Linking multi-temporal analysis and community consultation to evaluate the response to the impact of Hurricane Stan in coffee areas of Chiapas,Mexico

This paper analyses the responses related to land use of coffee growers in Chiapas, Mexico to the impact of Hurricane Stan (October 2005). A multi-temporal analysis of the effect on land cover was performed through the combination of unsupervised classification of SPOT multispectral images and visual interpretation of panchromatic images (8 months previous to the hurricane, and 2, 14, and 40 months after the hurricane). The information provided by this geographic analysis was interpreted in light of information gathered though household surveys. Although the hurricane wrecked havoc across the region, the main impact in the study area was in the riparian zones where the extent of the loss experienced in terms of coffee harvest and soil was such that, even 14 months after the event, households with land in those areas were struggling to recover. Nevertheless, after 40 months, the zones that had suffered total soil loss began to support soil and vegetation, indicating the possibility of replanting coffee in those areas. Although the hurricane occurred when the coffee sector was particularly fragile as a result of the preceding several years of poor prices, the impact did not trigger extensive land use change. The surveys showed, however, that people are now more informed of the risk of living and farming on the river margins and are now performing soil conservation practices and planting trees to reduce risk.     

Assessing hurricane damage costs in the presence of vulnerability model uncertainty

Probability-based assessment of hurricane damage costs for coastal communities is vital for policy-makers and insurers. The uncertainties associated with hurricane damage costs include both the inherent uncertainty due to the random nature of hurricane process and the model uncertainty of the mathematical representation of hurricane damage (vulnerability model). The hurricane vulnerability model has traditionally been modeled as a deterministic function of hurricane wind speed in the literature, without considering the effect of vulnerability model uncertainty on hurricane damage assessment. This paper develops two methods to assess the hurricane damage costs in the presence of vulnerability model uncertainty. To account for the non-stationarity in hurricane actions due to the potential impact of climate change, the hurricane occurrence process is modeled as a non-stationary Poisson process and the hurricane intensity is assumed to vary in time with time-variant statistical parameters of hurricane wind speed. A case study of Miami-Dade County, Florida, is conducted to illustrate the proposed methods and to investigate the impact of vulnerability model uncertainty on hurricane damage costs.     

A hurricane surge risk assessment framework using the joint probability method and surge response functions

Hurricane surge events have caused devastating damage in active-hurricane areas all over the world. The ability to predict surge elevations and to use this information for damage estimation is fundamental for saving lives and protecting property. In this study, we developed a framework for evaluating hurricane flood risk and identifying areas that are more prone to them. The approach is based on the joint probability method with optimal sampling (JPM-OS) using surge response functions (SRFs) (JPM-OS-SRF). Derived from a discrete set of high-fidelity storm surge simulations, SRFs are non-dimensional, physics-based empirical equations with an algebraic form, used to rapidly estimate surge as a function of hurricane parameters (i.e., central pressure, radius, forward speed, approach angle and landfall location). The advantage of an SRF-based approach is that a continuum of storm scenarios can be efficiently evaluated and used to estimate continuous probability density functions for surge extremes, producing more statistically stable surge hazard assessments without adding measurably to epistemic uncertainty. SRFs were developed along the coastline and then used to estimate maximum surge elevations with respect to a set of hurricane parameters. Integrating information such as ground elevation, property value and population with the JPM-OS-SRF allows quantification of storm surge-induced hazard impacts over the continuum of storm possibilities, yielding a framework to create the following risk-based products, which can be used to assist in hurricane hazard management and decision making: (1) expected annual loss maps; (2) flood damage versus return period relationships; and (3) affected business (e.g., number of business, number of employees) versus return period relationships. By employing several simplifying assumptions, the framework is demonstrated at three northern Gulf of Mexico study sites exhibiting similar surge hazard exposure. The framework results reveal Gulfport, MS, USA is at relatively more risk of economic loss than Corpus Christi, TX, USA, and Panama City, FL, USA. Note that economic processes are complex and very interrelated to most other human activities. Our intention here is to present a methodology to quantify the flood damage (i.e., infrastructure economic loss, number of businesses affected, number of employees in these affected businesses and sales volume in these affected businesses) but not to discuss the complex interactions of these damages with other economic activities and recovery plans.     

A hurricane surge risk assessment framework using the joint probability method and surge response functions

Hurricane surge events have caused devastating damage in active-hurricane areas all over the world. The ability to predict surge elevations and to use this information for damage estimation is fundamental for saving lives and protecting property. In this study, we developed a framework for evaluating hurricane flood risk and identifying areas that are more prone to them. The approach is based on the joint probability method with optimal sampling (JPM-OS) using surge response functions (SRFs) (JPM-OS-SRF). Derived from a discrete set of high-fidelity storm surge simulations, SRFs are non-dimensional, physics-based empirical equations with an algebraic form, used to rapidly estimate surge as a function of hurricane parameters (i.e., central pressure, radius, forward speed, approach angle and landfall location). The advantage of an SRF-based approach is that a continuum of storm scenarios can be efficiently evaluated and used to estimate continuous probability density functions for surge extremes, producing more statistically stable surge hazard assessments without adding measurably to epistemic uncertainty. SRFs were developed along the coastline and then used to estimate maximum surge elevations with respect to a set of hurricane parameters. Integrating information such as ground elevation, property value and population with the JPM-OS-SRF allows quantification of storm surge-induced hazard impacts over the continuum of storm possibilities, yielding a framework to create the following risk-based products, which can be used to assist in hurricane hazard management and decision making: (1) expected annual loss maps; (2) flood damage versus return period relationships; and (3) affected business (e.g., number of business, number of employees) versus return period relationships. By employing several simplifying assumptions, the framework is demonstrated at three northern Gulf of Mexico study sites exhibiting similar surge hazard exposure. The framework results reveal Gulfport, MS, USA is at relatively more risk of economic loss than Corpus Christi, TX, USA, and Panama City, FL, USA. Note that economic processes are complex and very interrelated to most other human activities. Our intention here is to present a methodology to quantify the flood damage (i.e., infrastructure economic loss, number of businesses affected, number of employees in these affected businesses and sales volume in these affected businesses) but not to discuss the complex interactions of these damages with other economic activities and recovery plans.

     

The catastrophic cyclone of April 1991: Its Impact on the economy of Bangladesh

A very severe cyclonic storm with wind speeds of over 240 km/h struck the coastal areas of Bangladesh in the full moon night of 29 April 1991. The path of the eye, close to the shore, raised a storm surge of unusual height, reportedly more than 9 m above the mean sea level, which devastated the offshore islands and the mainland coast. The damage to the physical infrastructure of the port of Chittagong and adjoining industrial area has been colossal, and recovery will take years. Death tolls from the cyclone, storm surge and its aftermath exceeded 145 000 making it one of the world's major natural disasters of this century.This paper is concerned with examining the magnitude and intensity of the disaster. It analyses how the people of Bangladesh, and the environment in which they live, were affected by the cyclone. A brief account is presented of loss of life and of the damage suffered in various sectors, including agriculture, industry, and physical infrastructure.The paper lays emphasis on the need of building a sufficient number of multipurpose cyclone shelters in the disaster-prone coastal areas of Bangladesh. Adequate measures should be taken for evacuating people from vulnerable areas and putting them into these shelters in the event of a cyclonic storm. Simplification of the current cyclone warning system is recommended.The difficulties of providing relief to the survivors are discussed. And finally, the need for improvement of the communication infrastructure in the coastal areas is highlighted.     

Measuring long-run economic effects of natural hazard

This paper studies the long-run economic effects of severe weather on regional economies. A catastrophic event, such as a hurricane, will have an effect on both the directly impacted region and adjacent regions. With dramatically increasing damage from catastrophic weather events over the past few decades, comprehensive assessment of the long-run economic impact of natural disasters across the broader region becomes more important than ever for planning for post-disaster recovery. We estimate the long-run effect of Hurricane Katrina on the unemployment rate of Houston, TX by employing time-series and fixed-effect models. Using Dallas as a control, we find that Katrina is associated with a higher long-run unemployment rate in Houston than would otherwise have been expected. This implies that the hurricane-generated adverse relative effects on Houston. Our findings suggest that areas that are geographically proximate to the directly impacted region can sustain lasting negative economic consequences.     

A methodology to estimate seismic vulnerability of health facilities. Case study: Mexico City,Mexico

We developed a model to estimate seismic vulnerability of health facilities in Mexico City, Mexico, following these steps: (1) designing a theoretical framework (TF) to measure structural, non-structural, functional, and administrative-organizational vulnerabilities; (2) measurement of the vulnerability conditions of the analyzed facility by using the TF; and (3) estimation of the hospital’s seismic vulnerability by comparing the measured vulnerability to the TF’s vulnerability indicators by taking into account the optimal case. The TF was developed considering a scoring system and international standards for risk management in hospitals. The methodology establishes the degree of vulnerability of the analyzed institution as well as its interrelations with external infrastructure systems. This tool also identifies existing failures to estimate expected damage. The methodology was applied to the National Cardiology Hospital, the Children’s Hospital “Dr. Federico Gómez,” and the “Hospital de Jesus” of Mexico City. The vulnerability problems in these three hospitals are common within them, and some of the main causes of vulnerability found are: (1) the lack of technology to resistant seismic shaking; (2) the need to develop or update disaster response plans; (3) the need of periodic and proper maintenance to hospitals’ buildings; (4) the lack of sufficient financial resources for vulnerability reduction projects and autonomous operations of the hospital during 3–5 days after a disaster occurs. We believe that vulnerability in these health facilities can be reduced with low-cost procedures and that the methodology developed here will support the decision-making processes to reduce seismic risk in Mexico City.     

Dissolved oxygen dynamics in Charlotte Harbor and its contributing watershed, in response to hurricanes Charley, Frances, and Jeanne—Impacts and recovery

On August 13, 2004, Hurricane Charley came ashore in the Charlotte Harbor watershed. Surface winds at the time of landfall were estimated at 130 knots. The track of the hurricane roughly followed the floodplain of the Peace River, causing massive defoliation and mortality of native vegetation and planted citrus groves, as well as substantial damage to human habitation and various infrastructure elements. Eight days after landfall, a water quality monitoring effort documented hypoxic (<2 mg I⁻¹) to nearly anaerobic (<0.5 mg I⁻¹) dissolved oxygen (DO) values throughout the vast majority of the Peace River's c. 6,000 km² watershed. Low DO values appeared to be related to high values of both dissolved organic matter and suspended materials. Hypoxic conditions in Charlotte Harbor itself, occurred within 2 wk of landfall. Approximately 3 wk after the landfall of Hurricane Charley, Hurricane Frances struck the east coast of Florida, causing further wind damage and bringing substantial amounts of rain to the Charlotte Harbor watershed. Three weeks later still, Hurricane Jeanne caused similar damage to the same area. In response to the combined effects of these three hurricanes, DO values in the Peace River did not recover to pre-hurricane levels until approximately 2–3 mo later. The spatial and temporal pattern of DO fluctuations appeared to be related to the proximity of sampling locations to the path of the eyewall of the first of the three hurricanes. Within the Harbor itself, the duration of hypoxic conditions was less than that recorded within the Peace River, perhaps reflecting greater dilution of oxygen-poor waters from the watershed with less-affected water from the Gulf of Mexico.     

Fluvial Geochemistry through a Short-Duration, Tropical-Cyclone Induced Discharge event in the Burdekin River and Hann Creek, North Queensland, Australia

The chemical composition of river water integrates a number of factors such as weathering, land use, climate, vegetation cover and human activity that individually affect its chemistry. Short term variations may also be significant. The Burdekin River, NE Australia, is an example of a class of tropical streams which experiences two to four orders of magnitude variation in discharge in response to seasonal but erratic monsoonal and cyclonic rainfall. In these systems individual discharge events last for days to weeks. Given the inherent difficulty sampling these events published data on water chemistry (and thus calculated fluxes and global budgets) may tend to be biased to low flow conditions. One such discharge event in February 1996 has been investigated for its impact on the chemistry of the water. Major cations (Na, Mg, K, Ca) all decreased in concentration as the water level rose, as did the minor elements Sr, Ba and U. Some other trace elements, notably Rb, Cr, Pb and REE were enriched in the peak flow waters. The flux of all measured elements increased substantially during the seven days of the discharge event. Such short term but significant events will have a major impact on the annual fluxes of elements delivered to the oceans from the land and global discharge budgets may need to take them into account when refining databases in the future.     

Risk-based input�Coutput analysis of hurricane impacts on interdependent regional workforce systems

Natural disasters, like hurricanes, can damage properties and critical infrastructure systems, degrade economic productivity, and in extreme situations can cause injuries and mortalities. This paper focuses particularly on workforce disruptions in the aftermath of hurricanes. We extend the dynamic inoperability input?Coutput model (DIIM) by formulating a workforce recovery model to identify critical industry sectors. A decision analysis tool is utilized by integrating the economic loss and inoperability metrics to study the interdependent effects of various hurricane intensities on Virginia??s workforce sectors. The extended DIIM and available workforce survey data are incorporated in the decision support tool to simulate various hurricane scenarios. For a low-intensity hurricane scenario, the simulated total economic loss to Virginia??s industry sectors due to workforce absenteeism is around $410 million. Examples of critical sectors that suffer the highest losses for this scenario include: (1) miscellaneous professional, scientific, and technical services; (2) federal general government; (3) state and local government enterprises; (4) construction; and (5) administrative and support services. This paper also explores the inoperability metric, which describes the proportion in which a sector capacity is disrupted. The inoperability metric reveals a different ranking of critical sectors, such as: (1) social assistance; (2) hospitals and nursing and residential care facilities; (3) educational services; (4) federal government enterprises; and (5) federal general government. Results of the study will help identify the critical workforce sectors and can ultimately provide insights into formulating preparedness decisions to expedite disaster recovery. The model was applied to the state of Virginia but can be generalized to other regions and other disaster scenarios.     

The tropical storm Noel and its effects on the territory of the Dominican Republic

In the period between the end of October and the beginning of November 2007, the Dominican Republic was hit by the tropical storm Noel, then turned into hurricane in its movement toward the Californian coasts. The passage of Noel was accompanied by huge precipitation especially in the south-western part of the country. In some areas, the rainfall registered in 6 days exceeded 700 mm, i.e., more than two-thirds of the mean annual precipitation. The return periods calculated for this rainfall event vary greatly from region to region: while they locally reach 200 years, such as in San José de Ocoa (50 km west of Santo Domingo), in other areas, as for instance in the territory of the capital Santo Domingo, return periods do not exceed 20 years. The tropical storm caused huge damage both in terms of human victims and economic losses, related to diffused inundations and landslide phenomena, which may be attributed only partially to the exceptionality of the event. As a matter of fact, in many regions, the inadequate answer of the territory—widely characterized by serious problems of land degradation and an almost complete lack of territorial planning—appears to be the major responsible for the occurred negative effects. The impact assessment, based on the calculation of an Impact Index, confirms this statement.     

Structural damages of the May 19, 2011, Kütahya–Simav earthquake in Turkey

Reconnaissance observations are presented on the building damage caused by the May 19, 2011, Kütahya–Simav earthquake in Western Turkey as well as an overview of strong ground motion data recorded during the earthquake is given. According to Disaster and Emergency Management Presidency of Turkey, the magnitude of the earthquake is 5.7 in local magnitude scale. Although the earthquake can be regarded as a moderate event when considering its magnitude and strong motion recordings, it caused excessive structural damage to buildings in Simav district and several villages in the near vicinity. During the field investigation, different types of structural damage were observed mainly in the reinforced concrete frame buildings with infill walls and masonry buildings with various types of construction materials. Observed damage resulted from several deficiencies in structural and non-structural components of the buildings. Poor construction materials and workmanship, non-conforming earthquake-resistant design and construction techniques and non-ductile detailing are the main reasons for such an extensive damage, as observed in many past earthquakes in Turkey.     

Geomorphological features of Northwestern Bangladesh and some problems on flood mitigation

The northwest region of Bangladesh is divided into four geomorphological units which show different flood features. The region has suffered severe flood damage both in 1987 and 1988. After these floods Bangladesh Action Plan for Flood Control was established by the World Bank. In the northwest region the plan proposed two major projects, namely, an interceptor drain and a diversion channel. A Polder Project is also going on in this region. However these major projects are mainly on structural methods and require much cost for long embankments. The author suggests smaller but reasonable projects combining structural and non-structural methods in the region.     

Characteristics of tropical cyclones making landfall on the Pacific coast of Mexico: 1970-2010

This study evaluates impacts from tropical cyclone (TC) landfalls on populated areas located along the Pacific Ocean coast of Mexico. The period of interest is from 1970 through 2010 and an international disaster database is used to identify the impact from the landfalling TCs. More than 30 landfall events occurred during the period; we examined the top 25 TCs based on rainfall accumulation, as well as the top 10 TC-related disasters based on the affected population. Each event resulted in affected population from 20 000 to more than 800 000. Strong winds and heavy rainfall, during periods of one to three days, are associated with property damage and loss of lives. Our results indicate that excessive rainfall accumulations and daily rates, over highly populated areas, are important elements associated with the occurrence of disasters. Six of the top 10 TC-related disasters occurred during El Niño and three during neutral conditions; however, looking at the top 25 events, 10 occurred during El Niño and 10 during neutral conditions. Three case studies that occurred during El Niño events (Liza in 1976, Pauline in 1997, and Lane in 2006) are documented in more detail as they affected areas with different population densities in the southern and northwestern coasts of Mexico.     

Risk perception and evacuation decisions of Florida tourists under hurricane threats: a stated preference analysis

Though most hurricane evacuation studies have focused on residents, tourists are also a vulnerable population. To assess their perceptions of risk and evacuation likelihood under different hurricane conditions, we surveyed 448 tourists visiting central Florida. Respondents viewed four maps emulating track forecast cones produced by the National Hurricane Center and text information featuring variations of storm intensity, coast of landfall, centerline position relative to the survey site, time until landfall, and event duration. We performed chi-square tests to determine which hurricane conditions, and aspects of tourists such as their demographics and previous hurricane experience, most likely influenced their ratings of risk and evacuation likelihood for respondents located on Pinellas County beaches or inland near Orlando, FL. Highly rated scenarios featured a Category 4 hurricane making landfall along the Gulf Coast with the centerline passing over the sampling site. Overall, tourists that indicated the highest risk and evacuation ratings were not previously affected by a hurricane, had a trip duration of less than 6 days, and had checked for the possibility of a hurricane strike before departure. However, results for other tourist attributes differed between tourists in coastal and inland locations. We found that although somewhat knowledgeable about hurricanes, tourists misinterpreted the track forecast cone and hurricane conditions, which led to a lower perception of risk and subsequent likelihood to evacuate. Tourists, particularly those from outside of Florida, need to be better educated about the risks they face from hurricanes that make landfall.     

Spatially explicit mapping of hurricane risk in New England, USA using ArcGIS

Hurricanes are one of the major natural disturbances affecting human livelihoods in coastal zones worldwide. Assessing hurricane risk is an important step toward mitigating the impact of tropical storms on human life and property. This study uses NOAA’s historical tropical cyclone database (HURDAT or ‘best-track’), geographic information systems, and kernel smoothing techniques to generate spatially explicit hurricane risk maps for New England. Southern New England had the highest hurricane risk across the region for all storm intensities. Long Island, western Connecticut, western Massachusetts, and southern Cape Cod, Martha’s Vineyard, and Nantucket had high storm probabilities and wind speeds. Results from this study suggest that these locations may be of central importance for focusing risk amelioration resources along the Long Island and New England coastlines. This paper presents a simple methodology for hurricane risk assessment that could be applied to other regions where long-term spatial storm track data exist.     

A geospatial framework to estimate depth of scour under buildings due to storm surge in coastal areas

Hurricanes and tropical storms represent one of the major hazards in coastal communities. Storm surge generated by strong winds and low pressure from these systems have the potential to bring extensive flooding in coastal areas. In many cases, the damage caused by the storm surge may exceed the damage from the wind resulting in the total collapse of buildings. Therefore, in coastal areas, one of the sources for major structural damage could be due to scour, where the soil below the building that serves as the foundation is swept away by the movement of the water. The existing methodologies to forecast hurricane flood damage do not differentiate between the different damage mechanisms (e.g., inundation vs. scour). Currently, there are no tools available that predominantly focus on forecasting scour-related damage for buildings. Such a tool could provide significant advantages for planning and/or preparing emergency responses. Therefore, the focus of this study was to develop a methodology to predict possible scour depth due to hurricane storm surges using an automated ArcGIS tool that incorporates the expected hurricane conditions (flow depth, velocity, and flood duration), site-specific building information, and the associated soil types for the foundation. A case study from Monmouth County (NJ), where the scour damages from 2012 Hurricane Sandy were recorded after the storm, was used to evaluate the accuracy of the developed forecasting tool and to relate the scour depth to potential scour damage. The results indicate that the developed tool provides relatively consistent results with the field observations.     

Is flooding in Toronto a concern?

Toronto is the largest city in Canada with a population of about 5.5 million in the Greater Toronto Area (GTA). Being located at the shores of Lake Ontario of the Great Lakes, which is the largest surface freshwater system in the world, and affected by air masses originating from the Gulf of Mexico, the Atlantic Ocean, and the Arctic, the city is vulnerable to extreme weather phenomena in socioeconomic and geographical terms. This short paper gives a brief overview of the history of main flooding occurrences in Toronto with an emphasis on the recent flooding of July 2013. An analysis of causes and physical dynamics of the event is presented using the structure of the watersheds and weather systems in the region. Based on the flood risk vulnerability assessment carried out on the 2013 flooding, several weaknesses in critical infrastructure and critical facilities have been highlighted. Future considerations and recommendations include revisiting of the flood damage mitigation strategies (e.g., use of new and adaptive infrastructure designs, social media, crowd-sourcing information), flood zoning update, tax incentives, insurance options, and retrofitting solutions for those living in flood-prone areas.     

Earthquake losses due to ground failure

Ground shaking is widely considered to be the primary cause of damage to structures, loss of life and injuries due to earthquakes. Nonetheless, there are numerous examples of earthquakes where the losses due to earthquake-induced ground failure have been significant. Whereas ground shaking causes structural and non-structural damage, with associated loss of function and income, ground failure is less likely to cause spectacular structural collapses, but is frequently the cause of major disruptions, particularly to lifelines, which can lead to prolonged loss of function and income, even for undamaged areas.Those involved in earthquake loss modelling are currently presented with three choices with respect to the incorporation of ground failure: they can choose to ignore it, assuming that any estimation of losses caused by shaking would effectively subsume the impact of these secondary hazards; they can include ground failure in a simple manner, using published approaches based upon qualitative data and a large degree of judgement; or, they can opt for a detailed site- or region-specific assessment of damage due to ground failure, with the associated time and expense.This paper presents a summary of the principal features of earthquake losses incurred in damaging earthquakes over the last 15 years. Survey data are impartially analysed, considering both ground failure and ground shaking as sources of damage, and their relative contribution to overall damage in each section of the regional infrastructure is presented. There are many other variables influencing these contributions, including the size of the earthquake, the economic status of the affected region, local geology and terrain and the building stock, which have been considered.The findings of the study are discussed from the point of view of loss modelling and which components of a model should merit the most time and resource allocation. The general assumption that ground shaking is the principal cause of damage and loss is strongly supported by the study. However, there are a number of scenarios identified where the failure to appropriately include the effects of ground failure would lead to unrealistic loss projections. Such scenarios include the assessment of building losses in small zones rather than on a regional basis, and the incorporation of lifeline damage or disruption and indirect losses into a model.     

Local housing price index analysis in wind-disaster-prone areas

This study examines the effect of severe wind events on the mean and variance of housing price indices of six metropolitan statistical areas (MSA) that are vulnerable to hurricanes and/or tornadoes. The research focuses on three areas that experienced significant tornado activity (Fort Worth-Arlington, Nashville, and Oklahoma City) and three hurricane-prone areas (Corpus Christi, Miami, and Wilmington, NC). An econometric time series model that captures the housing market responses to severe windstorms is utilized. The model estimates changes in the local housing price index (HPI) as a function of several control variables as well as dichotomous variables that correspond to the tornadoes and hurricanes. As expected, the statistical findings indicate an immediate but short-lived decline in housing prices following a tornado or hurricane. Somewhat surprising is the result that the impact on the housing market is remarkably consistent whether the wind event was a hurricane or a tornado. Hurricanes and tornadoes are vastly different in terms of the point probabilities of a hit, the scope of the affected area and the lead time that supports last minute preparation to mitigate damage. It appears that the market response to destruction of real property does not distinguish between the types of wind event that produced the damage to the region. Results suggest that windstorms result in an immediate one-half to two percent reduction in total MSA housing value. This corresponds to a range of $34 million to $580 million in lost housing value. Estimates indicate some differences in how long market values continue to decline in the periods following the wind event; however, most of the decline occurs within four quarters after the windstorm. These differences can be attributed to the particular time series characteristics of the specific housing markets and their respective housing price indices. The market serves the purpose of integrating and normalizing the losses. In so doing the market provides a metric— a method for calibrating and comparing structural damage caused by different phenomenon.