BIBLIOGRAPHIC REFERENCE

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2 BIBLIOGRAPHIC REFERENCE Power, W. L.; Wang, X.; Barberopoulou, A.; Mueller, C Validation of a deaggregation-based approach for tsunami evacuation mapping, GNS Science Report 2014/ p. W. L. Power, GNS Science, PO Box 30368, Lower Hutt 5040 X. Wang, GNS Science, PO Box 30368, Lower Hutt 5040 A. Barberopoulou, GNS Science, PO Box 30368, Lower Hutt C. Mueller, GNS Science, PO Box 30368, Lower Hutt Currently affiliated to: The National Observatory of Athens, Lofos Nymphon Thissio, PO Box , Athens Institute of Geological and Nuclear Sciences Limited, 2014 ISSN (Print) ISSN (Online) ISBN

3 CONTENTS ABSTRACT... V KEYWORDS... V 1.0 INTRODUCTION VALIDATION APPROACH STUDY SITES AND FIELD SURVEY DATA Digital Elevation Model (DEM) Data Field Survey Data SOURCE MODELS SOURCE MODELS OF THE 2011 TŌHOKU EARTHQUAKE Source Model by Romano et al. (2012) USGS Finite Fault Model Source Model by Dr Laura Wallace EARTHQUAKE SCENARIOS DERIVED FROM PROBABILISTIC TSUNAMI HAZARD ANALYSIS (PTHA) Mw9.36 Earthquake Scenario M W 9.28 Earthquake Scenario NUMERICAL METHODS TSUNAMI SIMULATION MODEL NUMERICAL GRIDS SURFACE ROUGHNESS TSUNAMI SIMULATIONS SIMULATED RESULTS WITH SOURCE MODELS OF THE 2011 TŌHOKU EARTHQUAKE Tsunami Inundation Estimates Tsunami Heights SIMULATED RESULTS WITH EARTHQUAKE SCENARIOS FROM PTHA Tsunami Inundation Estimates Tsunami heights DISCUSSION AND RECOMMENDATIONS CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES GNS Science Report 2014/36 i

4 FIGURES Figure 1.1 Geological setting of study region. The dark shaded area indicates the political range of Tohoku region in Honshu island of Japan Figure 1.2 Observed tsunami inundation limits (white dots) and locations of tsunami height observations (green and red circles see text) in Kesennuma, Japan for the 2011 Tōhoku event Figure 1.3 Observed tsunami inundation limits (dotted white lines) and locations of tsunami height observations (green and red circles see text) in Ishinomaki, Japan for the 2011 Tōhoku event... 6 Figure 1.4 Observed tsunami inundation limits (dotted white lines) and locations of tsunami height observations (green and red circles see text) in Shiogama, Japan for the 2011 Tōhoku event... 7 Figure 1.5 Observed tsunami inundation limits (dotted white lines) and locations of tsunami height observations (green and red circles see text) in Sendai, Japan for the 2011 Tōhoku event... 8 Figure 2.1 Computed vertical seafloor displacement for the source model of Romano et al. (2012) for the 2011 M W9.0 Tōhoku earthquake Figure 2.2 Computed vertical seafloor displacement for USGS Finite Fault model for the 2011 M W9.0 Tōhoku earthquake Figure 2.3 Computed vertical seafloor displacement of Dr Wallace s model for the 2011 Tōhoku earthquake Figure 2.4 Computed tsunami hazard curves for tsunami caused by Japan Trench subduction zone earthquakes, calculated for 20km coastal sections including: a) Kesennuma, b) Ishinomaki, c) Shiogama, d) Sendai Figure 2.5 Computed tsunami hazard curves for tsunami caused by Japan Trench subduction zone earthquakes, assuming that the maximum magnitude for Japan Trench earthquakes could be as low as M W8.6 (see text) Figure 2.6 Computed vertical seafloor displacement for a M W9.36 earthquake scenario Figure 2.7 Computed vertical seafloor displacement for a M W9.28 earthquake scenario Figure 3.1 Nested grid configuration for tsunami simulations Figure 4.1 Computed inundation ranges in Kessennuma for the 2011 Tōhoku event with different source models by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Figure 4.2 Computed inundation ranges in Ishinomaki for the 2011 Tōhoku event with different source models by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Figure 4.3 Computed inundation ranges in Shiogama for the 2011 Tōhoku event with different source models by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Figure 4.4 Computed inundation ranges in Sendai Plain for the 2011 Tōhoku event with different source models by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines Figure 4.5 Google Earth image from 24 March 2011 centred on area C (see Figure 4.3) which shows no obvious indication of tsunami damage, whereas area F to the east shows extensive damage, and area G to the west shows evidence of moderate damage (top) ii GNS Science Report 2014/36

5 Figure 4.6 Figure 4.7 Figure 4.8 Figure 4.9 Figure 4.10 Figure 4.11 Figure 4.12 Figure 4.13 Figure 4.14 Figure 4.15 Comparison between modelled and observed tsunami heights using the measure proposed by Aida (1978) for different source mechanisms of the M W9.0 Tōhoku event Computed inundation ranges in Kessennuma for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Computed inundation ranges in Ishinomaki for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Computed inundation ranges in Shiogama for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Computed inundation ranges in Sendai plain for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Computed inundation ranges in Kessennuma for Mw9.28 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Computed inundation ranges in Ishinomaki for Mw9.28 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Computed inundation ranges in Shiogama for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Computed inundation ranges in Sendai plain for Mw9.28 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively Comparison between modelled and observed tsunami heights using the measure proposed by Aida (1978) for different source mechanisms of the MW9.0 Tōhoku event and the earthquake scenarios derived from PTHA for the north east coast of Japan GNS Science Report 2014/36 iii

6 TABLES Table 2.1 Properties of Japan Trench subduction zone source (from Power, 2013). Mmax is the maximum value of M W, C is the coupling coefficient, and B-value is the Gutenberg- Richter B-value Table 3.1 Manning roughness coefficient, based on Wang et al. (2009) Table 4.1 Tsunami height ratio K and deviation factor κ between the simulations and observations for the source models of the 2011 Mw9.0 Tōhoku Earthquake Table 4.2 Tsunami height ratio K and deviation factor κ between the simulations and observations for all the source scenarios including the two earthquake scenarios derived from PTHA APPENDICES APPENDIX 1: SUMMARY OF PROPOSED LEVEL 3 GUIDELINES APPENDIX 2: RESULTS FROM THE LEVEL 2 GIS RULE FOR SENDAI PLAINS AND KESENNUMA APPENDIX 3: TESTS OF EFFECT OF ROUGHNESS ON INUNDATION EXTENT IN ISHINOMAKI, USING THE WALLACE SOURCE MODEL APPENDIX FIGURES Figure A2.1 Figure A2.2 Figure A3.1 Evacuation zone (yellow shaded) for the Sendai Plains, produced using a maximum possible run-up (at the coast) of 35 m and tidal level of m relative to Tokyo Peil datum. TTJT survey data points (inundation and run-up height; Mori et al., 2012) and maximum inundation extent (blue, copyright: Geographical Survey Institute, Japan) are shown for comparison. From Fraser and Power (2013) Evacuation zone (yellow shaded) for Kesennuma City (Oshima Island is also shown) produced using a maximum possible run-up (at the coast) of 35 m and tidal level m relative to Tokyo Peil datum Computed tsunami inundation extents in Ishinomaki using the Wallace source model of the 2011 Tohoku event iv GNS Science Report 2014/36

7 ABSTRACT In the recent report Review of Tsunami Hazard in New Zealand (2013 Update) a process for defining tsunami evacuation zones was outlined. That process involved modelling tsunami inundation scenarios based on earthquake events selected from a deaggregation of the probabilistic tsunami hazard at the 2500 year return period and 84% level of confidence. Deaggregation is a procedure for identifying individual scenarios that correspond to a particular level of hazard. It has been proposed that this process could be adopted as a replacement/update to the Level 3 tsunami evacuation mapping criteria, as recognised by the Ministry of Civil Defence and Emergency Management. Extensive data on tsunami inundation was collected following the 2011 Tōhoku tsunami in Japan. These data provide an opportunity to validate the proposed evacuation zoning method, by comparing zones developed according to the proposed technique against the actual inundation of the Tōhoku tsunami. A limiting factor in this validation is the quality of the topographic data. The data available for developing the tsunami inundation model was of lower quality than recommended under the proposed Level 3 criteria being based on interpolated 10m contour data, rather than having 1m or better vertical accuracy as under the proposed criteria. Four study sites were used for the validation exercise: Kesennuma, Ishinomaki, Shiogama, and the Sendai Plains. All of these are on the east coast of the Tōhoku Region, Honshu, Japan. In three of the four sites the proposed Level 3 approach to evacuation zoning produced suitable evacuation zones encompassing the inundation area of the 2011 tsunami. Areas of the remaining study site that were not on reclaimed land were also identified as evacuation zones by the method. Any exceptions were very small in area and appear to be attributable to the inaccuracy of the digital elevation model (DEM). spot height measurements reveal to be within a metre of sea level significantly lower than specified in our DEM model. Some of these areas were not inundated in our tsunami model, but were inundated by the 2011 tsunami. There is good reason to believe that if a DEM of the recommended accuracy for Level 3 had been used these areas would also have been inundated in our tsunami model, and would therefore have been included in the evacuation zone. Within the constraints of the topographic data quality, the results support the use of the proposed Level 3 criteria. KEYWORDS Tsunami, evacuation zone, deaggregation, validation, Tōhoku, East Japan, Probabilistic tsunami hazard assessment GNS Science Report 2014/36 v

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9 1.0 INTRODUCTION The Ministry of Civil Defence and Emergency Management (MCDEM) currently recognises four levels of modelling in determining the degree of potential inundation from a tsunami (MCDEM, 2008): Level 1 is the most basic of the models in which inundation is determined based on a maximum wave height projected inland from the coast to some cut-off elevation ( bathtub model). Level 2 uses a measure of rule-based wave height attenuation inland from the coast. This approach derives a more realistic output than a simple bathtub model but is still a rough estimate which cannot account for physical variations in wave behaviour. The rule is applied to probabilistic coastal wave heights derived separately. Level 3 is a computer-derived simulation model that theoretically allows for complexities that a rule cannot, such as varied surface roughness from different land uses, and water turning corners and travelling laterally to the coast on its inundation path. The model is applied to probabilistic coastal wave heights derived separately. Level 4 is the most complete approach, based on an envelope around all inundations from multiple well-tested computer models covering all credible scenarios and providing the most complex and accurate modelling. All these four levels of inundation modelling require a selection of source scenarios, preferably from probabilistic tsunami hazard analysis (PTHA). The national tsunami hazard review (Power, 2013) outlines a process for choosing scenarios from a Probabilistic Tsunami Hazard Analysis (PTHA) for use in inundation modelling and subsequent evacuation mapping. It has been proposed that this process (Appendix 1) be used to replace, or update, the current Level 3 criteria. However, the proposed process has not previously been tested against a real example of a severe tsunami. Post-tsunami field survey data collected after the 2011 M W 9.0 Tōhoku earthquake and tsunami event in Japan provides an opportunity to test how well the proposed level 3 evacuation mapping process works. 1.1 VALIDATION APPROACH In this validation of the Level 3 approach, tsunami hazard analysis is performed according to the process used in the national tsunami hazard review for New Zealand (Power, 2013), but concerned only with the east coast of the Tōhoku Region of Japan. The Level 3 approach requires drawing an evacuation zone that covers the area inundated by the 1:2500 year tsunami evaluated at the 84% confidence level (see explanation below). First, earthquake sources with the potential to cause tsunami at the study area are identified. Since the goal is to calculate the 2500 year 84% confidence inundation line, it should be sufficient to model only one source region, i.e., subduction-interface earthquakes on the Japan Trench, as this is believed to be the dominant tsunami source region at long return periods. GNS Science Report 2014/36 1

10 The analysis is based on creating synthetic catalogues of earthquakes over a 100,000 year period. Each earthquake scenario in a catalogue is simulated numerically to estimate the tsunami height at the coast in the study area. From the set of tsunami heights a hazard curve is constructed. This process is repeated for 300 different synthetic catalogues, each catalogue involves a sampling of uncertain parameters, such as those that control the earthquake magnitude-frequency distribution. From this a set of different hazard curves is created, whose distribution accounts for the uncertainties in the model; analysis of the set of curves allows us to set confidence limits on the hazard curve, which are effectively equivalent to error bars 2. Scenario earthquakes are determined by deaggregation, which is a process by which individual scenarios can be selected corresponding to specifed points on the hazard curve. In this case we do this by searching the sythetic catalogue to find events with tsunami heights equal to those of the 1:2500 year tsunami at the 84 percent confidence level. Once the appropriate earthquake scenarios are selected from the PTHA, tsunami inundation numerical modelling is conducted with these scenarios to obtain the tsunami inundation ranges and tsunami heights at the proposed study sites in Japan, and the computed results are then compared with the observations from post-tsunami field surveys after the 2011 Tōhoku event for the purpose of validation. The purpose here is to see how the proposed Level 3 method for calculating evacuation zones, based on a 2500 year 84% confidence criteria, would have performed in the 2011 tsunami had it been used to produce evacuation zones for Tōhoku. However, as a first step in validating the hazard model, it was decided to validate, and if necessary calibrate, the tsunami propagation and inundation models for the Tōhoku study sites by using tsunami source models proposed for the 2011 M W 9.0 Tōhoku earthquake and directly comparing the results against field observations. Three source models were adopted for this calibration process: the USGS finite fault model (2014); the fault mechanism by Romano et al. (2012); and source model derived by Dr Laura Wallace at GNS Science, New Zealand. These three source models were used to set up the parameter configurations for tsunami simulations, validate the input data and evaluate the performance of the COMCOT tsunami model. Once acceptable agreement was obtained between the modelled results and the observed data at the four study sites, the same set of numerical configurations were used to calculate tsunami inundations and tsunami heights with the two earthquake scenarios derived from the PTHA. The approach of computing inundation with deaggreagated earthquake scenarios falls under the MCDEM guideline of level 3 inundation modelling. The validation is deemed successful in producing an evacuation zone, if the modelled inundation extents exceed those recorded in the four study sites used in the validation In simple terms the 84 percent confidence level may be considered as the upper limit on an error bar; see Section 6.2 of Power (2013) for a more complete explanation of confidence level. The choice of a 2500 year return period and 84% confidence is part of the specification of the proposed Level 3 evacuation zone guidelines. The zones can be made more, or less, conservative by changing these criteria. One purpose of this report is to allow evaluation of this choice by comparison with an event that is well known to the public. A possible alternative conclusion, if it is found that the evacuation zones do not envelope the 2011 inundation, is that the 2011 tsunami lies outside of the 2500 year return period. Before drawing that conclusion it would be necessary to consider that an approximately similar tsunami occurred on the Tōhoku coast in AD GNS Science Report 2014/36

11 1.2 STUDY SITES AND FIELD SURVEY DATA Four study sites on the east coast of the Tōhoku Region were chosen to validate, and if necessary calibrate, the simulated inundation based on source models of the M W 9.0 Tōhoku event, and to validate the earthquake scenarios derived from the probabilistic tsunami hazard analysis for the north east Tōhoku coast as suitable for evacuation zoning. These four study sites are Kesennuma, Ishinomaki, Shiogama and the Sendai Plain where post-tsunami survey data and relatively high-resolution topographic and bathymetric data were available. Figure 1.1 Geological setting of study region. The dark shaded area indicates the political range of Tohoku region in Honshu island of Japan. The white rectangular box outlines the modelled range in this study and the red cross is the epicentre of the 2011 M w9.0 Tohoku earthquake Digital Elevation Model (DEM) Data The high resolution topographical data is from the Geographical Survey Institute of Japan (GSIJ) at 10m resolution ( 4, and was combined with a manually digitised coastline and bathymetric points based on nautical chart information. The GSIJ topographic dataset is derived from interpolation of 10m contour data (this is a lower quality DEM than is usually recommended for inundation modelling, and implications of this are discussed in Sections 4 and 5). The coastline was digitised using Japanese maps and topographic data. Some bathymetric points from the Japan Oceanographic Data Center JODC-Expert Grid data for Geography (J-EGG500) 500m bathymetry grid ( were also used, and SRTM data (Farr et al., 2007) was used to provide topographic data outside of the inner inundation grids. 4 This downloaded dataset was published on 1/2/2009, and is therefore derived from pre-earthquake topographic maps, see: The data was downloaded prior to the 28/2/2014 update of the Northern Region. The tsunami modelling process applies co-seismic deformation to the digital elevation model, and in this sense pre-earthquake topography data is preferred. GNS Science Report 2014/36 3

12 The topographical and bathymetric data were combined and interpolated to construct the DEM (Digital Elevation Model) data covering the whole source region as well as the east coast of Tōhoku including the four study sites (see Figure 3.1). The DEM datasets were created at three spatial resolutions: 1000m, 500m and 30m. The 1000m dataset covers the whole east coast of Tōhoku and its offshore region including the source area of the 2011 Tōhoku earthquake. The 500m dataset covers all the four study sites and their neighbouring regions. The 30m datasets cover each of the four study sites. For all the DEM datasets, land elevation and water depth are in terms of Mean Sea Level (MSL) Field Survey Data At the four study sites, the field survey data contains both tsunami inundation limits and maximum tsunami heights of the 2011 Tōhoku tsunami event. The field survey data was provided by The 2011 Tōhoku Earthquake Tsunami Joint Survey Group (TTJT) ( Mori et al., 2012) from their post-tsunami surveys. The line of maximum inundation extent is from the Geographical Survey Institute, Japan; The recorded tsunami heights have been corrected against MSL. Figure 1.1 to Figure 1.4 outline the observed tsunami inundation limits (lines of white dots) and the locations of tsunami height observations at the four study sites (red and green circles). Red circles indicate locations where the maximum water level observations in the field survey are below the land surface elevation in our DEM; this colouring has been used to identify inaccuracies in the DEM data 5. 5 Co-seismic subsidence could also cause this effect, but comparison of the differences in level with estimates of co-seismic subsidence show that only a small proportion of the red circles can be explained in that way. 4 GNS Science Report 2014/36

13 Figure 1.2 Observed tsunami inundation limits (white dots) and locations of tsunami height observations (green and red circles see text) in Kesennuma, Japan for the 2011 Tōhoku event. GNS Science Report 2014/36 5

14 Figure 1.3 Observed tsunami inundation limits (dotted white lines) and locations of tsunami height observations (green and red circles see text) in Ishinomaki, Japan for the 2011 Tōhoku event. 6 GNS Science Report 2014/36

15 Figure 1.4 Observed tsunami inundation limits (dotted white lines) and locations of tsunami height observations (green and red circles see text) in Shiogama, Japan for the 2011 Tōhoku event. GNS Science Report 2014/36 7

16 Figure 1.5 Observed tsunami inundation limits (dotted white lines) and locations of tsunami height observations (green and red circles see text) in Sendai, Japan for the 2011 Tōhoku event. 8 GNS Science Report 2014/36

17 2.0 SOURCE MODELS In this study, two groups of source models were used for tsunami inundation modelling in the four study sites for different purposes. The first group of source models includes three source mechanisms proposed for the 2011 M W 9.0 Tōhoku earthquake by Romano et al. (2012), researchers at the USGS (2014), and Laura Wallace (personal comm.)tōhoku. Seafloor displacements were calculated with these three source Tōhokumodels and are used as initial conditions of the tsunami simulations. These three source models were used to check the performance of the tsunami model (COMCOT), and validate the input data (topography, bathymetry and friction parameters). The second group of source models include two earthquake scenarios, derived from PTHA for the northeast coast of Tōhoku. These two scenario earthquakes were determined by deaggregation, which is a process by which individual scenarios can be selected corresponding to specified points on the tsunami hazard curve. In this case scenarios corresponding to the 1:2500 year tsunami at 84% confidence along the north east coast of Japan (the difference between the two scenarios represents the change in knowledge of the Tohoku subduction zone that occurred following the 2011 earthquake). This is the same method proposed for developing tsunami evacuation zones along the coast of New Zealand. Once acceptable agreement is obtained (after parameter tuning if necessary) between the modelled results and the observed data at the four study sites with the former group of models, the same set of numerical configurations will be used to calculate tsunami inundation at the four study sites with the PTHA-derived source models. The approach of computing inundation with the two earthquake scenarios falls under the MCDEM guideline of level 3 inundation modelling. For the validation, the modelled inundation limits and tsunami heights produced by the two earthquake scenarios was compared with observations at the four selected study sites. In a successful validation the modelled tsunami should envelope the observed inundation extents (n.b. this assumes that events such as the one in 2011 have return periods of 2500 years or less). 2.1 SOURCE MODELS OF THE 2011 TŌHOKU EARTHQUAKE Source Model by Romano et al. (2012) In this source model, the co-seismic slip distribution of the M W 9.0 Tōhoku earthquake was derived from a joint inversion of tsunami waveform data (including DART buoys, bottom pressure sensors, coastal wave gauges and GPS-buoys) and static geodetic data by Romano et al. (2012). The earthquake magnitude and maximum slip were computed to be Mw9.1 and 48.0 meters in this model. The vertical seafloor deformation computed from the co-seismic slip distribution of this source model is shown in Figure 2.1. GNS Science Report 2014/36 9

18 Figure 2.1 Computed vertical seafloor displacement for the source model of Romano et al. (2012) for the 2011 M W9.0 Tōhoku earthquake USGS Finite Fault Model This source model was developed in the National Earthquake Information Center (NEIC) of United States Geological Survey (USGS, 2014). In this source model, the slip distribution was inversely calculated on km-by-20km finite fault patches from worldwide seismic waveform recordings with a finite fault inverse algorithm (Ji et al., 2002). The moment magnitude and maximum slip were estimated as Mw9.0 and 33.5m. The final stage of vertical seafloor displacement for this source model was shown in Figure GNS Science Report 2014/36

19 Figure 2.2 Computed vertical seafloor displacement for USGS Finite Fault model for the 2011 M W9.0 Tōhoku earthquake ( Source Model by Dr Laura Wallace Dr Laura Wallace at GNS Science, New Zealand developed a source model by inversely calculating co-seismic slip distribution from continuous GPS 6 (cgps) displacements in Japan (Wallace, personal comm.). In this model, it was assumed that the slip direction on the interface was parallel to the relative motion between the northern Honshu block and the Pacific Plate, the maximum slip was capped at 30 m and the moment magnitude was calculated as M W Continuous GPS provides continually updated data on the precise locations of GPS instruments. GNS Science Report 2014/36 11

20 Figure 2.3 Computed vertical seafloor displacement of Dr Wallace s model for the 2011 Tōhoku earthquake. 2.2 EARTHQUAKE SCENARIOS DERIVED FROM PROBABILISTIC TSUNAMI HAZARD ANALYSIS (PTHA) The proposed Level 3 PTHA method involves dividing the coastline into zones, estimating a hazard curve for each zone, and then performing a deaggregation analysis to identify scenarios consistent with a chosen return period and confidence level (Power, 2013). For the New Zealand tsunami hazard model it was necessary to consider many tsunami sources at a variety of distances i.e., local, regional and distant, since different tsunami sources affect different coasts, and because the hazard model was intended to cover a wide range of return periods. For the current validation study a considerable simplification is possible, as we are only interested in the Tōhoku coast, and only seeking to evaluate the 2500 year, 84% confidence tsunami inundation. The historical record from the Tōhoku coast suggests that the only source required to define the tsunami hazard on this timeframe is the Japan Trench subduction zone (Table 2.1). Distant source tsunami in the Japanese historical record have been significantly smaller than the largest local events. 12 GNS Science Report 2014/36

21 Table 2.1 Properties of Japan Trench subduction zone source (from Power, 2013). Mmax is the maximum value of M W, C is the coupling coefficient, and B-value is the Gutenberg-Richter B-value. Left and Right REL_VEL are the relative velocities between the converging plates in mm/yr at the two ends of the subduction zone. Widthpref is the preferred estimate of the subduction zone width in km. Mmax-min is based on the magnitude of the largest known historical or paleo-tsunami, the value in brackets shows the values for Mmax-pref and Mmax-min that would have been deduced by the same methodology before the 2011 Tōhoku earthquake. Subduction Zone Mmax pref Mmax min Mmax max C pref C min C max B-value pref B-value min B-value - max Left_REL_VEL Right_REL_VEL Length (km) Width pref Japan Trench 9.07 (8.87) 9.00 (8.60) Tsunami propagation modelling of events on the Tōhoku subduction zone were modelled in the same way that New Zealand s local subduction zones were modelled in Power (2013). Specifically, a set of scenario earthquakes and their subsequent tsunami were modelled at a range of magnitudes and locations along the trench, and the calculated tsunami heights at the coast were recorded. This data was used to estimate the tsunami heights of events in a synthetic catalogue of earthquakes, generated to match the properties in Table 2.1, as follows: For each catalogue event, the most closely matching event in the set of precalculated tsunami scenarios was identified, then additional scaling (based on magnitude) was applied to better estimate the tsunami heights caused by each earthquake in the synthetic catalogue. Hazard curves were then generated based on this sequence of tsunami height estimates. See Power (2013) for full details of the probabilistic methodology. Based on analysis of the hazard curves for the study sites (Figure 2.4), and using the same statistical source model for the Japan Trench as used in Power (2013), it was found that the 2500 year 84% confidence tsunami source corresponds to a M W 9.36±0.01 uniform-slip subduction zone earthquake. Hence in the following sections tsunami inundation models initiated by an earthquake of this magnitude are used. It is important to note that the M W 9.36 represents the effective magnitude for a uniform slip earthquake for it to approximate the effects of lower magnitude earthquakes with realistically distributed (non-uniform) slip. Hence it is acceptable that the effective magnitude used for the inundation modelling exceeds the value of the maximum magnitude for the source region, i.e., is greater than Mmax-max in Table 2.1. Validating the appropriateness of this approximation is part of the purpose of this study. GNS Science Report 2014/36 13

22 a) Kesennuma b) Ishinomaki c) Shiogama d) Sendai Figure 2.4 Computed tsunami hazard curves for tsunami caused by Japan Trench subduction zone earthquakes, calculated for 20km coastal sections including: a) Kesennuma, b) Ishinomaki, c) Shiogama, d) Sendai. Note that at long return periods these curves are assumed to approximate the all-sources tsunami hazard curves. It was noted that the statistical source model for the Japan Trench used in Power (2013) was derived after the 2011 Tōhoku earthquake had taken place, and therefore includes the knowledge that M W ~9.0 earthquakes are possible in this region. To more fully replicate the hypothetical situation where the proposed Level 3 method is assumed to have been applied before the 2011 earthquake, it was decided to additionally evaluate the tsunami hazard based on the expectation that the maximum magnitude of earthquakes on the Japan Trench might be as low as M W 8.6 (this being the estimated magnitude of the largest known earthquakes prior to 2011). Changing Mmax-min (see Table 2.1) in the statistical model according to this assumption reduced the magnitude of the 2500 year 84-percent confidence event to M W 9.28±0.01 (Figure 2.5). Consequently in the following sections the impact of a tsunami created by an earthquake of this magnitude is also evaluated. 14 GNS Science Report 2014/36

23 a) Kesennuma b) Ishinomaki c) Shiogama d) Sendai Figure 2.5 Computed tsunami hazard curves for tsunami caused by Japan Trench subduction zone earthquakes, assuming that the maximum magnitude for Japan Trench earthquakes could be as low as M W8.6 (see text). Curves are calculated for 20km coastal sections including: a) Kesennuma, b) Ishinomaki, c) Shiogama, d) Sendai. Note that at long return periods these curves are assumed to approximate the all-sources tsunami hazard curves Mw9.36 Earthquake Scenario This source scenario was developed from the probabilistic tsunami hazard model. This identified a magnitude M W 9.36 earthquake as the tsunami source corresponding to the 2500 year, 84th percentile tsunami hazard at the study sites. The source model has been constructed from the NOAA unit source database (Gica et al., 2008), and assumes a downdip extent of 150 km, and an along strike extent of 1000 km, corresponding to a whole margin earthquake rupture. The initial surface deformation for this scenario is shown in Figure 2.6. GNS Science Report 2014/36 15

24 Figure 2.6 Computed vertical seafloor displacement for a M W9.36 earthquake scenario M W 9.28 Earthquake Scenario This source scenario was developed from the probabilistic tsunami hazard model, after changing the lower bound on the maximum magnitude of earthquakes on the Japan Trench to M W 8.6. In practise it is known that the Japan Trench can support earthquakes of at least M W 9.0, but the use of this assumption was intended to reproduce the state of knowledge that existed prior to the 2011 Tōhoku earthquake. After making this assumption a magnitude M W 9.28 earthquake was identified as the tsunami source corresponding to the 2500 year, 84th percentile tsunami hazard at the study sites. The source model has been constructed from the NOAA unit source database (Gica et al., 2008). The model assumes a down-dip extent of 150 km, and an along strike extent of 900 km. The initial surface deformation for this scenario is shown in Figure GNS Science Report 2014/36

25 Figure 2.7 Computed vertical seafloor displacement for a M W9.28 earthquake scenario. GNS Science Report 2014/36 17

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27 3.0 NUMERICAL METHODS 3.1 TSUNAMI SIMULATION MODEL The tsunami model, COMCOT (Cornell Multi-grid Coupled Tsunami model), was originally developed at Cornell University, USA in 1990 s (Liu et al., 1995) and since 2009 it has been continuing under development at GNS Science, New Zealand (Wang and Power, 2011). Using a modified staggered finite difference scheme to solve linear/nonlinear shallow water equations, COMCOT was developed to investigate the evolution of long waves in the ocean, particularly tsunami, including its generation, propagation, run-up and inundation. To account for the shallowness of water depth and ensure enough spatial resolution in near-shore regions, nested grid configuration is implemented in COMCOT, through which the model can use a relatively larger grid resolution to efficiently simulate the propagation of tsunamis in the deep ocean and then switch to apply finer grid resolutions in coastal regions. In this approach, the computational efficiency and the numerical accuracy will also be well balanced. This model has become publicly available and has been widely used by researchers to study different aspects of tsunami impacts. It has been systematically validated against analytical solutions (Cho, 1995), experimental studies (Liu, Cho and Fujima, 1994; Liu, et al., 1995; Cho, 1995) and benchmark problems (Wang, Orfila and Liu, 2008) and has consistently shown its satisfactory accuracy and efficiency. Some of its applications include the study of the 1960 Chilean Tsunami (Liu, et al., 1994), the 1986 Taiwan Hualien Tsunami (Liu, et al., 1998), the 2005 Algerian Tsunami (Wang and Liu, 2005), the 2004 Indian Ocean Tsunami (Wang and Liu, 2005, 2006, 2007), and the 2009 Samoa tsunami (Beaven et al., 2010). It has also been applied to evaluate the flooding and tsunami forces on structures in the coastal areas of Galle, Matara and Hambantota in Sri Lanka during the 2004 Indian Ocean (Wijetunge et al., 2008). 3.2 NUMERICAL GRIDS It is well known that as tsunami approach to coastal regions from deep ocean, its wave length becomes shorter and the amplitude becomes larger due to the shallowness of water in comparison with those in the deep ocean. Therefore, a variable spatial resolution is necessary in order to maintain the accuracy and efficiency of numerical computations. In this study, nested grids were implemented to deal with the spatial scale variation from the source region to the inundation in the four study sites for the 2011 Tōhoku event. Three levels of grid resolutions were implemented in different grid regions: 30 arc-seconds (firstlevel grid region layer01), 6 arc-seconds (second level grid region layer02) and 1.2 arcseconds (four study sites layer 03 06, ~24m), as shown in Figure 3.1. GNS Science Report 2014/36 19

28 Figure 3.1 Nested grid configuration for tsunami simulations. The left panel shows the nested grid arrangement of first-level grid layer (01) and the second-level grid layer (02). The right panel shows the nested grid arrangement of the second-level grid layer (02) and the four study sites (03-06). The colour scales indicate digitial elevation in meters in terms of MSL. The land elevations and water depths at numerical grids were interpolated from the corresponding DEM dataset. 3.3 SURFACE ROUGHNESS The characteristics of bathymetric and topographic features and friction of the land surface control the extent of inundation dynamics further inland. In COMCOT, Manning s formula is adopted to model these effects. The Manning roughness coefficient n is used to represent surface land use types, such as ground vegetation and buildings. This coefficient can be used as a single value for the entire region or vary according to the land use. Coastal features such as sand dunes, cliff, river mouth and channel or inlets, and vegetation covers as well as residential and industrial areas affect the extent of inundation further inland. Wang et al. (2009) reviewed the published literatures on the friction coefficient values used for inundation modelling, and flood risk and damage assessment studies (van der Sande et al., 2003; Imamura et al., 2006; Murashima et al., 2008), and summarised Manning s roughness n for different land use classes (Table 3.1) 20 GNS Science Report 2014/36

29 Table 3.1 Manning roughness coefficient, based on Wang et al. (2009) Land Use Conditions Manning s roughness n Oceans, Rivers Paved ground (industrial area, township/city road) Arable land (including waste land, open field) Woodland (including orchard, grass, bushes, low density forest, farm) Low density residential areas (building density < 30%) Mid density residential areas (building density 30 50%) 0.03 High density residential areas (building density > 50%) Buildings (large concrete residential or industrial) 0.2 In this study, Manning s roughness coefficients were kept constant across the land areas of each study site. The roughness coefficients for tsunami flooding on land were determined by the predominant types of land use in the four study areas, as identified from satellite images, and the values for roughness in Wang et al. (2009), as tabulated in Table 3.1: Ishinomaki (grid layer 3): combination of arable land, residential and industrial buildings, n=( )/3=0.085; Shiogama (grid layer 4): mid-density residential areas, n=0.03; Sendai Plains (grid layer 5): from arable land, farm land to low density residential areas, n=( )/2=0.025; Kesennuma (grid layer 6): mid-density residential areas, n=0.03. A constant roughness coefficient n=0.013 was used for all the water areas such as rivers and ocean. The use of a constant roughness over the whole on-land grid area represents an approximation as land-use, and hence roughness, varies across the model grid domains. The values chosen for Ishinomaki and Sendai were approximate averages based on the balance of different land-uses in low-lying areas. There is considerable variation in the choice of roughness parameters in the tsunami literature, and no simple process for the validation of roughness parameters as used for tsunami modelling. A major factor in this problem is that the use of bottom friction to describe the effects of impediments to tsunami movement, often from obstacles that do not simply lie on the ground surface and that may themselves change over time due to damage, represents a major approximation of the physical processes involved. A detailed analysis of roughness parameters is beyond the scope of this report, here we simply adopt the choices of Wang et al. (2009). GNS Science Report 2014/36 21

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31 4.0 TSUNAMI SIMULATIONS Tsunami evolutions over a period of ten hours following the earthquake were simulated with COMCOT in order to estimate maximum tsunami inundation limit and tsunami heights for the 2011 Tōhoku event. All the simulations covered the whole evolution process of a tsunami including its generation, propagation, run-up and inundation. Tsunami simulations were run on a DEM adjusted in COMCOT to reflect modelled co-seismic uplift/subsidence in the study areatōhoku. For each source model, linear superposition was used to combine seafloor deformation contributed from different fault patches which was then used as the initial condition for the tsunami simulations. The seafloor deformation was computed according to elastic fault plane theory by assuming fault plane/patches being buried in an elastic half-space medium (Okada, 1985). In addition to the source models of the 2011 Tōhoku earthquake, uniform slip M W 9.36 and M W 9.28 models were run based on deaggregation of the estimated 2500 year, 84% confidence, tsunami hazard (see Section 2 for details). 4.1 SIMULATED RESULTS WITH SOURCE MODELS OF THE 2011 TŌHOKU EARTHQUAKE Tsunami Inundation Estimates The modelled tsunami inundation ranges were determined by the maximum water levels computed in the first ten hours of the tsunami impact, together with land elevation information as specified in the DEM data. Figure 4.1 to Figure 4.4 present the inundation extents as modelled using the Romano et al. (2012), USGS (2014), and Wallace (personal comm.) source models respectively, see Section 2.1 for source details. GNS Science Report 2014/36 23

32 Figure 4.1 Computed inundation ranges in Kessennuma for the 2011 Tōhoku event with different source models by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. 24 GNS Science Report 2014/36

33 B A Figure 4.2 Computed inundation ranges in Ishinomaki for the 2011 Tōhoku event with different source models by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. Yellow letters label locations discussed in the main text. GNS Science Report 2014/36 25

34 E D C Figure 4.3 Computed inundation ranges in Shiogama for the 2011 Tōhoku event with different source models by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. Yellow letters label locations discussed in the main text. 26 GNS Science Report 2014/36

35 Figure 4.4 Computed inundation ranges in Sendai Plain for the 2011 Tōhoku event with different source models by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. All three models based on the 2011 earthquake produced a generally good correspondence with the observed inundation in Kesennuma (upper left subplots). This is likely due to the topographic constraints on inundation, which result from the steep topography in this area. All models underestimate the extent of inundation in the two areas marked by A and B in Figure 4.2 for Ishinomaki. Examination of Google Earth images suggests these are areas of very low-lying land interspersed with drainage ditches, probably areas of reclaimed marshland. It appears that the topographic DEM, constructed from interpolation of contour maps, has systematically overestimated the ground elevation in this area. This is confirmed by examination of spot heights in the Geographical Survey Institute (GSI) 1:2500 maps ( that indicate that these areas lie at or below sea level in post-earthquake data (n.b. co-seismic subsidence is ~0.5 1m, see Figure 2.1 to Figure 2.3), in contrast to our DEM data which typically places area A at ~6 7m, and area B at ~3m (pre-earthquake) 7. 7 An alternative explanation for the lack of inundation in the reclaimed areas is that the roughness parameter was set too high in our model, however tests with lower values of the roughness parameter (see Appendix 3) suggest that this is not the primary factor. GNS Science Report 2014/36 27

36 In general all three models provide a good estimate of inundation around Shiogama (Figure 4.3), when compared against the GSI maximum inundation extent field data. Three exceptions have been identified and investigated: Area C appears to contain an island free of inundation in all of the model results, but is not identified as such in the field data. This is despite the models producing generally good agreement to the inundation extent in the vicinity. We suspect that when identifying the extent of maximum inundation in 2011 this island (of no inundation) was overlooked: examination of post-earthquake Google Earth satellite images for this area showed no obvious signs of tsunami inundation here (see Figure 4.5). Areas D and E also contain isolated hills of up to about 20m that appear not to have been inundated by the tsunami (n.b. observed tsunami heights were generally less than 5m within the bay), but which were not identified in the maximum inundation extent field data. There are also small areas of reclaimed land within the bay whose elevations appear to have been overestimated in a similar way to the reclaimed land around Ishinomaki, though on a much smaller scale. The USGS and Wallace models provide a good match to the inundation extent in Sendai (Figure 4.4), while the Romano model tended to underestimate the extent of inundation here. 28 GNS Science Report 2014/36

37 G C F C F Figure 4.5 Google Earth image from 24 March 2011 centred on area C (see Figure 4.3) which shows no obvious indication of tsunami damage, whereas area F to the east shows extensive damage, and area G to the west shows evidence of moderate damage (top). Google Streetmaps images from April 2013: part of area C in which there is no obvious evidence of tsunami impact (middle), in contrast area F remains as open lots and bare foundations (bottom). GNS Science Report 2014/36 29

38 4.1.2 Tsunami Heights The tsunami heights from the numerical simulations were compared to the recorded tsunami heights at the field survey locations, in order to evaluate the performances of the source models. For the comparisons, a measure proposed by Aida (1978) was adopted to evaluate the agreement between the modelled tsunami heights and the observed tsunami heights and thus the performance of source models. The method uses the geometric average value of ratios of the modelled tsunami heights to the observed tsunami heights at survey locations as a measure of source model performance. It was originally developed to investigate the reliability of a tsunami source model given that observed tsunami heights are available at a set of observations stations (Aida, 1978). In this approach, at survey location i, the ratio of simulated value to observed value is represented by, For N stations in total, the geometric average value K of all the ratios ( ) is defined by the following equation The value K can be used as a correction factor to adjust the simulated tsunami heights such that on average they fit the observed values. K=1 means that on average the simulated tsunami heights match the observed values, K=2 would imply that on average the simulated heights were twice as high as the observations. Factor, an analogy to standard deviation defined by is used to measure the fluctuation in. For each of the source models for the 2011 M W 9.0 Tōhoku earthquake, the geometric average K was evaluated at each of the four study sites as well as all the four sites together as shown in Figure 4.6. Please note that geometric mean calculation only includes those locations where both the observed and the computed tsunami heights are larger than zeros to avoid singularity. 30 GNS Science Report 2014/36

39 Figure 4.6 Comparison between modelled and observed tsunami heights using the measure proposed by Aida (1978) for different source mechanisms of the M W9.0 Tōhoku event. Note that K has been plotted on a logarithmic scale. Table 4.1 Tsunami height ratio K and deviation factor κ between the simulations and observations for the source models of the 2011 Mw9.0 Tōhoku Earthquake Romano et al. USGS Wallace K κ K κ K κ Kessennuma Ishionamaki Shiogama Sendai Overall For those models that attempt to accurately represent the 2011 Japan Tsunami (Romano et al., USGS, Wallace) the desired result should to be as close as possible to K=1, indicating an unbiased model. This has successfully been achieved in the overall results for all three models, despite some within-error-bar variations at particular locations. Overall, given the quality of match between model results and field observations (which included a quantitative comparison of tsunami heights that is presented in this section), and the limits on precision arising from the accuracy of the DEM data, it was decided that no additional tuning of model parameters (in particular roughness) was necessary before proceeding to model the PTHA scenarios. GNS Science Report 2014/36 31

40 4.2 SIMULATED RESULTS WITH EARTHQUAKE SCENARIOS FROM PTHA Tsunami Inundation Estimates For the M W 9.36 earthquake scenario derived from the PTHA study, the modelled inundation ranges at the four study sites are shown in Figure 4.7 to Figure 4.10, in conjunction with the inundation ranges computed with the three source models of the 2011 Tōhoku earthquake. Figure 4.7 Computed inundation ranges in Kessennuma for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. 32 GNS Science Report 2014/36

41 B A Figure 4.8 Computed inundation ranges in Ishinomaki for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. Yellow letters label locations discussed in the main text. GNS Science Report 2014/36 33

42 E D C Figure 4.9 Computed inundation ranges in Shiogama for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. Yellow letters label locations discussed in the main text. 34 GNS Science Report 2014/36

43 Figure 4.10 Computed inundation ranges in Sendai plain for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. GNS Science Report 2014/36 35

44 For the M W 9.28 earthquake scenario derived from the PTHA study, the modelled inundation ranges at the four study sites are shown in Figure 4.11 to Figure 4.14, together with the inundation ranges computed with the three source models of the 2011 Tōhoku earthquake. Figure 4.11 Computed inundation ranges in Kessennuma for Mw9.28 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. 36 GNS Science Report 2014/36

45 B A Figure 4.12 Computed inundation ranges in Ishinomaki for Mw9.28 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. Yellow letters label locations discussed in the main text. GNS Science Report 2014/36 37

46 E D C Figure 4.13 Computed inundation ranges in Shiogama for Mw9.36 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. Yellow letters label locations discussed in the main text. 38 GNS Science Report 2014/36

47 Figure 4.14 Computed inundation ranges in Sendai plain for Mw9.28 earthquake scenario from PTHA (red lines), in combination with inundation ranges simulated with the source models of the 2011 Tōhoku earthquake by Romano et al. (pink lines), USGS (yellow lines) and Wallace (cyan lines), respectively. White dots denote the observed inundation limit and black line represents the shorelines. Both of the PTHA deaggregation models successfully enveloped the 2011 tsunami inundation in correspondence with the observed inundation in Kesennuma (Figure 4.7 and Figure 4.11). The PTHA based estimates of the area susceptible to inundation are noticeably smaller than the equivalent rule-based Level 2 evacuation zones (Fraser and Power, 2013; Appendix 2). This is consistent with our expectations: The rule based approach deliberately tends to overestimate inundation in harbours, because the simple rules need to be able to encompass the wide variety of effects that can occur in that environment, whereas the numerical inundation modelling approach can include more of the specific physics that controls inundation in each site. Both PTHA deaggregation models underestimate the extent of inundation in the areas marked A and B in the figures for Ishinomaki (Figure 4.8 and Figure 4.12). However, this is underestimated to a lesser extent than in the models based on the 2011 earthquake source (as illustrated by pink, yellow and cyan lines). These are areas of very low-lying reclaimed land interspersed with drainage ditches, whose elevation has been significantly GNS Science Report 2014/36 39

48 overestimated in the modelling DEM (see Section 4.1.1). These areas are so low that, if accurately represented in the DEM, co-seismic subsidence alone would be enough to put most of them below high tide level (and many areas below mean sea level). Thus they would be identified as inundated even without the additional factor of tsunami waves propagating up the drainage channels. Hence an accurate DEM would almost certainly result in these areas being placed in the evacuation zone. In reality, co-seismic subsidence in the 2011 earthquake has rendered much of this land unusable. In general both models provide a good estimate of inundation around Shiogama (Figure 4.9 and Figure 4.13) when compared with the GSI maximum inundation extent field data. Two exceptions have been identified and investigated: Area C appears to be a small island free of inundation in both models, but is not identified as such in the field data (see Section 4.1.1). Areas D and E also contain 20m hills that appear not to have been inundated, but were not identified as such in the maximum inundation extent data. These discrepancies are similar to, but smaller than, those identified in the 2011 scenario models (as illustrated by pink, yellow and cyan lines). Both the M W 9.36 and M W 9.28 models significantly overestimate the extent of inundation on the Sendai Plain (Figure 4.10 and Figure 4.14). The plain is intersected north-south by the Joban Expressway that sits on a ~7m high embankment intersected by drainage channels and road bridges. The expressway is not represented in our DEM, though it probably had a significant attenuation effect on the 2011 tsunami, which may explain the extent of inundation overestimation by the model Tsunami heights In order to further examine the validity of the earthquake scenarios derived from PTHA for the east coast of Tōhoku, the modelled tsunami heights from the numerical simulations were also compared to the recorded tsunami heights at the field survey locations, as shown in Figure 4.9, using the same approach described in Section The performances of the three source models of the 2011 Tōhoku earthquake were also included in Figure 4.15, in addition to those of the M w 9.36 and M w 9.28 earthquake scenarios from PTHA. We emphasize that for the purpose of validating the proposed evacuation zoning guidelines it is the inundation extents that are of primary importance, and that the K values are only calculated where the modelled and actual inundations overlap. The procedure presented here is intended to provide a secondary verification of model accuracy. 40 GNS Science Report 2014/36

49 Figure 4.15 Comparison between modelled and observed tsunami heights using the measure proposed by Aida (1978) for different source mechanisms of the MW9.0 Tōhoku event and the earthquake scenarios derived from PTHA for the north east coast of Japan. Note that K has been plotted on a logarithmic scale. For the M W 9.28 and M W 9.36 models from the PTHA analysis, our goal is to have enveloped the actual impacts of the 2011 tsunami, which is achieved by having K consistently greater than 1 (dashed line in Figure 4.15). The detailed values of K and its deviation factor κ are given in Table 4.2. Table 4.2 Tsunami height ratio K and deviation factor κ between the simulations and observations for all the source scenarios including the two earthquake scenarios derived from PTHA. Romano et al. USGS Wallace Mw9.28 Mw9.36 K κ K κ K κ K κ K κ Kessennuma Ishionamaki Shiogama Sendai Overall GNS Science Report 2014/36 41

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51 5.0 DISCUSSION AND RECOMMENDATIONS When applying the proposed Level 3 approach to evacuation modelling we sometimes encountered small isolated hills that were identified as safe areas, but have little area available for further evacuation in a larger event, these are most evident in the models of Shiogama. From an evacuation point of view these locations are not ideal for evacuation as they limit the scope for further retreat if the tsunami turns out to be larger than has been prepared for. Hence it would be preferable to avoid using these for evacuation if larger ridges and hills can be reached in the time available. For reasons such as the one above, and the practical problems that occur when an evacuation zone boundary passes through a building or block of land, we recommend that interpretation by evacuation-mapping specialists, and community consultation, should continue to be essential parts of the process for producing evacuation zone maps from inundation model outputs. Within the limitations imposed by the accuracy of the data used to prepare the preearthquake DEM we propose that the Level 3 approach is successfully validated. However, an unequivocally positive validation would require a DEM model of the full recommended accuracy (vertical errors of less than 1m). Hence we make the recommendation that such a validation be conducted if suitable data can be acquired. GNS Science Report 2014/36 43

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53 6.0 CONCLUSIONS In drawing conclusions from this study it is necessary to bear in mind that the topographic data used is of lower quality than is recommended in the proposed Level 3 evacuation mapping guidelines. The topographic data was based on interpolated 10m contour data, whereas the guidelines recommend a dataset with uncertainty in elevation of 1m or less. Application of the proposed Level 3 approach to evacuation zoning produced suitable evacuation zones encompassing the inundation area of the 2011 tsunami for 3 out of 4 study sites (Kesennuma, Shiogama and Sendai Plains), and for those areas of the fourth study site (Ishinomaki) that were not on reclaimed land. Any exceptions were very small in area and appear to be attributable to the inaccuracy of the digital elevation model (DEM). Ishinomaki contains large expanses of reclaimed land with elevations at or below sea level (post-earthquake). Some of these areas were not identified for evacuation in our method, but were inundated by the 2011 tsunami. There is good reason to believe that if a DEM of the recommended accuracy for Level 3 had been used these areas would also have been within the evacuation zone, as the DEM derived from 10m contours significantly overestimated the elevation here, and in an accurate DEM co-seismic subsidence alone would have placed most of these areas below the high-tide level and therefore in the evacuation zone. The Level 3 approach produced significantly smaller evacuation zones than the rulebased Level 2 approach in the harbour city of Kesennuma, while remaining conservative in relation to the recorded inundation extent. This is consistent with our expectation, and motivates the application of the Level 3 approach for New Zealand coastal cities, many of which are centred around harbours. GNS Science Report 2014/36 45

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55 7.0 ACKNOWLEDGEMENTS We would like to thank report reviewers Stuart Fraser (GNS Science) and David Burbidge (Geoscience Australia) for their insightful comments. We also thank Biljana Lukovic (GNS Science) for GIS support. 8.0 REFERENCES Aida, I. (1978). Reliability of a tsunami source model derived from fault parameters, Journal of Physics of Earth, 26, Beavan, R. J., Wang, X., Holden, C., Wilson, K. J., Power, W. L., Prasetya, G., Bevis, M., & Kautoke, R. (2010). Near-simultaneous great earthquakes at Tongan megathrust and outer rise in September Nature, 466(7309): ; doi: /nature Cho, Y.-S. (1995). Numerical simulation of tsunami and runup. PhD thesis, Cornell University, Farr, T. G., et al. (2007). The shuttle radar topography mission. Review of Geophysics 45. RG2004. doi: /2005rg Fraser, S. A., & Power, W. L. (2013). Validation of a GIS-based attenuation rule for indicative tsunami evacuation zone mapping. GNS Science Report, 2013/2, 21p. Gica, E., Spillane, M. C., Titov, V. V., Chamberlin, C. D., & Newman, J. C. (2008). Development of the forecast propagation database for NOAA s Short-Term Inundation Forecast for Tsunamis (SIFT), NOAA Tech. Memo. OAR PMEL-139, 89 pp. Imamura, F., Yalciner, A. C., & Ozyurt, G. (2006). Tsunami modelling manual, 58 p. ImamuraYalcinerOzyurt_apr06.pdf. Ji, C., Wald, D. J., & Helmberger, D. V. (2002). Source description of the 1999 Hector Mine, California earthquake; Part I: Wavelet domain inversion theory and resolution analysis, Bull. Seism. Soc. Am., Vol 92, No. 4. pp Liu, P. L.-F., Cho, Y.-S., Yoon, S. B., & Seo, S. N. (1994). Numerical simulations of the 1960 Chilean tsunami propagation and inundation at Hilo, Hawaii. In Recent Development in Tsunami Research, pp Kluwer Academic Publishers, Liu, P. L.-F., Cho, Y.-S., & Fujima, K. (1994). Numerical solutions of three-dimensional run-up on a circular island, Proc. Of Int. Sym.: Waves Physical and Numerical Modelling, pp , Canada. Liu, P. L.-F., Cho, Y.-S., Briggs, M. J., Synolakis, C. E., & Kanoglu, U. (1995). Run-up of solitary waves on circular island. J. Fluid Mech., 302: , Liu, P. L.-F., Wang, X., & Salisbury, A. J. (2009). Tsunami hazard and early warning system in South China Sea. Journal of Asian Earth Science. Accepted on Dec 26, 2008, to be published in Liu, P. L.-F., Woo, S.-B., & Cho, Y.-S. (1998). Computer programs for tsunami propagation and inundation. Technical Report, Cornell University, Liu, P. L.-F., & Wang, X. (2008). Tsunami source region parameter identification and tsunami forecasting. Journal of Earthquake and Tsunami. Vol.2, No.2 (2008) pp GNS Science Report 2014/36 47

56 Liu, P. L.-F., Cho, Y.-S., Briggs, M. J., Synolakis, C. E., & Kanoglu, U. (1995). Run-up of solitary waves on circular island. J. Fluid Mech., 302: , Liu, P.L.-F., & Wang, X. (2008). Tsunami source region parameter identification and tsunami forecasting. Journal of Earthquake and Tsunami. Vol.2, No.2 (2008) pp MCDEM. (2008). Tsunami evacuation zones: Director's guideline for Civil Defence Emergency Management Groups [DGL08/08]. Wellington: Ministry of Civil Defence and Emergency Management. Murashima, Y., Takeuchi, H., Imamura, F., Koshimura, S., Fujiwara, K., & Suzuki, T. (2008). The International Archives of the Photogrammetry, remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B8. pp Okada, M. (1985). Surface deformation due to shear and tensile faults in a half-space. Bull. Seism. Soc. Am., 75(4): , Power, W. L. (compiler). (2013). Review of Tsunami Hazard in New Zealand (2013 Update), GNS Science Consultancy Report 2013/ p. Romano, F., Piatanesi, A., Lorito, S., D Agostino, N., Hirata, K., Atzori, S., Yamazaki, Y., & Cocco, M. (2012). Clues from joint inversion of tsunami and geodetic data of the 2011 Tōhoku-Oki earthquake. Scientific Reports 2, 385; DOI: /srep USGS. (2014). Updated Result of the Mar 11, 2011 Mw 9.0 Earthquake Offshore Honshu, Japan. Page maintained by Gavin Hayes (USGS). Access date March Link: Van der Sande, C. J., de Jong, S. M., de Roo, A. P. J. (2003). A segmentation and classification approach of IKONOS-2 imagery for land cover mapping to assist flood risk and flood damage assessment. International Journal of Applied Earth Observation and Geoinformation. Vol.4. pp Wallace, L. (2011). Personal communication, GNS Science. Wang, X., and Liu, P.L.-F. (2005). A numerical investigation of Boumerdes-Zemmouri (Algeria) earthquake and tsunami. Computer Modeling in Engineering and Science, Vol.10, No.2, pp Wang, X., & Liu, P. L.-F. (2006). An analysis of 2004 Sumatra earthquake fault plane mechanisms and Indian Ocean tsunami. Journal of Hydraulic Research, Vol. 44, No.2 (2006), pp Wang, X., & Liu, P. L.-F. (2007). Numerical simulation of the 2004 Indian Ocean tsunami Coastal Effects. Journal of Earthquake and Tsunami. Vol.1, No.3 (2007). pp Wang, X. (2008). Numerical Modelling of surface and internal waves over shallow and intermediate water. PhD thesis, Cornell University Wang, X., Orfila, A., & Liu, P.L.-F. (2008). Numerical simulations of tsunami runup onto a threedimensional beach with shallow water equations. ACOE. vol.10, pp , World Scientific Publishing Co. Wang, X., & Power, W. L. (2011). COMCOT: A Tsunami Generation Propagation and Run-up Model. GNS Science Report 2011/43 in press. Wijetunge, J. J., Wang, X., & Liu, P. L.-F. (2008). Indian ocean tsunami on 26 December 2004: numerical modelling of inundation in three cities on the south coast of Sri Lanka. Journal of Earthquake and Tsunami. Vol.2, No.2 (2008) GNS Science Report 2014/36

57 APPENDICES

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59 APPENDIX 1: SUMMARY OF PROPOSED LEVEL 3 GUIDELINES Previously the guidelines for what constitutes the different Levels for calculating evacuation zones (MCDEM, 2008) focussed only on the calculation methodology. Since the quality of results is also dependent on the quality of input data, we propose that data quality requirements should be included in future guidelines. Stated below are the proposed guidelines for the Level 3 approach to drawing selfevacuation zones, typically identified as Yellow Zones on New Zealand evacuation maps. Data Requirements: A digital elevation model (DEM) based on topographic data with 1m or better vertical accuracy. Bathymetric data for the DEM should be of nautical navigational chart quality or better. The DEM grid (or finite-element mesh) should have a horizontal resolution of 30m or less. Methodology: Deaggregation of the tsunami hazard at the 2500 year, 84% confidence level should be used to define modelling scenarios. Source scenarios should include the six largest source contributors to the deaggregation. Sources that constitute less than 5% of the total deaggregation may be omitted. Inundation should be simulated for each of the identified sources, at the selected magnitude from the deaggregation. If the deaggregation method of Power (2013) is used the sources should be modelled as uniform slip events at the effective magnitude given by the deaggregation. The inundation modelling should assume that the simulated tsunamis occur when the tide level is at Mean High Water Spring the highest tidal level. The evacuation area consists of the area inundated by one or more of the modelled scenarios. Note that derivation of Orange Zones using the Level 3 approach, which are tied to the threat levels issued in tsunami warnings, will require a different method for identifying the set of scenarios to be modelled. The same is true for a Level 3 method for land-use planning and risk assessment, and this may also require a different approach to the interpretation of the results. GNS Science Report 2014/36 51

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61 APPENDIX 2: RESULTS FROM THE LEVEL 2 GIS RULE FOR SENDAI PLAINS AND KESENNUMA These figures present the results of the Level 2 GIS analysis by Fraser and Power (2013) for the Sendai Plains and Kesennuma. The topographic data used to generate the evacuation zones is the same as used in this report. Figure A2.1 Evacuation zone (yellow shaded) for the Sendai Plains, produced using a maximum possible run-up (at the coast) of 35 m and tidal level of m relative to Tokyo Peil datum. TTJT survey data points (inundation and run-up height; Mori et al., 2012) and maximum inundation extent (blue, copyright: Geographical Survey Institute, Japan) are shown for comparison. From Fraser and Power (2013). GNS Science Report 2014/36 53

62 Figure A2.2 Evacuation zone (yellow shaded) for Kesennuma City (Oshima Island is also shown) produced using a maximum possible run-up (at the coast) of 35 m and tidal level m relative to Tokyo Peil datum. TTJT surveyed inundation and run-up data points (Mori et al., 2012) and the extent of maximum inundation (blue, copyright: Geographical Survey Institute, Japan) are shown for comparison. From Fraser and Power (2013). 54 GNS Science Report 2014/36