# Changeset 7451

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Timestamp:
Aug 30, 2009, 4:45:41 AM (13 years ago)
Message:

john: update tsunami validation paper

Location:
anuga_work/publications/boxing_day_validation_2008
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7 edited

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• ## anuga_work/publications/boxing_day_validation_2008/appendix.tex

 r7450 \end{figure} \begin{figure}[ht] \begin{center} %\includegraphics[width=6cm,keepaspectratio=true]{sensitivity_f0_0003_depth} %\includegraphics[width=6cm,keepaspectratio=true]{sensitivity_f0_03_depth} \includegraphics[width=\textwidth,keepaspectratio=true]{figures/sensitivity_friction} \caption{Model results for different values of Manning's friction coefficient shown to assess sensitivities. The reference inundation extent for a friction value of 0.01 is shown in Figure \protect \ref{fig:reference_model} (left).  The left and right images show the inundation results for friction values of 0.0003 and 0.03 respectively. The inundation extent increases for the lower friction value while the higher slows the flow and decreases the inundation extent. Ideally, friction should vary across the entire domain depending on terrain and vegetation, but this is beyond the scope of this study.} \label{fig:sensitivity_friction} \end{center} \end{figure} %\begin{figure}[ht] %\begin{center} %\includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_f0_0003_speed} %\includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_f0_03_speed} %\caption{The maximal flow speeds for the same model parameterisations %  found in Figure \protect \ref{fig:sensitivity_friction}. The %  reference flow speeds are shown in Figure \protect %  \ref{fig:reference_model} (right).} %\label{fig:sensitivity_friction_speed} %\end{center} %\end{figure} % John: I do not think we need to show sensitivity to flow speeds \begin{figure}[ht] \begin{center} \includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_minus10cm_speed} \includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_plus10cm_speed} \caption{The maximal flow speeds for the same model parameterisations found in Figure \protect \ref{fig:sensitivity_boundary}. The reference flow speeds are shown in Figure \protect \ref{fig:reference_model} (right).} \label{fig:sensitivity_boundary_speed} \end{center} \end{figure} %\begin{figure}[ht] %\begin{center} %\includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_minus10cm_speed} %\includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_plus10cm_speed} %\caption{The maximal flow speeds for the same model parameterisations %  found in Figure \protect \ref{fig:sensitivity_boundary}. The %  reference flow speeds are shown in Figure \protect %  \ref{fig:reference_model} (right).} %\label{fig:sensitivity_boundary_speed} %\end{center} %\end{figure} \begin{figure}[ht] \end{figure} \begin{figure}[ht] \begin{center} %\includegraphics[width=6cm,keepaspectratio=true]{sensitivity_f0_0003_depth} %\includegraphics[width=6cm,keepaspectratio=true]{sensitivity_f0_03_depth} \includegraphics[width=\textwidth,keepaspectratio=true]{figures/sensitivity_friction} \caption{Model results for different values of Manning's friction coefficient shown to assess sensitivities. The reference inundation extent for a friction value of 0.01 is shown in Figure \protect \ref{fig:reference_model} (left).  The left and right images show the inundation results for friction values of 0.0003 and 0.03 respectively. The inundation extent increases for the lower friction value while the higher slows the flow and decreases the inundation extent. Ideally, friction should vary across the entire domain depending on terrain and vegetation, but this is beyond the scope of this study.} \label{fig:sensitivity_friction} \end{center} \end{figure} \begin{figure}[ht] \begin{center} \includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_f0_0003_speed} \includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_f0_03_speed} \caption{The maximal flow speeds for the same model parameterisations found in Figure \protect \ref{fig:sensitivity_friction}. The reference flow speeds are shown in Figure \protect \ref{fig:reference_model} (right).} \label{fig:sensitivity_friction_speed} \end{center} \end{figure}
• ## anuga_work/publications/boxing_day_validation_2008/conclusion.tex

 r7450 utilises the uniquely large amount of observational data for model comparison obtained during, and immediately following, the Sumatra--Andaman tsunami of 26 December 2004. Unlike the small number of existing benchmarks, the proposed test validates all three stages of tsunami evolution - generation, propagation and inundation. In an attempt to provide higher visibility and easier Sumatra--Andaman tsunami of 26 December 2004. The proposed benchmark is intended to aid validation of tsunami inundation, which is the most important stage of tsunami evolution. However individual tests are presented to facilitate model evaluation for the generation and propagation phases as well. In an attempt to provide higher visibility and easier accessibility for tsunami benchmark problems, the data used to construct the proposed benchmark is documented and freely available at \url{http://tinyurl.com/patong2004-data}. This study also shows that the tsunami impact modelling methodology adopted is credible and able to predict inundation extents with reasonable accuracy.  An associated aim of this paper was to further validate the hydrodynamic modelling tool \textsc{anuga} which is used to simulate the tsunami inundation. Model predictions matched well the geodetic measurements of the Sumatra--Andaman earthquake, altimetry data from the \textsc{jason}, eye-witness accounts of wave front arrival times and flow speeds and a detailed inundation survey of Patong Bay, Thailand. An associated aim of this paper was to further validate the \textsc{ursga--anuga} tsunami modelling methodology employed by Geoscience Australiawhich is used to simulate the tsunami inundation. This study ashows that the tsunami  modelling methodology adopted is credible and able to predict detailed inundation extents with reasonable accuracy. Model predictions matched well a detailed inundation survey of Patong Bay, Thailand as well as altimetry data from the \textsc{jason}, eye-witness accounts of wave front arrival times and onshore flow speeds. A simple sensitivity analysis was performed to assess the influence of the presence of buildings and other structures on the model predictions. Of these three, the presence of buildings was shown to have the greatest influence on the simulated inundation extent. The value of friction and small have the greatest influence on the simulated inundation extent. This result indicates that the influence of human-made structures should be included, where possible in any future studies. The value of friction and small perturbations in the waveheight at the \textsc{anuga} boundary have comparatively little effect on the model results.
• ## anuga_work/publications/boxing_day_validation_2008/data.tex

 r7450 model validity. In fact for non-physics based models it may not be possible to validate the generation and propagation phases of tsunami evolution. For physics-based models evaluation of the model during the generation and propagation phases is still useful. If a model is physics-based one should ensure that all physics are being modelled accurately. Moreover evaluation of all three stages of tsunami evolution can help identify the cause of any discrepancies between modelled and observed inundation. Consequently in this section we present data not only to facilitate validation of inundation but to also aid in assessment of tsunami generation and propagation. However, for physics-based models evaluation of the model during the generation and propagation phases is still useful. If a model is physics-based one should ensure that all physics are being modelled accurately. Moreover evaluation of all three stages of tsunami evolution can help identify the cause of any discrepancies between modelled and observed inundation. Consequently in this section we present data not only to facilitate validation of inundation but to also aid the assessment of tsunami generation and propagation. \subsection{Generation}\label{sec:gen_data} high quality field measurements are also required. For the proposed benchmark a high resolution topography data set and a high quality inundation survey map from the (FIXME(John): what data set was used to generate the topogaphy? RICHARD ) survey map from the Coordinating Committee Co-ordinating Committee for Geoscience Programmes in East and Southeast Asia (CCOP) (\cite{szczucinski06}) was obtained \includegraphics[width=\textwidth,keepaspectratio=true]{figures/gauges.jpg} \caption{Location of timeseries extracted from the model output. FIXME(John): should we combine inundation map with gauages map?} should we combine the inundation map with the gauages map?} \label{fig:gauge_locations} \end{center} the eye-witness videos, that fall within the bounds obtained from the videos. \item reproduce the \textsc{jason} satellite altimetry sea surface anomalies (see Section~\ref{sec:data_jason}), \item reproduce the vertical deformation observed in north-western Sumatra and along the Nicobar--Andaman islands (see Section~\ref{sec:gen_data}), \item reproduce the \textsc{jason} satellite altimetry sea surface anomalies (see Section~\ref{sec:data_jason}), \end{itemize}
• ## anuga_work/publications/boxing_day_validation_2008/introduction.tex

 r7450 localised and highly detailed spatially distributed assessment of modelled inundation. To the authors knowledge it is also the first benchmark to assess model inundation under influenced by numerous human structures. Eye-witness videos also allow the qualitative assessment of onshore flow patterns. assess model inundation under influenced by numerous human structures. Eye-witness videos also allow the qualitative assessment of onshore flow patterns. An associated aim of this paper is to illustrate the use of this new benchmark to validate a dedicated inundation model called \textsc{anuga} used by Geoscience Australia. A description of \textsc{anuga} is given in Section~\ref{sec:models} and the validation benchmark to validate the three step modelling methodology employed by Geoscience Australia to model tsunami inundation. A description of the model components is provided in Section~\ref{sec:models} and the validation results are given in Section~\ref{sec:results}. However, model uncertainty should not be ignored. Section ~\ref{sec:sensitivity} provides a simple analysis that can be used to investigate the sensitivity of model predictions to model parameters. be used to investigate the sensitivity of model predictions to a number of model parameters.
• ## anuga_work/publications/boxing_day_validation_2008/paper.tex

 r7450 propagation and a detailed inundation survey of Patong city, Thailand to compare model and observed inundation. Furthermore we utilise this benchmark to further validate the hydrodynamic modelling tool \textsc{ursga--anuga} which is used to simulate the tsunami benchmark to further validate the \textsc{ursga--anuga} modelling methodology used by Geoscience Australia to simulate the tsunami inundation. Important buildings and other structures were incorporated into the underlying computational mesh and shown to have a large
• ## anuga_work/publications/boxing_day_validation_2008/results.tex

 r7450 This section presents a validation of the modelling practice of Geoscience Australia against the new proposed benchmarks. The criteria outlined in Section~\ref{sec:checkList} are addressed for each of the three stages of tsunami evolution. in Section~\ref{sec:checkList} are addressed.S \subsection{Generation}\label{modelGeneration} not surprising, since the original slip model was chosen by~\cite{chlieh07} to fit the motion and seismic data well. Consequently the replication of the generation data has little meaning for the model structure presented in Section~\ref{sec:models}. But for uncalibrated source models or source models calibrated on other data this test of generation would be more meaningful. % %This does demonstrate, however, that \textsc{edgrn} and our modified version of \end{center} \end{figure} FIXME (Jane): This graph does not look nice. The legend URS Model should be URSGA model. \subsection{Inundation} FIXME (Jane): This graph does not look nice. After propagating the tsunami in the open ocean using \textsc{ursga}, the approximated ocean and surface elevation and horisontal flow region in Patong Bay. The coarse resolution was chosen to be commensurate with the model output from the \textsc{ursga} model (FIXME - this has to be clearly stated in ursga section) RICHARD while the latter was chosen to match the available resolution of topographic data and building data in Patong city. reasonable. Maximum onshore inundation depth was computed from the model \subsection{Inundation} The \textsc{anuga} simulation described in the previous section and used to model shallow water propgation also predicts inundation. Maximum onshore inundation depth was computed from the model throughout the entire Patong Bay region and used to generate a measure of the inundated area. \rho_{in}=\frac{A(I_m\cap I_o)}{A(I_o)} representing the ratio $\rho_{in}$ of the observed inundation region $I_o$ captured by the model $I_m$. Another useful representing the ratio of the area of the observed inundation region $I_o$ and the area of the observed inundation region captured by the model $I_m$. Another useful measure is the fraction of the modelled inundation area that falls outside the observed inundation area given by the formula missing data in the field survey data itself. The impact of some of these sources of uncertainties are is investigated in Section~\ref{sec:sensitivity} Section~\ref{sec:sensitivity}. \subsection{Eye-witness accounts} \begin{figure}[ht] \begin{center} \includegraphics[width=\textwidth,keepaspectratio=true]{gauges_hotels_depths.jpg} \includegraphics[width=\textwidth,keepaspectratio=true]{gauges_hotels_speed.jpg} \includegraphics[width=\textwidth,keepaspectratio=true]{figures/gauges_hotels_depths.jpg} \includegraphics[width=\textwidth,keepaspectratio=true]{figures/gauges_hotels_speed.jpg} \caption{Time series obtained from the two onshore locations, North and South, shown in Figure \protect \ref{fig:gauge_locations}.}
• ## anuga_work/publications/boxing_day_validation_2008/sensitivity.tex

 r7450 \section{Sensitivity Analysis} \label{sec:sensitivity} The numerical models used to simulate tsunami impact are computationally intensive and high resolution models of the entire evolution process will often take a number of days to run. Consequently, the uncertainty in model predictions is difficult to quantify as it would require a very large number of runs. However, model uncertainty should not be ignored. The aim of this section is not to provide a detailed investigation of sensitivity but to rather illustrate that changes in important parameters of the \textsc{usrga--anuga} model  produce behaviour consistent with the known physics and that small changes in these parameters produce bounded variations in the output. This section investigates the effect of different values of Manning's friction coefficient, changing waveheight at the 100 m depth contour, and the presence and absence of buildings in the elevation dataset on model maximum inundation. The reference model is the one reported in Figure~\ref{fig:inundationcomparison1cm} (right) with a friction coefficient of 0.01, buildings included and the boundary condition produced by the model maximum inundation. The reference model is the one reported in Figure~\ref{fig:inundationcomparison1cm} (right) with a friction coefficient of 0.01, buildings included and the boundary condition produced by the \textsc{ursga} model. we simulated the maximum onshore inundation using a Manning's coefficient of 0.0003 and 0.03. The resulting inundation maps are shown in Figure~\ref{fig:sensitivity_friction} and the maximum flow speeds in Figure~\ref{fig:sensitivity_friction_speed}. These figures show that the on-shore inundation extent decreases with increasing shown in Figure~\ref{fig:sensitivity_friction} % and the maximum flow speeds in Figure~\ref{fig:sensitivity_friction_speed}. The figure, along with Table~\ref{table:inundationAreas}, shows that the on-shore inundation extent decreases with increasing friction and that small perturbations in the friction cause bounded changes in the output. This is consistent with the conclusions of The effect of the wave height used as input to the inundation model \textsc{anuga} was also investigated. Figure~\ref{fig:sensitivity_boundary} indicates that the inundation Figure~\ref{fig:sensitivity_boundary} and  Table~\ref{table:inundationAreas} indicate that the inundation severity is directly proportional to the boundary waveheight but small perturbations in the input wave height of 10 cm appear to have little The presence or absence of physical buildings in the elevation model was also investigated. Figure~\ref{fig:sensitivity_nobuildings} shows the inundated area and the associated maximum flow speeds in the presence and absence of buildings. It is apparent that densely built-up areas act as dissipators greatly reducing the inundated area. However, flow speeds tend to increase in passages between buildings. Figure~\ref{fig:sensitivity_nobuildings} shows the inundated area %and the associated maximum flow speeds in the presence and absence of buildings. From Table~\ref{table:inundationAreas} it is apparent that densely built-up areas act as dissipators greatly reducing the inundated area. This result suggest that, when possible the presence of human-made structures should be included into the model topography. Furthermore this result also indicates that simply matching point sites with much lower resolution meshes than used here is an over simplification. Such simulations cannot capture the fine detail that so clearly affects inundation. %However, flow speeds tend to increase in passages between buildings.
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