source: anuga_work/production/dampier_2006/report/modelling_methodology.tex @ 3988

The Risk Research Group 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.
Initial hazard assessments have been based on reporting the 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. Subsequent hazard assessments are been developed in a 
probabilistic manner which are being derived from the URS Corporation's
Probabilistic Tsunami Hazard Analysis model \cite{somerville:urs}. 
%The maximal wave height at a fixed contour line near the coastline
%(e.g. 50m) is then reported as the hazard to communities ashore. 
%Models such as Method of Splitting Tsunamis (MOST) \cite{VT:MOST} and the 
%URS Corporation's
%Probabilistic Tsunami Hazard Analysis  
%\cite{somerville:urs} follow this paradigm.

While MOST and URS are suitable for generating and propagating the tsunami wave from its source, it is 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 covers 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 the URS model and modelling the impact with ANUGA. 
In this way, the output from URS serves as an input to ANUGA. 
In modelling terms, the URS output is a boundary condition for ANUGA.

The event chosen for this study has been determined from the probabilistic
hazard modelling being undertaken by the Earthquake and Hazards Project.
The low probability, high potential impact Mw 9.0 event has been chosen
for this study.

%\begin{figure}[h]

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

%  \caption{Maximum wave height (in cms) for a Mw 9.0 event off the 
%coast of Java}
%  \label{fig:mw9}
%\end{figure}