A forecast of the type of losses that the New York City area could suffer after an earthquake is the subject of this paper, which estimates the scale and extent of damage and disruption that may result from a series of potential earthquakes in Manhattan. The primary objective of this study was to develop and implement a comprehensive risk and loss characterization for Manhattan in the event of an earthquake. To this end, a complete building inventory of every structure in Manhattan was assembled from a variety of sources. The inventory included information about the location, height, total square footage, structural type, structural material, age, quality of construction, and seismic design level of every building in Manhattan. Combined with a detailed geotechnical soil characterization of Manhattan, this building inventory has been used to model scenario earthquakes in HAZUS (Hazards US), a standardized earthquake loss estimation methodology and modeling program. Deterministic and probabilistic earthquake scenarios were modeled and simulated in Manhattan, which provided intensities of ground shaking, dollar losses associated with capital (the building inventory) and subsequent income losses. Casualties are also estimated. This study has also implemented a detailed critical (essential) facilities analysis, assessing damage probabilities and facility functionality after an earthquake. Although only hospitals are specifically discussed, the critical (essential) facilities also include similar studies for police stations, fire stations, and schools in Manhattan. This research is unique, because it is currently one of the most detailed and site-specific applications of HAZUS or any other earthquake loss estimation code. Eventually, the aim of this loss estimation project will provide a framework for businesses and agencies to take mitigative action to reduce potential damage and losses, which might be experienced after earthquakes and other major natural disasters once other HAZUS loss algorithms become available.
展开▼
