01 april 2007 Solomon Island tsunami : case study to validate JRC tsunami codes.
Date: 2016-06-15
Institutions: Institute for the Protection and Security of the Citizen
Subjects: Solomon Islands, earthquake, environmental risk prevention, natural disaster, research report

AUTHORS 

01 APRIL 2007 SOLOMON ISLAND TSUNAMI: 
CASE STUDY TO VALIDATE JRC TSUNAMI CODES 

Natalia Zamora1 
Giovanni Franchello2 
Alessandro Annunziato2 
1 - University of Costa Rica 
2 -  Joint Research Centre, European Commission 

EUR 24783 EN  -  2011 

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The mission of the JRC-IPSC is to provide research results and to support EU policy-makers in their effort 
towards  global  security  and  towards  protection  of  European  citizens  from  accidents,  deliberate  attacks, 
fraud and illegal actions against EU policies. 

European Commission 
Joint Research Centre 
Institute for the Protection and Security of the Citizen 

Contact information: Giovanni Franchello 
Address: JRC Ispra Site, Via Enrico Fermi 2749, I-1027 Ispra (VA), Italy 
E-mail: giovanni.franchello@jrc.ec.europa.eu 
Tel.: +39 0332 785066 
Fax: +39 0332 785154 

http://ipsc.jrc.ec.europa.eu/ 
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JRC 62983 

EUR 24783 EN 
ISBN 978-92-79-19852-6 (pdf) 

ISSN 1831-9424  

doi:10.2788/86247  

Luxembourg: Publications Office of the European Union 

© European Union, 2011 

Reproduction is authorised provided the source is acknowledged 

Printed in Italy 

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Executive Summary 

On  April  1st  2007  a  large  earthquake  of  magnitude  8.1  occurred  offshore  Solomon  Islands  at 
20:40:38  UTC.  Numerical  simulations  of  the  tsunami  event  caused  by  the  earthquake  have  been 
performed to compare the results obtained by the SWAN-JRC code (Annunziato, 2007), the TUNAMI 
(Imamura, 1996) and the HYFLUX2 (Franchello, 2008). The analysis conducted using these numerical 
simulations were also compared with NOAA-MOST code unit source results. 

The  tsunami  event  has  been  simulated  considering  several  options  for  the    seismological 
parameters as input data: Finite Fault Model (USGS, 2007), the Centroid Moment Tensor fault model 
and other mechanisms derived from the field survey analysis (Tanioka model). 

The main aim of this study is to assess how the different fault models affect the overall results 
and  to  perform  a  comparison  among  the  various  codes  in  the  wave  propagation  phase.  Another 
objective of this study is to  use HYFLUX2 code to calculate inundation and compare the simulation 
results with site field measurements. 

The  study  has  been  separated  into  two  main  parts.  The  first  one  represents  the  collection  of 
information about focal mechanisms: the fault analysis in chapter 4 covers one of the main aims of this 
research where different fault  scenarios have been tested using published field data. The second part 
describes the  different  calculations  that have been  performed in  order to  analyze  the response of  the 
wave  propagation  models  to  various  fault  deformation  models.  For  the  inundation  assessment,  more 
detailed calculations at 300m grid size resolutions have been performed, using the fault model that best 
represent the deformation. 

The calculations in the propagation assessment subsection were performed using: SWAN-JRC, 
HYFLUX2,  TUNAMI-N2  and  NOAA-MOST  code.  In  the  inundation  assessment  the  HYFLUX2 
numerical code, initialized with the Tanioka fault model was used.  

The  deformation  comparison  with  field  measured  data  shows  that  none  of  the  “quick”  fault 
mechanism was able to estimate correctly the measured value. The best model is the empirical model 
by Tanioka which was obtained by trying to reproduce the measured value.  

From the published fault mechanism the one that shows a better correlation with measurements 
is  the  simple  cosinuosoidal  model.  Results  of  simulations  done  with  300  m  grid,  show  a  maximum 
wave height of 7.5 m. Though the maximum run up reported was 10 m in Tapurai site, Simbi Island, 
the simulation results are encouraging. 

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INDEX  

EXECUTIVE SUMMARY  _____________________________________________ 3 

1. INTRODUCTION ___________________________________________________ 5 

2. ADOPTED NUMERICAL CODES  ____________________________________ 6 

2.1 TSUNAMI WAVE PROPAGATION MODELS  ______________________________________________  6 
2.2 TSUNAMI INUNDATION MODEL ______________________________________________________  8 

3.  TECTONIC SUMMARY AND TSUNAMI EVENT _____________________ 10 

3.1 DESCRIPTION OF THE DEFORMATION ZONE  ___________________________________________  11 

3.2 DESCRIPTION OF THE TSUNAMI EVENT  _________________________ 12 

3.3 IMPACTS ______________________________________________________________________  12 

4. FAULT MODELS ASSESSMENT ____________________________________ 14 

4.1 FAULT MODELS _________________________________________________________________  14 
4.2 FAULT MODEL AND RELATED SIMULATION RESULTS ____________________________________  16 

5. PROPAGATION CALCULATIONS __________________________________ 23 

5.1 CALCULATIONS WITH CMT, FINITE FAULT, USGS AND WITH TANIOKA MODELS _____________  23 
5.2 EARLY WARNING CALCULATIONS (JRC MODEL IN GDACS) _____________________________  30 
5.3 CODE TO CODE COMPARISON WITH TANIOKA MODEL [900 M RESOLUTION GRID] ______________  35 

6. INUNDATION CALCULATIONS [300 M RESOLUTION] _______________ 43 

8.1 GRID I: VELLA LAVELLA, RANONGGA AND GIZO  ______________________________________  44 
8.2 GRID II: SIMBO ISLAND. __________________________________________________________  48 
8.3  GRID III: RENDOVA,  NEW GEORGIA AND PARARA ISLANDS. _____________________________  50 

7. FINAL REMARKS _________________________________________________ 55 

8. REFERENCES ____________________________________________________ 56 

APPENDIX _________________________________________________________ 59 

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1. INTRODUCTION 

On  April  1st  2007  an  earthquake  of  magnitude  8.1  occurred  offshore  the  Solomon  Islands  at 
20:40:38  UTC  causing  a  tsunami  which  affected  the  surrounding  islands.  The  tsunami  caused 
approximately  100 fatalities on the islands close to  the epicentre. The European Commission  Global 
Disaster  Alert  and  Coordination  System  (GDACS),  an  early  warning  system  created  to  alert  the 
humanitarian community of potential disasters, issued a red alert as a result of the so called UNESCO 
Matrix (according to this logic an earthquake of Richter scale greater than 7.5 struck a location in the 
open  sea1.  Simulations  were  automatically  launched  by  the  GDACS  system  and  the  calculated 
maximum wave height was 2.2 m in Vanikuva, Solomon Islands: this simulation was available 30-40 
min after the event. The online calculation code is SWAN-JRC. 

The JRC Tsunami Assessment Tool has been developed to retrieve and perform new calculations 
when requested by the GDACS system. When a new event is detected by GDACS using data from the 
seismological  sources  (USGS,  EMSC),  an  evaluation  of  the  event  is  performed  to  estimate  his 
importance from humanitarian point of view.  

As the crustal deformation is one of the main inputs for a reliable tsunami numerical simulation, 

this research intends to evaluate different fault models together with numerical code behaviours.  

In this report more detailed analyses have been conducted using SWAN-JRC code (Annunziato, 
2007),  the  TUNAMI-N2  (Imamura,  1996)  and  the  HYFLUX2  (Franchello,  2008).  The  analysis 
conducted using these numerical codes were also compared with MOST code unit source results used 
by  US  National  Oceanic  and  Atmospheric  Administration  (NOAA)  The  Solomon  Island  event  is  a 
good  example  to  understand  and  to  evaluate  the  approach  of  these  numerical  codes  in  earthquakes 
occurring  very  close  to  the  coast  and  in  which  tsunami  alert  is  a  challenge  due  to  the  small  time 
available. Near field tsunami events are also good to assess the accuracy of ground deformation which 
constitutes the input of the hydrodynamic models. 

First the various deformation models are analysed and compared with field data. Once the best 
model is identified, it is used to estimate the wave propagation with the codes used for early warning; 
the inundation is calculated using HYFLUX2 code. 

Different  bathymetry  and  topography  resolutions  have  been  used  in  the  analysis.  In  order  to 
reduce the calculation time, the early warning system requires a rather coarse resolution; for this case a 
2.6 min cell size was used. Resolutions of 1.6 min and 0.5 min are also used to compare the results.  

1 In 2007 the pre-calculated tsunami scenario matrix was not yet available; in that case an estimate 
of 2.8 m would have been calculated and thus, the event would have been classified as orange alert. This 
scenario matrix means that the GDACS system does not perform actual tsunami wave propagation calculations after 
an earthquake, but instead uses a database of pre-calculated scenarios. These scenarios have the maximum wave height and 
arrival time for all nearby coastal populated places, which is used to establish an alert level. When no scenario is available, 
the system falls back on the UNESCO method, which is based on earthquake magnitude only. 

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2. ADOPTED NUMERICAL CODES 

2.1 Tsunami wave propagation models 

The  numerical  codes  SWAN-JRC,  TUNAMI-N2  and  HYFLUX2  solve  the  shallow  water 
equations  using  different  numerical  methods:  SWAN  and  TUNAMI  use  the  finite  different  method 
(FD) while HYFLUX2 uses the finite volume method (FV).  

The shallow water equation is commonly used to describe tsunami wave propagation and general 
features of the inundation processes. The shallow water equations can be derived in a number of ways 
and  different  numerical  approaches,  all  of  which  relies  on  the  assumption  that  the  flow  is  vertically 
hydrostatic,  the  fluid  is  incompressible,  the  pressure  at  the  free  surface  is  constant  and  the  vertical 
velocity and the acceleration are negligible. 

The  finite  difference  method  is  largely  used  to  model  Tsunami  wave  propagation  and  run-up. 
Models based on finite difference schemes are usually less time consuming than those based on finite 
volumes.  However,  most  of  the  FD  schemes  fail  when  dealing  with  flow  discontinuities  such  as 
wetting and drying interfaces and bore formation. 

The finite volume method has been developed in the past to simulate dam-break and recently is 
used  also  in  Tsunami  modelling.  The  finite  volume  method  is  conservative  in  terms  of  mass  and 
momentum and, if the dry/wet front is well modelled, the method is particularly suitable for run-up and 
inundation modelling.    

Commonly, most of the numerical tsunami models use nested computational grids from coarse to 
high-resolution, to get more detail into the area of interest. Nested grids are used to have a minimum 
number of nodes in a wavelength in order to resolve the wave with minimum error.  

SWAN-JRC code 

SWAN-JRC  is  the  numerical  code  implemented  for  Global  Disaster  Alerts  and  Coordination 
System (GDACS). GDACS has been jointly developed by the European Commission and the United 
Nations and combines existing web-based disaster information management systems, with the aim to 
alert  the  international  community  in  case  of  major  sudden-onset  disasters  and  to  facilitate  the 
coordination  of  international  response  during  the  relief  phase  of  the  disaster.  When  a  new  event  is 
detected  by  the  seismological  sources  (USGS,  EMSC),  an  evaluation  of  the  event  is  performed  to 
estimate the importance of the event from humanitarian point of view. In case of an earthquake event 
occurring  under  water  and  of  magnitude  greater  than  6.5,  the  JRC  Tsunami  Assessment  Tool  is 
invoked and a new calculation is requested. 

The  SWAN-JRC  model  (Annunziato,  2007)  solves  the  shallow  water  equations  by  the  finite 

difference numerical scheme based on Mader code SWAN (1988). 

SWAN-JRC  code  estimates  also  the  fault  length,  height  and  direction  to  determine  the  initial 
water  displacement.  The  code  initializes  the  calculation  space,  performs  the  travel  time  propagation 
calculation,  verified  at  each  step  if  there  are  locations  reached  by  the  wave  and  thus  updates  the 
visualization and animation files. For early warning purposes the model can run in automatic mode in 
order  to  publish  automatically  the  results  in  the  GDACS  web  site.  For  post  event  calculations  the 
Okada model and Finite Fault Model as well as other earthquake parameters can be used to compare or 
enhance simulation results.  

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TUNAMI-N2 code 

TUNAMI-N2 code was developed by the Disaster Control Research Center through the Tsunami 
Inundation Exchange Modeling (TIME) Program (Goto et al. 1997) and improved by Dao and Tkalich 
(2007). 

 The TUNAMI-N2 code is based on the shallow water equation. The TUNAMI code consists of 

several codes:  

(a) TUNAMI-N1, linear theory with constant grids. 
 (b) TUNAMI-N2, linear theory in deep sea, shallow-water theory in shallow sea and run up on 
land with constant grids. 
 (c) TUNAMI-N3, linear theory with varying grids. 
(d) TUNAMI-F1, linear theory for propagation in the ocean in the spherical co-ordinates.  
(e) TUNAMI-F2. linear theory for propagation in the ocean and coastal waters. \ 
In this analysis TUNAMI-N2 has been used. TUNAMI code is included in the SWAN-JRC suite 

and therefore the results can be easily produced with the same environment as the SWAN code. 

HYFLUX2 code 

The  HyFlux2  model  has  been  developed  to  simulate  severe  inundation  scenario  due  to  dam 
break,  flash  flood  and  tsunami-wave  run-up.  The  model  solves  the  conservative  form  of  the  two-
dimensional shallow water equations using a finite volume method. The interface flux is computed by 
a  Flux  Vector  Splitting  method  for  shallow  water  equations  based  on  a  Godunov-type  approach.  A 
second-order scheme is applied to the water surface level and velocity. Physical models are included to 
deal with bottom steps and shorelines. The second-order scheme together with the shoreline-tracking 
method  makes  the  model  well  balanced  in  respect  to  mass  and  momentum  conservation  laws, 
providing  reliable  and  robust  results.  In  HYFLUX2,  the  numerical  stability  is  ensured  under  the 
Courant-Friedrich-Levy criteria (Franchello, 2009). 

In addition, HYFLUX2 is included in the suite of codes that can be invoked by the SWAN-JRC 

suite, thus enabling an easy comparison of the code results. 

NOAA-MOST code 

The MOST (Method  of Splitting Tsunami)  is  a suite of numerical  simulation  codes capable of 
simulating three processes of tsunami evolution: earthquake, transoceanic propagation and inundation.  

MOST Tsunami modelling proceeds in three distinct stages: 

• A Deformation Phase generates the initial conditions for a tsunami by simulating ocean 

floor changes due to a seismic event. 

•  A  Propagation  Phase  propagates  the  generated  tsunami  across  deep  ocean  using 

Nonlinear Shallow Water (NSW) wave equations.  

• An Inundation Phase simulates the shallow ocean behaviour of a tsunami by extending 
the  NSW  calculations  using  a  multi-grid  “run-up”  algorithm  to  predict  coastal  flooding  and 
inundation. 

The  tsunami  generation  process  is  based  on  a  fault  plane  model  of  the  earthquake  source 
(Gusiakov, 1978; Okada, 1985) which assumes an incompressible liquid layer on an underlying elastic 

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half  space  to  characterize  the  ocean  and  the  Earth’s  crust.  The  implementation  of  this  elastic  fault 
plane  model  (Titov,  1997)  utilizes  a  formula  for  static  sea-floor  deformation  to  calculate  the  initial 
conditions required for subsequent computations of tsunami propagation and inundation. 

The near–real time calculations performed by NOAA considered the best fitting scenario used at 
the moment of an event. NOAA’s Pacific Marine Environmental Laboratory (PMEL) forecast system 
combines real-time seismic and tsunami data with a forecast database of pre-computed scenarios. The 
database model  scenarios for unit sources  consist  on fault blocks of 100  km  along strike  and 50  km 
down dip. The model requirement in this case is similar to hindcast studies: the solution must provide 
the best fit to the observations (Titov et al., 2005) and use seismic or dart scaling factors to fit the data. 
The  use  of  these  scaling  laws  may  be  inadequate  for  complex  events  resulting  in  forecast  errors 
(Weinstein and Lundgren, 2008). 

NOAA-MOST  initial  conditions  are  adjusted  by  direct  comparison  with  the  Deep-ocean 
Assessment and Reporting of Tsunamis (DART) buoys stations available records, in order to estimate 
correctly  the  source  parameters  that  better  represent  the  results  (tsunami  forecast)  2.  For  this  event 
under analysis, the factor calculated by the inversion of DART recorded data is: 12*nvszb10 (Mw 8.2) 
and the seismic factor is: 3.96* nvszb12 + 3.96* nvszb11. 

2.2 Tsunami inundation model 

The  coastal  flooding  and  inundation  is  commonly  simulated  by  extending  propagation 
calculations with  a nested grid approach. The code requires as input detailed information on seismic 
source  mechanisms,  gridded  bathymetric  data  for  the  open  sea  propagation,  and  a  set  of  gridded 
Digital Elevation Models (DEM) containing detailed bathymetry and topography in order to model the 
inundation phase. 

The  most  common  procedure  to  track  movements  of  the  shoreline  (Imamura,  1996;  Liu  et  al., 
1998  Imamura  et  al.,  2006)  is  the  moving  boundary  treatment.  Run  up  is  calculated  with  nonlinear 
computations.  

HYFLUX2  uses  a  shoreline  tracking  method  to  model  the  interface  between  dry  and  wet. 
(Franchello,  2009,  (Fig.  1).  HYFLUX2  inundation  2D  scheme  has  been  designed  to  identify  the 
shoreline  as  intersection  between  two  planar  surfaces  which  describe  the  bottom  and  the  water  free 
surface (Figure ). With this method a cell can be partially wetted, i.e. the fraction of cell that is wetted 
is a result of the proposed shoreline tracking methodology. 

In HYFLUX2 it has been realized a preservation of mass conservation at almost zero velocity, 
without the reconstruction of the bottom topography as was proposed by other authors (Audusse et al., 
2004;  Fabien  Marche,  2004;  Brufau  and  Garcia-Navarro,  2000).  The  HYFLUX2  method  does  not 
include a shoreline coordinate transformation or a moving boundary. The numerical codes COMCOT, 
TUNAMI-N2  and  MOST,  among  others,  use  the  moving  boundary  approach  in  inundation 
quantification (Fig. 2).. 

2 NOAA-MOST results are accessed online through an agreement between NOAA and JRC. 

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In the TUNAMI-N2 code a numerical algorithm is needed to determine if the total water depth is 
high enough to flood the neighbouring dry cells (land) and hence to move the shoreline. Momentum 
equations are used to update the volume in the wet cells only. When water surface is raising (Figure , 
case  2)  the  volume  flux  is  no  longer  zero  and  the  shoreline  moves  one  grid  point  in  the  onshore 
direction.  

Figure 1. Inundation scheme (shoreline tracking) in HyFlux2 

Figure 2. Inundation scheme in TUNAMI-N2 

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3.  TECTONIC SUMMARY AND TSUNAMI EVENT 

The Solomon Islands arc (Fig. 3) experiences a very high frequency of earthquake activity and 
many shocks of Mw 7 and larger have been recorded since the early decades of the twentieth century. 
The April 1, 2007 (UTC) earthquake, nucleated in a 250 km-long segment of the arc that had produced 
no shocks of Mw 7 or larger since the early 20th century (USGS)3. 

The event  occurred close to  Solomon  Islands located on the southwestern Pacific plate.  In this 
region the Pacific plate is being subducted by the Solomon Sea, Woodlark and Australian plate. The 
latter three plates converge to the northeast  (Woodlark) or east-northeast (Australia) with the Pacific 
plate with velocities of 9.0-10.5 cm/yr. 

The Solomon Islands arc lies along the south-western boundary of the Pacific plate, where  the 
geometry  of  the  subduction  zone  is  complicated  by  the  presence  of  several  sub-plates,  however  the 
overall slip direction of the Indian plate with respect to the Pacific plate is relatively uniform over the 
entire region (Kagan and Jackson, 1980).  

Large, shallow, thrust earthquakes in the Solomon Islands region tend to occur in closely related 
pairs  or  doublets.  This  is  where  two  large  magnitude  earthquakes  occur  in  a  range  of  hours  or  days 
(Kagan  and  Jackson,  1980)  as  described  in  several  events  in  this  region  (Lay  and  Kanamori,  1980; 
Schwartz et al., 1989).  

Historic events: Most of the historic doublets in the Solomon Islands have occurred north of the 
2007 earthquake in the vicinity of Bougainville Island and along the New Britain subduction zone. The 
largest of these doublets are a pair of M=8.0 and 8.1 earthquakes that occurred 12 days apart in 1971 
(Schwartz  et  al.,  1989).  The  portion  of  the  fault  that  ruptured  in  the  first  earthquake  of  the  1971 
doublet reruptured in a different manner during a M=7.7 earthquake in 1995 (Schwartz, 1999). Since 
1907  (1919-1920,  1923,  1945-1946,  1971,  1974,  1975),  and  a  triplet  in  1977  (Lay  and  Kanamori, 
1980; USGS, 2008) six doublet sets ranging on Mw 7-8 have occurred in this region. However none 
produced a noticeable tsunami, except an unconfirmed event around the turn of the 20th century noted 
by the locals (Fritz and Kalligeris, 2008). 

3 http://earthquake.usgs.gov/earthquakes/eqinthenews/2007/us2007aqbk/#summary 

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Figure 3. Tectonic setting.  
http://walrus.wr.usgs.gov/tsunami/solomon07/ 

3.1 Description of the deformation zone 

The  earthquake  focal  mechanism  indicated  thrust  faulting  earthquake.  The  largest  slip  area  is 
located  near  a  triple  junction  among  Woodlark,  Australia  and  Pacific  plates  (Miyagi  et  al.,  2009; 
Tomita et al., 2008). The main April 2007 Solomon earthquake was not a typical interplate earthquake 
which ruptured the plate interface, but rather an earthquake that occurred on a dislocation extent of the 
main fault, maybe because of subduction of the Woodlard ridge system (Fig. 4a). Bathymetric ridges 
entering  the  subduction  zones  like  the  Woodlark  Rise  and  Woodlark  Ridge  appear  to  influence  the 
distribution of slip during the earthquake. It is interesting to note that the fault ruptured directly across 
where an active spreading center is being subducted (USGS). 

Over  geologic  time,  ridge  subduction  contributes  to  the  uplift  of  the  overriding  plate  and  the 
generation  of  islands  such  as  Simbo,  Ghizo,  and  Ranunga  very  near  the  Solomon  trench.  These 
processes can affect tsunami generation and need to be investigated in the future. A coseismic crustal 
deformation surveys were conducted in Ghizo, Simo, Ranongga, Vella Lavella, Kolombangara, New 
Georgia, Parara and Rendova Islands (Fig. 4b). The field data have been used in the evaluation of JRC 
codes mapping of the deformation as well as the hydrodynamic behaviour (e.g.  amplitudes, run up). 
Different fault parameters were used in the Okada model. The Finite Fault Model and the sinusoidal 
model  were  also  used  in  the  wave  height  simulations  to  be  reproduced  by  the  JRC  numerical  code. 
Also data from  InSAR (Miyagi et al., in press; Lubis and Isezaki, 2009) has been useful to compare 
proposed major slip patches and the generation of co-seismic uplift or subsidence on the coast with the 
deformation generated by the numerical codes. 

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The  large  displacements  gradients  on  Rannongga  Island  were  measured  in  the  field  and  also 
using INSAR techniques. With the latter, a slip of 10 m has been estimated west of Ranongga Island 
(Miyagi et al., 2009). The slip location is consistent with the centroid determined by the Global CMT 
Project and according to assessments using InSAR (Miyagi et al., 2009), the slip is higher than the one 
reproduced by the models. This will be analyzed further in chapter 4. 

Figure 4. a. Solomon April 2007 event deformation scheme.  
b. Deformation measurements (Tomita et al., 2008). 

3.2 Description of the tsunami event 

The  maximum  wave  height  (run  up)  reported  at  the  US  National  Geophysical  Data  Center 
(NGDC)  website  was  10  m.  There  were  not  available  buoys  or  tidal  gauges  close  to  the  region 
analyzed in this study. However, data from field survey done by McAdoo et al. (2007) and data from 
field surveys have been used to compare the simulation results. 

3.3 Impacts 

Information  about  the  impacts  of  the  tsunami  has  been  retrieved  from  several  news  and  field 
surveys (Tomita et al., 2007; Fritz and Kalligeris, 2008) that was delivered after the post event survey. 
Description of the wave height, sediments deposited and damage on the islands of Ghizo, Ranongga, 
Simbo  and  the  uninhabited  reef-islands  around  Ghizo  are  available.  The  tsunami  hit  the  villages  of 
Tapurai where a run up of 10 m had been measured; at Pailongge the runup was 6 m; at Titiana, 6 m 
(Fritz and Kalligeris, 2008). As it was described, the islands infrastructure suffered severe damage. 

In Pailongge and Titiana, on Ghizo, homes made of thatched grasses and palm fronds were lifted 
off  their  foundations,  floated  some  tens  of  meters  inland,  and  deposited  with  surprisingly  minimal 
structural damage. Vehicles in these villages were not rolled, suggesting that the wave did not come as 
a turbulent and fast moving bore, but rather as a rapidly-rising tide (Fritz and Kalligeris, 2008).  

12 

 
 
 
 
 
 
Table1. Mortality statistics. Island name in bold, followed by community name, where it can be noted 
that the Gilbertese population suffered higher per capita mortality rates. [From McAdoo et al., 2007]. 

The event generated a tsunami that caused hundreds of affected persons (Table 1). As mentioned 
above,  the  tsunami  hit  both  Pailongge  and  Titiana  with  similar  magnitudes,  yet  13  people  died  in 
Titiana  (6  of  which  were  children  under  8  years  old),  and  none  died  in  Pailongge.  The  people  of 
Titiana are of Gilbertese (Polynesian) descent who migrated to the Solomons in the 1950s, and have no 
indigenous  knowledge  of  tsunamigenic  earthquakes.  Many  were  exploring  the  lagoon  as  it  emptied 
with  the  leading  depression  wave,  and  were  overwhelmed  by  the  subsequent  peak.  The  Melanesian 
population  of  Pailongge,  however,  gathered  together  the  oldest  and  youngest  members  of  the 
community and headed for higher ground after the shaking stopped, demonstrating an effective use of 
indigenous knowledge that saved their lives. 

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4. FAULT MODELS ASSESSMENT 

4.1 Fault models 

The generation stage of tsunami evolution includes the formation of the initial disturbance of the 
ocean  surface  due  to  the  earthquake-triggered  deformation  of  the  seafloor.  This  initial  water  surface 
disturbance evolves into a long gravity wave radiating from the earthquake source.  Modelling of the 
initial  stage  of  tsunami  generation  is  therefore  closely  linked  to  studies  of  earthquake  source 
mechanisms (Titov, 2005). 

In the following sections discussion on the five fault model results are presented (Fig. 6). 

a)  Cosinusoidal model used in GDACS early warning calculations 
b)  USGS Global Tensor model, available few hours after the event 
c)  Harvard Global CMT, available few hours after the event 
d)  USGS Finite Fault Model, available few days after the event 
e)  Tanioka model, obtained to fit field data observations 

Cosinusoidal model used in GDACS early warning calculations 

This  model is  used in  the GDACS online calculations. These calculations  are  performed using 
the  reported  epicentre  and  the  magnitude  of  the  earthquake  and  calculating  the  rupture  length  and 
width by using empirical relationship proposed by Ward (2002). The deformation is directly applied to 
the water surface, without  using an Okada model.  For this reason the model  is  conservative because 
the deformation is similar to a very shallow earthquake if the deformation is filtered through an Okada 
model. 

However as could be seen in overlaid field data this model doesn’t take into account subsidence. 
In cases where the fault is close to the shoreline this is very important as had happened at Simbo Island 
in this event. 

USGS Moment Tensor solution, available few hours after the event 

This model solution has been determined using the body-wave moment tensor inversion method 
developed  by  Sipkin  (1982).  Globally  distributed  seismograph  stations  are  used  with  distances 
between  approximately  30  and  95  degrees  to  have  suitable  P  waveforms.  Only  long-period  vertical 
components  are  used.  The  source  depth  used  is  the  depth  that  gives  the  smallest  normalized  mean-
squared-error.  Depth  is  the  only  hypocentral  parameter  determined  since  the  inversion  procedure  is 
insensitive  to  small  errors  in  both  epicenter  and  origin  time.  Data  in  the  National  Earthquake 
Information Center (NEIC) catalog are available starting January 1980. The resulted fault mechanism 
of  location  of  epicenter  (lat/lon),  depth,  strike,  dip,  slip  and  Mw  is  used  in  the  Okada  Model  to 
represent deformation area. 

14 

 
 
 
 
 
 
 
 
 
 
Harvard CMT, available few hours after the event 

These  solutions  have  been  determined  using  the  long  period  body  and  mantle  wave  moment 
tensor  inversion  method  described  by  Dziewonski,  et.al.  (1981).  considering  corrections  due  to  an 
aspherical earth structure of model SH8/U4L8 (Dziewonski and Woodward, 1991).  

Currently GSN and IDA/IRIS data are used. Long-period body waves and mantle waves are also 
used.  Mantle  waves  are  routinely  used  in  inversion  for  sources  with  moments  greater  than  5*1018 
Newton-meters  (Nm).  Data  are  available  starting  from  January  1977.  Moreover,  the  resulted  fault 
mechanism  of  location  of  epicenter  (lat/lon),  depth,  strike,  dip,  slip  and  Mw  is  used  in  the  Okada 
Model to represent deformation area. 

USGS Finite Fault Model, available few days after the event 

The  Finite  Fault  Model  (Fig.  8)  is  proposed  as  one  of  the  best  approaches  for  tsunami  source 
estimation  (Weinstein  and  Lundgren,  2008).  For  the  case  of  Solomon  Islands  earthquake,  the  Finite 
Fault Model is represented by 180 subfaults (15 km x 10 km) delivered a smaller slip than what had 
been  measured  in  reality.  Similar  situation  occurred  when  using  the  Global  CMT  and  USGS  CMT 
parameters in the Okada Model (Fig.6). 

Tanioka model, obtained to fit field data observations 

The Tanioka Fault parameters (Fig. 11) were obtained based on measured field data, taking into 
account regions of major ground dislocation and extent of deformation. This fault model was judged as 
the best one, therefore it was chosen for inundation calculations and for the subsequent evaluation of 
HYFLUX2 numerical code. 

15 

 
 
 
 
 
 
 
 
 
4.2 Fault model and related simulation results 

The  fault  scenarios  generated  with  different  parameters  and  fault  models  provide  the  basis  to 
obtain  the  tsunami  model  initialization.  Different  fault  models  have  been  compared  with  ground 
deformation field measurements (Fig 7-11). 

Figure 5. Measured deformation data [Tomita et al., 2007]. 
Post  seismic  deformation  might  have  occurred,  although  our  analysis  was  done  on  the  results 
provided by Tomita et al. (2008) and other publications where co-seismic data has been discussed. The 
above mentioned models  provide the profiles indicated in  the following figures. The various models 
are also compared individually with the measured uplift or subsidence  

16 

 
 
 
 
 
 
Figure  6. Deformation models and profiles.  

17 

 
 
 
 
 
 
 
 
 
The best agreement between field measurements and deformation values calculated by the fault 

models is achieved by the Tanioka fault model (Figure 7), and followed by the Cosinuosoidal model. 

Profile comparison of field data with fault models deformation values are presented (Fig. 7). The 

ratio between Cosinussoidal crust deformation model and averaged field measurements is 2.5. 

Figure 7. Fault distribution – Sinusoidal form and the measurements of ground 

deformation.  

18 

 
 
 
 
 
 
Profile comparison of field data with fault models deformation values are presented (Fig. 8). 
The  ratio  between  the  wave  heights  calculated  with  Okada  model  -  using  the  fault  parameters 
published by USGS - and the field measurements is 0.45. 

Figure 8. Fault distribution –Okada Model USGS/NEIC Centroid Moment and the 

measurements of ground deformation. 

19 

 
 
 
 
 
 
 
Profile comparison of field data with fault models deformation values are presented (Fig. 9). 
The  ratio  between  the  wave  heights  calculated  with  Okada  model  -  using  the  fault  parameters 
published by Harvard CMT - and the field measurements is 0.27. 

Figure 9. Fault distribution –Okada Model Global Centroid Moment and the 

measurements of ground deformation. 

20 

 
 
 
 
 
 
 
 
Profile  comparison  of  field  data  with  fault  models  deformation  values  are  presented  (Fig.  10). 
The ratio between the wave heights defined with the Finite Fault Model and the field measurements is 
0.32. 

Figure 10. Fault distribution – Finite Fault Model and the measurements of ground 

deformation. 

21 

 
 
 
 
 
 
Profile comparison of field data with fault models deformation values are presented (Fig. 11). 
The  ratio  between  the  wave  heights  propsed  by  Tanioka  (Tomita  et  al.,  2008)    and  the  field 
measurements is 1.14. 

Figure 11. Fault distribution – Okada Model (Tanioka fault parameters) and the 

measurements of ground deformation. 

22 

 
 
 
5. PROPAGATION CALCULATIONS 

The use of one of the models described in the previous section could drive different wave height 
results at different locations. Although it has been deeply discussed how fault scenarios influence the 
directivity,  amplitude  and  inundation  pattern,  among  others,  this  chapter  is  intended  to  show  the 
difference of the use of several models reflected on the wave heights obtained from the calculations. 

5.1 Calculations with CMT, Finite Fault, USGS and with Tanioka models 

The fault mechanism is one of the most significant aspects for a reliable tsunami propagation and 
inundation assessment. In this subsection we compare 4 fault parameters using  the HYFLUX2 code. 
Those  4  faults  are  Global  CMT,  NEIC/USGS,  Finite  Fault  Model  and  Tanioka  fault  parameters  as 
shown in Chapter 4. 

The following map shows the location of the watch points analyzed. These points are consistent 
with  the  field  measurements.  The  maps  have  been  separated  by  islands  to  facilitate  the  view  of 
different  results.  Although  error  calculation  and  correlation  of  the  data  has  been  done  for  each 
simulation (Fig. 12) and the field measurements.  

The results showing  a comparison of 5 fault scenarios was done using the above section fault 
mechanism. Most of the calculations done with different fault scenarios delivered very different data 
when compared to the field measurements. However it could be recognized that the best approach is 
given by the Tanioka (Tomita et al., 2008) fault parameters. 

The subsequently figures show the differences in the wave heights that are generated according 
to  the  fault  parameters  used.As  it  is  expected  the  major  differences  are  related  to  the  strike  and 
consequently the directivity of the wave and the closeness to major slip. 

As  could  be  seen  in.  Iringila  the  measurements  are  very  high  compared  with  the  results.  The 
measurement plot presents the highest wave height value; the wave height and run up values measured 
around  this  site  ranges  from  1.86  m  -  4.5  m.  Similar  situation  is  shown  for  Lengana  where 
measurements range from 3.5 – 5.0 m.  

The range of field wave height measurements in Ghizo site is 1.4 m - 2.08 m and in Givusu 0.9 
m - 1.4 m. At Suve the wave height measurements vary from 4.0 m - 5.5 m. The major variety in the 
wave height measurements were found in Titiana and Tapurai where major run up had been measured 
(9.0-10 m respectively). The range of run up varies from 4 m – 10 m (Fig. 12). 

Chapter 4 demonstrated that a better comparison is obtained when using the Tanioka model. It is 
interesting  now  to  understand  the  impact  of  the  various  crustal  deformation  models  or  focal 
mechanisms, on the sea level behaviour. Therefore the HYFLUX2 or SWAN code has been selected 
and the various models have been applied. 

The  conclusion  is  that  the  Tanioka  parameters  using  Okada  Model,  was  one  of  the  fault 

deformation model to predict the correct behaviour on the coast. 

23 

 
 
 
 
24 

 
Figure 12. Wave heights calculations and field measurements. 

The comparison of each wave height value resulted from the different fault models is shown in 
table  2.  The  best  fitting  model  is  Tanioka  when  comparing  the  average  ratio  between  the  simulated 
wave heights and field measurements. The calculations have been done with HYFLUX2 code. 

Statistics of deformation 

Fault parameters  

Ratio AV[sim/meas] 

Cosinuosoidal Mw 8.2 
USGS Centroid Moment Tensor solution 
Global Centroid Moment Tensor 
Finite Fault Model 
Tanioka fault parameters 

2.5 
0.45 
0.27 
0.32 
1.14 

Table 2. Statistics of deformation: measured data and simulated data. 

In the following graph comparisons of wave height measurements and simulations, obtained by 
using the different fault models are presented. The purpose of the simulations was to assess how the 
selection  of  a  fault  source  will  impact  the  results.  Understanding  these  parameters  is  important 
especially in case of near coast fault scenarios like this Solomon rupture.  

The  higher  run  up  was  measured  in  Tapurai  at  Simbo  Island.  The  calculated  wave  heights 
summarize values more greater than 0.5 m. Graphs in figure 13 show in better scale the wave heights 
presented in figure 12. 

25 

 
 
 
 
 
Figure 13.  Calculated wave heights using different scenarios. 

The  profiles  in  Figure  15  indicate  differences  of  sea  level  trends  when  using  the  available 
seismic  information.  Results  of  two  site  off  shore  and  two  sites  close  to  the  shoreline  have  been 
presented (see Figure 14 for the sensor position). 

26 

 
 
 
 
 
 
 
 
 
 
Figure 14. The sensor position (light green, sensor S1, S2, Keara, Kolobangara).  
[Run Grid size: 900 m]. 

a. Offshore S1 

27 

 
  
 
 
b. Off Iringila 

c. Off Kolombangara 

28 

 
 
 
 
d. Sensor S2 offshore. 
Figure 15. Sea level trends at several sensors. All faults are shown together to highlight 

differences related to fault mechanism and fault model. 

29 

 
 
 
 
5.2 Early Warning Calculations (JRC model in GDACS) 

JRC systems  detected the  earthquake 16 minutes (Table 2;  3) after the event  as soon as it was 
published by the United States Geological Survey4. Subsequently, the online JRC SWAN model was 
activated, spending about 20 minutes to complete the wave height propagation calculation. The online 
JRC  SWAN  model  calculated  maximum  tsunami  wave  heights  of  3.2  m  in  Kunji  and  2.7  m  in 
Vanikuva and Harai in the Solomon Islands.  

The  assumed  initial  fault  conditions  for  these  calculations  are  shown  in  Table  3.  The  major 
difference in respect to other models is the strike angle which is due to the fact that the system looks 
for the closer fault line direction.  

Table 3: Simulation parameters of the JRC pre-calculated grid scenario (Mw 8.0) and the online JRC 
SWAN model (Mw 8.1) 

The analysis is performed by showing the results of the calculations in some points (S1 to S5) in 
some  interesting  locations.  In  order  to  have  other  reference  the  results  of  the  JRC-SWAN  are 
compared  with  the  ones  of  NOAA-MOST  and  with  the  grid  pre-calculations  available  for  this 
equivalent event, i.e. the calculation that would be currently selected by the large JRC pre-calculated 
scenario. 

4 After the event detection a grid pre-calculation would immediately be retrieved from the JRC pre-

calculated scenario. Unfortunately at the time of the earthquake such a database was not yet completed.  

30 

Grid calculationsLat/Lon-8.5, 157Mw 8.0Fault Length158 kmFault Width44 kmSlip3.16 mFault Angle124Bathymetry cell size2.64 minCalculation time2.2 hrEarthquake data Lat/Lon-8.4807, 156.9781Mw 8.1Fault Lenght177 kmFault Width49 kmSlip3.54 mFault Angle141.11Bathymetry cell size2.937 minCPU Time/Calculation20 min for 2.5 hrCalculation detailsInitial conditions, fault geometry and calculation time. 
 
 
 
 
 
 
                                                 
Figure 16. Location of sensors [5 km -2.937’ grid size]. 

The main difference between the pre-calculated grid scenario and the online calculation are in 
the amplitudes. This is expected because basically the seismic input parameters used at the beginning 
were  slightly  different  in  the  magnitude  respect  to  the  final  values  of  the  event.  However,  when 
compared with MOST code calculations an important difference could be assessed, mostly due to the 
different strike in the fault parameters used by the two calculations. 

31 

 
 
 
Figure 17. Sea level at sensor S1. Pre-calculated grid scenario (Mw8.0), online calculations 

(Mw 8.1) and MOST code results 

. 

Figure 18. Sea level at sensor S2. Pre-calculated grid scenario (Mw8.0), online calculations 

(Mw 8.1) and MOST code results 

. 

32 

 
 
 
 
Figure 19. Sea level at sensor S3. Pre-calculated grid scenario (Mw8.0), online calculations 

(Mw 8.1) and MOST code results. 

Figure 20. Sea level at sensor S4. Pre-calculated grid scenario (Mw8.0), online calculations 

(Mw 8.1) and MOST code results. 

33 

 
 
 
 
 
 
Figure 21. Sea level at sensor S5. Pre-calculated grid scenario (Mw8.0), online calculations 

(Mw 8.1) and MOST code results. 

Depending on the location of the sensor (e.g. offshore, close to shoreline) wave differences could 
be found. The comparison of calculated wave heights is done with run up measurement. The following 
graph shows wave height trends.  

Although  an  overestimation  of  the  calculation  resulted  in  the  majority  of  sites  (Fig.  22),  at 
Iringila the wave height is underestimated. According to the JRC-SWAN, the expected value was 1 m. 
However the value of the inundation wave height and run up ranged between 1.9 – 4.4 m. 

34 

 
 
 
 
Figure 22. Wave height comparison in selected sites.  
(Legend Colours: 8.1Mw Blue, 8.0Mw Red, mesurements Green) 

5.3 Code to code comparison with Tanioka model [900 m resolution grid] 

A  comparisons  of  the  propagation  waves  simulated  by  various  codes,  Swan-JRC,  HYFLUX2 
and TUNAMI-N2, have been performed. A resolution of 0.5 min (900 m) was used for the simulations 
(Fig. 23). The Tanioka model was used to initialize the crust deformation. 

Six locations  (sensors S) were selected for this analysis and are shown in the following figures. 
Amplitude and arrival times are very similar in HYFLUX2 and SWAN-JRC calculations, while time is 
different for TUNAMI-N2 calculations which is delayed in respect to the previous codes. The sea level 
trends are similar although for HYFLUX2 the sea level curve is always smoother. (Fig. 24-30). 

At location S1 the first wave is negative for all the codes and the maximum wave height is about 
40  cm  at  about  30  min.  Sea  level  trend  off  shore  (sensor  S3)  resulted  with  TUNAMI-N2  is  very 
oscillatory. Sensor 5 located off shore is very consistent among the codes except that the trend of the 
TUNAMI-N2 is more oscillatory. 

In  all  the  cases  a  main  first  wave  is  present  followed  by  a  second  smaller  wave.  The  highest 

calculated sea level trend is close to the epicenter, on Rendova island.  

In terms of CPU time HYFLUX2 processing time was 4 hours 59 minutes, the numerical code 
SWAN-JRC duration for this simulation was 0.5 hour and the TUNAMI-N2 numerical code duration 
was 0.8 hour (48 minutes). 

35 

 
 
 
 
 
Table 4. Simulation main parameters [Tanioka proposed fault] 

Figure 23. Grid delimitation [red -900 m bathymetry resolution-]. 

36 

EPICENTER: CALCULATIONS PARAMETERS: Epicenter- Lat -8.655° Lon: 157.0°FinTime: 1 hrCenter- Lat: -8.25° Lon: 156.8°Tsave: 1 min Magnitude: 8.1 dtMax: 0.5 sDate tsunami: 4/1/2007 8:40:38 PM fanning: 0.015FAULT PARAMETERS: GRID PARAMETERS: Flenght: 100 kmWidth: 2.5° Batgrid: 0.5 minfwidth: 35 kmLonmin154.3° Lonmax: 159.3°strike: 315° (geog North=0) Latmin: -10.75° Latmax: -5.75°slip: 7 m Bathymetry: SWANdip: 35°rake: 90 °  
 
 
  
 
Figure 24. Sensor location [900 m resolution grid]. 

Figure 25. Calculations at S1 done with 900 m resolution. HYFLUX2 (blue), SWAN-JRC 

(pink) and TUNAMI-N2 (grey). 

37 

 
 
 
 
 
Figure 26. Calculations at S2 done with 900 m resolution. HYFLUX2 (blue), SWAN-JRC 

(pink) and TUNAMI-N2 (grey). 

Figure 27. Calculations at S3 done with 900 m resolution. HYFLUX2 (blue), SWAN-JRC 

(pink) and TUNAMI-N2 (grey). 

38 

 
 
 
 
 
Figure 28. Calculations at S4 done with 900 m resolution. HYFLUX2 (blue), SWAN-JRC 

(pink) and TUNAMI-N2 (grey). 

Figure 29. Calculations at S5 done with 900 m resolution. HYFLUX2 (blue), SWAN-JRC 

(pink) and TUNAMI-N2 (grey). 

39 

 
 
 
 
 
Figure 30. Calculations at S6 done with 900 m resolution. HYFLUX2 (blue), SWAN-JRC 

(pink) and TUNAMI-N2 (grey). 

The ratio (HYFLUX2 code/ SWAN-JRC code) between the simulated maximum wave heights at 
the analyzed  locations is 0.732 (Fig. 31). The ratio  between the simulated maximum  wave heights  - 
calculated with HYFLUX2 and TUNAMI-N2  codes - is 0.5. The greater sea level height estimated by 
SWAN_JRC code and TUNAMI-N2 code in respect to HYFLUX2 can be explained by the fact that 
such finite difference codes show oscillations which increase near-shore. As can be seen in Figures 25 
to Figure 30 the higher predicted wave height is given by TUNAMI-N2 

.

40 

 
 
 
41 

 
Figure 31. Location of wave heights resulted from 3 codes using the Tanioka fault 

parameters.  

42 

 
 
 
 
6. INUNDATION CALCULATIONS [300 m resolution] 

The  aim  of  this  section  is  to  evaluate  in  more  detail  the  local  sea  level  trends  to  make 
comparisons with the measured field data. When the wave reaches shallow water its length becomes 
shorter and the amplitude increases. Such phenomena are emphasized in the bays, where reflection and 
resonance took place. Therefore in order to describe with more details the wave, the adopted grid size 
resolution  must  be  higher.  Consequently,  a  grid  size  in  the  order  of  10-30  m  is  requested  if  an 
inundation impact assessment is intended.  In other report (Franchello et al., 2010) it was shown that a 
30 m grid size resolution could have noticeably improved the simulation, providing information on the 
inundation extent. However, in the above mentioned report it was shown that the simulation performed 
at 300m grid size resolution allowed to evaluate the maximum wave height at the shoreline  with an 
acceptable  accuracy,  providing  also  an  indication  on  which  are  the  localities  where  inundation  were 
occurred. 

Unfortunately  the  best  resolution  of  available  data  on  bathymetry  and  topography  on  a  global 
scale is 30 arc sec (~ 900 m). The interpolation of the available DEM to very low grid size (i.e. lower 
tan 100 m) does not make sense, considering that the elevation of hills and bays of size lower than 1 
km are averaged to 1 point. A compromise for inundation simulations can be 300 m grid size (Fig. 32), 
which is interpolated from the 900 m available information. With such resolution the wave length at 
the shore is quite well represented, but the information on run up distance and inundation extent are 
quite poor when the measured values are lower than the chosen 300 m grid size.   Therefore, despite 
the onsite survey provided detailed information on horizontal inundation and run up distance (which is 
always  lower  the  300m),  the  bathymetry  grid  is  still  a  limitation  for  a  real  inundation  assessments. 
Therefore,  in  the  present  section  the  field  measurement  data  are  compared  with  the  calculated  wave 
height at the shoreline. 

The fault parameters are based on the previously described Tanioka Model (Tomita et al., 2008) 
while  the  HYFLUX2  code  has  been  used  for  these  calculations  (Franchello,  2009).  Three  nested 
simulations have been performed as indicated in the figure below: the simulation results at 900 m grid 
size  resolution  (the  bigger  window)  are  used  as  boundary  conditions  of  the  simulations  with  300  m 
grid size (smaller windows). 

The  comparison  with  the  simulated  results  and  the  inundation  field  measurements  have  been 
done by setting a 1 km search radius of the maximum values inland. Since the best resolution used for 
this calculations is 300 m, and the maximum inundation distance reported is 200 m (at Rendova Is.), 
analysis for horizontal inundation cannot be carried out in detail. 

43 

 
 
 
1 

2 

3 

Figure32. Delimitation of simulations at 300 m bathymetry resolution. 

8.1 Grid I: Vella Lavella, Ranongga and Gizo  

The maximum simulated sea level is represented in figure 33. The maximum water height value 

at the shoreline is 7.5 m SE of Ranongga Island.    

Vella Lavella 

Ghizo 

Ranongga 

Figure 33. Grid I - Simulated Maximum sea level  

44 

 
  
 
 
      
 
 
 
 
  Vella Lavella Island 

The island was severly affected by the tsunami, mainly the town of Iringgila located N-NW of 
Vella Lavella Island. According to Tomita et al (2008) the inundation height measured on the field was 
4.37 m and inundation depth on the ground level was 2.90 m.  

In several sites of Vella Lavella Island (Fig 36), the HYFLUX2 code calculations results are in 
good  agreement  although  detailed  bathymetry  resolution  is  still  a  strong  constraint  for  the  tsunami 
impact analysis. As shown (Tomita et al., 2008), the local change of tsunami height around Iringgila is 
probably attributed to the complicated bathymetry and topography. As it was described (Tomita et al., 
2008) very shallow water area in front of the village may have converged energy of tsunami generating 
high local tsunami height.  

Figure 34. Maximum wave height comparison.  

45 

 
 
 
The difference between the maximum wave height measured on the field and the wave height at 
the  shoreline  obtained  with  HYFLUX2  varied  for  more  than  1  meter.  The  average  ratio  between 
simulated and measured data is 1.3, i.e., the code overestimate at several sites (Fig.37). Although the 
poor  DEM  resolution  used  for  the  simulations,  the  overall  comparisons  for  these  sites  has  an 
acceptable behaviour.  
Maximum measured inundation distance is 124 m for Vella Lavella Island, which is much lower than 
the grid size resolution of 300 m. 

Figure 35. Vella Lavella Isl. Maximum wave height simulated with HYFLUX2 (red) 

compared with field measurements. (blue) 

  Ranongga Island 

This island was one of the most affected by the earth quake and tsunami. The ground uplifting 

values range from about 0.9 m (Vori and Vori Point) to about 3 m (Lale).  

The tsunami run up and inundation heights ranged from about 1.9 (Vori and Koriovuku) to about 
5.5 m  (Lale) from north to  south, except  for a  measurement of 5.6 m at  Saguru located on the  west 
coast in the middle of the island. At Lale ground uplift and wave heights were the highest of Ranongga 
Island (Fig. 36). The ratio between simulated and measured data is 1.5. 

The main differences on wave amplitudes appear to be at VoriVori, where according to observed 
images, reefs appear to be very shallow. Herein, the resolution and local site effects might be giving an 
overestimation  of  wave  height  calculations  because  the  higher  friction  due  to  the  reef  has  not  been 
taken into account.  In addition, the maximum inundation distance of 131 m was measured in Keara.  

46 

0.001.002.003.004.005.006.007.008.00IringilaKearaLamb LambMaravariNiarovaiReonaSupatoSamboraVonunoMaximum wave height field measurements (m)Maximum simulated wave height -at shore (m)VELLA LAVELLA ISLANDRatiomes/sim: 0.77 
 
 
 
 
Figure 36. Ranongga Isl. Maximum wave height simulated with HYFLUX2 (red) compared 

with field measurements. (blue) 

  Ghizo Island  

This island is located about 45 km NW of the epicentre (Fig. 32). The southern coast of Ghizo 
was  strongly  affected  by  high  tsunami  waves  that  had  a  maximum  inundation  distance  measured  in 
Ghizo Island of 128 m. The maximum run up measured at Ghizo Island was in the site of Titiana (8.92 
m), where almost no houses were destroyed by earthquake, but 10 people were killed by the tsunami 
(Tomita et al., 2008).  

In  this  island  the  calculations  have  given  different  results  when  comparing  with  field  data 

(Figure 37). The ratio between simulated and calculated data is 1.7. 

47 

0.001.002.003.004.005.006.007.00LaleMondoSaguruVorivoriKukunduSekasukuruMaximum wave height field measuremnts (m)Maximum simulated wave height -at shore (m)RANONGGA ISLANDRatio mes/sim: 0.68 
 
 
Figure 37. Ghizo Isl. Maximum wave height simulated with HYFLUX2 (red) compared 

with field measurements. (blue) 

8.2 Grid II: Simbo Island. 

This calculation includes Simbo Island (Fig. 38) and some details of south Ranongga and Ghizo 
Islands.   The  highest  wave  heights  are  simulated  between  7m  to  8  m  in  Simbo  Island  and  SW 
Ranongga Island. 

Simbo 

Figure 38. Grid II - Simulated Maximum sea level 

  Simbo Island  

48 

0.001.002.003.004.005.006.007.008.00GhizoGhizo airport WLoghaSagheraghiSuveTitianaMaximum wave height field measurements (m)Wave height at shore (m)GHIZO ISLANDRatio mes/sim: 0.6 
 
 
 
 
 
 
 
The highest ground subsidence was measured at Simbo Island (3.2 m). In addition, the highest 
run up value (10 m) was measured in Tapurai, the northernmost tip of Simbo Island. This island was 
strongly affected by the tsunami that killed people and swept away all houses. Field measurements on 
Tapurai  described widespread damage; in  this  site all structures were destroyed by a possible higher 
turbulence  due  to  local  bathymetry  influence  (Fritz  and  Kalligaris,  2008).  The  maximum  inundation 
distance of 175 m at Simbo Island was measured in Lengana. 

a. Maximum wave height comparison. 

49 

 
 
b. Comparison of waves of Simbo Island. 
Figure 39. a. Selected sites to be compared b. Comparison of waves of Simbo Island. 

8.3  Grid III: Rendova,  New Georgia and Parara Islands. 

This calculation includes a detail of south Parara, Rendova and New Georgia Island. The highest 

wave heights are simulated between 7m to 8 m in Parara Island and SW Ranongga Island (Fig. 40). 

New Geoargia 

Parara 

Rendova 

  Rendova Island 

Figure 40. Grid III – Simulated Maxim Sea level. 

This  island  is  on  the  eastern  boundary  of  the  deformation  area.  This  calculation  indicated 
important  differences  with  the  field  measurements.  This  site  was  less  studied  in  the  field  and  the 

50 

0.001.002.003.004.005.006.007.008.009.0010.00LenganaMalolomoMenggeMondoRiguruTapuraiMaximum wave height field measurements (m)Maximum simulated wave heights -at shore (m)SIMBO ISLANDRatio mes/sim: 0.86 
 
 
 
 
 
 
 
differences in the amplitudes at Givusu, Vunerima, Munda2, Kenelo and Randuvu could have several 
explanations in the local bathymetry behaviour. In addition, further analysis of the friction coefficient 
could be done to understand why this big differences. The maximum inundation distance of 204 m was 
measured at Randuru in Rendova Island. The ratio between simulated and measured data is 1.56 (Figs. 
41, 42). 

  New Georgia Island 

In  this  side  of  the  island  reefs  have  developed  800  m  and  3000  m  offshore  along  the  south 
Munda  coast;  these  reefs  act  as  natural  breakwaters.  The  measured  inundation  height  was  1.05  m, 
while the simulated wave height at the shoreline was 7.1 m (Figs. 41,43). These values have a big bias 
from the measured one that could be related to the increased friction due to the reef. This friction has 
not  been  taken  into  account  in  these  simulations.  However  if  finer  resolution  bathymetry  is  found  a 
higher friction should be considered. 

  Parara Island 

This  island  has  few  inhabitants,  no  witness  description  exist:  however  marks  of  wave  heights 
were found. A run up height of more than 3.3 m was measured at Ndivulani, which is part of the chain 
of islands on the extending coral reef. The uplift of the ground was estimated at about 1m. A run up 
height of 1.3 m was measured at Rarumana, the village on the main island of Parara. The uplift at this 
site was estimated of 0.8 m. This village suffered no damage, maybe because the coast is sheltered by 
the extending reef and the ground was uplifted by the earthquake. The simulated maximum height is of 
the order of 8 m (Figs 41, 44). 

51 

 
 
 
 
 
 
Figure 41. Wave heights calculations at Kolombangara Island, Rendova Island and Parara 

Island. 

52 

 
 
Figure 42. Wave heights calculations Rendova Island. 

Figure 43. Wave heights calculations at New Georgia Island. 

53 

0.001.002.003.004.005.006.00HopongoKeneloRanduvuMaximum wave height field measurements (m)Maximum simulated wave height -at shore (m)RENDOVA ISLANDRatio mes/sim: 0.640.001.002.003.004.005.006.007.008.00NoroMunda2RarumanaViloraeWave height field measurements (m)Maximum simulated wave height -at shore (m)NEW GEORGIAISLANDRatio mes/sim: 0.66 
 
 
Figure 44. Wave heights calculations at Parara Island. 

54 

0.001.002.003.004.005.006.007.008.009.00ArundelGivusuVunerimaNdivulaniMaximum wave height field measurements (m)Maximum simulated wave height -at shore (m)Ratio mes/sim: 0.33PARARAISLAND 
 
 
 
 
 
 
Wave heights major than 1 m simulated on several islands -

300 m 

7. FINAL REMARKS 

In  this  report  the  influence  of  the  fault  model  on  the  coseismic  deformation  was  studied  by 
comparing  modelling  results  with  measured  values.  It  was  shown  that  none  of  the  classical  models 
were  able  to  estimate  correctly  the  measured  value.  The  best  comparison  with  experimental  data  is 
obtained using the fault mechanism parameters of the so called Tanioka model, obtained by fitting the 
surveyed measured data points. However, it should be noted that this type of parameters estimation can 
be available only after the field surveys are carried out. 

The  second  part  of  the  report  was  dedicated  to  assess  the  hydrodynamic  models  which  are 
currently used at the JRC. Several codes were used with the initial boundary conditions provided by 
“Tanioka model”. The main differences among the codes were related to the high oscillations present 
in  finite  difference  methods  codes  when  compared  with  finite  volumes  code.  However,  the  overall 
behaviour of the simulations was rather similar and correctly identified most of the affected locations. 
We find that the resulted offshore wave heights are in good correlation for the three codes that were 
assessed. 

In  order  to  have  a  reliable  sea  level  prediction  on  the  coast  it  is  necessary  to  use  much  finer 
nodalizations. This was done by using a 300 m resolution grid and the finite volume HYFLUX2 code 
was used for the simulations. A better bathymetry resolution could have even improved the results but 
it  was  not  available.  However,  the  simulation  performed  at  300m  grid  size  resolution  allowed  to 
evaluate  the  maximum  wave  height  at  the  shoreline,  showing  a  quite  good  agreement  with  the 
measured inundation and run-up.  

Finally,  differences  have  been  noticed  within  CPU  time  among  the  various  codes.  The  CPU 
needed  when  using  HYFLUX2  numerical  code  is  higher  than  when  calculations  are  performed  with 
TUNAMI-N2 or SWAN-JRC. Activities are under way to improve the performance and to produce a 
parallel version of the code in order to get quicker results. 

As  a  final  remark,  the  fact  that  the  Tanioka  model  was  able  to  reproduce  both  the  seafloor 
deformation  as  well  as  the  sea  level  wave  propagation,  it  gives  more  credit  to  the  idea  that  if  the 
deformation  could  be  estimated  accurately  and  be  available  immediately  (i.e.  with  GPS  online 
measurements),  this  would  allow  to  have  a  more  reliable  early  warning  calculation.  Of  course  GPS 
measurements can be available only in case of near-field crustal deformation, not offshore. 

55 

 
 
 
 
8. REFERENCES 

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Wei,  Y.  Uslu,  B.,  H.  M.  Fritz,  V.  Titov,  C.  Chamberlin  (in  press).  Solomon  Islands  2007 
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58 

 
 
 
 
 
APPENDIX 

I. Historic events originated in the Solomon Islands Subduction Zone 

59 

FocalDepthYearMoDyHrMnSecTsuNameLatitudeLongitude1900729SOLOMON ISLANDS: SANTA CRUZ ISLANDS-11166.18.119091292323SOLOMON ISLANDS-101657.71926916175912TsuSOLOMON ISLANDS-11.5160507.11931103191313TsuSOLOMON ISLANDS: SAN CRISTOBAL ISLAND-10.5161.75337.919311010019SOLOMON ISLANDS-10161607.71934718194015TsuSOLOMON ISLANDS: SANTA CRUZ ISLANDS-11.75166.5257.2193836156TsuSOLOMON ISLANDS-5.1153.11950118TsuSOLOMON ISLANDS: SOLOMON SEA-10159.53319559832716TsuSOLOMON ISLANDS-6.9155.7336.5195711TsuSOLOMON ISLANDS195712171350SOLOMON ISLANDS: SANTA CRUZ ISLANDS-12.3166.71207.8195981721440TsuSOLOMON ISLANDS-7.51567.31966123118233.9TsuSOLOMON ISLANDS: SANTA CRUZ ISLANDS-11.8166.5337.519661231221514TsuSOLOMON ISLANDS: SANTA CRUZ ISLANDS-11.3164.8337.31969151326SOLOMON ISLANDS: SANTA ISABEL ISLAND-7.9158.9477.5197413123305.3TsuSOLOMON ISLANDS-7.5155.934719742131233TsuSOLOMON ISLANDS-7.4155.6407.11977420231310TsuSOLOMON ISLANDS-9.828160.323336.81977420234251TsuSOLOMON ISLANDS-9.89160.348197.61977420234913SOLOMON ISLANDS-9.844160.822337.519774214249.6TsuSOLOMON ISLANDS-9.965160.731338.1198078231920SOLOMON ISLANDS: SANTA CRUZ ISLANDS: BANKS-12.41166.381337.51980717194223TsuSOLOMON ISLANDS: SANTA CRUZ ISLANDS; VANUATU-12.525165.916337.9198285203353SOLOMON ISLANDS: SANTA CRUZ ISLANDS-12.597165.931317.5198427213321SOLOMON ISLANDS: GUADALCANAL-10.012160.469187.519859273398.5SOLOMON ISLANDS: HONIARA, GUADACANAL-9.829159.854326.9198881043826TsuSOLOMON ISLANDS: SAN CRISTOBAL, GUADALCANAL-10.366160.819347.4199129161858TsuSOLOMON ISLANDS-9.929159.139106.919911014155813TsuSOLOMON ISLANDS-9.094158.442237.2199252751339TsuSOLOMON ISLANDS: SANTA CRUZ ISLANDS-11.122165.2391971996429144041SOLOMON ISLANDS: BOUGAINVILLE ISLAND-6.518154.999447.2199742112226TsuSOLOMON ISLANDS: SANTA CRUZ ISLANDS; VANUATU-12.584166.676337.720031208436TsuSOLOMON ISLANDS: HONIARA, SAN CRISTOBAL-10.491160.77337.3200741203956TsuSOLOMON ISLANDS-8.466157.043248.12007921518TsuSOLOMON ISLANDS: SANTA CRUZ ISLANDS-11.61165.762357.22009107221851SOLOMON ISLANDS: SANTA CRUZ ISLANDS-12.517166.382357.820101321486TsuSOLOMON ISLANDS-8.88157.325106.5201013223630TsuSOLOMON ISLANDS-8.912157.307307.2201015121536TsuSOLOMON ISLANDS-8.886157.522356.9DateAssocEarthquake LocationEarthquake ParametersMag 
 
 
 
 
II. Tsunami events documented from 1900-2010 (NGDC data base) 

. 

60 

Tsunami ParametersEarth-Vol-Maxquake MagcanoWaterYearMoDyHrMnSecCountryNameLatitudeLongitudeHeight1926916175912417.1SOLOMON ISLANDSSOLOMON ISLANDS-11.516021931103191313417.9SOLOMON ISLANDSSAN CRISTOBAL ISLAND-10.5161.759193943025530318.1SOLOMON ISLANDSSOLOMON ISLANDS-10.5158.510.519571121*SOLOMON ISLANDSSOLOMON ISLANDS2.7195981721440417.3SOLOMON ISLANDSSOLOMON ISLANDS-7.51561196131821SOLOMON ISLANDSSOLOMON ISLANDS3.619618153953216.6SOLOMON ISLANDSSOLOMON SEA-9.9160.50.9196661505946317.6SOLOMON ISLANDSSOLOMON ISLANDS-10.4160.80.11966112810SOLOMON ISLANDSMOHAWK BAY, SANTA CRUZ ISLANDS-101681966123118233.9417.5SOLOMON ISLANDSSANTA CRUZ ISLANDS-11.8166.52.0319661231221514417.3SOLOMON ISLANDSSANTA CRUZ ISLANDS-11.3164.81.5219671118234418.1SOLOMON ISLANDSSOLOMON ISLANDS-11.8166.521971962046VolSOLOMON ISLANDSTINAKULA, SANTA CRUZ-10.38165.8197413123305.3417SOLOMON ISLANDSSOLOMON ISLANDS-7.5155.91.519742131233417.1SOLOMON ISLANDSSOLOMON ISLANDS-7.4155.64.51977420231310416.8SOLOMON ISLANDSSOLOMON ISLANDS-9.828163.320.161977420234251417.6SOLOMON ISLANDSSOLOMON ISLANDS-9.89160.35198761814315116SOLOMON ISLANDSSOLOMON ISLANDS-10.71162.330.1198881043826417.6SOLOMON ISLANDSSOLOMON ISLANDS-10.37160.820.09199129161858417SOLOMON ISLANDSSOLOMON ISLANDS-9.929159.140.119911014155813417.3SOLOMON ISLANDSSOLOMON ISLANDS-9.09158.440.2199252751339117.1SOLOMON ISLANDSSANTA CRUZ ISLANDS-11.12165.240.1199742112226417.7SOLOMON ISLANDSSANTA CRUZ IS. VANUATU-12.58166.68320031208436417.3SOLOMON ISLANDSSOLOMON ISLANDS-10.49160.772200741203956418.1SOLOMON ISLANDSSOLOMON ISLANDS-8.46157.04102007921518417.2SOLOMON ISLANDSSANTA CRUZ ISLANDS-11.61165.760.0520101321486416.5SOLOMON ISLANDSSOLOMON ISLANDS-8.88157.33201013223630417.2SOLOMON ISLANDSSOLOMON ISLANDS-8.912157.313201015121536416.9SOLOMON ISLANDSSOLOMON ISLANDS-8.886157.520.03DateTsunami CauseTsunami Source LocationValCode 
  
 
European Commission  

EUR 24783 EN –  Joint Research Centre – Institute for the Protection and Security of the Citizen 
Title: 01 APRIL 2007 SOLOMON ISLAND TSUNAMI: CASE STUDY TO VALIDATE JRC TSUNAMI CODES 
Author(s): Natalia Zamora, Giovanni Franchello, Alessandro Annunziato 

Luxembourg: Publications Office of the European Union 
2011 – 62 pp. – 29.7 x 21 cm 
EUR – Scientific and Technical Research series – ISSN 1018-5593 (print) ISSN 1831-9424 (online) 

ISBN 978-92-79-19851-9 (print)  
ISBN 978-92-79-19852-6 (pdf)  

doi:10.2788/859  

Abstract 

On  April  1st  2007  a  large  earthquake  of  magnitude  8.1  occurred  offshore  Solomon  Islands  at 
20:40:38  UTC.  Numerical  simulations  of  the  tsunami  event  caused  by  the  earthquake  have  been 
performed to compare the results obtained by the SWAN-JRC code (Annunziato, 2007), the TUNAMI 
(Imamura, 1996) and the HYFLUX2 (Franchello, 2008). The analysis conducted using these numerical 
simulations were also compared with NOAA-MOST code unit source results. 

The  tsunami  event  has  been  simulated  considering  several  options  for  the    seismological 
parameters as input data: Finite Fault Model (USGS, 2007), the Centroid Moment Tensor fault model 
and other mechanisms derived from the field survey analysis (Tanioka model). 

The main aim of this study is to assess how the different fault models affect the overall results 
and  to  perform  a  comparison  among  the  various  codes  in  the  wave  propagation  phase.  Another 
objective of this study is to use HYFLUX2 code to calculate inundation and compare the simulation 
results with site field measurements. 

The  study  has  been  separated  into  two  main  parts.  The  first  one  represents  the  collection  of 
information about focal mechanisms: the fault analysis in chapter 4 covers one of the main aims of this 
research where different fault scenarios have been tested using published field data. The second part 
describes the  different  calculations  that have been performed in  order to  analyze the response of  the 
wave  propagation  models  to  various  fault  deformation  models.  For  the  inundation  assessment,  more 
detailed  calculations  at  300m  grid  siaze  resolutions  have  been  performed,  using  the  fault  model  that 
best represent the deformation. 

The calculations in the propagation assessment  subsection were performed using: SWAN-JRC, 
HYFLUX2,  TUNAMI-N2  and  NOAA-MOST  code.  In  the  inundation  assessment  the  HYFLUX2 
numerical code, initialized with the Tanioka fault model was used.  

The  deformation  comparison  with  field  measured  data  shows  that  none  of  the  “quick”  fault 
mechanism was able to estimate correctly the measured value. The best model is the empirical model 
by Tanioka which was obtained trying to reproduce the measured value.  

From the published fault mechanism the one that shows a better correlation with measurements 
is  the  simple  cosinuosoidal  model.  Results  of  simulations  done  with  300  m  grid,  show  a  maximum 
wave height of 7.5 m. Though the maximum run up reported was 10 m in Tapurai site, Simbi Island, 
the simulation results are encouraging. 

61 

 
 
 
 
 
 
 
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