities, property losses, and crop losses—illustrate where the impacts are the greatest, and where there could be challenges in responding to and recovering from disasters. Geographic patterns of losses, when compared with available data on housing, population growth, income level, and types of natural hazards, allow understanding of some of the driving factors of exposure and vulnerability to hazards and disasters (see also Chapter 2), and can lead more readily to appropriate paths to increase resilience. This kind of analysis also reveals gaps in our knowledge of natural, built, and socioeconomic systems—including their interrelationships—and is useful in prioritizing research needs. The following sections review disaster losses in terms of U.S. and global tendencies; geographic variation in economic losses, human losses, and patterns of exposure; and population growth. Each section draws upon available data and also presents evidence for gaps in data collection, analysis, and availability.

U.S. and Global Patterns in Economic Losses

Because local and national patterns in disaster losses occur within a larger global context, a useful way to assess the current state of resilience in the United States is to examine the magnitude of global events and losses. As estimated by Munich RE (2012), the costliest year on record for natural disasters around the world (based on preliminary global data for the year) was 2011, with more than $380 billion in losses (of which only $105 billion was insured), exceeding the previous record set in 2005. The earthquakes in New Zealand, the March earthquake and tsunami in Japan, and flooding in Australia and Thailand all contributed to these new levels of loss. The Japanese earthquake and tsunami combined were the most costly events globally in 2011. In the United States, estimated losses were $64 billion, of which $35.8 billion were insured losses (Munich RE, 2012). The snows of February, severe storms in April and May which brought many tornadoes, the extensive flooding in the Midwest and Great Plains, wildfires in Texas and the Southwest, and Hurricane Irene impacting much of the U.S. East Coast all contributed to the total (see also Figure 1.1).

Establishing the tendencies in economic losses provides the baseline against which we can monitor losses avoided due to improved resilience. Data that have been collected in a consistent manner are essential for measuring losses in absolute terms over time or in different locations, or simply attempting to monitor loss history for a single location. Existing global loss databases are useful for certain kinds of analyses, but require improvement in measurements, accuracy, and consistency. For example, there is an ongoing debate in the literature over whether losses from natural disasters are actually increasing over time (Figure 3.1), or whether the data reflect large, recent singular extreme events (e.g., the Tohoku earthquake and tsunami), changes in asset values, changes in reporting, changes in housing stock, improved awareness, or some combination of these. When national losses are normalized for population and wealth, upward patterns in normalized losses appear to become less significant (Pielke and Landsea, 1998; Brooks and Doswell, 2001; Miller et al., 2008); however, other evidence suggests that even with normalization for population and wealth, losses are increasing significantly, especially in the United States (Gall et al., 2012) (Figure 3.2). Improvements in disaster-data collection will help clarify these fundamental tendencies.

FIGURE 3.1 Natural hazard losses worldwide 1980-2011. Source: Munich RE (2012).

FIGURE 3.2 Trends in per-capita property and crop losses (adjusted to $2010) from natural hazards, 1960-2010. According to Gall et al. (2012), per-capita losses appear to be escalating in the United States, even when normalized by population, and have more than tripled per person since the 1960s. Source: S. Cutter; compiled from SHELDUS.

Another issue in analyzing loss data is that not all losses are counted and valued (Box 3.3). In the case of Munich RE, the NatCatSERVICE database provides property losses (total and insured) and insured business interruption losses, estimated from known insured losses. Because of the differences in loss estimation techniques, thresholds for inclusion in the database (large versus small events; insured versus uninsured losses), and data availability (public versus proprietary), natural-hazard loss databases are rarely comparable with one another. For example, comparisons among four publicly accessible databases show different total dollar loss estimates for the United States in 2010 attributed to weather perils such as winter storms, hurricanes, tornadoes, and flooding (Table 3.1). In the health arena, some losses of life and health may occur days or months after the disaster and thus may go uncounted.

Geographic Variation in Economic Losses

Long-term disaster loss data for specific geographic regions provide a baseline from which to measure improvements in resilience. The success of measures to reduce disaster risk and impacts are difficult to evaluate without this baseline information. A number of federal agencies compile separate data on disaster losses and costs including the National Oceanic and Atmospheric Administration (NOAA), FEMA, the U.S. Geological Survey (USGS), and the Department of Agriculture. These data serve quite specific and useful purposes, but in aggregate are incomplete, often incompatible with one another, have limited economic impact information, and are less useful for mapping the geographic distribution and impact of such losses at the local (community to state) scale. Currently, no comprehensive federal database or national archive for disaster loss data exists (Mileti, 1999; NRC, 1999; Cutter, 2001). The SHELDUS® (Spatial Hazard Event and Loss Database for the United States), compiled from existing federal data sources, is the closest approximation to a U.S. national inventory of direct disaster losses from natural hazards, but it also underestimates the total value of losses because indirect losses and business interruption are not included, for example. Such indirect losses can be substantial (see Box 3.4).

SHELDUS information can be used to examine patterns losses from natural hazards within the United States over the last 50 years. Figure 3.3 shows that these losses tend to be concentrated in a few regions and within a few states. The overall patterns highlight losses on the hurricane coast along the Gulf of Mexico extending from Texas to Florida and up the Atlantic Coast to the Carolinas. When normalized to losses per square mile (Figure 3.3b) the largest cumulative losses are concentrated in California, western Washington, the Gulf Coast and Florida, the Carolinas, the Northeast, and in the upper Midwest.

Table 3.1 Losses from Selected Weather-Related Hazards in the United States for 2010.

Databaseaa

Loss ($ Billion)

Deaths

¹ Unless otherwise noted, economic losses refer to property damage or crop losses (or both, if noted).