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28 | |
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29 | \title{Inundation Modelling from an Earthquake Source} |
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30 | \date{} |
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31 | |
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32 | \begin{document} |
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33 | |
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34 | \maketitle |
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35 | \begin{abstract} |
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36 | The Risk Research Group at Geoscience Australia is playing a role in building |
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37 | the capability for the Australian Tsunami Warning System (ATWS). |
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38 | The ATWS aims to detect and warn the community |
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39 | of tsunami-genic events as well as develop community education programs for |
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40 | preparation of the event. Risk mitigation involves understanding the relative |
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41 | risk |
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42 | of tsunamis to communities so that appropropriate evacuation plans can be |
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43 | put in place. |
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44 | To develop an understanding of the risk, the Risk Research Group is developing |
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45 | decision support tools to assist emergency managers. These tools consist |
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46 | of inundation |
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47 | maps and damage modelling overlaid on aerial photography of the region |
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48 | detailing critical |
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49 | infrastructure. This report deals with the tsunami inundation modelling |
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50 | and the interaction with the event propagation model, Method of |
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51 | Splitting Tsunami (MOST). |
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52 | |
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53 | \end{abstract} |
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54 | |
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55 | \tableofcontents |
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56 | |
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57 | \section{Introduction} |
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58 | \label{intro} |
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59 | |
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60 | To determine tsunami risk, we follow the risk methodology of |
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61 | determining the hazard, consequence and |
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62 | exposure. The tsunami hazard can be generated by |
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63 | submarine earthquakes and mass failures, as well as volcanoes and asteroid |
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64 | impacts. Here, we concentrate on submarine earthquakes only. The |
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65 | Method of Splitting Tsunami (MOST) models the earthquake event and |
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66 | propagates the tsunami wave in deep water, \cite{titov:most}. |
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67 | GA has used this model to develop |
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68 | a preliminary hazard map for Australia which is based |
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69 | on generating a series of earthquakes along the relevant subduction |
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70 | zones surrounding Australia. The map details the average wave height |
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71 | at the 50m contour line and has been used in nominating areas of |
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72 | detailed inundation modelling by the Fire and Emergency Services Authority |
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73 | in Western Australia. MOST uses a finite difference technique and is |
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74 | based on a fixed grid structure. Inputs include bathymetric data, typically |
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75 | on the order of 100m grid spacing, and details regarding the source, such |
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76 | as location, size, slip angle, for example. |
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77 | |
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78 | In determining the |
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79 | consequence of the tsunami wave once is reaches the coastline, |
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80 | we use the software tool ANUGA which solves the shallow water |
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81 | wave equation to |
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82 | calculate the maximum inundation depth ashore. ANUGA uses the |
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83 | finite volume technique, \cite{ON:modsim} with the |
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84 | advantage being that the cell resolution can be changed |
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85 | according to areas of interest and that wetting and drying |
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86 | is treated robustly as part of the numerical scheme. |
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87 | ANUGA requires a number |
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88 | of inputs including on and offshore data, |
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89 | an initial condition (such as the tidal height), forcing |
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90 | terms (such as wind) and the boundary condition (such as the form of |
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91 | the tsunami wave). This report discusses the details of the latter point, |
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92 | i.e the interaction between ANUGA and MOST |
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93 | focussing on the location at which information is ``best'' |
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94 | passed from one model |
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95 | to the next. |
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96 | |
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97 | Drivers for this study surround computational processing time |
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98 | to develop both {\it tactical} and {\it strategic} decision support tools. |
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99 | Tactical tools support ``real time'' consequence prediction for |
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100 | emergency manager use |
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101 | to obtain assessments of tsunami impact and expected |
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102 | consequences to guide initial resource deployment. Strategic tools are based |
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103 | on using estimated recurrence rates of tsunamigenic events (the hazard), |
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104 | the modelled |
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105 | inundation and associated damage (exposure) |
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106 | to present a national tsunami risk map. |
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107 | On another strategic level, |
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108 | the precomputed simulations |
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109 | and risk maps will comprise a library of scenarios for the Australian Tsunami |
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110 | Warning System to assist in mitigation, warning, response and community |
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111 | recovery in the event of a tsunami disaster. |
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112 | |
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113 | \section{The modelling environment} |
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114 | \label{models} |
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115 | |
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116 | The purpose of this section is to briefly describe the process of how |
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117 | ANUGA and MOST interact through the boundary condition. MOST is |
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118 | based on a fixed grid and outputs water depth and momentum at |
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119 | each grid point. For the preliminary hazard map, a 250m (?) grid was used. |
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120 | By contrast, ANUGA uses an unstructured triangular mesh which therefore |
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121 | calls for interpolation from the MOST output to the defined boundary. As |
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122 | MOST is modelling the tsunami wave from its source and is often made |
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123 | up of a series of waves, |
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124 | ANUGA needs to account for its time varying nature. |
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125 | ANUGA deals with a time varying boundary in the following way. |
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126 | |
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127 | |
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128 | \section{Comparisons} |
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129 | \label{compare} |
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130 | |
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131 | This section details a range of comparisons at |
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132 | virtual ``gauge'' points located |
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133 | within the study area, including the boundary. Note, these gauges are |
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134 | constructed for computational purposes only and are not physical tide |
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135 | gauges. The purpose is to ascertain |
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136 | any relationships between the bathymetric topography and the ``matching'' |
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137 | of the ANUGA and MOST outputs. The difficult question is to |
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138 | how to define this matching. In this report, we will investigate |
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139 | the comparison between MOST and ANUGA to determine the point of divergence. |
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140 | Secondly, we are also interested in the difference in impact ashore |
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141 | when the boundary is placed at 100m and 50m contour lines. |
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142 | Section \ref{sec:mostanugaonslow} deals with the first |
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143 | issue with Section \ref{sec:compare50100onslow} dealing with the second. |
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144 | |
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145 | |
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146 | Firstly, at what water depth should we place the ANUGA boundary? Where |
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147 | is the transition from deep water to shallow water? Some have |
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148 | suggested this can be determined |
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149 | by the ratio of the water's depth to the wavelength of the wave. |
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150 | In particular, |
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151 | when the depth of the water, |
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152 | $d$, becomes less than one half of the wavelength of the wave, |
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153 | $\lambda$ |
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154 | \footnote{http://electron4.phys.utk.edu/141/dec8/December\%208.htm}. |
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155 | Wavelengths can often be of the order of 100km which would place the |
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156 | transition at 50km! This then aligns with the following NOAA statement, |
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157 | "[t]sunami waves are shallow-water waves with long periods and wave lengths." |
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158 | \footnote{http://www.pmel.noaa.gov/tsunami-hazard/tsunami\_faqs.htm} |
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159 | |
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160 | Unfortunately, this doesn't help the modelling effort as the study area |
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161 | is constrained by UTM zones and the computational load. However, the |
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162 | former issue |
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163 | is planned for investigation and the latter is underway through the |
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164 | parallelisation of ANUGA. |
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165 | |
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166 | need some words here about why 100m has been chosen |
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167 | |
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168 | need some words about the choice of gauge locations. Nick, do they line up |
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169 | to the grid points used in MOST? |
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170 | |
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171 | \subsection{Onslow case study} |
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172 | |
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173 | \subsubsection{MOST and ANUGA comparison - 100m contour} |
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174 | \label{sec:mostanugaonslow} |
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175 | |
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176 | Before considering any comparison, we will investigate how the maximum |
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177 | amplitude varies as the tsunami wave reaches the shore. The theory |
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178 | says that the amplitude will grow and the velocity decrease to zero. |
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179 | |
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180 | have a plot here that has the bed elevation on the x-axis and the |
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181 | maximum amplitude on the y-axis |
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182 | |
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183 | have a plot here that has the bed elevation on the x-axis and the |
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184 | maximum amplitude on the y-axis |
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185 | |
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186 | We want to compare MOST and ANUGA all the way to the shore - as |
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187 | close as practical anyway. It is important to note here |
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188 | that MOST and ANUGA are using different bathymetry data sets, with MOST |
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189 | typically using a much coarser grid than ANUGA. We interpolate |
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190 | both MOST and ANUGA output onto the defined point locations. Due to the |
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191 | fact that ANUGA is utilising a finer resolution bathymetry set, |
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192 | we will expect to see richer detail in the ANUGA output. |
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193 | |
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194 | \input{comparison_onslow} |
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195 | |
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196 | The table should show us where it is appropriate to place |
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197 | the boundary. |
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198 | |
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199 | \begin{table} |
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200 | \label{table:mostanugacomparisononslow} |
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201 | \caption{Comparison in output between ANUGA boundary at 100m |
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202 | MOST output.} |
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203 | \centering |
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204 | \begin{tabular}{|l|l|l|}\hline |
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205 | Point location & MOST & ANUGA \\ \hline |
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206 | & some sort of measure of fit - eg max/min amplitude& \\ \hline |
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207 | \end{tabular} |
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208 | \end{table} |
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209 | |
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210 | or perhaps ditch the table and repeat the graphs above |
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211 | with both ANUGA and MOST |
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212 | |
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213 | \subsubsection{ANUGA comparison - 50m and 100m contour} |
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214 | \label{sec:compare50100onslow} |
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215 | |
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216 | The following shows the time series for the point locations |
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217 | described in Table \ref{table:locationsonslow}. |
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218 | It is evident from the model output when the boundary is placed |
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219 | at the 50m contour does not pick up the |
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220 | detail which is evident in the output for the 100m contour. This |
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221 | is due to the fact that the output |
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222 | for the 100m contour has been propagated by ANUGA which is more effective |
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223 | in modelling the propagation in shallow water. |
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224 | It seems that the maximum amplitudes are |
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225 | effectively matched for most of the locations chosen; |
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226 | see for example the output for the Ocean polygon 1 and 2 locations. |
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227 | |
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228 | \input{50100MOSTcomparison_onslow} |
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229 | |
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230 | It is more instructive in this case to compare differences in |
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231 | inundation depths and extent ashore as the boundary location is changed. |
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232 | Table \ref{table:anugacomparisononslow} lists inundation depths |
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233 | for locations within the internal polygon with the finest resolution. |
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234 | |
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235 | \begin{table} |
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236 | \label{table:anugacomparisononslow} |
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237 | \caption{Comparison in inundation depth at select locations when ANUGA boundary |
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238 | is at the 50m and 100m contour.} |
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239 | \centering |
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240 | \begin{tabular}{|l|l|l|}\hline |
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241 | Point location & Boundary at 50m contour & Boundary at 100m contour \\ \hline |
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242 | & & \\ \hline |
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243 | \end{tabular} |
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244 | \end{table} |
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245 | |
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246 | \begin{figure} |
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247 | \caption{Map showing inundation extent for 50m and 100m contour line.} |
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248 | \label{fig:extentcomparisononslow} |
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249 | \end{figure} |
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250 | |
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251 | \subsection{Pt Hedland case study} |
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252 | |
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253 | \subsubsection{MOST and ANUGA comparison - 100m contour} |
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254 | \label{mostanugapthedland} |
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255 | |
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256 | \begin{table} |
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257 | \label{table:mostanugacomparisonpthedland} |
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258 | \caption{Comparison in output between ANUGA boundary at 100m |
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259 | MOST output.} |
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260 | \centering |
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261 | \begin{tabular}{|l|l|l|}\hline |
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262 | Point location & MOST & ANUGA \\ \hline |
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263 | & some sort of measure of fit & \\ \hline |
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264 | \end{tabular} |
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265 | \end{table} |
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266 | |
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267 | \subsubsection{ANUGA comparison - 50m and 100m contour} |
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268 | \label{compare50100pthedland} |
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269 | |
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270 | %\input{comparison_pt_hedland} |
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271 | |
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272 | \begin{table} |
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273 | \label{table:anugacomparisonpthedland} |
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274 | \caption{Comparison in inundation depth at select location when ANUGA boundary |
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275 | is at the 50m and 100m contour.} |
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276 | \centering |
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277 | \begin{tabular}{|l|l|l|}\hline |
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278 | Point location & Boundary at 50m contour & Boundary at 100m contour \\ \hline |
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279 | & & \\ \hline |
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280 | \end{tabular} |
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281 | \end{table} |
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282 | |
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283 | \begin{figure} |
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284 | \caption{Map showing inundation extent for 50m and 100m contour line.} |
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285 | \label{fig:extentcomparisonpthedland} |
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286 | \end{figure} |
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287 | |
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288 | \section{Summary} |
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289 | \label{summary} |
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290 | |
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291 | \begin{thebibliography}{99} |
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292 | |
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293 | \bibitem{titov:most} Titov, V.V., and F.I. Gonzalez (1997), Implementation |
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294 | and testing of |
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295 | the Method of Splitting Tsunami (MOST) model, NOAA Technical Memorandum |
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296 | ERL PMEL-112. |
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297 | |
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298 | \bibitem{ON:modsim} Nielsen, O., S. Robers, D. Gray, A. McPherson, and |
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299 | A. Hitchman (2005) |
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300 | Hydrodynamic modelling of coastal inundation, MODSIM 2005 International |
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301 | Congress on Modelling and Simulation. Modelling and Simulation Society |
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302 | of Australian and New Zealand, 518-523, \newline URL: |
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303 | http://www.mssanz.org.au/modsim05/papers/nielsen.pdf |
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304 | |
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305 | |
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306 | \end{thebibliography} |
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307 | |
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308 | \end{document} |
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