Changeset 6593


Ignore:
Timestamp:
Mar 24, 2009, 12:57:30 PM (16 years ago)
Author:
jakeman
Message:

Jakeman: I have begun cleaning up validation article correct referencing is now implemented and dependency on modsim07.sty removed

Location:
anuga_work/publications/boxing_day_validation_2008
Files:
1 added
1 edited

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  • anuga_work/publications/boxing_day_validation_2008/patong_validation.tex

    r6590 r6593  
    11\documentclass[a4paper]{article}
    2 \usepackage{modsim07}
    32\usepackage{graphicx}
    43\usepackage{hyperref}
    5 
    6 %================Start of Document================
    7 \begin{document}
     4\usepackage{amsfonts}
     5\usepackage{url}      % for URLs and DOIs
     6\newcommand{\doi}[1]{\url{http://dx.doi.org/#1}}
    87
    98%----------title-------------%
    … …  
    1413% FIXME(Ole): The 'ands' appear in the text, they shouldn't
    1514\author{J.D.~Jakeman$^1$~~and~~O.~Nielsen$^2$~~and~~R.~Mleczko$^2$~~and~~K.~VanPutten$^2$~~and~~S.G~Roberts$^1$}
    16 
    17 %------Affiliation----------
    18 \institute{$^1$The Australian National University, Canberra, Australia \\
    19 $^2$Geoscience Australia, Canberra, Australia\\
    20 Email: \href{mailto:jakeman@maths.anu.edu.au}{john.jakeman@anu.edu.au}}
    21 \keywords{ANUGA, Finite Volume Method, Natural Hazards, Indian Ocean Tsunami, Inundation, Thailand, Phuket, Patong Bay, Post Tsunami Runup Survey, Bathymetry, Model Verification, Shallow Water Wave Equations}
    22 
     15\author{J.~D. Jakeman\thanks{The Australian National University, Canberra, \textsc{Australia}.
     16\protect\url{mailto:john.jakeman@anu.edu.au}}
     17\and O.Nielsen\thanks{Geoscience Australia, Canberra, \textsc{Australia}}
     18\and R. Mleczko\footnotemark[2]
     19\and K. VanPutten\footnotemark[2]
     20\and S.~G Roberts\footnotemark[1]
     21}
     22
     23%================Start of Document================
     24\begin{document}
    2325\maketitle
    24 
    2526%------Abstract--------------
    2627\begin{abstract}
    2728
    2829\end{abstract}
    29 %======================Section 1=================
     30
     31\tableofcontents
     32%================Section===========================
    3033
    3134\section{Introduction}
    32 Tsunami are a potential hazard to coastal communities all over the world. A number of recent large events have increased community and scientific awareness of the need for effective tsunami hazard mitigation. Tsunami modelling is major component of hazard mitigation, which involves detection, forecasting, and emergency preparedness (Synolakis {\it et al.} 2005). Accurate models can be used to provide information that increases the effectiveness of action undertaken before the event to minimise damage (early warning systems, breakwalls etc.) and protocols put in place to be followed when the flood waters subside.
    33 
    34 Several approaches are currently used to model tsunami propagation and inundation. These methods differ in both the formulation used to describe the evolution of the tsunami and the numerical methods used to solve the governing equations. The shallow water wave equations, linearised shallow water wave equations, and Boussinesq-type equations are commonly accepted descriptions of flow. The nonlinear nature of these equations, the highly variable nature of the phenomena that they describe and the complex reality of the geometry they operate in necessitate the use of numerical models. These models are typically used to predict quantities such as arrival times, wave speeds and heights and inundation extents which are used to develop efficient hazard mitigation plans. Inaccuracies in model prediction can result in inappropriate evacuation plans and town zoning which may result in loss of life and large financial losses. Consequently tsunami models must undergo sufficient testing to increase scientific and community confidence in the model predictions.
    35 
    36 Complete confidence in a model of a physical system cannot be established. A model only be shown not to fail for a specific experiment (FIXME - fiddle with this sentence). However, the utility of a model can be assessed through a process of validation and verification. Validation assesses the accuracy of the numerical method used to solve the governing equations and verification is used to investigate whether the model adequately represents the physical system (\cite{XXX}). %Verification must be used to reduce numerical error before validation is used to assess model structure. In some situations it may be possible to increase the numerical accuracy of a model and produce a worse fit of the observed data.
    37 
    38 The sources of data used to validate and verify a model can be separated into three main categories; analytical solutions, scale experiments and field measurements. Analytical solutions of the governing equations of a model, if available, provide the best means of validating a numerical hydrodynamic model.
    39 (FIXME: CAN WE GET RID OF THIS: The solutions provide spatially and temporally distributed values of important observables that can be compared against modelled results). However analytical solutions to the governing equations are frequently limited to a small set of idealised examples that do not completely capture the more complex behaviour of 'real' events. Scale experiments, typically in the form of wave-tank experiments provide a much more realistic source of data that better captures the complex dynamics of natural tsunami, whilst allowing control of the event and much easier and accurate measurement of the tsunami properties. However comparison of numerical predictions with field data provides one of the most stringent test of model veracity. The use of field data increases the generality and significance of conclusions made regarding model utility. However the use of field data also significantly increase the uncertainty of the validation experiment that may constrain the ability to make unequivocal statements~\cite{lane94}.
    40 
    41 Currently the extent of tsunami related field data is limited. The cost of tsunami monitoring programs and bathymetry and topography surveys prohibits the collection of data in many of the regions in which tsunamis pose greatest threat. The resulting lack of data has limited the number of field data sets available to validate tsunami models, particularly those modelling tsunami inundation. Synolakis et. al~\cite{synolakis07} have developed a set of standards, criteria and procedures for evaluating numerical models of tsunami. They propose three analytical solutions to help identify the validity of a model and  five scale comparisons (wave-tank benchmarks) and two field events to assess model veracity.  The two field data benchmarks are very useful but only capture a small subset of possible tsunami behaviours (FIXME: What?) and only one of the benchmarks can be used to validate tsunami inundation (FIXME: Why?). The type and size of a tsunami source, propagation extent, and local bathymetry and topography all affect the energy, waveform and subsequent inundation of a tsunami. Consequently additional field data benchmarks that further capture the variability and sensitivity of the real world system would be useful to allow model developers verify their models and subsequently use their models with greater confidence.
    42 
    43 In this paper we develop a field data benchmark to be used in conjunction with the other tests proposed by Synolakis et al. to validate and verify tsunami inundation. The benchmark is constructed from data collected around Patong Bay, Thailand immediately following the 2004 Indian Ocean tsunami. This area was chosen because the authors were able to obtain high resolution bathymetry and topography data in this area and an inundation map generated from a survey performed in the aftermath of the tsunami. A description of this data is give in Section~\ref{sec:data}.
    44 
    45 An associated aim of this paper is to illustrate the use of this new benchmark to validate an operational tsunami model called ANUGA (see Secion~\ref{sec:veri_procedure}). The specific intention is to test the ability of ANUGA to reproduce the inundation survey of maximum runup. ANUGA is a hydrodynamic modelling tool used to simulate the tsunami propagation and run rain-induced floods.
    46 
    47 %=================Section=====================
    48 
    49 \section{Indian Ocean tsunami of 24th December 2004}
    50 The devastation caused by the 2004 Indian Ocean tsunami has heightened community, scientific and governmental interest in tsunami and in doing so has provided a unique opportunity for further validation of tsunami models. Data sets from seismometers, tide gauges, GPS stations, a few satellite overpasses, subsequent coastal field surveys of run-up and flooding and measurements from ship-based expeditions, have now been made available (Vigny {\it et al.} 2005, Amnon {\it et al.} 2005, Kawata {\it et al.} 2005, and Liu {\it et al.} 2005)\nocite{vigny05,amnon05,kawata05,liu05}. A number of studies have utilised this data to calibrate models of the tsunami source\cite{grilli07} , match tide gauge recordings\cite{}, maximum wave heights~\cite{asavanant08} and runup locations~\cite{ioualalen07}. We propose to use this event as an additional field-data benchmark for verification of tsunami models. This event captures certain tsunami behaviours that are not present in the benchmarks proposed by Synolakis et.\ al~\cite{synolakis07}. FIXME: What kind of behaviours???
     35Tsunami are a potential hazard to coastal communities all over the world. A number of recent large events have increased community and scientific awareness of the need for effective tsunami hazard mitigation. Tsunami modelling is major component of hazard mitigation, which involves detection, forecasting, and emergency preparedness~\cite{synolakis05}. Accurate models can be used to provide information that increases the effectiveness of action undertaken before the event to minimise damage (early warning systems, breakwalls etc.) and protocols put in place to be followed when the flood waters subside.
     36
     37Several approaches are currently used to model tsunami propagation and inundation. These methods differ in both the formulation used to describe the evolution of the tsunami and the numerical methods used to solve the governing equations. The shallow water wave equations, linearised shallow water wave equations, and Boussinesq-type equations are frequently used to simulate tsunami propagation. The nonlinear nature of these equations, the highly variable nature of the phenomena that they describe and the complex reality of the geometry they operate in necessitate the use of numerical models. These models are typically used to predict quantities such as arrival times, wave speeds and heights and inundation extents which are used to develop efficient hazard mitigation plans. Inaccuracies in model prediction can result in inappropriate evacuation plans and town zoning which may result in loss of life and large financial losses. Consequently tsunami models must undergo sufficient testing to increase scientific and community confidence in the model predictions.
     38
     39Complete confidence in a model of a physical system frequently in general cannot be established.  One can only hope to state under what conditions the model hypothesis holds true. Specifically the utility of a model can be assessed through a process of validation and verification. Validation assesses the accuracy of the numerical method used to solve the governing equations and verification is used to investigate whether the model adequately represents the physical system. Together these processes can be used to establish the likelihood that that a model is a legitimate hypothesis~\cite{bates01}.
     40
     41The sources of data used to validate and verify a model can be separated into three main categories; analytical solutions, scale experiments and field measurements. Analytical solutions of the governing equations of a model, if available, provide the best means of validating a numerical hydrodynamic model. However analytical solutions to the governing equations are frequently limited to a small set of idealised examples that do not completely capture the more complex behaviour of `real' events. Scale experiments, typically in the form of wave-tank experiments provide a much more realistic source of data that better captures the complex dynamics of natural tsunami, whilst allowing control of the event and much easier and accurate measurement of the tsunami properties. However comparison of numerical predictions with field data provides the most stringent test of model veracity. The use of field data increases the generality and significance of conclusions made regarding model utility. However the use of field data also significantly increases the uncertainty of the validation experiment that may constrain the ability to make unequivocal statements~\cite{bates01}.
     42
     43Currently the extent of tsunami related field data is limited. The cost of tsunami monitoring programs and bathymetry and topography surveys prohibits the collection of data in many of the regions in which tsunamis pose greatest threat. The resulting lack of data has limited the number of field data sets available to validate tsunami models, particularly those modelling tsunami inundation. Synolakis et. al~\cite{synolakis07} have developed a set of standards, criteria and procedures for evaluating numerical models of tsunami. They propose three analytical solutions to help identify the validity of a model and  five scale comparisons (wave-tank benchmarks) and two field events to assess model veracity.  The two field data benchmarks are very useful but only capture a small subset of possible tsunami behaviours. The type and size of a tsunami source, propagation extent, and local bathymetry and topography all affect the energy, waveform and subsequent inundation of a tsunami. Consequently additional field data benchmarks that further capture the variability and sensitivity of the real world system would be useful to allow model developers verify their models and subsequently use their models with greater confidence.
     44
     45In this paper we develop a field data benchmark to be used in conjunction with the other tests proposed by Synolakis et al.~\cite{synolakis07} to validate and verify tsunami inundation. The benchmark is constructed from data collected around Patong Bay, Thailand immediately following the 2004 Indian Ocean tsunami. This area was chosen because the authors were able to obtain high resolution bathymetry and topography data in this area and an inundation map generated from a survey performed in the aftermath of the tsunami. A description of this data is give in Section~\ref{sec:data}.
     46
     47An associated aim of this paper is to illustrate the use of this new benchmark to validate an operational tsunami model called \textsc{anuga} (see Secion~\ref{sec:veri_procedure}). The specific intention is to test the ability of \textsc{anuga} to reproduce the inundation survey of maximum runup. \textsc{Anuga} is a hydrodynamic modelling tool used to simulate the tsunami propagation and run rain-induced floods.
     48
     49%================Section===========================
     50
     51\section{Event Description}
     52The devastation caused by the 2004 Samatra-Andaman tsunami has heightened community, scientific and governmental interest in tsunami and in doing so has provided a unique opportunity for further validation of tsunami models. Data sets from seismometers, tide gauges, GPS stations, a few satellite overpasses, subsequent coastal field surveys of run-up and flooding and measurements from ship-based expeditions, have now been made available~\cite{vigny05,amnon05,kawata05,liu05}. A number of studies have utilised this data to calibrate models of the tsunami source\cite{asavanant08,arcas06,grilli07,ioualalen07}. We propose to use this event as an additional field-data benchmark for verification of tsunami models. This event captures certain tsunami behaviours that are not present in the benchmarks proposed by Synolakis et. al~\cite{synolakis07}. FIXME: What kind of behaviours???
    5153
    5254Synolakis detail two field data benchmarks. The first test compares model results against observed data from the Hokkaido-Nansei-Oki tsunami that occurred around Okushiri Island, Japan on the 12th of July 1993. This tsunami provides an example of extreme runup generated from reflections and constructive interference resulting from local topography and bathymetry. The benchmark consists of two tide gauge records and numerous spatially distributed point sites at which maximum runup elevations were observed. The second benchmark is based upon the Rat Islands Tsunami that occurred off the coast of Alaska on the 17th of November 2003. Rat island tsunami provides a good test for real-time forecasting models since tsunami was recorded at three tsunameters. The test requires matching the propagation model data with the DART recording to constrain the tsunami source model and using a propagation model to to reproduce the tide gauge record at Hilo.
    5355
    54 %The tsunamis used by the two standard benchmarks and the 2004 tsunami are quite different. They all arise from coseismic displacement resulting from an earthquake, however they all occur in very different geographical regions. The Hokkaido-Nansei-Oki tsunami was generated by an earthquake with a magnitude of 7.8 and only travelled a small distance before inundating Okishiri Island. The event provides an example of extreme runup generated from reflections and constructive interference resulting from local topography and bathymetry. In comparison the Rat islands tsunami was generated by an earthquake of the same magnitude but had to travel a much greater distance. The event provides a number of tide gauge recordings that capture the change in wave form as the tsunami evolved.
    55 
    5656The 2004 Indian Ocean tsunami was a much larger event than the previous two described (See Section \ref{sec:source}). Consequently the energy of the resulting wave was much larger than the waves generated from the more localised and smaller magnitude aforementioned events. WAS THE WAVELENGTH< VELOCITY (and thus average ocean depth) DIFFERENT FROM THESE TWO EVENTS??? If so state something like. This larger wavelength and energy and simply the different geology of the area produced different a wave signal and different pattern of inundation. Here we focus on the large inundation experienced at Patong Bay on the west coast of Thailand.
    5757
    5858\section{Data}\label{sec:data}
    59 (FIXME (OLE): Remove? Hydrodynamic simulations require very little data in comparison to models of many other environmental systems). Tsunami models typically only require baythymetry and topography data to approximate the local geography, parameterisation of the tsunami source from which appropriate initial conditions can be generated, and a locally distributed quantity such as Manning's friction coefficient to approximate friction. Here we discuss the bathymetric and topographical data sets and source condition that are necessary to implement the proposed benchmark. Friction is discussed in Section~\ref{sec:inundation}
    60 
    61 An unusually large amount of data for the 2004 tsunami, necessary for tsunami verification, is available at Patong Bay and surrounding regions. A number of raw data sets were obtained, analysed and checked for quality and subsequently gridded for easier visualisation and input into the tsunami models.
     59Tsunami models typically require baythymetry and topography data to approximate the local geography, parameterisation of the tsunami source from which appropriate initial conditions can be generated, and certain paramter values such Manning's friction coefficient. Here we discuss the ncessary data needed to implement the proposed benchmark.
    6260
    6361\subsection{Bathymetric and topographic data}
    64 
    65 NOTE: Richard, could you please look into these issues and also those in your appendix?
    66 
    67 FIXME(OLE): Need Intro to this section aka: we obtained data sets at different resolutions from various sources and merged them to build a model appropriate for inundation modelling. The resolution required was generally relatively coarse in the deeper water and progressively finer towards the bay itself with the finest data in the intertidal zone and around the built environment.
    68 
     62An unusually large amount of data for the 2004 tsunami, necessary for tsunami verification, is available at Patong Bay and surrounding regions. A number of raw data sets were obtained, analysed and checked for quality and subsequently gridded for easier visualisation and input into the tsunami models. The resulting grid data is relatively coarse in the deeper water and becomes progressively finer as the distance to Patong Bay decreases.
    6963
    7064The two minute arc grid data set, DBDB2, was obtained from US Naval Research Labs and used to approximate the bathymetry in the Bay of Bengal. This grid was further interpolated to a 27 second arc grid. In the Andaman Sea the DBDB2 data was replaced with a 3 second grid obtained from NOAA (REF?). Finally, a 1 second grid was used to approximate the bathymetry in Patong Bay and the immediately adjacent regions (FROM WHERE?). This elevation data was created from the digitised Thai Navy bathymetry chart, no 358. A visualisation of the elevation data set used in Patong bay is shown in Figure~\ref{fig:patong_bathymetry}. The continuous topography is an interpolation of known elevation measured at the coloured dots.
    71 
    72 The sub-sampling of larger grids was performed by using {\bf resample} a GMT program (\cite{XXX}). The gridding of data was performed using {\bf Intrepid} a commercial geophysical processing package developed by Intrepid Geophysics. The gridding scheme employed the nearest neighbour algorithm followed by and application of minimum curvature akima spline smoothing.
    73 
    7465
    7566\begin{figure}[ht]
    7667\begin{center}
    7768\includegraphics[width=8.0cm,keepaspectratio=true]{patong_bay_data.jpg}
    78 \caption{Is there a new picture with river included???}
     69\caption{Visualisation of the elevation data set used in Patong Bay. FIXME: Can we generate a new picture with river included Preferably without the arrows and logo???}
    7970\label{fig:patong_bathymetry}
    8071\end{center}
    8172\end{figure}
    8273
    83 Details of the lineage of this dataset is outlined in Appendix~\ref{XXXXX} and the final dataset
    84 is available at XXXX.
    85 
     74The sub-sampling of larger grids was performed by using {\bf resample} a GMT program (\cite{XXX}). The gridding of data was performed using {\bf Intrepid} a commercial geophysical processing package developed by Intrepid Geophysics. The gridding scheme employed the nearest neighbour algorithm followed by and application of minimum curvature akima spline smoothing. Details of the lineage of this dataset is outlined in the Appendix and the final dataset is available at XXXX.
     75
     76
     77FIXME(Richard): Could you please look into these issues and also those in your appendix?
    8678
    8779\subsection{Tsunami source}\label{sec:source}
    8880
    89 NOTE: Richard, could you please look into these issues
    90 
    91 
    92 The 2004 Indian Ocean tsunami was generated by severe coseismic displacement of the sea floor as a result of one of the largest earthquakes on record. The M$_w$=9.3 mega-thrust earthquake occurred on the 26 December 2004 at 0h58'53'' UTC approximately 70 km offshore North Sumatra. The disturbance propagated 1200-1300 km along the Sumatra-Andaman trench time at a rate of 2.5-3 km.s$^{-1}$ and lasted approximately 8-10 minutes (Amnon {\it et al.} 2005)\nocite{amnon05}.
    93 
    94 Many models of this earthquake are available FIXME: CITATIONS NEEDED \cite{YYY}. Some are determined from various geological surveys of the site, others solve an inverse problem which calibrates the source based upon the tsunami wave signal and or runup. The source parameters used to simulate the 2004 Indian Ocean Tsunami were taken from Chlieh (2007) \cite{XXX}.
    95 This model was created by inversion of the seismic data and fits both coseismic, tsunami and GPS data in the Andaman Sea well. DOES ANYONE HAVE A COPY THEY COULD SEND ME PLEASE? The resulting sea floor displacement ranges from about - 5.0 to 5.0 metres and is shown in Figure~\ref{fig:chlieh_slip_model}.
     81The 2004 Indian Ocean tsunami was generated by severe coseismic displacement of the sea floor as a result of one of the largest earthquakes on record. The M$_w$=9.3 mega-thrust earthquake occurred on the 26 December 2004 at 0h58'53'' UTC approximately 70 km offshore North Sumatra. The disturbance propagated 1200-1300 km along the Sumatra-Andaman trench time at a rate of 2.5-3 km.s$^{-1}$ and lasted approximately 8-10 minutes~\cite{amnon05}.
     82
     83Many models of this earthquake are available~\cite{chlieh07,XXX}. Some are determined from various geological surveys of the site, others solve an inverse problem which calibrates the source based upon the tsunami wave signal and or runup. The source parameters used to simulate the 2004 Indian Ocean Tsunami were taken from Chlieh~\cite{chlieh07}. This model was created by inversion of the seismic data from GPS measurements and fits both coseismic, tsunami and GPS data in the Andaman Sea well. The resulting sea floor displacement ranges from about - 5.0 to 5.0 metres and is shown in Figure~\ref{fig:chlieh_slip_model}.
    9684
    9785\begin{figure}[ht]
    9886\begin{center}
    99 \includegraphics[width=8.0cm,keepaspectratio=true]{chlieh_slip_model.png}
    100 \caption{Location and magnitude of the sea floor displacement associated with the 2004 Indian Ocean tsunami. Source parameters from Chlieh {\it et al.} (2007) \cite{XXX}}
     87\includegraphics[width=5.0cm,keepaspectratio=true]{chlieh_slip_model.png}
     88\caption{Location and magnitude of the sea floor displacement associated with the 2004 Indian Ocean tsunami. Source parameters from Chlieh et al.~\cite{chlieh07}}
    10189\label{fig:chlieh_slip_model}
    10290\end{center}
    10391\end{figure}
    10492
    105 \subsection{Inundation survey data}
    106 
    107 ...
    108 
    109 FIXME: This needs to be rephrased. This is about survey data not about bathymetric and source parameters. And it appears that this paragraph really belongs under the next section.
    110 
    111 The bathymetry data and source parameterisation can be inserted into the tsunami model and run. From the simulation runup and ocean surface elevation can be obtained. We propose that a `correct' tsunami model should reproduce the inundation map shown in Figure~\ref{fig:patongescapemap}. Furthermore the model should simulate a leading depression followed by 3??? crests. Is there any eye witness accounts of how many waves arrived a patong??? FIXME: Who will chase this? Richard has the video footage recorded, can you do it?
     93\subsection{Validation data}
     94 Eyewitness accounts detailed in~\cite{papadopoulos06} report that most people at Patong Beach observed an initial retreat of the shoreline of more than 100m followed a few minutes later by a strong wave (crest). Another less powerful wave arrived another five or ten minutes later. Eyewitness statments place the arrival time of the strong wave between 2 hours and 55 inutes to 3 hours and 5 minutes after the source rupture (09:55am to 10:05am local time). After the event (HOw long?) a survey mapped the maximum observed inundation at Patong beach.  The inundation map is shown in Figure~\ref{fig:patongescapemap} and was obatined from the Thai Department of Mineral Resources \protect \cite{XXX}.
    11295
    11396\begin{figure}[ht]
    … …  
    119102\end{figure}
    120103
    121 
     104FIXME(Richard): More information deailting construction of this map is needed here. Is more accurate information on arrival times of crests and depression available
     105
     106%================Section===========================
    122107\section{Verification Procedure}\label{sec:veri_procedure}
    123 
    124 %=================Section=====================
     108Intro\\\\
     109
     110The following observations need to be matched by any numerical tsuanmi model:
     111\begin{itemize}
     112 \item Simulate a leading depression followed by two distinct crests of decreasing magnitude.
     113 \item The arrival time of the first crest should arrive at Patong beach bewtween 2 hours and 55 inutes to 3 hours and 5 minutes after the intial rupture of the source. The subsequent crest arrive five to ten minutes later.
     114 \item Simulated inundation in Patong bay should reproduce well the inundation map in Figure~\ref{fig:patongescapemap}.
     115\end{itemize}
     116
    125117
    126118\subsection{ANUGA}
    127 ANUGA is an Open Source hydrodynamic inundation tool that solves the depth integrated nonlinear shallow water wave equations. The scheme used by ANUGA, first presented by Zoppou and Roberts (1999)\nocite{zoppou99}, is a high-resolution Godunov-type method that uses the rotational invariance property of the shallow water equations to transform the two-dimensional problem into local one-dimensional problems. These local Riemann problems are then solved using the semi-discrete central-upwind scheme of Kurganov {\it et al.} (2001) \nocite{kurganov01} for solving one-dimensional conservation equations. The numerical scheme is presented in detail in (Zoppou and Roberts 1999, Zoppou and Roberts 2000, and Roberts and Zoppou 2000, Nielsen {\it et al.} 2005) \nocite{zoppou99,zoppou00,roberts00,nielsen05}. An important capability of the software is that it can model the process of wetting and drying as water enters and leaves an area. This means that it is suitable for simulating water flow onto a beach or dry land and around structures such as buildings. It is also capable of adequately resolving hydraulic jumps due to the ability of the finite-volume method to handle discontinuities. ANUGA has been validated against a number of analytical solutions and the wave tank simulation of the 1993 Okushiri Island tsunami (Roberts {\it et al.} 2006 and Nielsen {\it et al.} 2005) \nocite{roberts06,nielsen05}.
     119\textsc{Anuga} is an Open Source hydrodynamic inundation tool that solves the depth integrated nonlinear shallow water wave equations. The scheme used by \textsc{anuga}, first presented by Zoppou and Roberts~\cite{zoppou99}, is a high-resolution Godunov-type method that uses the rotational invariance property of the shallow water equations to transform the two-dimensional problem into local one-dimensional problems. These local Riemann problems are then solved using the semi-discrete central-upwind scheme of Kurganov et al.~\cite{kurganov01} for solving one-dimensional conservation equations. The numerical scheme is presented in detail in Zoppou and Roberts~\cite{zoppou99}, Zoppou and Roberts~\cite{zoppou00}, and Roberts and Zoppou~\cite{roberts00}, Nielsen et al.~\cite{nielsen05}. An important capability of the software is that it can model the process of wetting and drying as water enters and leaves an area. This means that it is suitable for simulating water flow onto a beach or dry land and around structures such as buildings. It is also capable of adequately resolving hydraulic jumps due to the ability of the finite-volume method to handle discontinuities. \textsc{Anuga} has been validated against a number of analytical solutions and the wave tank simulation of the 1993 Okushiri Island tsunami~\cite{roberts06,nielsen05}.
    128120
    129121\subsection{URSGA}
    130 URSGA is a hydrodynamic code that models the propagation of the tsunami in deep water using the finite difference method to solve the depth integrated nonlinear shallow water equations in spherical co-ordinates with friction and Coriolis terms. The code is based on Satake (1995) with significant modifications made by the URS corporation (Thio et al. 2007) and Geoscience Australia (Burbidge et al. 2007). The tsunami is propagated via a staggered grid system starting with coarser grids and ending with the finest one. URSGA is not publicly available. FIXME: Check with David.
     122\textsc{ursga} is a hydrodynamic code that models the propagation of the tsunami in deep water using the finite difference method to solve the depth integrated nonlinear shallow water equations in spherical co-ordinates with friction and Coriolis terms. The code is based on Satake~\cite{satake95} with significant modifications made by the URS corporation~\cite{thio07} and Geoscience Australia~\cite{burbidge07}. The tsunami is propagated via a staggered grid system. Coarse grids are used in the open ocean and the finest resolution grid is employed in the region of most interest. \textsc{Ursga} is not publicly available. FIXME: Check with David.
    131123
    132124
    133125\subsection{Tsunami Source and Propagation}
    134 The utility of the URSGA model decreases with water depth unless an intricate sequence of nested grids is employed. In comparison ANUGA is designed to produce robust and accurate predictions of on-shore inundation in mind, but is less suitable for earthquake source modelling and large study areas. Consequently, the Geoscience Australia tsunami modelling methodology is based on a hybrid approach using models like URSGA for tsunami generation and propagation up to a 100m depth contour. This information then forms a boundary condition for ANUGA and is propagated on shore to model the inundation. Specifically we use the URSGA model to simulate the propagation of the 2004 Indian Ocean tsunami in the deep ocean, based on a discrete representation of the initial deformation of the sea floor, described in Section~\ref{sec:source}. The resulting tsunami was propagated over the entire Bay of Bengal and the wave signal measured along the 100m depth contour offshore Phuket, Thailand. The wave signal is then used as a time varying boundary condition for the ANUGA inundation simulation.
    135 
    136 ???The URS code is also capable of calculating inundation. CAN WE PRODUCE AN INUNDATION MAP OVER THE SAME AREA TO COMPARE WITH ANUGA???
     126The utility of the \textsc{ursga} model decreases with water depth unless an intricate sequence of nested grids is employed. In comparison \textsc{anuga} is designed to produce robust and accurate predictions of on-shore inundation in mind, but is less suitable for earthquake source modelling and large study areas. Consequently, the Geoscience Australia tsunami modelling methodology is based on a hybrid approach using models like \textsc{ursga} for tsunami generation and propagation up to a 100m depth contour. This information then forms a boundary condition for \textsc{anuga} and is propagated on shore to model the inundation. Specifically we use the \textsc{ursga} model to simulate the propagation of the 2004 Indian Ocean tsunami in the deep ocean, based on a discrete representation of the initial deformation of the sea floor, described in Section~\ref{sec:source}. The resulting tsunami was propagated over the entire Bay of Bengal and the wave signal measured along the 100m depth contour offshore Phuket, Thailand. The wave signal is then used as a time varying boundary condition for the \textsc{anuga} inundation simulation.
     127
     128???The \textsc{ursga} code is also capable of calculating inundation. CAN WE PRODUCE AN INUNDATION MAP OVER THE SAME AREA TO COMPARE WITH \textsc{anuga}???
    137129
    138130\subsection{Tsunami Inundation}\label{sec:inundation}
    139 In this case the open ocean boundary of the ANUGA study area was chosen to roughly follow the 100m depth contour along the west coast of Phuket Island. The computational domain is shown in Figure \ref{fig:computational_domain}
     131In this case the interface betwen the \textsc{ursga} and \textsc{anuga} models was chosen to roughly follow the 100m depth contour along the west coast of Phuket Island. The computational domain is shown in Figure \ref{fig:computational_domain}
    140132\begin{figure}[ht]
    141133\begin{center}
    142 \includegraphics[width=8.0cm,keepaspectratio=true]{new_domain.png}
    143 \caption{Computational domain of the ANUGA simulation. CAN WE CREATE A PICTURE LIKE THIS FOR OUR NEW SCENARIO???
    144 FIXME: Is this still the case?}
     134\includegraphics[width=5.0cm,keepaspectratio=true]{new_domain.png}
     135\caption{Computational domain of the \textsc{anuga} simulation. FIXME: Insert picture of new domain here.}
    145136\label{fig:computational_domain}
    146137\end{center}
    … …  
    151142The boundary condition at each side of the domain towards the south and the north where no data was available was chosen as a transmissive boundary condition effectively replicating the time dependent wave height present just inside the computational domain. Momentum was set to zero. Other choices include applying the mean tide value as a Dirichlet type boundary condition but experiments as well as the result of the verification reported here showed that this approach tends to under estimate the tsunami impact due to the tempering of the wave near the side boundaries. FIXME(OLE): Should we include Nick's test example?
    152143
    153 %================Section======================
     144%================Section===========================
    154145\section{Results}
    155146Maximum onshore inundation elevation was simulated throughout the entire Patong Bay region. Figure~\ref{fig:inundationcomparison1cm} shows very good agreement between the measured and simulated inundation. Discrepencies between the survey data and the modelled inundated area are apparant and would be due to a number of issues: These include uncertainties in the elevation data, simplifications in the models involved, effects of erosion and deposition by the tsunami event, unknown distribution of surface roughness, as well as measurement errors and missing data in the field survey data itself.
    … …  
    160151FIXME: Take some of this commentary after final runs have been completed.
    161152FIXME: Also need a commentary on the dynamics of what is being observed and whether it aligns with eye witness observations.
    162 %The ANUGA simulation determines a region to be inundated if at some point in time it was covered by at least 1cm of water. This precision in field measurements is impossible to obtain. The inundation boundary is determined by observing water marks and other signs left by the receeding waters. The precision of the observed inundation map is, most likely, at least an order of magnitude worse than the ANUGA simulation. The simulated inundation based upon a 10cm threshold is shown in Figure~\ref{fig:inundationcomparison10cm}.
    163 
    164 Both the URS model and the ANUGA inundation model shows that the event comprises a train of waves some with preciding drawdown effects (ADD details of waveform with a graph from URL and a gauge from ANUGA and discuss). In \cite{papadopoulos06} eyewitness accounts report
    165 \emph{In Patong beach, most people observed at least two
    166 waves. It is likely that the leading wave described in both
    167 Sri Lanka and Maldives was not observed in Patong beach.
    168 What people said is that the first sea motion was a retreat
    169 of more than 100 m. A few minutes later the strong wave
    170 arrived. Then, after another 5 or 10 min. one more wave attacked
    171 but less violently than the first one. Nearly all the
    172 interviewed persons reported that the tsunami inundation
    173 in the Patong beach varied from 150 m to at least 750 m
    174 (Fig. 16). One eyewitness reported inundation of only 20
    175 m. As for the arrival time of the strong wave the eyewitnesses
    176 do not agree. However, most reports concentrated
    177 around 02:55 to 03:05 (09:55 to 10:05 local) which seems
    178 to be a reliable description.}
    179 
    180 FIXME(Ole): Need discussion of model results in this context.
    181 
    182 
     153%The \textsc{anuga} simulation determines a region to be inundated if at some point in time it was covered by at least 1cm of water. This precision in field measurements is impossible to obtain. The inundation boundary is determined by observing water marks and other signs left by the receeding waters. The precision of the observed inundation map is, most likely, at least an order of magnitude worse than the \textsc{anuga} simulation. The simulated inundation based upon a 10cm threshold is shown in Figure~\ref{fig:inundationcomparison10cm}.
     154
     155Both the URS model and the \textsc{anuga} inundation model shows that the event comprises a train of waves some with preciding drawdown effects (ADD details of waveform with a graph from URL and a gauge from \textsc{anuga} and discuss).
    183156
    184157\begin{figure}[ht]
    … …  
    193166
    194167
    195 %================Section=====================
     168%================Section===========================
    196169
    197170\section{Conclusion}
    198171This paper proposes an additional field data benchmark for the verification of tsunami inundation models. Currently, there is a scarcity of appropriate validation datasets due to a lack of well documented historical tsunami impacts. This new benchmark involves the comparison of model predictions of onshore inundation in Patong Bay, Phuket Thailand caused by the 2004 Indian Ocean tsunami. Specifically a field survey mapping of observed inundation is used as a spatially distributed test of model performance. Although two other field data benchmarks exist (FIXME: WHICH?), this proposed benchmark provides a novel investigation of the dynamics of extreme tsunami events not before tested. The benchmark could be further improved with the inclusion of local tide gauge data, against which wave signal could be compared, however, to the authors knowledge no such data exist for this event.
    199172
    200 This paper also illustrates the effectiveness of the proposed new benchmark. The benchmark is used to test the veracity of the hydrodynamic ANUGA designed spcefically to model on-shore inundation. Very good agreement is obtained between the observed and simulated runup. The URSGA tsunami package was also tested. Much worse results were obtained??
     173This paper also illustrates the effectiveness of the proposed new benchmark. The benchmark is used to test the veracity of the hydrodynamic \textsc{anuga} designed spcefically to model on-shore inundation. Very good agreement is obtained between the observed and simulated runup. The \textsc{ursga} tsunami package was also tested. Much worse results were obtained??
    201174
    202175
    203176%================Acknowledgement===================
    204 \section{Acknowledgements}
     177\section*{Acknowledgements}
    205178This project was undertaken at Geoscience Australia and the Department of Mathematics, The Australian National University. The authors would like to thank Niran Chaimanee from the CCOP, Thailand for providing the post 2004 tsunami survey data and the elevation data for Patong beach.
    206179
    207 
    208 
    209 FIXME: Cite more of these and use the proper citation system of LaTeX or even BiBTeX.
    210 
    211 %====================Bibliography==============
    212 %\bibliographystyle{thebibliography}
    213 %\bibliography{tsunami07}
    214 
    215 % GET Bib item from end of this document for Papadopoulus06
     180%====================Bibliography==================
     181\bibliographystyle{plain}
     182\bibliography{tsunami07}
     183
     184%===============Appendicies========================
     185
     186\section*{Appendix A. Figures and Tables}
     187\label{sec:appendix}
     188\subsection*{Datasets and gridding}
     189
     190This section outlines the origins and processes by which the elevation data was created. In general high resolution data sets were embedded into coarser data sets to match the modelled areas of interest.
     191
     192
     193FIXME: Is there a standard template for data lineage.
     194
     195\begin{verbatim}
     196E.g.
     197Data Source:
     1982 min: DBDB 2
     1999 sec: NOAA
     2003 sec: aontehusoe
     201
     202
     203Process:
     204  ...
     205  ...
     206  ...
     207\end{verbatim}
     208 
     209FIXME: Could we have a map with the nested data sets?
     210
     211
     212
     213
     214
     215Gridded data sets used:
     216
     217DBDB2 2 minute of arc grid from the US Naval Research Labs.
     218This grid was also interpolated to 27 sec of arc and used in a nested grid scheme.
     219
     220Indian Ocean 27 sec of arc grid created by:
     221Interpolating the DBDB2 2 minute of arc grid.
     222In the region where the 9 sec grid sits the data was cut out and replaced by the 9 sec data.
     223Any points that deviated from the general trend near the boundary were deleted.
     224The data was then re-gridded.
     225
     226Andaman Sea 9 sec of arc grid created by:
     227Sub-sampling the 3 sec of arc grid from NOAA.
     228In the region where the 3 sec grid sits the data was cut out and replaced by the 3 sec data.
     229Any points that deviated from the general trend near the boundary were deleted.
     230The data was then re-gridded.
     231
     232Thailand off-shore 3 sec of arc grid created by:
     233cropping a much larger 3 sec of arc grid covering the whole of the Andaman Sea which itself was based on Thai charts 45 and 362.
     234This grid was obtained from NOAA.
     235In the region where the 1 sec grid sits the data was cut out and replaced by the 1 sec data.
     236Any points that deviated from the general trend near the boundary were deleted.
     237The data was then re-gridded.
     238
     239Patong Bay 1 second of arc grid created from:
     240elevation data contained in a GIS of Patong Bay supplied by Niran Chaimanee, Geo-environment Sector Manager, CCOP T/S, Bangkok.
     241Digitised Thai Navy bathymetry chart no 358.
     242
     243The sub-sampling of larger grids was performed by using {\bf resample}  a GMT program.
     244The gridding of data was performed using {\bf Intrepid} a commercial geophysical processing package developed by Intrepid Geophysics.
     245The gridding scheme was nearest neighbour followed by minimum curvature akima spline smoothing.
     246
     247
     248
     249\subsection*{Earthquake Source Model}
     250FIXME: Is this appendix needed?
     251
     252The earthquake source model of Chlieh was adopted to generate the tsunami simulation. This model was created by carefull inversion of the seismic
     253data and fits both coseismic, tsunami and GPS data in the Andaman Sea well.
     254
     255\subsection*{Tsunami Propagation}
     256FIXME: Is this appendix needed?
     257
     258To to generate and propagate the tsunami the URS code was used. This program solves the shallow water equations using the finite difference method.
     259It can also be used in a nexted grid scheme and does on-shore inundation.
     260
     261%%%%%%%%%%%%%%%%%%%%%%%
     262
     263\end{document}
     264
     265
     266Main source of uncertainty arises from inaccuracies in initial condition (source), inaccurate bathymetry data, to a lesser extent friction
     267
     268single experiment can refute model but cannot validate it. Need as many tests as possible to be confident in rpediction. Question arises. How mnay should we do. With finite experiments more weight should be given to a particular experiment if the range of the inout function and the material properties are both broad so that the universal character of the model is tested.
     269
     270Expressions:
     271sufficient verification/falsification of model
     272Confidently utilise a model
     273
     274Predictive valdiation of only one aspect of model evaluation. Need to assess model explanation.
     275
     276Conservation of mass
     277convergence
     278
     279spatial and temporal discretisation errors, round off errors due to limited numerical precision
     280
     281analytical benchmarking:
     282ensuring equations are solved accurately
     283single wave on a beach
     284Solitary wave on composite beach
     285subaerial landslide on simple beach
     286
     287Analytical solutions only represent idealised and simplfied events that do not fully capture the complexity of 'real' flows. Provide temporally and spatially distributed data that field data can rearely match.
     288
     289scale comparisions (laboratory benchmarking):
     290Scale differences are not belived to be important. scale experiments generally do not have same bootom firction characteristics as real scenario but has not proven to be a problem. The long wavelngth of tsunami tends to mean that the friction is less important in comparison to the motion of the wave
     291Single wave on a simple beacj
     292Solitary wave on composite beach
     293Conical island
     294Monai Valley
     295Landslide
     296
     297includes comparisons with validation data sets generated by other models of higher dimensionality and resolution.
     298
     299Often flow geometries are simplified
     300
     301
     302Field benchmarking:
     303Most important verification process
     304Hydrodynamic inversion to predict the source is an ill posed problem
     30512 July 1993 Hokkaido-Nansei-Oki tsunami around Okushiri Island Japan exreme runup height of 31.7m was found at the tip of a narrow gulley with the small cove at Monai
     30617 November 2003 Rat Islands Tsunami
     307
     308Construction of more than one model can reveal biases in a single model. Two types of comparisons 1 between those that are comceptually simailar and those that re different. In former case interested in how choice of numerical solver and discretisation effects results and the later can help determine the level of physical processs representation necessary to represent an observed data set.
     309
     310Movinf to field data increases the gnereality and siginificance of svientifice evidence obatined. However we also significantly incerase the uncertainty of the validation experioment that may constrain the ability to make unequivacol statments. E.g. in bathymetry source condition friction.
     311
     312Calibratino of the model is often used to compensate for uncertainty in the model inputs. Calibartion results in a further loss of experimental control as a unique solution may not exist.
     313
     314verfication need to assess point data, spatially distributed data and bulk (lumped) data.
     315
     316Synolakis et. al~\cite{synolakis07} detail two field events that have been previoulsy used to validate tsunami models, the Hokkaido-Nansei-Oki tsunami that occured around Okushiri Island, Japan on 2nd of July 1993 and the Rat Islands Tsunami that inundated the occured off the coast of Alaska on the 17th of November 2003.
     317
     318
     319inundation map only useful if mesh and topography resolution fine enough hard to measure what the model predicts how deep does inundation need to be for it to be visible during a field study
     320
     321Notes:
     322Okushiri provides an example of extreme runup genereated from reflections and constructive interference resulting from local topography and bathymetry. Numerous point sites at which runup elevations were observed are available.  The highest runup of 31.7 m in a valley north of Monai needs to be approximated with the numerical model. In addition, two tide gage records at Iwanai and Esashi need to be estimated.
     323
     324
     325
     326Rat Island tsuanmi provides a good test for real-time forecasting models since tsnumai was recorded at three tsunameters. The test requires matching the propagation model data with the recordings to constrain the tsunami source model. The inundation model is to reproduce the tide gauge record at Hilo.
     327
     328Patong Bay benchmark provides spatially distributed field data for comparison.
     329
     330single experiment can refute model but cannot validate it. Need as many tests as possible to be confident in prediction. Question arises. How mnay should we do.
     331
     332DO I SAY WE HAVE MUX @ FILES DESCRIBING SHAPE OF WAVE YES. MAKES CONSISTENT
     333
     334Notes:  * Model source developed independently of inundation data.
     335        * Patong region was chosen because high resolution inundation map and bathymetry and topography data was available there
     336
     337Geoscience Australia, in an open collaboration with the Mathematical Sciences Institute, The Australian National University, is developing a software application, \textsc{anuga}, to model the hydrodynamics of tsunamis, floods and storm surges. The open source software implements a finite volume central-upwind Godunov method to solve the non-linear depth-averaged shallow water wave equations. This paper investigates the veracity of \textsc{anuga}  when used to model tsunami inundation.  A particular aim was to make use of the comparatively large amount of observed data corresponding to the Indian ocean tsunmai event of December 2004, to provide a conditional assessment of the computational model's performance. Specifically a comparison is made between an inundation map, constructed from observed data, against modelled maximum inundation. This comparison shows that there is very good agreement between the simulated and observed values. The sensitivity of model results to the resolution of bathymetry data used in the model was also investigated. It was found that the performance of the model could be drastically improved by using finer bathymetric data which better captures local topographic features. The effects of two different source models was also explored.
     338
     339different even types submarine mass failure generate larger events because of proximity more directional wave generation
     340
     341even if data is available it is hard to access
    216342
    217343\begin{thebibliography}{7}
    … …  
    282408\end{thebibliography}
    283409
    284 
    285 %===============Appendicis
    286 
    287 \section*{Appendix A. Figures and Tables}
    288 
    289 \subsection{Datasets and gridding}
    290 
    291 This section outlines the origins and processes by which the elevation data was created. In general high resolution data sets were embedded into coarser data sets to match the modelled areas of interest.
    292 
    293 
    294 FIXME: Is there a standard template for data lineage.
    295 
    296 \begin{verbatim}
    297 E.g.
    298 Data Source:
    299 2 min: DBDB 2
    300 9 sec: NOAA
    301 3 sec: aontehusoe
    302 
    303 
    304 Process:
    305   ...
    306   ...
    307   ...
    308 \end{verbatim}
    309  
    310 FIXME: Could we have a map with the nested data sets?
    311 
    312 
    313 
    314 
    315 
    316 Gridded data sets used:
    317 
    318 DBDB2 2 minute of arc grid from the US Naval Research Labs.
    319 This grid was also interpolated to 27 sec of arc and used in a nested grid scheme.
    320 
    321 Indian Ocean 27 sec of arc grid created by:
    322 Interpolating the DBDB2 2 minute of arc grid.
    323 In the region where the 9 sec grid sits the data was cut out and replaced by the 9 sec data.
    324 Any points that deviated from the general trend near the boundary were deleted.
    325 The data was then re-gridded.
    326 
    327 Andaman Sea 9 sec of arc grid created by:
    328 Sub-sampling the 3 sec of arc grid from NOAA.
    329 In the region where the 3 sec grid sits the data was cut out and replaced by the 3 sec data.
    330 Any points that deviated from the general trend near the boundary were deleted.
    331 The data was then re-gridded.
    332 
    333 Thailand off-shore 3 sec of arc grid created by:
    334 cropping a much larger 3 sec of arc grid covering the whole of the Andaman Sea which itself was based on Thai charts 45 and 362.
    335 This grid was obtained from NOAA.
    336 In the region where the 1 sec grid sits the data was cut out and replaced by the 1 sec data.
    337 Any points that deviated from the general trend near the boundary were deleted.
    338 The data was then re-gridded.
    339 
    340 Patong Bay 1 second of arc grid created from:
    341 elevation data contained in a GIS of Patong Bay supplied by Niran Chaimanee, Geo-environment Sector Manager, CCOP T/S, Bangkok.
    342 Digitised Thai Navy bathymetry chart no 358.
    343 
    344 The sub-sampling of larger grids was performed by using {\bf resample}  a GMT program.
    345 The gridding of data was performed using {\bf Intrepid} a commercial geophysical processing package developed by Intrepid Geophysics.
    346 The gridding scheme was nearest neighbour followed by minimum curvature akima spline smoothing.
    347 
    348 
    349 
    350 \subsection{Earthquake Source Model}
    351 FIXME: Is this appendix needed?
    352 
    353 The earthquake source model of Chlieh was adopted to generate the tsunami simulation. This model was created by carefull inversion of the seismic
    354 data and fits both coseismic, tsunami and GPS data in the Andaman Sea well.
    355 
    356 \subsection{Tsunami Propagation}
    357 FIXME: Is this appendix needed?
    358 
    359 To to generate and propagate the tsunami the URS code was used. This program solves the shallow water equations using the finite difference method.
    360 It can also be used in a nexted grid scheme and does on-shore inundation.
    361 
    362 %%%%%%%%%%%%%%%%%%%%%%%
    363 
    364 \end{document}
    365 
    366 
    367 Main source of uncertainty arises from inaccuracies in initial condition (source), inaccurate bathymetry data, to a lesser extent friction
    368 
    369 single experiment can refute model but cannot validate it. Need as many tests as possible to be confident in rpediction. Question arises. How mnay should we do. With finite experiments more weight should be given to a particular experiment if the range of the inout function and the material properties are both broad so that the universal character of the model is tested.
    370 
    371 Expressions:
    372 sufficient verification/falsification of model
    373 Confidently utilise a model
    374 
    375 Predictive valdiation of only one aspect of model evaluation. Need to assess model explanation.
    376 
    377 Conservation of mass
    378 convergence
    379 
    380 spatial and temporal discretisation errors, round off errors due to limited numerical precision
    381 
    382 analytical benchmarking:
    383 ensuring equations are solved accurately
    384 single wave on a beach
    385 Solitary wave on composite beach
    386 subaerial landslide on simple beach
    387 
    388 Analytical solutions only represent idealised and simplfied events that do not fully capture the complexity of 'real' flows. Provide temporally and spatially distributed data that field data can rearely match.
    389 
    390 scale comparisions (laboratory benchmarking):
    391 Scale differences are not belived to be important. scale experiments generally do not have same bootom firction characteristics as real scenario but has not proven to be a problem. The long wavelngth of tsunami tends to mean that the friction is less important in comparison to the motion of the wave
    392 Single wave on a simple beacj
    393 Solitary wave on composite beach
    394 Conical island
    395 Monai Valley
    396 Landslide
    397 
    398 includes comparisons with validation data sets generated by other models of higher dimensionality and resolution.
    399 
    400 Often flow geometries are simplified
    401 
    402 
    403 Field benchmarking:
    404 Most important verification process
    405 Hydrodynamic inversion to predict the source is an ill posed problem
    406 12 July 1993 Hokkaido-Nansei-Oki tsunami around Okushiri Island Japan exreme runup height of 31.7m was found at the tip of a narrow gulley with the small cove at Monai
    407 17 November 2003 Rat Islands Tsunami
    408 
    409 Construction of more than one model can reveal biases in a single model. Two types of comparisons 1 between those that are comceptually simailar and those that re different. In former case interested in how choice of numerical solver and discretisation effects results and the later can help determine the level of physical processs representation necessary to represent an observed data set.
    410 
    411 Movinf to field data increases the gnereality and siginificance of svientifice evidence obatined. However we also significantly incerase the uncertainty of the validation experioment that may constrain the ability to make unequivacol statments. E.g. in bathymetry source condition friction.
    412 
    413 Calibratino of the model is often used to compensate for uncertainty in the model inputs. Calibartion results in a further loss of experimental control as a unique solution may not exist.
    414 
    415 verfication need to assess point data, spatially distributed data and bulk (lumped) data.
    416 
    417 Synolakis et. al~\cite{synolakis07} detail two field events that have been previoulsy used to validate tsunami models, the Hokkaido-Nansei-Oki tsunami that occured around Okushiri Island, Japan on 2nd of July 1993 and the Rat Islands Tsunami that inundated the occured off the coast of Alaska on the 17th of November 2003.
    418 
    419 
    420 inundation map only useful if mesh and topography resolution fine enough hard to measure what the model predicts how deep does inundation need to be for it to be visible during a field study
    421 
    422 Notes:
    423 Okushiri provides an example of extreme runup genereated from reflections and constructive interference resulting from local topography and bathymetry. Numerous point sites at which runup elevations were observed are available.  The highest runup of 31.7 m in a valley north of Monai needs to be approximated with the numerical model. In addition, two tide gage records at Iwanai and Esashi need to be estimated.
    424 
    425 
    426 
    427 Rat Island tsuanmi provides a good test for real-time forecasting models since tsnumai was recorded at three tsunameters. The test requires matching the propagation model data with the recordings to constrain the tsunami source model. The inundation model is to reproduce the tide gauge record at Hilo.
    428 
    429 Patong Bay benchmark provides spatially distributed field data for comparison.
    430 
    431 single experiment can refute model but cannot validate it. Need as many tests as possible to be confident in prediction. Question arises. How mnay should we do.
    432 
    433 DO I SAY WE HAVE MUX @ FILES DESCRIBING SHAPE OF WAVE YES. MAKES CONSISTENT
    434 
    435 Notes:  * Model source developed independently of inundation data.
    436         * Patong region was chosen because high resolution inundation map and bathymetry and topography data was available there
    437 
    438 Geoscience Australia, in an open collaboration with the Mathematical Sciences Institute, The Australian National University, is developing a software application, ANUGA, to model the hydrodynamics of tsunamis, floods and storm surges. The open source software implements a finite volume central-upwind Godunov method to solve the non-linear depth-averaged shallow water wave equations. This paper investigates the veracity of ANUGA  when used to model tsunami inundation.  A particular aim was to make use of the comparatively large amount of observed data corresponding to the Indian ocean tsunmai event of December 2004, to provide a conditional assessment of the computational model's performance. Specifically a comparison is made between an inundation map, constructed from observed data, against modelled maximum inundation. This comparison shows that there is very good agreement between the simulated and observed values. The sensitivity of model results to the resolution of bathymetry data used in the model was also investigated. It was found that the performance of the model could be drastically improved by using finer bathymetric data which better captures local topographic features. The effects of two different source models was also explored.
    439 
    440 different even types submarine mass failure generate larger events because of proximity more directional wave generation
    441 
    442 even if data is available it is hard to access
    443 
    444 article={ioualalen07,
    445 title={Modeling the 26 December 2004 Indian Ocean tsunami: Case study of impact in Thailand},
    446 author=-{Ioualalen, M. and Asavanant, J. and  Kaewbanjak, N. and Grilli, S.~T. and Kirby, J.~T. and Watts, P.},
    447 year={2007},
    448 journal ={ J. Geophys. Res.},
    449 volume={112},
    450 doi={http://dx.doi.org/10.1029/2006JC003850}
    451 }
    452 
    453 article={hirata06
    454 title={The 2004 Indian Ocean tsunami: Tsunami source model from satellite altimetry},
    455 author={Hirata, K. and Satake, K. and Tanioka, Y. and  Kuragano, T. and Hasegawa, Y. and   Hayashi, Y. and Hamada, N.},
    456 journal={Earth, Planets and Space}
    457 year={2006},
    458 volume={58},
    459 number={2},
    460 pages={195--201}
    461 }
    462 
    463 
    464 article={papadopoulos06
    465 title={The large tsunami of 26 December 2004: Field observations and eyewitnesses accounts from Sri Lanka, Maldives Is. and Thailand},
    466 author={Gerassimos A. Papadopoulos, Riccardo Caputo, Brian McAdoo, Spyros Pavlides, Vassilios Karastathis,  Fokaefs1, Katerina Orfanogiannaki1, and Sotiris Valkaniotis},
    467 journal={Earth, Planets and Space}
    468 year={2006},
    469 volume={58},
    470 pages={233--241}
    471 }
    472 
    473 
    474 @InBook{asavanant08,
    475 ALTauthor = {Asavanant, J. and  Ioualalen, M. and Kaewbanjak, N. and Grilli, S.~T. and Watts, P. and Kirby, J.~T. and Shi, F.},
    476 ALTeditor = {},
    477 title = {Modeling, Simulation and Optimization of Complex Processes},
    478 chapter = {Numerical Simulation of the December 26, 2004: Indian Ocean Tsunami },
    479 publisher = {   Springer Berlin Heidelberg},
    480 year = {2008},
    481 pages = {59--68},
    482 }
    483 
    484 @article{grilli07,
    485 author = {St\'{e}phan T. Grilli and Mansour Ioualalen and Jack Asavanant and Fengyan Shi and James T. Kirby and Philip Watts},
    486 title = {Source Constraints and Model Simulation of the December 26, 2004, Indian Ocean Tsunami},
    487 publisher = {ASCE},
    488 year = {2007},
    489 journal = {Journal of Waterway, Port, Coastal, and Ocean Engineering},
    490 volume = {133},
    491 number = {6},
    492 pages = {414-428},
    493 url = {http://link.aip.org/link/?QWW/133/414/1},
    494 doi = {10.1061/(ASCE)0733-950X(2007)133:6(414)}
    495 }
     410In \cite{papadopoulos06} eyewitness accounts report
     411\emph{In Patong beach, most people observed at least two
     412waves. It is likely that the leading wave described in both
     413Sri Lanka and Maldives was not observed in Patong beach.
     414What people said is that the first sea motion was a retreat
     415of more than 100 m. A few minutes later the strong wave
     416arrived. Then, after another 5 or 10 min. one more wave attacked
     417but less violently than the first one. Nearly all the
     418interviewed persons reported that the tsunami inundation
     419in the Patong beach varied from 150 m to at least 750 m
     420(Fig. 16). One eyewitness reported inundation of only 20
     421m. As for the arrival time of the strong wave the eyewitnesses
     422do not agree. However, most reports concentrated
     423around 02:55 to 03:05 (09:55 to 10:05 local) which seems
     424to be a reliable description.}
     425
     426FIXME(Ole): Need discussion of model results in this context.
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