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| Titel |
The influence of land cover roughness on the results of high resolution tsunami inundation modeling |
| VerfasserIn |
G. Kaiser, L. Scheele, A. Kortenhaus, F. Løvholt, H. Römer, S. Leschka |
| 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 Science ; 11, no. 9 ; Nr. 11, no. 9 (2011-09-22), S.2521-2540 |
| Datensatznummer |
250009676
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| Publikation (Nr.) |
 copernicus.org/nhess-11-2521-2011.pdf |
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| Zusammenfassung |
| In this paper a local case study is presented in which detailed inundation
simulations have been performed to support damage analysis and risk
assessment related to the 2004 tsunami in Phang Nga and Phuket,
Thailand. Besides tsunami sources, bathymetry and topography, bottom
roughness induced by vegetation and built environment is considered to
influence inundation characteristics, such as water depths or flow velocities
and therefore attracts major attention in this work. Plenty of information
available on the 2004 tsunami event, high-resolution satellite imagery and
extensive field measurements to derive land cover information and forest
stand parameters facilitated the generation of topographic datasets, land
cover maps and site-specific Manning values for the most prominent land
cover classes in the study areas. The numerical models ComMIT and Mike 21 FM
were used to hindcast the observed tsunami inundation and to draw
conclusions on the influence of land cover on inundation patterns. Results
show a strong influence of dense vegetation on flow velocities, which were
reduced by up to 50% by mangroves, while the inundation extent is
influenced only to a lesser extent. In urban areas, the disregard of
buildings in the model led to a significant overestimation of the inundation
extent. Hence different approaches to consider buildings were used and
analyzed in the model. The case study highlights the importance and
quantifies the effects of considering land cover roughness in inundation
simulations used for local risk assessment. |
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