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Multi-Hazard Models

Hazus can perform multi-hazard analysis by providing access to the average annualized loss and probabilistic results from the hurricane wind, flood and earthquake models and combining them to provide integrated multi-hazard reports and graphs. A unique feature of Hazus is the national inventory that comes with the model. Inventory data includes 1) Essential Facilities: police, fire, emergency operations facilities, schools, medical facilities; 2) Lifelines: utilities and transportation; 3) General Building Stock: residential, commercial and industrial (aggregated by square footage) and 4) Demographic Data, which can be aggregated by age, income, sex, households and other attributes that have a direct bearing on vulnerability to disasters.

Graphic of HAZUS-MH Models

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Hazus estimates losses through three models: Earthquake, Hurricane Wind and Flood. These models are continuously revised and updated through input from engineers, scientists, software developers and hazards specialists to provide increasingly accurate loss estimates. The geographic datasets used in conjunction with the Hazus application are downloaded separately as state specific datasets or can be input by the user manually.

The Hazus Earthquake Model provides estimates of damage and loss to buildings, essential facilities, transportation lifelines, utility lifelines and population based on scenario or probabilistic earthquakes.  The model estimates debris generation, fire-following damage, casualties and shelter requirements.  Direct economic losses are estimated based on physical damage to structures, contents, inventory and building interiors.  Specialized capabilities include adding new custom building types and importing U.S. Geological Survey (USGS) Shake Maps and optimized software for faster performance during rapid loss assessment. The latest version of Hazus updates the probabilistic maps with the latest version from USGS.  Details about the Earthquake Model.

The Hazus Hurricane Wind Model allows users in the Atlantic and Gulf Coast regions and Hawaii to estimate hurricane winds and potential damage and loss to residential, commercial and industrial buildings.  It also estimates direct economic loss, post-storm shelter needs and building and tree debris quantities and allows assessment of specific structural changes to buildings to strengthen them for mitigation. The model has the capability to define hurricane scenarios using National Weather Service forecasts/advisories and the software is optimized for rapid loss assessment. The new MR4 version now permits the creation of a study region using a hurricane track.  Details about the Hurricane Wind Model.

The Hazus Flood Model can be used to assess both riverine and coastal flooding and estimates potential damage to buildings, essential facilities, transportation lifelines, utility lifelines, vehicles and agricultural crops. The model addresses building debris generation and shelter requirements. Direct losses are estimated based on physical damage to structures, contents and building interiors. The effects of flood warning are taken into account, as are flow velocity effects.  The new model provides a dam/levee analysis capability. This model also now incorporates National Flood Insurance Program (NFIP) entry dates that permit it to distinguish between census blocks that are Pre-Flood Insurance Rate Map (Pre-FIRM) and those that are Post- Flood Insurance Rate Map (Post-FIRM); modifies topological data for Census Tract and Census Block geometrics; provides for consistent generation of debris results; allows digital elevation mapping for Hawaii and corrects mapping in the Inventory tables for utilities and day time and night time vehicle count and dollar exposure, among other enhancements and fixes. Details about the Flood Model.

One of the truly unique attributes of Hazus is the national inventory of hazard data, “point data” (e.g., essential facilities) and aggregated data on the general building stock. The Summary of Hazus Databases provides a very useful reference for these databases.

 

Last Updated: 
09/12/2016 - 13:57