Changeset 7451
- Timestamp:
- Aug 30, 2009, 4:45:41 AM (14 years ago)
- Location:
- anuga_work/publications/boxing_day_validation_2008
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anuga_work/publications/boxing_day_validation_2008/appendix.tex
r7450 r7451 21 21 \end{figure} 22 22 23 \begin{figure}[ht] 24 \begin{center} 25 %\includegraphics[width=6cm,keepaspectratio=true]{sensitivity_f0_0003_depth} 26 %\includegraphics[width=6cm,keepaspectratio=true]{sensitivity_f0_03_depth} 27 \includegraphics[width=\textwidth,keepaspectratio=true]{figures/sensitivity_friction} 28 \caption{Model results for different values of Manning's friction 29 coefficient shown to assess sensitivities. 30 The reference inundation extent for a 31 friction value of 0.01 is shown in Figure 32 \protect \ref{fig:reference_model} (left). The left and right images 33 show the inundation results for friction values of 0.0003 and 34 0.03 respectively. The inundation extent increases for the lower 35 friction value while the higher slows the flow and decreases the 36 inundation extent. Ideally, friction should vary across the entire 37 domain depending on terrain and vegetation, but this is beyond the 38 scope of this study.} 39 \label{fig:sensitivity_friction} 40 \end{center} 41 \end{figure} 42 43 %\begin{figure}[ht] 44 %\begin{center} 45 %\includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_f0_0003_speed} 46 %\includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_f0_03_speed} 47 %\caption{The maximal flow speeds for the same model parameterisations 48 % found in Figure \protect \ref{fig:sensitivity_friction}. The 49 % reference flow speeds are shown in Figure \protect 50 % \ref{fig:reference_model} (right).} 51 %\label{fig:sensitivity_friction_speed} 52 %\end{center} 53 %\end{figure} 54 % John: I do not think we need to show sensitivity to flow speeds 23 55 24 56 … … 43 75 44 76 45 \begin{figure}[ht]46 \begin{center}47 \includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_minus10cm_speed}48 \includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_plus10cm_speed}49 \caption{The maximal flow speeds for the same model parameterisations50 found in Figure \protect \ref{fig:sensitivity_boundary}. The51 reference flow speeds are shown in Figure \protect52 \ref{fig:reference_model} (right).}53 \label{fig:sensitivity_boundary_speed}54 \end{center}55 \end{figure}77 %\begin{figure}[ht] 78 %\begin{center} 79 %\includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_minus10cm_speed} 80 %\includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_plus10cm_speed} 81 %\caption{The maximal flow speeds for the same model parameterisations 82 % found in Figure \protect \ref{fig:sensitivity_boundary}. The 83 % reference flow speeds are shown in Figure \protect 84 % \ref{fig:reference_model} (right).} 85 %\label{fig:sensitivity_boundary_speed} 86 %\end{center} 87 %\end{figure} 56 88 57 89 \begin{figure}[ht] … … 78 110 \end{figure} 79 111 80 81 \begin{figure}[ht]82 \begin{center}83 %\includegraphics[width=6cm,keepaspectratio=true]{sensitivity_f0_0003_depth}84 %\includegraphics[width=6cm,keepaspectratio=true]{sensitivity_f0_03_depth}85 \includegraphics[width=\textwidth,keepaspectratio=true]{figures/sensitivity_friction}86 \caption{Model results for different values of Manning's friction87 coefficient shown to assess sensitivities.88 The reference inundation extent for a89 friction value of 0.01 is shown in Figure90 \protect \ref{fig:reference_model} (left). The left and right images91 show the inundation results for friction values of 0.0003 and92 0.03 respectively. The inundation extent increases for the lower93 friction value while the higher slows the flow and decreases the94 inundation extent. Ideally, friction should vary across the entire95 domain depending on terrain and vegetation, but this is beyond the96 scope of this study.}97 \label{fig:sensitivity_friction}98 \end{center}99 \end{figure}100 101 \begin{figure}[ht]102 \begin{center}103 \includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_f0_0003_speed}104 \includegraphics[width=6cm,keepaspectratio=true]{figures/sensitivity_f0_03_speed}105 \caption{The maximal flow speeds for the same model parameterisations106 found in Figure \protect \ref{fig:sensitivity_friction}. The107 reference flow speeds are shown in Figure \protect108 \ref{fig:reference_model} (right).}109 \label{fig:sensitivity_friction_speed}110 \end{center}111 \end{figure} -
anuga_work/publications/boxing_day_validation_2008/conclusion.tex
r7450 r7451 6 6 utilises the uniquely large amount of observational data for model 7 7 comparison obtained during, and immediately following, the 8 Sumatra--Andaman tsunami of 26 December 2004. Unlike the small9 number of existing benchmarks, the proposed test validates all three 10 stages of tsunami evolution - generation, propagation and 11 inundation. In an attempt to provide higher visibility and easier8 Sumatra--Andaman tsunami of 26 December 2004. The proposed benchmark is intended to aid validation of tsunami inundation, which is the most important stage 9 of tsunami evolution. However individual tests are presented to 10 facilitate model evaluation for the generation and propagation 11 phases as well. In an attempt to provide higher visibility and easier 12 12 accessibility for tsunami benchmark problems, the data used to 13 13 construct the proposed benchmark is documented and freely available at 14 14 \url{http://tinyurl.com/patong2004-data}. 15 15 16 This study also shows that the tsunami impact modelling methodology 17 adopted is credible and able to predict inundation extents with reasonable 18 accuracy. An associated aim of this paper was to further validate the 19 hydrodynamic modelling tool \textsc{anuga} which is used to simulate 20 the tsunami inundation. Model predictions 21 matched well the geodetic measurements of the Sumatra--Andaman earthquake, 22 altimetry data from the \textsc{jason}, eye-witness accounts of wave 23 front arrival times and flow speeds and a detailed inundation survey 24 of Patong Bay, Thailand. 16 An associated aim of this paper was to further validate the 17 \textsc{ursga--anuga} tsunami modelling methodology employed by Geoscience 18 Australiawhich is used to simulate the tsunami inundation. 19 This study ashows that the tsunami modelling methodology adopted is credible 20 and able to predict detailed inundation extents with reasonable accuracy. 21 Model predictions matched well a detailed inundation survey 22 of Patong Bay, Thailand as well as altimetry data from the \textsc{jason}, 23 eye-witness accounts of wave front arrival times and onshore flow speeds. 25 24 26 25 A simple sensitivity analysis was performed to assess the influence of … … 28 27 the presence of buildings and other structures on the model 29 28 predictions. Of these three, the presence of buildings was shown to 30 have the greatest influence on 31 the simulated inundation extent. The value of friction and small 29 have the greatest influence on the simulated inundation extent. This result 30 indicates that the influence of human-made structures should be included, 31 where possible in any future studies. The value of friction and small 32 32 perturbations in the waveheight at the \textsc{anuga} boundary have 33 33 comparatively little effect on the model results. -
anuga_work/publications/boxing_day_validation_2008/data.tex
r7450 r7451 16 16 model validity. In fact for non-physics based models it may not be possible 17 17 to validate the generation and propagation phases of tsunami evolution. 18 For physics-based models evaluation of the model during the generation and 19 propagation phases is still useful. If a model is physics-based one should 20 ensure that all physics are being modelled accurately. Moreover evaluation 21 of all three stages of tsunami evolution can help identify the cause of any 22 discrepancies between modelled and observed inundation. Consequently in this 23 section we present data not only to facilitate validation of inundation but 24 to also aid in assessment of tsunami generation and propagation. 18 However, for physics-based models evaluation of the model during the generation 19 and propagation phases is still useful. If a model is physics-based one 20 should ensure that all physics are being modelled accurately. Moreover 21 evaluation of all three stages of tsunami evolution can help identify the 22 cause of any discrepancies between modelled and observed inundation. 23 Consequently in this section we present data not only to facilitate 24 validation of inundation but to also aid the assessment of tsunami 25 generation and propagation. 25 26 26 27 \subsection{Generation}\label{sec:gen_data} … … 153 154 high quality field measurements are also required. For the proposed 154 155 benchmark a high resolution topography data set and a high quality inundation 155 survey map from the (FIXME(John): what data set was used to generate the topogaphy? RICHARD )156 survey map from the 156 157 Coordinating Committee Co-ordinating Committee for Geoscience Programmes 157 158 in East and Southeast Asia (CCOP) (\cite{szczucinski06}) was obtained … … 231 232 \includegraphics[width=\textwidth,keepaspectratio=true]{figures/gauges.jpg} 232 233 \caption{Location of timeseries extracted from the model output. FIXME(John): 233 should we combine inundation map withgauages map?}234 should we combine the inundation map with the gauages map?} 234 235 \label{fig:gauge_locations} 235 236 \end{center} … … 296 297 the eye-witness videos, that fall within the bounds obtained from 297 298 the videos. 299 \item reproduce the \textsc{jason} satellite altimetry sea surface 300 anomalies (see Section~\ref{sec:data_jason}), 298 301 \item reproduce the vertical deformation observed in north-western 299 302 Sumatra and along the Nicobar--Andaman islands (see 300 303 Section~\ref{sec:gen_data}), 301 \item reproduce the \textsc{jason} satellite altimetry sea surface302 anomalies (see Section~\ref{sec:data_jason}),303 304 \end{itemize} 304 305 -
anuga_work/publications/boxing_day_validation_2008/introduction.tex
r7450 r7451 117 117 localised and highly detailed spatially distributed assessment of 118 118 modelled inundation. To the authors knowledge it is also the first benchmark to 119 assess model inundation under influenced by numerous human structures. Eye-witness videos also allow the qualitative assessment of onshore flow patterns. 119 assess model inundation under influenced by numerous human structures. 120 Eye-witness videos also allow the qualitative assessment of onshore flow 121 patterns. 120 122 121 123 An associated aim of this paper is to illustrate the use of this new 122 benchmark to validate a dedicated inundation model called123 \textsc{anuga} used by Geoscience Australia. A description of 124 \textsc{anuga} is givenin Section~\ref{sec:models} and the validation124 benchmark to validate the three step modelling methodology employed by 125 Geoscience Australia to model tsunami inundation. A description of the model 126 components is provided in Section~\ref{sec:models} and the validation 125 127 results are given in Section~\ref{sec:results}. 126 128 … … 132 134 However, model uncertainty should not be ignored. Section 133 135 ~\ref{sec:sensitivity} provides a simple analysis that can 134 be used to investigate the sensitivity of model predictions to model135 parameters.136 be used to investigate the sensitivity of model predictions to a number 137 of model parameters. -
anuga_work/publications/boxing_day_validation_2008/paper.tex
r7450 r7451 53 53 propagation and a detailed inundation survey of Patong city, Thailand 54 54 to compare model and observed inundation. Furthermore we utilise this 55 benchmark to further validate the hydrodynamic modelling tool56 \textsc{ursga--anuga} which is usedto simulate the tsunami55 benchmark to further validate the \textsc{ursga--anuga} modelling methodology 56 used by Geoscience Australia to simulate the tsunami 57 57 inundation. Important buildings and other structures were incorporated 58 58 into the underlying computational mesh and shown to have a large -
anuga_work/publications/boxing_day_validation_2008/results.tex
r7450 r7451 2 2 This section presents a validation of the modelling practice of Geoscience 3 3 Australia against the new proposed benchmarks. The criteria outlined 4 in Section~\ref{sec:checkList} are addressed for each of the three stages 5 of tsunami evolution. 4 in Section~\ref{sec:checkList} are addressed.S 6 5 7 6 \subsection{Generation}\label{modelGeneration} … … 41 40 not surprising, since the original slip model was chosen 42 41 by~\cite{chlieh07} to fit the motion and seismic data well. 43 42 Consequently the replication of the generation data has little meaning for 43 the model structure presented in Section~\ref{sec:models}. But for 44 uncalibrated source models or source models calibrated on other data 45 this test of generation would be more meaningful. 44 46 % 45 47 %This does demonstrate, however, that \textsc{edgrn} and our modified version of … … 129 131 \end{center} 130 132 \end{figure} 131 FIXME (Jane): This graph does not look nice. The legend URS Model should 132 be URSGA model. 133 134 \subsection{Inundation} 133 FIXME (Jane): This graph does not look nice. 134 135 135 After propagating the tsunami in the open ocean using \textsc{ursga}, 136 136 the approximated ocean and surface elevation and horisontal flow … … 153 153 region in Patong Bay. The coarse resolution was chosen to be 154 154 commensurate with the model output from the \textsc{ursga} model 155 (FIXME - this has to be clearly stated in ursga section) RICHARD156 155 while the latter was chosen to match the available resolution of topographic 157 156 data and building data in Patong city. … … 188 187 reasonable. 189 188 190 Maximum onshore inundation depth was computed from the model 189 \subsection{Inundation} 190 The \textsc{anuga} simulation described in the previous section and used to 191 model shallow water propgation also predicts 192 inundation. Maximum onshore inundation depth was computed from the model 191 193 throughout the entire Patong Bay region and used to generate 192 194 a measure of the inundated area. … … 241 243 \rho_{in}=\frac{A(I_m\cap I_o)}{A(I_o)} 242 244 \end{equation} 243 representing the ratio $\rho_{in}$ of the observed 244 inundation region $I_o$ captured by the model $I_m$. Another useful 245 representing the ratio of the area of the observed 246 inundation region $I_o$ and the area of the observed inundation region 247 captured by the model $I_m$. Another useful 245 248 measure is the fraction of the modelled inundation area that falls 246 249 outside the observed inundation area given by the formula … … 262 265 missing data in the field survey data itself. The impact of some of 263 266 these sources of uncertainties are is investigated in 264 Section~\ref{sec:sensitivity} 267 Section~\ref{sec:sensitivity}. 265 268 266 269 \subsection{Eye-witness accounts} … … 284 287 \begin{figure}[ht] 285 288 \begin{center} 286 \includegraphics[width=\textwidth,keepaspectratio=true]{ gauges_hotels_depths.jpg}287 \includegraphics[width=\textwidth,keepaspectratio=true]{ gauges_hotels_speed.jpg}289 \includegraphics[width=\textwidth,keepaspectratio=true]{figures/gauges_hotels_depths.jpg} 290 \includegraphics[width=\textwidth,keepaspectratio=true]{figures/gauges_hotels_speed.jpg} 288 291 \caption{Time series obtained from the two onshore locations, North and South, 289 292 shown in Figure \protect \ref{fig:gauge_locations}.} -
anuga_work/publications/boxing_day_validation_2008/sensitivity.tex
r7450 r7451 2 2 \section{Sensitivity Analysis} 3 3 \label{sec:sensitivity} 4 The numerical models used to simulate tsunami impact 5 are computationally intensive and high resolution models of the entire 6 evolution process will often take a number of days to 7 run. Consequently, the uncertainty in model predictions is difficult to 8 quantify as it would require a very large number of runs. 9 However, model uncertainty should not be ignored. The aim of this section is 10 not to provide a detailed investigation of sensitivity but to rather 11 illustrate that changes in important parameters of the \textsc{usrga--anuga} 12 model produce behaviour consistent with the known physics and that 13 small changes in these parameters produce bounded variations in the output. 14 4 15 This section investigates the effect of different values of Manning's 5 16 friction coefficient, changing waveheight at the 100 m depth contour, 6 17 and the presence and absence of buildings in the elevation dataset on 7 model maximum inundation. The reference model is the one reported in 8 Figure~\ref{fig:inundationcomparison1cm} (right) with a friction coefficient of 0.01, 9 buildings included and the boundary condition produced by the 18 model maximum inundation. 19 20 The reference model is the one reported in 21 Figure~\ref{fig:inundationcomparison1cm} (right) with a friction coefficient of 0.01, buildings included and the boundary condition produced by the 10 22 \textsc{ursga} model. 11 23 … … 20 32 we simulated the maximum onshore inundation using a Manning's 21 33 coefficient of 0.0003 and 0.03. The resulting inundation maps are 22 shown in Figure~\ref{fig:sensitivity_friction} and the maximum flow 23 speeds in Figure~\ref{fig:sensitivity_friction_speed}. These figures 24 show that the on-shore inundation extent decreases with increasing 34 shown in Figure~\ref{fig:sensitivity_friction} 35 % and the maximum flow speeds in Figure~\ref{fig:sensitivity_friction_speed}. 36 The figure, along with Table~\ref{table:inundationAreas}, 37 shows that the on-shore inundation extent decreases with increasing 25 38 friction and that small perturbations in the friction cause bounded 26 39 changes in the output. This is consistent with the conclusions of … … 33 46 The effect of the wave height used as input to the inundation model 34 47 \textsc{anuga} was also investigated. 35 Figure~\ref{fig:sensitivity_boundary} indicates that the inundation 48 Figure~\ref{fig:sensitivity_boundary} and Table~\ref{table:inundationAreas} 49 indicate that the inundation 36 50 severity is directly proportional to the boundary waveheight but small 37 51 perturbations in the input wave height of 10 cm appear to have little … … 49 63 The presence or absence of physical buildings in the elevation model was also 50 64 investigated. 51 Figure~\ref{fig:sensitivity_nobuildings} shows the inundated area and 52 the associated maximum flow speeds 53 in the presence and absence of buildings. It 54 is apparent that densely built-up areas act as 55 dissipators greatly reducing the inundated area. However, flow speeds 56 tend to increase in passages between buildings. 65 Figure~\ref{fig:sensitivity_nobuildings} shows the inundated area 66 %and the associated maximum flow speeds 67 in the presence and absence of buildings. From 68 Table~\ref{table:inundationAreas} it is apparent that densely built-up 69 areas act as dissipators greatly reducing the inundated area. 70 This result suggest that, when possible the presence of human-made structures 71 should be included into the model topography. Furthermore this result also 72 indicates that simply matching point sites with much lower resolution meshes 73 than used here is an over simplification. Such simulations cannot capture the 74 fine detail that so clearly affects inundation. 75 %However, flow speeds tend to increase in passages between buildings. 57 76 58 77
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