4.6 Article

The effects of transportation network failure on people's accessibility to hurricane disaster relief goods: a modeling approach and application to a Florida case study

Journal

NATURAL HAZARDS
Volume 59, Issue 3, Pages 1619-1634

Publisher

SPRINGER
DOI: 10.1007/s11069-011-9855-z

Keywords

Disaster relief; Hurricanes; Networks; Transportation; Computation; Simulation; GIS

Funding

  1. US National Science Foundation [BCS-0550330]

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Following the catastrophic and devastating Atlantic Hurricane seasons in 2004 and 2005, there has been increased interest in formulating planning directives and policy aimed at minimizing the societal impacts of future storms. Not all populations will evacuate an area forecast to be affected by a hurricane, so emergency managers must plan for these people who remain behind. Such planning includes making food, water, ice, and other provisions available at strategic locations throughout an affected area. Recent research has tackled problems related to humanitarian and relief goods distribution with respect to hurricanes. Experience shows that the torrential rains and heavy winds associated with hurricanes can severely damage transportation network infrastructure rendering it unusable. Scanning the literature on hurricane disaster relief provision, there are no studies that expressly consider the potential damage that may be caused to a transportation network by strong storms. This paper examines the impacts of simulated network failures on hurricane disaster relief planning strategies, using a smaller Florida City as an example. A relief distribution protocol is assumed where goods distribution points are set up in pre-determined locations following the passage of a storm. Simulation results reveal that modest disruptions to the transportation network produce marked changes in the number and spatial configuration of relief facilities. At the same time, the transportation network appears to be robust and is able to support relief service provision even at elevated levels of hypothesized disruption.

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