[3240] | 1 | Tsunami hazard models have been available for some time. They generally |
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| 2 | work by converting the energy released by a subduction earthquake into |
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| 3 | a vertical displacement of the ocean surface. The resulting wave is |
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| 4 | then propagated across a sometimes vast stretch of ocean using a |
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| 5 | relatively coarse model based on bathymetries with a typical |
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| 6 | resolution of two arc minutes (check this with David). |
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| 7 | The maximal wave height at a fixed contour line near the coastline |
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| 8 | (e.g.\ 50m) is then reported as the hazard to communities ashore. |
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| 9 | Models such as Method of Splitting Tsunamis (MOST) \cite{VT:MOST} and the |
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| 10 | URS Corporation's |
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| 11 | Probabilistic Tsunami Hazard Analysis |
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| 12 | \cite{somerville:urs} follow this paradigm. |
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| 13 | |
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| 14 | To capture the \emph{impact} of a hydrological disaster such as tsunamis on a |
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| 15 | community one must model the details of how waves are reflected and otherwise |
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| 16 | shaped by the local bathymetries as well as the dynamics of the |
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| 17 | runup process onto the topography in question. |
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| 18 | It is well known that local bathymetric and topographic effects are |
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| 19 | critical in determining the severity of a hydrological disaster |
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| 20 | \cite{matsuyama:1999}. To model the |
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| 21 | details of tsunami inundation of a community one must therefore capture what is |
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| 22 | known as non-linear effects and use a much higher resolution for the |
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| 23 | elevation data. |
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| 24 | Linear models typically use data resolutions of the order |
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| 25 | of hundreds of metres, which is sufficient to model the tsunami waves |
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| 26 | in deeper water where the wavelength is longer. |
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| 27 | Non-linear models however require much finer resolution in order to capture |
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| 28 | the complexity associated with the water flow from off to onshore. By contrast, the data |
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| 29 | resolution required is typically of the order of tens of metres. |
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| 30 | The model ANUGA \cite{ON:modsim} is suitable for this type of non-linear |
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| 31 | modelling. |
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| 32 | Using a non-linear model capable of resolving local bathymetric effects |
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| 33 | and runup using detailed elevation data will require much more computational |
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| 34 | resources than the typical hazard model making it infeasible to use it |
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| 35 | for the entire, end-to-end, modelling. |
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| 36 | |
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| 37 | We have adopted a hybrid approach whereby we use the output from the |
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| 38 | hazard model MOST as input to ANUGA at the seaward boundary of its study area. |
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| 39 | In other words, the output of MOST serves as boundary condition for the |
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| 40 | ANUGA model. In this way, we restrict the computationally intensive part only to |
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| 41 | regions where we are interested in the detailed inundation process. |
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| 42 | |
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| 43 | Furthermore, to avoid unnecessary computations ANUGA works with an |
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| 44 | unstructured triangular mesh rather than the rectangular grids |
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| 45 | used by e.g.\ MOST. The advantage of an unstructured mesh |
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| 46 | is that different regions can have different resolutions allowing |
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| 47 | computational resources to be directed where they are most needed. |
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| 48 | For example, one might use very high resolution near a community |
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| 49 | or in an estuary, whereas a coarser resolution may be sufficient |
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| 50 | in deeper water where the bathymetric effects are less pronounced. |
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| 51 | Figure \ref{fig:refinedmesh} shows a mesh of variable resolution. |
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| 52 | |
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| 53 | \begin{figure}[hbt] |
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| 54 | |
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| 55 | \centerline{ \includegraphics[width=100mm, height=75mm] |
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| 56 | {../report_figures/refined_mesh.jpg}} |
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| 57 | |
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| 58 | \caption{Unstructured mesh with variable resolution.} |
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| 59 | \label{fig:refinedmesh} |
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| 60 | \end{figure} |
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| 61 | |
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| 62 | |
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| 63 | |
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| 64 | |
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| 65 | |
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