source: production/pt_hedland_2006/report/modelling_methodology.tex @ 3373

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1GA bases its risk modelling on the process of understanding the hazard and a community's
2vulnerability in order to determine the impact of a particular hazard event.
3The resultant risk relies on an assessment of the likelihood of the event.
4An overall risk assessment for a particular hazard would then rely on scaling
5each event's impact by its likelihood.
6
7To develop a tsunami risk assessment,
8the tsunami hazard itself must first be understood. These events are generally modelled by converting
9the energy released by a subduction earthquake into a vertical displacement of the ocean surface.
10%Tsunami hazard models have been available for some time.
11The resulting wave is
12then propagated across a sometimes vast stretch of ocean towards the
13area of interest.
14%using a relatively coarse model
15%based on bathymetries with a typical resolution of two arc minutes.
16The hazard itself is then reported as a maximum wave height at a fixed contour line near the coastline,
17(e.g. 50m). This is how the preliminary tsunami hazard assessment was reported by GA
18to FESA in September 2005 \cite{BC:FESA}. That assessment used the Method of Splitting Tsunamis (MOST)
19\cite{VT:MOST} model.
20%The maximal wave height at a fixed contour line near the coastline
21%(e.g. 50m) is then reported as the hazard to communities ashore.
22%Models such as Method of Splitting Tsunamis (MOST) \cite{VT:MOST} and the
23%URS Corporation's
24%Probabilistic Tsunami Hazard Analysis 
25%\cite{somerville:urs} follow this paradigm.
26
27MOST, which generates and propagates the tsunami wave from its source, is not adequate to
28model the wave's impact to communities ashore. 
29To capture the \emph{impact} of a tsunami to a coastal community,
30the model must be capable of capturing more detail about the wave,
31particularly how it is affected by the local bathymetry, as well as the
32local topography as the wave penetrates onshore.
33%the details of how waves are reflected and otherwise
34%shaped by the local bathymetries as well as the dynamics of the
35%runup process onto the topography in question.
36It is well known that local bathymetric and topographic effects are
37critical in determining the severity of a hydrological disaster
38\cite{matsuyama:1999}. To model the impact of the tsunami wave on the
39coastal community, we use ANUGA \cite{ON:modsim}. In order to capture the
40details of the wave and its interactions, a much finer resolution is
41required than that of the hazard model. As a result, ANUGA concentrates
42on a specific coastal community. MOST by contrast can tolerate a
43coarser resolution and covers often vast areas. To develop the impact
44from an earthquake event a distant source, we adopt the hybrid approach of
45modelling the event itself with MOST and modelling the impact with ANUGA.
46In this way, the output from MOST serves as an input to ANUGA.
47In modelling terms, the MOST output is a boundary condition for ANUGA.
48 
49The risk of this tsunami event cannot be determined until the
50likelihood of the event is known. GA is currently building a
51complete probabilistic hazard map which is due for completion
52later this year. Therefore, we report on the impact of a single
53tsunami event only. As the hazard map is completed, the impact
54will be assessed for a range of events which will ultimately
55determine a tsunami risk assessment for the NW shelf.
56%To model the
57%details of tsunami inundation of a community one must therefore capture %what is
58%known as non-linear effects and use a much higher resolution for the
59%elevation data.
60%Linear models typically use data resolutions of the order
61%of hundreds of metres, which is sufficient to model the tsunami waves
62%in deeper water where the wavelength is longer.
63%Non-linear models however require much finer resolution in order to %capture
64%the complexity associated with the water flow from offshore
65%to onshore. By contrast, the data
66%resolution required is typically of the order of tens of metres.
67%The model ANUGA \cite{ON:modsim} is suitable for this type of non-linear
68%modelling.
69%Using a non-linear model capable of resolving local bathymetric effects
70%and runup using detailed elevation data will require more computational
71%resources than the typical hazard model making it infeasible to use it
72%for the entire, end-to-end, modelling.
73
74%We have adopted a hybrid approach whereby the output from the 
75%hazard model MOST is used as input to ANUGA at the seaward boundary of its %study area.
76%In other words, the output of MOST serves as boundary condition for the
77%ANUGA model. In this way, we restrict the computationally intensive part %only to
78%regions where we are interested in the detailed inundation process. 
79
80%Furthermore, to avoid unnecessary computations ANUGA works with an
81%unstructured triangular mesh rather than the rectangular grids
82%used by e.g.\ MOST. The advantage of an unstructured mesh
83%is that different regions can have different resolutions allowing
84%computational resources to be directed where they are most needed.
85%For example, one might use very high resolution near a community
86%or in an estuary, whereas a coarser resolution may be sufficient
87%in deeper water where the bathymetric effects are less pronounced.
88%Figure \ref{fig:refinedmesh} shows a mesh of variable resolution.
89
90%\begin{figure}[hbt]
91%
92%  \centerline{ \includegraphics[width=100mm, height=75mm]
93%             {../report_figures/refined_mesh.jpg}}
94%
95%  \caption{Unstructured mesh with variable resolution.}
96%  \label{fig:refinedmesh}
97%\end{figure}
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