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Titel |
Continental Portuguese Territory Flood Susceptibility Index – contribution to a vulnerability index |
VerfasserIn |
R. Jacinto, N. Grosso, E. Reis, L. Dias, F. D. Santos, P. Garrett |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1561-8633
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Digitales Dokument |
URL |
Erschienen |
In: Natural Hazards and Earth System Sciences ; 15, no. 8 ; Nr. 15, no. 8 (2015-08-26), S.1907-1919 |
Datensatznummer |
250119644
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Publikation (Nr.) |
copernicus.org/nhess-15-1907-2015.pdf |
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Zusammenfassung |
This work defines a national flood susceptibility index for the Portuguese
continental territory, by proposing the aggregation of different variables
which represent natural conditions for permeability, runoff and
accumulation. This index is part of the national vulnerability index
developed in the scope of Flood Maps in Climate Change Scenarios (CIRAC)
project, supported by the Portuguese Association of Insurers (APS).
This approach expands on previous works by trying to bridge the gap between
different flood mechanisms (e.g. progressive and flash floods) occurring at
different spatial scales in the Portuguese territory through (a) selecting
homogeneously processed data sets and (b) aggregating their values to better
translate the spatially continuous and cumulative influence in floods at
multiple spatial scales.
Results show a good ability to capture, in the higher susceptibility
classes, different flood types: fluvial floods and flash floods. Lower
values are usually related to mountainous areas, low water accumulation
potential and more permeable soils. Validation with independent flood
data sets confirmed these index characteristics, although some overestimation
can be seen in the southern region of Alentejo where, due to a dense
hydrographic network and an overall low slope, floods are not as frequent as
a result of lower precipitation mean values.
Future work will focus on (i) including extreme precipitation data sets to
represent the triggering factor, (ii) improving representation of smaller and
stepper basins, (iii) optimizing variable weight definition process and (iii)
developing more robust independent flood validation data sets. |
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