Changeset 3402
- Timestamp:
- Jul 21, 2006, 5:28:16 PM (19 years ago)
- Location:
- production/onslow_2006/report
- Files:
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- 9 edited
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anuga.tex (modified) (2 diffs)
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computational_setup.tex (modified) (1 diff)
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damage.tex (modified) (6 diffs)
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data.tex (modified) (6 diffs)
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execsum.tex (modified) (3 diffs)
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introduction.tex (modified) (3 diffs)
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modelling_methodology.tex (modified) (4 diffs)
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summary.tex (modified) (1 diff)
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tsunami_scenario.tex (modified) (1 diff)
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production/onslow_2006/report/anuga.tex
r3390 r3402 14 14 according to areas of interest and that wetting and drying 15 15 is treated robustly as part of the numerical scheme.}. 16 ANUGA is continually being developed and validated to ensure16 ANUGA is continually being refined and validated to ensure 17 17 the modelling approximations are as accurate as possible. 18 18 However, model sensitivity to errors in bathymetric data, … … 43 43 thus it has not been incorporated 44 44 in the scenario. The 45 results are therefore likely to be over estimat ions.45 results are therefore likely to be over estimates. 46 46 -
production/onslow_2006/report/computational_setup.tex
r3393 r3402 1 1 To set up a model for the tsunami scenario, a study area is first 2 determined. Preliminary investigations have indicated th e point3 at which the output from MOST is the input to ANUGA is 4 sufficient at the 100m bathymetric contour line\footnote{2 determined. Preliminary investigations have indicated that the 3 output from MOST should be input to ANUGA 4 at the 100m water depth\footnote{ 5 5 Preliminary investigations indicate that MOST and ANUGA compare 6 well at the 100m contour line. In addition, the resolution for7 the MOST modelling indicate that it can theoretically model 8 tsunami s with a wavelength of 20-30km, and the wavelength of9 the tsunami wave at the boundary i s approximately 20km. A much6 well at a water depth of 100 m. In addition, the resolution for 7 the MOST modelling indicate that it can theoretically model a 8 tsunami wave with a wavelength of 20-30 km. The wavelength of 9 the tsunami wave at the boundary in this scenario is approximately 20 km. A much 10 10 higher model resolution will be used in developing the probabilistic 11 models for further studies.}. Historical run-up heights are 12 of the order of 10m and we would expect that a tsunami wave 13 would penetrate no higher for this scenario. 11 models for further studies so that tsunami waves with shorter wavelengths 12 can be captured.}. Historical run-up heights are 13 of the order of 10 m and we would expect that a tsunami wave 14 would penetrate no higher for this scenario, hence we have 15 bounded our study region at 10m elevation. 14 16 Current computation requirements define a coastline 15 extent of around 100 km. Therefore, the study area of around 6300 km$^2$16 covers approximately 100 km of17 extent of around 100 km. Therefore, the study area of around 6300 km$^2$ 18 covers approximately 100 km of 17 19 coastline and extends offshore to the 100m contour line and inshore to 18 20 approximately 10m elevation. 19 21 20 The finite volume technique relies on the construction of a triangular mesh which covers the study region. This mesh can be altered to suit the needs of the scenario in question. The mesh can be refined in areas of interest, particularly in the coastal region where complex behaviour is likely to occur. In setting up the model, the user defines the area of the triangular cells in each region of interest\footnote{Note that the cell 22 The finite volume technique relies on the construction of a triangular mesh which covers the study region. 23 This mesh can be altered to suit the needs of the scenario in question. The mesh can be refined in areas of 24 interest, particularly in the coastal region where complex behaviour is likely to occur. 25 In setting up the model, the user defines the area of the triangular cells in each region of interest\footnote{Note that the cell 21 26 area will be the maximum cell area within the defined region and that each 22 27 cell in the region does not necessarily have the same area.}. 23 The area should not be too small as to exceed realistic computational time, and not too great as to inadequately capture important behaviour. There are no gains in choosing the area to be less than the supporting data. 24 Figure \ref{fig:onslow_area} shows the study area and where further mesh refinement has been made. For each region, a maximum triangular cell area is defined and its associated lateral accuracy. 25 With these cell areas, the study area consists of 401939 triangles 26 in which water levels and momentums are tracked through time. The lateral accuracy refers to the distance at which we are confident in stating a region is inundated. Therefore we can only be confident in the calculated inundation extent in the Onslow town centre to within 30m. 28 The cell areas should not be too small as this will cause unrealisticly long computational time, 29 and not too great as this may inadequately capture important behaviour. 30 %There are no gains in choosing the area to be less than the supporting data. 31 Figure \ref{fig:onslow_area} shows the study area with regions of difference cell areas. The total number 32 of cells is 401939. 33 Lateral accuracy refers to the distance at which we are confident in stating a region is inundated. 34 Figure \ref{fig:onslow_area} shows the maximum triangular cell area and lateral accuracy for each region. 35 Therefore we can only be confident in the calculated inundation extent in the Onslow town centre to within 30 m. 36 27 37 28 38 \begin{figure}[hbt] 29 39 30 \centerline{ \includegraphics[scale=0.15] 31 {../report_figures/onslow_resolution_zones.jpg}} 40 \centerline{ \includegraphics[scale=0.15]{../report_figures/onslow_resolution_zones.jpg}} 32 41 33 42 \caption{Study area for Onslow scenario highlighting four regions of increased refinement. 34 Region 1: Surrounds Onslow town centre with a cell area of 500 m$^2$ (lateral accuracy 30 m).35 Region 2: Surrounds the coastal region with a cell area of 2500 m$^2$ (lateral accuracy 70 m).36 Region 3: Water depths to the 50m contour line (approximately) with a cell area of 20000 m$^2$ (lateral accuracy 200 m).37 Region 4: Water depths to the boundary (approximately 100m contour line) with a cell area of 100000 m$^2$ (lateral accuracy 445 m).43 Region 1: Surrounds Onslow town centre with a cell area of 500 m$^2$ (lateral accuracy 30 m). 44 Region 2: Surrounds the coastal region with a cell area of 2500 m$^2$ (lateral accuracy 70 m). 45 Region 3: Water depths to the 50m contour line (approximately) with a cell area of 20000 m$^2$ (lateral accuracy 200 m). 46 Region 4: Water depths to the boundary (approximately 100m contour line) with a cell area of 100000 m$^2$ (lateral accuracy 445 m). 38 47 } 39 48 \label{fig:onslow_area} -
production/onslow_2006/report/damage.tex
r3397 r3402 11 11 residential collapse vulnerability models and casualty models were developed. 12 12 The vulnerability models have been developed for 13 framed residential construction using data from the Indian Ocean tsunami event. The models predict the collapse 13 framed residential construction based on limited data found in the literature 14 as well as observations from the Indian Ocean tsunami event. 15 The models predict the collapse 14 16 probability for an exposed population and incorporates the following 15 parameters knownto influence building damage \cite{papathoma:vulnerability},17 parameters thought to influence building damage \cite{papathoma:vulnerability}, 16 18 17 19 \begin{itemize} … … 41 43 and the injury categories are presented in Table \ref{table:injury}. 42 44 Input data comprised of resident population data at census 43 district level derived from the ABS 2001 Census. 45 district level derived from the ABS 2001 Census. Give the exposure database is 46 based on residential structures, we assume that the 47 population are at home and sleeping when the event occurs and that there is no 48 warning. Therefore, the casualty estimates would be significantly different 49 if the event were to occur during the day when people are at work, travelling 50 in a vehicle, spending time on the beach, for example, or if the event occurred 51 during a major holiday season. 44 52 45 53 There are an estimated … … 52 60 of \$71M. Likewise, the percentage of contents loss shown is 53 61 based on the total contents value of \$101M for 54 the Onslow region .62 the Onslow region\footnote{These values are based on 2003 figures.}. 55 63 The injuries sustained is summarised in Table \ref{table:injuries}. 56 64 The HAT scenario is the only scenario to cause damage … … 65 73 &Inundated & Collapsed & Repair Cost 66 74 & of Total Value & Losses & of Total Value \\ \hline 67 %MSL & & 1 & \$ & \% & \$ & \% \\ \hline68 75 HAT & 100 &2&\$8M & 11\%&\$16M & \%16 \\ \hline 69 %LAT & & & & & & \\ \hline 76 MSL & & 1 & \$ & \% & \$ & \% \\ \hline 77 LAT & & & & & & \\ \hline 70 78 \end{tabular} 71 79 \end{center} … … 78 86 \begin{tabular}{|l|l|l|l|l|l|}\hline 79 87 &Minor & Moderate & Serious & Fatal \\ \hline 80 #MSL & & & &\\ \hline81 HAT & > 50 & < 50 & < 50 & < 50\\ \hline82 #LAT & & & & \\ \hline88 HAT & 10's & 10's & 10's & 10's \\ \hline 89 MSL & & & & \\ \hline 90 LAT & & & & \\ \hline 83 91 \end{tabular} 84 92 \end{center} … … 86 94 87 95 Tsunami impact on indigeneous communities should be considered 88 especiallyas a number of communities exist in coastal regions of north west WA.96 in the future as a number of communities exist in coastal regions of north west WA. 89 97 These communities are typically not included in national residential databases 90 98 and would be therefore overlooked in damage model estimates. -
production/onslow_2006/report/data.tex
r3390 r3402 1 The calculated run-up height and resulting inundation ashore is determined by1 The calculated run-up height and resulting inundation ashore is controlled by 2 2 the input topographic and bathymetric elevation, the 3 3 initial and boundary conditions, as well as the cell area of the computational 4 4 mesh. 5 Ideally, the data should adequately capture all complex features 5 Ideally, the topographic and bathymetric data 6 should adequately capture all complex features 6 7 of the underlying bathymetry and topography. Any limitations 7 8 in the resolution and accuracy of the data will introduce … … 14 15 and Lowest Astronomical Tide (LAT) defined as 1.5m AHD 15 16 and -1.5m AHD respectively for Onslow \cite{antt:06}. 16 These values are tidal 17 predictions based on continous tidal observations from Standard Ports 18 over a period of 19 at least one year, with the Australian Hydrographic Service 20 recommending this be extended to three years to capture 21 changes to the mean sea level. Onslow is listed as 22 a Standard Port. As an aside, current work at GA is 17 As an aside, current work at GA is 23 18 extracting information from LANDSAT imagery to reconstruct the 24 19 tidal variations for various WA locations. Future modelling of … … 36 31 DLI data is distorted by vegetation and buildings. 37 32 33 With respect to the offshore data, the Department of Planning and 34 Infrastructure (DPI) have provided state digital fairsheet data around 35 Onslow. This data covers a very small geographic area. 36 Similar data have been provided by DPI for Pt Hedland and Broome. 37 The Australian Hydrographic Office (AHO) has supplied extensive 38 fairsheet data which has also been utilised. In contrast to the onshore data, 39 the offshore data is a series of survey points which is typically 40 not supplied on a fixed grid. In addition, offshore data typically 41 does not have the coverage of the onshore data, and often the 42 offshore data will have gaps where surveys have not been conducted. 43 The coastline has been generated by 44 using the aerial photography, two detailed surveys provided 45 by WA DPI and a number of total station surveys \footnote{Total station survey information 46 has been used to verify the elevation data. A total station is an 47 electronic device that combines the ability to measure a position 48 horizontally and vertically at the same time.} of Onslow. 49 The WA DLI data surrounding the coast are error prone and 50 have been clipped at the derived coastline. 51 38 52 Figure \ref{fig:contours_compare}(a) shows the contour lines for 39 53 HAT, MSL and LAT for Onslow using the DTED data where it is evident … … 41 55 parts of Onslow town appears to be inundated at HAT before a tsunami has 42 56 even been generated. This is due to 43 short 57 shortcomings with the digital elevation model (DEM) created from 44 58 the DTED data. 45 59 Figure \ref{fig:contours_compare}(b) shows 46 60 the contour lines for HAT, MSL and LAT for Onslow using the WA DLI data. 47 61 It is obvious that there are significant differences in each DEM with 48 t otal station survey information and the knowledge62 the total station survey information and the knowledge 49 63 of the HAT contour line pointing to increased confidence in the WA DLI 50 64 data over the DTED data for use in the inundation modelling. 51 The impact difference based on these two onshore data sets 52 will be discussed in Section \ref{sec:issues}. 65 Consequently the DLI data has been used in this study. 53 66 54 67 … … 75 88 \end{figure} 76 89 77 With respect to the offshore data, the Department of Planning and 78 Infrastructure (DPI) have provided state digital fairsheet data around 79 Onslow. This data cover only a very small geographic area. (Note, 80 similar data have been provided by DPI for Pt Hedland and Broome.) 81 The Australian Hydrographic Office (AHO) has supplied extensive 82 fairsheet data which has also been utilised. In contrast to the onshore data, the offshore data is a series of survey points which is typically not supplied on a fixed grid. In addition, offshore data typically does not have the coverage of the onshore data, and often the offshore data will have gaps where surveys have not been conducted. 83 The coastline has been generated by 84 using the aerial photography, two detailed surveys provided 85 by WA DPI and a number of total station surveys of Onslow. 86 The WA DLI data surrounding the coast are error prone and 87 have been clipped at the derived coastline. 90 88 91 Appendix \ref{sec:metadata} provides more details and the supporting metadata 89 92 for this study, including images of the data extent. … … 95 98 \begin{center} 96 99 \begin{tabular}{|l|l|}\hline 97 Data & Detail\\ \hline100 Data & Specifications \\ \hline 98 101 DIGO DTED Level 2 & Onshore, 1 second $\approx$ 30m \\ \hline 99 102 DLI & Onshore, 20m DEM and orthophotography \\ \hline -
production/onslow_2006/report/execsum.tex
r3389 r3402 2 2 (FESA) as part of the Collaborative Research Agreement (CRA) 3 3 with Geoscience Australia (GA). 4 FESA recognisesthe potential vulnerability of the Western Australia5 coastline to tsunami genic earthquakes originating from6 the Sunda Arc subduction zone that caused the December 2004 event.7 There is historic evidence of tsunami eventsaffecting the4 FESA has recognised the potential vulnerability of the Western Australia 5 coastline to tsunami originating from earthquakes on 6 the Sunda Arc subduction zone. 7 There is historic evidence of tsunami affecting the 8 8 Western Australia coastline, \cite{CB:ausgeo}, 9 9 and FESA has sought to assess … … 11 11 threat and develop detailed response plans for a range of plausible events. 12 12 13 This report describes the modelling methodology and firstresults14 for a particulartsunami-genic event as it impacts the Onslow township13 This report describes the modelling methodology and initial results 14 for a specific tsunami-genic event as it impacts the Onslow township 15 15 and its surrounds. Future studies 16 16 will present a series of scenarios for a range of return periods to … … 18 18 This report and the decision support tool are the 19 19 June 2006 deliverables of the Collaborative Research Agreement 20 between FESA and GA .20 between FESA and GA, Tsunami Impact Modelling for WA . 21 21 -
production/onslow_2006/report/introduction.tex
r3375 r3402 1 The Fire and Emergency Services Authority of Western Australia (FESA)and1 The Fire and Emergency Services Authority (FESA) of Western Australia and 2 2 associated volunteers respond to a wide range of emergencies 3 3 as well as undertaking search and rescue operations on land and 4 4 water\footnote{http://www.fesa.wa.gov.au/internet/}. 5 FESA helps the West Australian 6 community prepare, prevent (where possible) and respond safely to disasters. 5 7 FESA also aims to reduce injury, loss of life and destruction of property in 6 8 Western Australian communities through proactive measures. 7 FESA helps the West Australian 8 community prepare, prevent (where possible) and respond safely to disasters. 9 These risk mitigation activities involve understanding the relative risk 9 These measures involve understanding the relative risk 10 10 of the disaster so that resources can be directed to appropriate areas 11 11 and corresponding evacuation plans put in place. … … 24 24 This report is the first in a series of tsunami assessments 25 25 of the North West Shelf. The scenario used for this study has 26 an unknown return period, but considered a plausible event (see26 an unknown return period, but is considered a plausible event (see 27 27 Section \ref{sec:tsunamiscenario}). 28 28 Subsequent assessments will use refined hazard models with 29 associate return rates for other localities, as advised by FESA. 29 associate return periods. A suite of assessments will be 30 made for Onslow and other localities, as advised by FESA. 30 31 31 32 Onslow has a population of around 800 and … … 37 38 38 39 The modelling technique to simulate the 39 impact ashore will be discussed in Section \ref{sec:anuga} and data inputs40 impact ashore is discussed in Section \ref{sec:methodology} and data inputs 40 41 discussed in Section \ref{sec:data}. 41 42 The inundation results are presented and discussed in Section \ref{sec:results} -
production/onslow_2006/report/modelling_methodology.tex
r3390 r3402 3 3 by a range of rapid onset natural hazards. Through the integration of natural hazard research, defining national exposure and 4 4 estimating socio-economic vulnerabilities, predictions of the likely impacts of events can be made. 5 Hazards include earthquakes, landslides, tsunami, severe winds and cyclones.6 7 5 By modelling the likely impacts on urban communities as accurately as possible and 8 6 building these estimates into land use planning and emergency … … 28 26 The hazard itself is then reported as a maximum wave height at a fixed contour line near the coastline, 29 27 (e.g. 50m). This is how the preliminary tsunami hazard assessment was reported by GA 30 to FESA in September 2005 \cite{BC:FESA}. The assessment used the Method of Splitting Tsunamis (MOST) 28 to FESA in September 2005 \cite{BC:FESA} for a suite of Mw 9 earthquakes 29 evenly spaced along the Sunda Arc subduction zone. 30 The assessment used the Method of Splitting Tsunamis (MOST) 31 31 \cite{VT:MOST} model. 32 32 %The maximal wave height at a fixed contour line near the coastline … … 60 60 61 61 \bigskip %FIXME (Ole): Should this be a subsection even? 62 The risk of the scenario tsunami eventcannot be determined until the63 likelihood of the eventis known. GA is currently building a62 The risk of a given tsunami scenario cannot be determined until the 63 likelihood of the tsunami is known. GA is currently building a 64 64 complete probabilistic hazard map which is due for completion 65 65 in late 2006. We therefore report on the impact of a single … … 67 67 will be assessed for a range of events which will ultimately 68 68 determine a tsunami risk assessment for the NW shelf. 69 70 FESA is interested in the ``most frequent worst case scenario''. Whilst 71 we currently cannot determine exactly what that event may be, the 72 preliminary hazard assessment suggested that the maximum 73 magnitude of earthquakes off Java was considered to be at 74 least 8.5 and could potentially be as high as 9. Therefore, 75 the Mw 9 event 76 provides a plausible worst case scenario and is used as the tsunami 77 source in this report. 78 Figure \ref{fig:mw9} shows the maximum wave height of a tsunami initiated 79 by a Mw 9 event off 80 the coast of Java. This event provides the source and 81 boundary condition to the 82 inundation model presented in Section \ref{sec:anuga}. 83 84 \begin{figure}[hbt] 85 86 \centerline{ \includegraphics[width=140mm, height=100mm] 87 {../report_figures/mw9.jpg}} 88 89 \caption{Maximum wave height (in cms) for a Mw 9 event off the 90 coast of Java} 91 \label{fig:mw9} 92 \end{figure} 93 69 94 %To model the 70 95 %details of tsunami inundation of a community one must therefore capture %what is -
production/onslow_2006/report/summary.tex
r3396 r3402 3 3 occurring at Highest Astronomical Tide, Lowest Astronomical Tide 4 4 and Mean Sea Level. 5 There is no knowledge of the return period for this event. The5 As yet, there is no knowledge of the return period for this event. The 6 6 modelling methodology, assumptions and data sources for the Onslow 7 7 scenario have also been described. -
production/onslow_2006/report/tsunami_scenario.tex
r3375 r3402 33 33 \begin{figure}[hbt] 34 34 35 \centerline{ \includegraphics[width=1 00mm, height=75mm]35 \centerline{ \includegraphics[width=140mm, height=100mm] 36 36 {../report_figures/mw9.jpg}} 37 37
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