source: production/onslow_2006/report/modelling_methodology.tex @ 3390

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. 
Hazards include earthquakes, landslides, tsunami, severe winds and cyclones.

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}. The assessment used the Method of Splitting Tsunamis (MOST)
\cite{VT:MOST} model. 
%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 is 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 by contrast uses 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 MOST and modelling the impact with ANUGA. 
In this way, the output from MOST serves as an input to ANUGA. 
In modelling terms, the MOST output is a boundary condition for ANUGA.

\bigskip %FIXME (Ole): Should this be a subsection even? 
The risk of the scenario tsunami event cannot be determined until the 
likelihood of the event 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.
%To model the
%details of tsunami inundation of a community one must therefore capture %what is 
%known as non-linear effects and use a much higher resolution for the 
%elevation data. 
%Linear models typically use data resolutions of the order
%of hundreds of metres, which is sufficient to model the tsunami waves
%in deeper water where the wavelength is longer. 
%Non-linear models however require much finer resolution in order to %capture
%the complexity associated with the water flow from offshore 
%to onshore. By contrast, the data
%resolution required is typically of the order of tens of metres.
%The model ANUGA \cite{ON:modsim} is suitable for this type of non-linear
%modelling.
%Using a non-linear model capable of resolving local bathymetric effects 
%and runup using detailed elevation data will require more computational 
%resources than the typical hazard model making it infeasible to use it 
%for the entire, end-to-end, modelling. 

%We have adopted a hybrid approach whereby the output from the  
%hazard model MOST is used as input to ANUGA at the seaward boundary of its %study area. 
%In other words, the output of MOST serves as boundary condition for the 
%ANUGA model. In this way, we restrict the computationally intensive part %only to 
%regions where we are interested in the detailed inundation process.  

%Furthermore, to avoid unnecessary computations ANUGA works with an 
%unstructured triangular mesh rather than the rectangular grids 
%used by e.g.\ MOST. The advantage of an unstructured mesh 
%is that different regions can have different resolutions allowing 
%computational resources to be directed where they are most needed. 
%For example, one might use very high resolution near a community 
%or in an estuary, whereas a coarser resolution may be sufficient 
%in deeper water where the bathymetric effects are less pronounced. 
%Figure \ref{fig:refinedmesh} shows a mesh of variable resolution.

%\begin{figure}[hbt]
%
%  \centerline{ \includegraphics[width=100mm, height=75mm]
%             {../report_figures/refined_mesh.jpg}}
%
%  \caption{Unstructured mesh with variable resolution.}
%  \label{fig:refinedmesh}
%\end{figure}