Changeset 3340


Ignore:
Timestamp:
Jul 17, 2006, 6:45:02 PM (18 years ago)
Author:
sexton
Message:
 
Location:
production/onslow_2006/report
Files:
12 edited

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  • production/onslow_2006/report/HAT_map.tex

    r3329 r3340  
    11\begin{figure}[hbt]
    22\centerline{ \includegraphics[width=\paperwidth]{../report_figures/high_tide_20060704_063005.jpg}}
    3 \caption{Maximum inundation map for the HAT scenario for Onslow region.
     3\caption{Maximum inundation map for the HAT scenario for Onslow region. Data: WA DLI, DPI and AHO.
    44\label{fig:HAT_max_inundation}
    55\end{figure}
  • production/onslow_2006/report/MSL_map.tex

    r3329 r3340  
    11\begin{figure}[hbt]
    22\centerline{ \includegraphics[width=\paperwidth]{../report_figures/mid_tide_20060704_063234.jpg}} 
    3 \caption{Maximum inundation map for the MSL scenario for Onslow region.
     3\caption{Maximum inundation map for the MSL scenario for Onslow region. Data: WA DLI, DPI and AHO.
    44\label{fig:MSL_max_inundation}
    55\end{figure}
  • production/onslow_2006/report/anuga.tex

    r3313 r3340  
    1 
    2 The software tool, ANUGA \cite{ON:modsim}, has been used to develop the
    3 inundation extent
     1The software tool, ANUGA \cite{ON:modsim}, has been used to estimate
     2the inundation extent
    43and associated water level at various points in space and time.
    54ANUGA has been developed by GA and the Australian National University
    65(ANU) to solve the nonlinear shallow water
    7 wave equation using the finite volume technique.
    8 An advantage of this technique is that the cell area can be changed
     6wave equation using the finite volume technique\footnote{The finite volume
     7technique belongs to the class of computational fluid dynamic (CFD)
     8methods which is based on discretizing the study area in
     9control ''volumes''. The method satisfices conservation
     10of mass, momentum and energy and is exactly satisfied for
     11each control volume.
     12An advantage of this technique is that the discretization
     13can be changed
    914according to areas of interest and that wetting and drying
    10 is treated robustly as part of the numerical scheme.
     15is treated robustly as part of the numerical scheme.}.
    1116ANUGA is continually being developed and validated to ensure
    1217the modelling approximations reflect new theory or
    1318available experimental data sets.
    14 As such, the current results represent ongoing work
    15 and may change in the future.
     19As such, the current results are preliminary.
    1620
    17 The following set of information is required to undertake the
     21The following information is required to undertake the
    1822inundation modelling;
    1923
     
    2226see Section \ref{sec:data}),
    2327\item initial conditions, such as initial water levels (e.g. determined by tides),
    24 \item boundary condition (the tsunami source as described in
    25 Section \ref{sec:tsunamiscenario}),
     28\item boundary conditions (the tsunami source as described in
     29Section \ref{sec:tsunamiscenario}), and
    2630\item computational requirements relating to the mesh construction.
    2731\end{itemize}
     
    2933As part of the CRA, it was decided to provide results for the
    3034extremes of the tidal regimes to understand the potential range of impacts
    31 from the event. The Highest Astronomical Tide (HAT) and Lowest
    32 Astronomical Tide (LAT) are defined as 1.5m Australian Height Datum (AHD)
    33 and -1.5m AHD respectively for Onslow, \cite{antt:06}, with
    34 Mean Sea Level (MSL) approximately equal to 0m AHD. These values are tidal
     35from the event. In this study, we used the Australian Height Datum (AHD)
     36as the vertical datum. Mean Sea Level (MSL) is approximately equal to
     370m AHD with the Highest Astronomical Tide (HAT)
     38and Lowest Astronomical Tide (LAT) defined as 1.5m AHD
     39and -1.5m AHD respectively for Onslow, \cite{antt:06}.
     40These values are tidal
    3541predictions based on continous tidal observations from Standard Ports
    3642over a period of
     
    4349these areas will incorporate this information.
    4450
    45 
    46 The initial conditions used for this scenario is then MSL, HAT and LAT.
     51The initial conditions used for this scenario are MSL, HAT and LAT.
    4752The dynamics of
    4853tidal effects (that is, the changes in water height over time for
    49 the entire study area) is not currently modelled.
    50 Bottom friction will generally provide resistance to the water flow
    51 and thus reduce the impact somewhat. However, it is an open area
    52 of research on how to determine the friction coefficients, and
     54the entire study area) are not currently modelled.
     55Sea floor friction will generally provide resistance to the water flow
     56and thus reduce the impact somewhat. However, limited
     57research has been carried out to determine
     58the friction coefficients, and
    5359thus it has not been incorporated
    54 in the scenario presented in this report. Therefore, the
    55 results presented are over estimated to some degree.
     60in the scenario presented in this report. The
     61results are therefore likely to be over estimations.
    5662
  • production/onslow_2006/report/computational_setup.tex

    r3290 r3340  
     1To set up a model for the tsunami scenario, a study area is first
     2determined. Preliminary investigations have indicated that point
     3at which the deep water and shallow water models can exchange data is
     4sufficiently OK at the
     5100m bathymetric contour line.
     6Current computation requirements define a coastline
     7extent of around 100km.
     8Preliminary investigations indicate that MOST and ANUGA compare
     9well at the 100m contour line. In addition, the resolution for
     10the MOST modelling indicate that it can theoretically model
     11tsunamis with a wavelength of 20-30km, and the wavelength of
     12the tsunami wave at the boundary is approximately 20km. A much
     13higher model resolution will be used in developing the probabilistic
     14models for further studies.
     15Therefore, the study area cof around 6300 km$^2$
     16covers approximately 100km of
     17coastline and extends offshore to the 100m contour line and inshore to
     18approximately 10m elevation.
     19
    120To initiate the modelling, a triangular mesh is constructed to
    2 cover the study region which has an area of around 6300 km$^2$.
     21cover the study region
    322The cell size is chosen to balance
    423computational time and desired resolution in areas of interest,
     
    928of the refinement is based around the inter-tidal zones and
    1029other important features such as islands and rivers.
    11 The study area covers approximately 100km of
    12 coastline and extends offshore to the 100m contour line and inshore to
    13 approximately 10m elevation.
    14 Preliminary investigations indicate that MOST and ANUGA compare
    15 well at the 100m contour line. In addition, the resolution for
    16 the MOST modelling indicate that it can theoretically model
    17 tsunamis with a wavelength of 20-30km, and the wavelength of
    18 the tsunami wave at the boundary is approximately 20km. A much
    19 higher model resolution will be used in developing the probabilistic
    20 models for further studies.
    2130
    2231\begin{figure}[hbt]
     
    98107\includegraphics[width=0.49\linewidth, height=50mm]{../report_figures/point_line_3d.png}&
    99108\includegraphics[width=0.49\linewidth, height=50mm]{../report_figures/solution_surfaceMOST.png}\\
     109(a) & (b) \\
    100110\end{tabular}
    101111 \caption{Point locations used to illustrate the form of the tsunami wave and the
  • production/onslow_2006/report/damage.tex

    r3339 r3340  
     1In this report, impact modelling refers to casualties and
     2damage to residential buildings as a result
     3of the inundation described in Section \ref{sec:results}. It is assumed
     4that the event occurs at night.
     5Exposure data are sourced from the National Building Exposure Database (NBED),
     6developed by GA\footnote{http://www.ga.gov.au/urban/projects/ramp/NBED.jsp}.
     7It contains information about residential buildings, people, and the
     8cost of replacing buildings and contents.
    19
    2 %This section deals with impact modelling which covers damage
    3 %modelling and economic impact analysis.
    4 In this report, impact modelling refers to damage as a result
    5 of the inundation described in Section \ref{sec:results}. This damage
    6 is reported as damage to infrastructure as well as
    7 number of human injuries and is determined assuming
    8 that the event occurs at night. The infrastructure
    9 refers to residential structures only and is sourced from the
    10 the National Building Exposure Database (NBED). The NBED has been
    11 created by Geoscience Australia so that consistent risk assessments for a range
    12 of natural hazards can be
    13 conducted\footnote{http://www.ga.gov.au/urban/projects/ramp/NBED.jsp}.
    14 It contains information
    15 about residential buildings, people, infrastructure,
    16 structure value and building contents.
    17 From this database, we find that there
    18 are 325 residential structures and a population of approximately 770
    19 in Onslow\footnote{Population is determined by census data and an ABS
    20 housing survey}.
    21 
    22 
    23 To develop building damage and casuality estimates, we briefly describe
    24 residential collapse probability models and casualty models and their
    25 application to inundation modelling. There is limited data found in
    26 the international literature to support the development of
    27 vulnerability models. However,
    28 with reported observations made of building performance during the
    29 recent Indian Ocean tsunami, vulnerability models have been proposed for
    30 framed residential construction. The models predict the collapse
     10To develop building damage and casuality estimates,
     11residential collapse vulnerability models and casualty models were developed.
     12The vulnerability models have been developed for
     13framed residential construction using data from teh Indian Ocean tsunami event.
     14The models predict the collapse
    3115probability for an exposed population and incorporate the following
    3216parameters known to influence building damage \cite{papathoma:vulnerability},
     
    3418\begin{itemize}
    3519\item   inundation depth at building   
    36 \item   building row from coast
     20\item   distance from the coast
    3721\item   building material (residential framed construction)     
    38 \item   inundation depth at house above floor level
     22\item   inundation depth in house above floor level
    3923\end{itemize}   
    4024
    4125The collapse vulnerability models used are presented in Table \ref{table:collapse}.
    42 In applying the model all structures in the inundation zone were
    43 spatially located and the local water depth and building row
    44 number from the exposed edge of the suburb were determined for each.
     26%In applying the model, all structures in the inundation zone were
     27%spatially located and the local water depth and building row
     28%number from the exposed edge of the suburb were determined for each structure.
    4529
    46 Casualty models were developed by making reference to the
     30Casualty models were based on the
    4731storm surge models used for the Cairns Cyclone Scenario and
    4832through consultation with Dr David Cooper of NSW Health, \cite{cooper:2005}.
    49 The injury probabilities for exposed populations were selected
     33The injury probabilities for exposed populations were determined
    5034based on the nocturnal nature of the event, the collapse outcome
    5135for the structure, the water depth with respect to
     
    5842and the injury categories are presented in Table \ref{table:injury}.
    5943Input data comprised of resident population data at census
    60 district level derived from the ABS 2001 census.
     44district level derived from the ABS 2001 Census.
    6145
     46From this database, we find that there
     47are 325 residential structures and a population of approximately 770
     48in Onslow\footnote{Population is determined by census data and the 19??
     49ABS housing survey}.
    6250The damage to the residential structures in the Onslow community
    6351is summarised in Table \ref{table:damageoutput}. The percentage
     
    10189\end{table}
    10290
    103 Impact on indigeneous communities are important considerations when determining
    104 tsunami impact, especially as a number of communities exist in coastal regions.
     91Tsunami impact on indigeneous communities should be considered
     92especially as a number of communities exist in coastal regions of north west WA.
    10593These communities are typically not included in national residential databases
    10694and would be therefore overlooked in damage model estimates.
     
    11098(18 \% of the Onslow population)
    11199and is situated close to the coast as seen in Figure \ref{fig:points}.
    112 During the HAT scenario,
    113 over 1m of water will inundate parts of the community (Figure
    114 \ref{fig:gaugeBindiBindiCommunity}) causing significant damage.
     100During the HAT scenario, over 1m of water will inundate parts of the community (Figure
     101\ref{fig:gaugeBindiBindiCommunity}) causing significant impact.
  • production/onslow_2006/report/data.tex

    r3285 r3340  
    1313Data for this study have been sourced from a number of agencies. With
    1414respect to the onshore data, the Defence Imagery and Geospatial
    15 Organisation (DIGO) supplied the DTED (Digital Terrain Elevation
    16 Data) Level 2 data which has been authorised for Australian Tsunami
    17 Warning System use only. This data has a resolution of 1 second
    18 (about 30 metres), produced from 1:50 000 contours, elevations and
     15Organisation (DIGO) supplied the Digital Terrain Elevation
     16Data Level 2 (DTED) which has been authorised for Australian Tsunami
     17Warning System use only. The resolution of this data is 1 second
     18(about 30 metres), and has been produced from 1:50 000 contours, elevations and
    1919drainage. In addition, the Department of Land Information (DLI) has provided a
    202020m Digital Elevation Model (DEM) and orthophotography
    21 covering the NW Shelf. The DTED Level 2 data is ``bare earth'' with
    22 the DLI data is distored by vegetation and buildings. The WA DLI data
    23 is used for the simulation results which follow, due to its overall
    24 increased accuracy over the DTED data. Further discussion on the comparison
    25 between these data sets is deferred to Section \ref{sec:issues}.
    26 %However, the 30m
    27 %DTED Level 2 data is ``bare earth'' whereas the DLI data is distorted by
    28 %vegetation
    29 %and buildings so we have chosen to use the DTED as the onshore
    30 %topographic data set. It is also important to note that the DEM does
    31 %not include features such as rock walls, berths etc.
     21covering the NW Shelf. The DTED Level 2 data is ``bare earth'' and
     22the DLI data distorted by vegetation and buildings. The WA DLI data
     23is used for the simulation results, due to its overall
     24increased accuracy over the DTED data.
     25
     26Figure \ref{fig:contours_compare} shows the contour lines for
     27HAT, MSL and LAT for Onslow using the DTED data where it is evident
     28that the extent of the tidal inundation is exaggerated. This is due to
     29short comings with the digital elevation model (DEM) created from
     30the DTED data. The DEM has been
     31derived from 20m contour lines. {\bf Need some words from hamish here.}
     32As a result, we turned to the WA DLI onshore data to present
     33the results in this report. Figure \ref{fig:contours_compare} shows
     34the contour lines for HAT, MSL and LAT for Onslow using the WA DLI data.
     35It is obvious that there are significant differences in each DEM with
     36secondary information regarding total station surveys and the knowledge
     37of the HAT contour line pointing to increased confidence in the WA DLI
     38data over the DTED data for use in inundation modelling.
     39The impact difference based on these two onshore data sets
     40will be discussed in Section \ref{sec:issues}.
     41
     42\pagebreak
     43
     44\begin{figure}[p]
     45(a)
     46  \centerline{ \includegraphics[width=150mm, height=100mm]
     47{../report_figures/onslow_dted_contour.jpg}}
     48
     49 % \caption{Onslow region showing the -1.5m AHD (LAT), 0m AHD (MSL)
     50 %and -1.5m AHD (LAT) contour lines using the DTED Level 2 data.}
     51 % \label{fig:contours_dted}
     52%\end{figure}
     53
     54%\begin{figure}[hbt]
     55(b)
     56  \centerline{ \includegraphics[width=150mm, height=100mm]
     57{../report_figures/onslow_dli_contour.jpg}}
     58
     59  \caption{Onslow region showing the -1.5m AHD (LAT), 0m AHD (MSL)
     60and 1.5m AHD (HAT) contour lines using the DTED Level 2 data (a) and
     61the WA DLI data (b).}
     62 % \label{fig:contours_dli}
     63 \label{fig:contours_compare}
     64\end{figure}
    3265
    3366With respect to the offshore data, the Department of Planning and
    3467Infrastructure (DPI) have provided state digital fairsheet data around
    35 Onslow. This data covers only a very small geographic area. (Note,
    36 similar data has been provided for Pt Hedland and Broome by DPI.)
     68Onslow. This data cover only a very small geographic area. (Note,
     69similar data have been provided by DPI for Pt Hedland and Broome.)
    3770The Australian Hydrographic Office (AHO) has supplied extensive
    3871fairsheet data which has also been utilised.
     
    4073using the aerial photography, two detailed surveys provided
    4174by WA DPI and a number of total station surveys of Onslow.
    42 The WA DLI data surrounding the coast is error prone and
    43 has been clipped at the derived coastline.
    44 Appendix \ref{sec:metadata} provides more details and metadata for data
    45 used for this study.
     75The WA DLI data surrounding the coast are error prone and
     76have been clipped at the derived coastline.
     77Appendix \ref{sec:metadata} provides more details and the supporting metadata
     78for this study.
    4679Table \ref{table:data} summarises the available data for this study.
    4780
  • production/onslow_2006/report/discussion.tex

    r3332 r3340  
    1 %As part of the CRA, it was decided to provide results for the
    2 %extremes of the tidal regimes to understand the potential range of impacts
    3 %from the event. The Highest Astronomical Tide (HAT) and Lowest
    4 %Astronomical Tide (LAT) are defined as 1.5m AHD and -1.5m AHD
    5 %respectively for Onslow, \cite{antt:06}. These values are tidal
    6 %predictions based on continous tidal observations from Standard Ports
    7 %over a period of
    8 %at least one year, with the Australian Hydrographic Service
    9 %recommending this be extended to three years to capture
    10 %changes to the mean sea level. Onslow is listed as
    11 %a Standard Port.
    12 
    13 %As an aside, current work at GA is
    14 %extracting information from LANDSAT imagery to reconstruct the
    15 %tidal variations for various WA locations. Future modelling of
    16 %these areas will incorporate this information.
    17 
    18 Initial simulations for this study used the DIGO DTED Level 2 data
    19 (see Section \ref{sec:data}) due to the fact it is
    20 ``bare earth'', whereas the DLI data is distorted by
    21 vegetation and buildings.
    22 Figure \ref{fig:contours_compare} shows the contour lines for
    23 HAT, MSL and LAT for Onslow using the DTED data where it is evident
    24 that the extent of the tidal inundation is exaggerated. This is due to
    25 short comings with the digital elevation model (DEM) created from
    26 the DTED data. The DEM has been
    27 derived from 20m contour lines. {\bf Need some words from hamish here.}
    28 As a result, we turned to the WA DLI onshore data to present
    29 the results in this report. Figure \ref{fig:contours_compare} shows
    30 the contour lines for HAT, MSL and LAT for Onslow using the WA DLI data.
    31 It is obvious that there are significant differences in each DEM with
    32 secondary information regarding total station surveys and the knowledge
    33 of the HAT contour line pointing to increased confidence in the WA DLI
    34 data over the DTED data for use in inundation modelling.
    35 
    361The purpose of this section then is to show the differences to the impact
    37 ashore when each data set is used to demonstrate the importance of using the
    38 best possible data set. The maximum inundation map is shown for the MSL
    39 scenario using the DTED data in
    40 Figure \ref{fig:MSL_map_DTED} which can be compared with the equivalent map for
    41 the WA DLI data, Figure \ref{fig:MSL_max_inundation}. Given that the 1.5m contour
     2when each data set is used to demonstrate the importance of using the
     3best possible data set. Given that the 1.5m AHD contour
    424line is further from the coast for the DTED data than the DLI data, we
    43 expect to see the inundation to reach further and thus be greater than
    44 that seen in Figure \ref{fig:MSL_max_inundation}. This is confirmed by
    45 Figure \ref{fig:MSL_map_DTED}. These results point to the need for the best
     5expect the inundation to extend further and thus be greater than
     6that seen in Figure \ref{fig:MSL_map}. Further, the impact modelling
     7will result in inflated structural and contents loss figures as well as
     8numbers of people affected.
     9These results point to the need for the best
    4610available data so that more accurate predictions regarding the
    4711inundation can be made.
    4812
    49 Additionally, we show the time history of the water's stage and
    50 velocity for the point locations in Table \ref{table:locations} for
    51 both the DTED and DLI data at MSL. These results are shown in Section
    52 \ref{sec:timeseriescompare}.
    53 \pagebreak
    5413
    55 \begin{figure}[p]
    5614
    57   \centerline{ \includegraphics[width=150mm, height=100mm]
    58 {../report_figures/onslow_dted_contour.jpg}}
    59 
    60  % \caption{Onslow region showing the -1.5m AHD (LAT), 0m AHD (MSL)
    61  %and -1.5m AHD (LAT) contour lines using the DTED Level 2 data.}
    62  % \label{fig:contours_dted}
    63 %\end{figure}
    64 
    65 %\begin{figure}[hbt]
    66 
    67   \centerline{ \includegraphics[width=150mm, height=100mm]
    68 {../report_figures/onslow_dli_contour.jpg}}
    69 
    70   \caption{Onslow region showing the -1.5m AHD (LAT), 0m AHD (MSL)
    71 and -1.5m AHD (LAT) contour lines using the DTED Level 2 data and
    72 the WA DLI data.}
    73  % \label{fig:contours_dli}
    74  \label{fig:contours_compare}
    75 \end{figure}
    76 
    77 \begin{figure}[p]
    78 
    79   \centerline{ \includegraphics[width=\paperwidth]
    80 {../report_figures/mid_tide_DTED.jpg}}
    81 
    82   \caption{Maximum inundation map for the Onslow region using
    83   the DTED data.}
    84   \label{fig:MSL_map_DTED}
    85 \end{figure}
    86 
  • production/onslow_2006/report/execsum.tex

    r3268 r3340  
    1 The Fire and Emergency Services Authority of Western Australia (FESA) and
    2 associated volunteers respond to a wide range of emergencies
    3 as well as undertaking search and rescue operations on land and
    4 water\footnote{http://www.fesa.wa.gov.au/internet/}.
    5 FESA also aims to reduce injury, loss of life and destruction of property in
    6 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
    10 of the disaster so that resources can be directed to appropriate areas
    11 and corresponding evacuation plans put in place. 
    12 
    13 The key role of the Risk Research Group at Geoscience Australian
    14 is to develop knowledge on the risk from natural and
    15 human-caused hazards for input to policy and operational decision makers
    16 for the mitigation of risk to Australian communities. The group achieves
    17 this through the development of computational methods, models and decision
    18 support tools that assess the hazard, vulnerability and risk posed by hazards.
    19 To develop an understanding of the tsunami risk, these
    20 decision support tools consist of inundation
    21 maps overlaid on aerial photography of the region
    22 detailing critical infrastructure as well as damage modelling estimates.
     1This report is being provided to the Fire and Emergency Services Authority
     2(FESA) as part of the Collaborative Research Agreement (CRA)
     3with Geoscience Australia (GA).
     4FESA recognises the potential vulnerability of the Western Australia
     5coastline to tsunamigenic earthquakes originating from
     6the Sunda Arc subduction zone that caused the December 2004 event.
     7There is historic evidence of tsunami events affecting the
     8Western Australia coastline, \cite{CB:ausgeo},
     9and FESA has sought to assess
     10the relative risk of its urban and regional communities to the tsunami
     11threat and develop detailed response plans for a range of plausible events.
    2312
    2413This report describes the modelling methodology and the results
    25 for a particular tsunami-genic event as it impacts Onslow on the North
    26 West Shelf. This report and the decision support tool are the
     14for a particular tsunami-genic event as it impacts the Onslow township
     15and its surrounds. This report and the decision support tool are the
    2716June 2006 deliverables of the Collaborative Research Agreement
    2817between FESA and GA.
  • production/onslow_2006/report/interpretation.tex

    r3330 r3340  
    11The main features of the
    22tsunami wave and resultant impact ashore is described in this section.
    3 To assist this description, we have
     3We have
    44chosen a number of locations which we believe would be important
    55in an emergency situation, such as the hospital and power station, or
     
    26261 & leisurely stroll pace\\ \hline
    27271.5 & average walking pace \\ \hline
    28 2 & 100m Olympic male freestyle \\ \hline
    29 3 & mackeral \\ \hline
     28%2 & 100m Olympic male freestyle \\ \hline
     29%3 & mackeral \\ \hline
    30304 & average person maintain for 1000m \\ \hline
    31 5 & blue whale \\ \hline
     31%5 & blue whale \\ \hline
    323210 & 100m Olympic male sprinter \\ \hline
    333316 & car travelling in urban zones (60 km/hr) \\ \hline
     
    6464The speeds at west and east of Beadon Bay are quite similar
    6565(Figure \ref{fig:gaugeBeadonBayeast} and Figure \ref{fig:gaugeBeadonBaywest}).
    66 however, there are increased amplitudes (from drawdown to maximum
     66However, there are increased amplitudes (from drawdown to maximum
    6767amplitude), in the eastern location which is in shallower water than the western
    6868location.
     
    8080There is inundation between the western sand dunes at high
    8181tide, Figure \ref{fig:HAT_max_inundation}, however, this water
    82 penetrated from the north east (via
     82penetrates from the north east (via
    8383Onslow town centre) rather than seaward. (The DEM indicates that
    84 this area is under 1.5m which is automatically deemed to inundated
     84this area is under 1.5m AHD which is automatically deemed to be inundated
    8585at HAT.)
    8686The same feature is evident for the sand dunes east of Onslow.
     
    104104river which becomes increasingly inundated as the initial condition
    105105changes from 0m AHD to 1.5m AHD. Only the
    106 entry to the wharf on Beadon Creek Rd is sufficiently inundated at -1.5m AHD
    107 to stop traffic. At 1.5m AHD however, essentially the entire road
    108 would be impassable.
     106entry to the wharf on Beadon Creek Rd is sufficiently inundated to
     107stop traffic at -1.5m AHD.
     108At 1.5m AHD however, essentially the entire road would be impassable.
    109109
    110110There is significant inundation of at
    111111least 2m on the foreshore of Onslow for 0m AHD and 1.5m AHD.
    112 The inundation extent increases the initial condition increases above 0m AHD,
    113 pushing the edges
    114 of the majority of the road infrastructure in the Onslow town centre.
     112The inundation extent increases as the initial condition increases above 0m AHD,
     113reaching the southern boundaries of
     114the road infrastructure in the Onslow town centre.
  • production/onslow_2006/report/introduction.tex

    r3252 r3340  
     1The Fire and Emergency Services Authority of Western Australia (FESA) and
     2associated volunteers respond to a wide range of emergencies
     3as well as undertaking search and rescue operations on land and
     4water\footnote{http://www.fesa.wa.gov.au/internet/}.
     5FESA also aims to reduce injury, loss of life and destruction of property in
     6Western Australian communities through proactive measures.
     7FESA helps the West Australian
     8community prepare, prevent (where possible) and respond safely to disasters.
     9These risk mitigation activities involve understanding the relative risk
     10of the disaster so that resources can be directed to appropriate areas
     11and corresponding evacuation plans put in place. 
    112
    2 This report is being provided to the Fire and Emergency Services Authority
    3 (FESA) as part of the Collaborative Research Agreement (CRA)
    4 with Geoscience Australia (GA).
    5 FESA recognises the potential vulnerability of the Western Australia
    6 coastline to tsunamigenic earthquakes originating from
    7 the Sunda Arc subduction zone that caused the December 2004 event which
    8 fortunately had no impact on Australia.
    9 However, there is historic evidence of tsunami events affecting the
    10 Western Australia coastline, \cite{CB:ausgeo},
    11 and FESA has sought to assess
    12 the relative risk of its urban and regional communities to the tsunami
    13 threat and develop detailed response plans for a range of plausible events.
     13The key role of the Risk Research Group at Geoscience Australian
     14is to develop knowledge on the risk from natural and
     15human-caused hazards for input to policy and operational decision makers
     16for the mitigation of risk to Australian communities. The group achieves
     17this through the development of computational methods, models and decision
     18support tools that assess the hazard, vulnerability and risk posed by hazards.
     19To develop an understanding of the tsunami risk, these
     20decision support tools consist of inundation
     21maps overlaid on aerial photography of the region
     22detailing critical infrastructure as well as damage modelling estimates.
    1423
    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
    18 describe studies for other localities, they will also revisit these
    19 scenarios as more refined hazard models with associated return rates
    20 become available. In this report,
     24This report is the first in a series of tsunami assessments
     25of the North West Shelf. The scenario used for this study has
     26an unknown return period, however it is a plausible event (see
     27Section \ref{sec:tsunamiscenario}.
     28Subsequent assessments will use refined hazard models with
     29associate return rates for other localities, as advised by FESA.
     30In this report,
    2131the methods, assumptions and impacts of a
    2232single tsunami source scenario is described for the Onslow area in the
    23 North West shelf region.
    24 Onslow has a population of around 800
     33North West shelf region. Future studies
     34will present a series of scenarios for a range of return periods to
     35assist FESA in developing appropriate plans for a range of event impacts.
     36Onslow has a population of around 800 and
    2537is part of the Shire of Ashburton in the Pilbara region of
    2638Western Autralia\footnote{http://www.pdc.wa.gov.au/region/political.htm}.
     
    2941fishing and tourism.
    3042
    31 The report will outline the methods of modelling the tsunami from its
    32 source to its impact ashore and present the predicted consequences.
    33 The scenario used for this study has an unknown
    34 return period, however it
    35 is a plausible event, see Section \ref{sec:tsunamiscenario}.
    36 Future studies
    37 will present a series of scenarios for a range of return periods to
    38 assist FESA in developing appropriate plans for a range of event impacts.
    39 The details of the hazard modelling will not be described here, however,
    40 the modelling technique to simulate the
    41 impact ashore will be discussed in Section \ref{sec:anuga} with data inputs
     43The modelling technique to simulate the
     44impact ashore will be discussed in Section \ref{sec:anuga} and data inputs
    4245discussed in Section \ref{sec:data}.
    43 The inundation results will be shown and discussed in Section \ref{sec:results}
    44 with the impact modelling outputs shown in Section \ref{sec:impact}.
    45 The report concludes with a summary of the results detailing issues
    46 regarding underlying data and further model development.
     46The inundation results are presented and discussed in Section \ref{sec:results}
     47and the impact modelling results outlined in Section \ref{sec:impact}.
     48A summary of the results detailing issues
     49regarding underlying data and further model development, are discussed
     50in Section \ref{sec:summary}.
    4751
  • production/onslow_2006/report/summary.tex

    r3330 r3340  
    44and Mean Sea Level.
    55There is no knowledge of the return period for this event. The
    6 modelling methodology, assumptions and data sources which are
    7 required to determine the impact to Onslow have also
    8 been described.
     6modelling methodology, assumptions and data sources for the Onslow
     7scenario have also been described.
    98As discussed in Section \ref{sec:issues}, it is imperative
    109that the best available data is used to increase confidence
    11 in the inundation maps. It is not yet clear what onshore grid resolution
    12 is required.
     10in the inundation maps. An onshore grid resolution of the order
     11of tens of metres is required, however, it is more important that the data
     12is accurate (or at least well known).
    1313These scenarios will be revisited once the probabilistic models
    1414are complete so that a suite of tsunami impact assessments can be made.
  • production/onslow_2006/report/tsunami_scenario.tex

    r3240 r3340  
    1 The tsunamigenic event used for this study was developed for a
    2 preliminary tsunami hazard assessment study delivered to FESA in September 2005,
     1The tsunamigenic event used in this report was developed for a
     2preliminary tsunami hazard assessment study delivered by GA
     3to FESA in September 2005,
    34\cite{BC:FESA}. In that assessment, a suite of Mw 9 earthquakes
    45were evenly spaced along the Sunda Arc subduction zone and there
    56was no consideration of the likelihood of each event.
    6 Other sources were not considered, such
     7Other less likely sources were not considered, such
    78as intra-plate earthquakes near the WA coast, volcanoes, landslides
    8 or asteroids as they are known to be less likely.
    9 The preliminary assessment argued
    10 that the maximum magnitude of earthquakes off Java is at least 8.5 and
    11 could potentially be as high as 9.
     9or asteroids.
     10In the preliminary assessment,
     11the maximum magnitude of earthquakes off Java was considered to be
     12at least 8.5 and could potentially be as high as 9.
    1213
    13 FESA are interested in the ``most frequent worst case scenario''. Whilst
     14FESA is interested in the ``most frequent worst case scenario''. Whilst
    1415we currently cannot determine exactly what that event may be, the Mw 9 event
    1516provides a plausible worst case scenario. To understand the
    1617frequency of these tsunami-genic events,
    17 current studies underway in GA are building probabilistic
     18GA is building probabilistic
    1819models to develop a more complete tsunami hazard assessment
    1920for the Sunda Arc subduction zone,
    2021due for completion in late 2006. In the preliminary assessment for
    21 example, it was argued that while Mw 7 and 8 earthquakes are expected
     22example, it was suggested that while Mw 7 and 8 earthquakes are expected
    2223to occur with a greater frequency than Mw 9 events,
    2324they are likely to pose a comparatively low and more localised hazard to WA.
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