Changeset 3242
- Timestamp:
- Jun 27, 2006, 10:49:13 AM (19 years ago)
- Location:
- production/onslow_2006/report
- Files:
-
- 4 edited
Legend:
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production/onslow_2006/report/damage.tex
r3240 r3242 24 24 residential collapse probability models and casualty models and their 25 25 application to inundation modelling. There is limited data found in 26 the international literature to support t o the development of26 the international literature to support the development of 27 27 vulnerability models. However, 28 28 with reported observations made of building performance during the -
production/onslow_2006/report/execsum.tex
r3241 r3242 19 19 To develop an understanding of the tsunami risk, these 20 20 decision support tools consist of inundation 21 maps and damage modellingoverlaid on aerial photography of the region22 detailing critical infrastructure .21 maps overlaid on aerial photography of the region 22 detailing critical infrastructure as as damage modelling estimates. 23 23 24 24 This report describes the modelling methodology and the results -
production/onslow_2006/report/interpretation.tex
r3240 r3242 9 9 as a function of time in the series of graphs shown in 10 10 Section \ref{sec:timeseries}. Stage is defined as the absolute 11 water level relative to AHD. Both stage and sp ped are shown11 water level relative to AHD. Both stage and speed are shown 12 12 on consistent scales to allow comparison between point locations. 13 13 %The graphs show these time series for -
production/onslow_2006/report/introduction.tex
r3240 r3242 13 13 threat and develop detailed response plans for a range of plausible events. 14 14 15 This report is the first in a series of studies which 16 go towards building the suite of tsunami assessments for the North West 17 Shelf. 18 Subsequent reports will not only 15 This report is the first in a series of studies 16 for input to the suite of tsunami assessments for the North West 17 Shelf. Subsequent reports will not only 19 18 describe studies for other localities, they will also revisit these 20 19 scenarios as more refined hazard models with associated return rates
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