source: anuga_work/production/onslow_2006/report/modelling_methodology.tex @ 4147

Geoscience Australia aims to define the economic and social threat posed to urban communities 
by a range of rapid onset natural hazards. Through the integration of natural hazard research, defining national exposure and 
estimating socio-economic vulnerabilities, predictions of the likely impacts of events can be made. 
By modelling the likely impacts on urban communities as accurately as possible and
building these estimates into land use planning and emergency
management, communities will be better prepared to respond to
natural disasters when they occur.


%GA bases its risk modelling on the process of understanding the hazard and a community's 
%vulnerability in order to determine the impact of a particular hazard event. 
%The resultant risk relies on an assessment of the likelihood of the event. 
%An overall risk assessment for a particular hazard would then rely on scaling 
%each event's impact by its likelihood.

To develop a tsunami risk assessment, 
the tsunami hazard itself must first be understood. These events are generally modelled by converting
the energy released by a subduction earthquake into a vertical displacement of the ocean surface. 
%Tsunami hazard models have been available for some time. 
The resulting wave is
then propagated across a sometimes vast stretch of ocean towards the
area of interest. 
%using a relatively coarse model 
%based on bathymetries with a typical resolution of two arc minutes.
The hazard itself is then reported as a maximum wave height at a fixed contour line near the coastline, 
(e.g. 50m). This is how the preliminary tsunami hazard assessment was reported by GA 
to FESA in September 2005 \cite{BC:FESA} for a suite of Mw 9 earthquakes
evenly spaced along the Sunda Arc subduction zone. 
The assessment used the Method of Splitting Tsunamis (MOST)
\cite{VT:MOST} model. This preliminary hazard map had no probability attached to the event which is
required to conduct a tsunami risk assessment. Using
the Probabilistic Tsunami Hazard Analysis \cite{somerville:urs} paradigm
used by the URS corporation, a detailed probabilistic hazard map has now been completed
for the WA coastline \cite{prob:fesa}. 

While MOST and URS are suitable for generating and propagating the tsunami wave from its source, 
they are not adequate to
model the wave's impact on communities ashore.  
To capture the \emph{impact} of a tsunami to a coastal community, 
the model must be capable of capturing more detail about the wave, 
particularly how it is affected by the local bathymetry, as well as the 
local topography as the wave moves onshore. 
%the details of how waves are reflected and otherwise 
%shaped by the local bathymetries as well as the dynamics of the 
%runup process onto the topography in question.
It is well known that local bathymetric and topographic effects are 
critical in determining the severity of a hydrological disaster 
\cite{matsuyama:1999}. To model the impact of the tsunami wave on the 
coastal community, we use ANUGA \cite{ON:modsim}. In order to capture the 
details of the wave and its interactions, a much finer resolution is 
required than that of the hazard model. As a result, ANUGA simulations concentrate 
on specific coastal communities. MOST and URS by contrast use a 
coarser resolution and cover often vast areas. To develop the impact 
from an earthquake event from a distant source, we adopt a hybrid approach of 
modelling the event itself with MOST or URS and modelling the impact with ANUGA. 
In this way, the output from MOST or URS serve as an input to ANUGA. 
In modelling terms, the MOST or URS output is a boundary condition for ANUGA.
Further details
regarding the inundation modelling requirements for this study can be found in 
Appendix \ref{sec:anugasetup}.

The risk of a given tsunami scenario can only be determined when the likelihood
of the event is known. The probabilistic hazard map for WA \cite{prob:fesa}
calculates which events pose the most threat to an identified region. Figure
\ref{fig:probonslow} describes the probability of each event generated along the Java trench
impacting Onslow. For example, an event generated at point A end would have a
smaller chance of impacting Onslow than an event generated at point B.

\begin{figure}[h]

%\centerline{ \includegraphics[width=140mm, height=100mm]{../report_figures/}}

  \caption{}
  \label{fig:probonslow}
\end{figure}

To prepare a tsunami risk assessment, a number of events will be chosen
for a range of probabilities (or return periods). As Figure \ref{fig:probonslow}
shows, for a given probability, a number of events are possible. The resulting
impact to Onslow would then vary depending on the source of the event.  The
tsunami scenarios selected for the tsunami risk assessment 
are discussed in Section \ref{sec:tsunamiscenario}.

% used for the 2005 report when looking at one event
%\bigskip %FIXME (Ole): Should this be a subsection even? 
%The risk of a given tsunami scenario cannot be determined until the 
%likelihood of the tsunami is known. GA is currently building a 
%complete probabilistic hazard map which is due for completion 
%in late 2006. We therefore report on the impact of a single 
%tsunami event only. When the hazard map is completed, the impact 
%will be assessed for a range of events which will ultimately 
%determine a tsunami risk assessment for the NW shelf.

%FESA is interested in the ``most frequent worst case scenario''. Whilst
%we currently cannot determine exactly what that event may be, the
%preliminary hazard assessment suggested that the maximum
%magnitude of earthquakes off Java was considered to be at 
%least 8.5 and could potentially be as high as 9. Therefore, 
%the Mw 9 event 
%provides a plausible worst case scenario and is used as the tsunami
%source in this report.
%Figure \ref{fig:mw9} shows the maximum wave height of a tsunami initiated 
%by a Mw 9 event off
%the coast of Java. This event provides the source and
%boundary condition to the
%inundation model presented in Section \ref{sec:anuga}. 

%\begin{figure}[h]

%  \centerline{ \includegraphics[width=140mm, height=100mm]
%{../report_figures/mw9.jpg}}

%  \caption{Maximum wave height (in cms) for a Mw 9 event off the 
%coast of Java}
%  \label{fig:mw9}
%\end{figure}