HR: 0800h
AN: H41G-0846    [Abstracts]
TI: Hurricane related flooding monitoring: a method to delineate potentially affected areas by using a GIS model in the Caribbean area
AU: * Melelli, L
EM: lmelelli@unipg.it
AF: Università  degli Studi di Perugia, p.zza dell'Università  1, Perugia, PG 06100, Italy
AU: Taramelli, A
EM: ataram@ldeo.columia.edu
AF: LDEO Columbia University, 9W Palisades, New York, NW 10964, United States
AU: Sorichetta, A
EM: sorichetta@hotmail.com
AF: School of Earth and Environmental Sciences, Queens College of CUNY, 65-30 Kissena Blvd, Flushing, New York, NY 11367, United States
AU: Pasqui, M
EM: pasqui@lamma.rete.toscana.it
AF: CNR - IBIMET, Sesto Fiorentino, Firenze, FI 50019, Italy
AB: This research integrates the concept that the subject of natural hazards and the use of existing remote sensing systems in the different phases of a disaster management for a specific hurricane hazard, is based on the applicability of GIS model for increasing preparedness and providing early warning. The modelling of an hurricane event in potentially affected areas by GIS has recently become a major topic of research. In this context the disastrous effects of hurricanes on coastal communities and surroundings areas are well known, but there is a need to better understand the causes and the hazards contributions of the different events related to an hurricane, like storm surge, flooding and high winds. This blend formed the basis of a semi- quantitative and promising approach in order to model the spatial distribution of the final hazard along the affected areas. The applied model determines a sudden onset zoning from a set of available parameters starting from topography based on Shuttle Radar Topography Mission (SRTM) data. From the Digital Elevation Model as a first step the river network is derived and then classified based on the Strahler order account as proportional to flooding area. Then we use a hydrologic model that uses the wetness index (a parameter of specific catchment area defined as upslope area per unit contour length) to better quantify the drainage area that contributes to the flooded events. Complementary data for the final model includes remote sensed density rain dataset for the hurricane events taking into account and existing hurricane tracks inventories together with hurricane structure model (different buffers related to wind speed hurricane parameters in a GIS environment). To assess the overall susceptibility, the hazard results were overlaid with population dataset and landcover. The approach, which made use of a number of available global data sets, was then validated on a regional basis using past experience on hurricane frequency study over an area that covers both developed and developing countries in the Caribbean region. As a final result we can state that remote sensing data analysed together with meteorological and environmental data in an integrated GIS system give a spatially resolved picture of the surface conditions and, in our context, informations on the occurrence, extent and severity of hurricane hazard. The applied GIS model has then given rise to a long-lead system that can be set-up to allow such a early warning to go ahead.
DE: 1817 Extreme events
DE: 1821 Floods
DE: 1855 Remote sensing (1640)
SC: Hydrology [H]
MN: 2007 Fall Meeting