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Summary

The M w 7.8 2006 July 17 earthquake off the southern coast of Java, Indonesia, has been responsible for a very large tsunami causing more than 700 casualties. The tsunami has been observed on at least 200 km of coastline in the region of Pangandaran (West Java), with run-up heights from 5 to more than 20 m. Such a large tsunami, with respect to the source magnitude, has been attributed to the slow character of the seismic rupture, defining the event as a so-called tsunami earthquake, but it has also been suggested that the largest run-up heights are actually the result of a second local landslide source. Here we test whether a single slow earthquake source can explain the tsunami run-up, using a combination of new detailed data in the region of the largest run-ups and comparison with modelled run-ups for a range of plausible earthquake source models.

Using high-resolution satellite imagery (SPOT 5 and Quickbird), the coastal impact of the tsunami is refined in the surroundings of the high-security Permisan prison on Nusa Kambangan island, where 20 m run-up had been recorded directly after the event. These data confirm the extreme inundation lengths close to the prison, and extend the area of maximum impact further along the Nusa Kambangan island (about 20 km of shoreline), where inundation lengths reach several hundreds of metres, suggesting run-up as high as 10-15 m.

Tsunami modelling has been conducted in detail for the high run-up Permisan area (Nusa Kambangan) and the PLTU power plant about 25 km eastwards, where run-up reached only 4-6 m and a video recording of the tsunami arrival is available. For the Permisan prison a high-resolution DEM was built from stereoscopic satellite imagery. The regular basin of the PLTU plant was designed using photographs and direct observations. For the earthquake's mechanism, both static (infinite) and finite (kinematic) ruptures are investigated using two published source models. The models account rather well for the sea level variation at PLTU, showing a better agreement in arrival times with the finite rupture, and predict the Permisan area to be one of the regions where tsunami waves would have focussed. However, the earthquake models that match the data at PTLU do not predict that the wave heights at Permisan are an overall maximum, and do not predict there more than 10 m of the 21 observed. Hence, our results confirm that an additional localized tsunami source off Nusa Kambangan island, such as a submarine landslide, may have increased the tsunami impact for the Permisan site. This reinforces the importance for hazard assessment of further mapping and understanding local potential for submarine sliding, as a tsunami source added to usual earthquake sources.

1 The 2006 July 17 Earthquake and Tsunami

The 2006 July 17 earthquake occurred on the Java Trench ( Fig. 1), about 200 km south to a coast where holiday resorts host thousands of tourists, especially in the Pangandaran area. The M w magnitude estimated to 7.8, the thrusting mechanism and the shallow depth (almost 10 km) of the event were such that a tsunami was triggered, which reached the Java coastline within 1 hr following the main shock ( Lavigne et al. 2007), and caused more than 700 casualties among harbours, holiday resorts and beaches.

1.1 A 'tsunami earthquake'

The very high tsunami heights (in excess of 10 m) rapidly reported in the devastated area were actually much larger than the moment magnitude of the event could have indicated, suggesting that the earthquake was a so-called 'tsunami earthquake' ( Kanamori 1972). The 2006 earthquake occurred about 500 km to the west of a former strong earthquake that struck eastern Java in 1994 ( M w = 7.9), and that similarly had triggered an important tsunami ( Maramai & Tinti 1997; Abercrombie et al. 2001). This earlier event was also recognized as a 'tsunami earthquake': the earthquake rupture was very shallow, thus possibly involving the thick sedimentary layers in the accretionary wedge, combined to a very heterogeneous subducting plate, all these characteristics contributing to variations in frictional properties during the rupture ( Polet & Thio 2003). Most of these events create huge tsunami waves regarding their magnitude, which rarely exceed 7.5-7.9. Their rupture is assumed to be slow, as it was also suggested for the 2006 earthquake, reflecting several sequences of moment release on a smooth rupture consistent with a surrounding weak material ( Ammon et al. 2006).

As in 1994, or in 1992 in Nicaragua ( Satake 1994), or in 1996 in Peru ( Heinrich et al. 1998), these events were found to be unusually rich in low-frequency energy released at shallow depths below the seafloor where it is especially efficient in triggering tsunami waves. These seismic events, usually hardly felt by coastal populations because of their moderate high-frequency waves, pose a great danger regarding the tsunami hazard since the common warning produced by the seismic shaking does not urge populations to escape on the surrounding heights. In addition Watch Bulletins issued in less than 20 min after the quake by Pacific Tsunami Warning Center and Japan Meteorological Agency ( International Tsunami Information Center 2006) could not be efficiently delivered to local authorities ( Mori et al. 2007).

1.2 Run-up data set

A series of several international survey teams dispatched to the affected area in the days and weeks following the tsunami. Most of them are summarized in Fig. 2. Within the first days, Japanese and Indonesian scientists revealed the extent of the impacted coastline, above 250 km in length ( Mori et al. 2007), especially in the area of the Pangandaran tourist resorts. Severe damage (from collapsed walls to complete destruction) was reported within several hundreds of metres from the shore; consistent with run-up values from 6 to 8 m on average. The data collected by another Japanese team (Tsuji, http://www.eri.u-tokyo.ac.jp/tsunami/javasurvey/index_e.htm; PARI-JSCE Group, http://www.nda.ac.jp/~fujima/TMD/index.html) confirmed these values, both in longitudinal extent (at least 200 km) and amplitude (above 4-6 m), with an especially high value (6.2 m) close to the Power Plant PLTU (6 km NE to Cilacap), and the largest run-up (11.4 m) west of Pangandaran. A study of sedimentary deposits in the region of Cilacap also indicates a sandy layer up to 20 cm thick, that is consistent with the passage of at least two individual waves ( Moore et al. 2011).

All these surveys had missed the extreme tsunami run-up values gathered when the Nusa Kambangan island was finally reached by two different teams. This island, only separated from Java by a narrow channel, hosts a high security prison close to the city of Permisan, and access is therefore very restricted. Extreme run-up values were measured here, up to 21- and 10-m-high water waves inundated the wide place cleared in the tropical forest where the prison is built ( Fritz et al. 2007). Another team also confirmed very high flow depths and run-up heights of 15.7 m ( Lavigne et al. 2007) close to the prison.

1.3 Which kind of source for such a large tsunami?

The overall tsunami data set ( Fig. 2) exhibits an average tsunami height of 4-8 m along 200 km at least, and the reported values in the Permisan area are strikingly exceeding this trend. This large tsunami impact questions the possibility for an additional source to have contributed to these high amplitudes, namely a submarine landsliding source, as is accepted for some events, as in Papua New Guinea in 1998 ( Heinrich et al. 2001), and as was already suggested for this 2006 event. Indeed the very localized extreme 21 m run-up measured in the Permisan area was attributed to a possible contribution of an additional submarine landslide ( Fritz et al. 2007). Such a landslide source generally contributes to extreme run-up values along a coastal portion less extended than for earthquake sources ( Okal & Synolakis 2004), a pattern which besides provides a way to discriminate the tsunami origin.

In this purpose of investigating the relative importance of both possible sources, we first need a better assessment of the extent of the high run-up area along the coast. In the following study, we provide additional constraints given by a detailed analysis of satellite imagery in the area of maximum run-up values on the Nusa Kambangan island, confirming very large values reached all along this shoreline. Then, using available earthquake rupture parameters for the 2006 earthquake, we carry out for the first time detailed numerical modellings of the tsunami in the area of the Permisan prison, where the highest run-up height was reported ( Fritz et al. 2007; Lavigne et al. 2007), and where we use satellite images to build a refined elevation model. We also model the tsunami for the PLTU power plant basin, located to the east of Cilacap City, where a surveillance camera recording has been converted into a temporal sea level variation ( Lavigne et al. 2007) and can be compared to models. Finally, on the basis of the imagery analysis and of the tsunami modelling, we discuss the source process that was responsible for this large tsunami, indicating that an additional landslide source may also be requested to better explain the observation for the Nusa Kambangan island specifically.

2 Run-Up Distribution from Remote Sensing Data

In this section we attempt to complement the original data set using high-resolution satellite imagery. On a regional scale, we show that the whole coastline of the Nusa Kambangan island was struck by tsunami waves having reached inundation distances similar to the Permisan area.

2.1 Method

In the aftermath of strong tsunamis, satellite imagery is more and more frequently used to identify the devastated areas, provide guidance for the rescuing operations and help to characterize the event, especially in comparing with field survey data ( Fritz et al. 2008, 2011). Space agencies support these activities while giving rapid access to high-resolution images in the days following such events, for instance in the frame of the International Charter Space and Major Disasters ( International Charter 2011). Concerning tsunamis, they give additional constraints on the flooding extent, the damage intensity and the coastal vulnerability ( Borrero 2005; Chen et al. 2006). Providing accurate run-up values is more difficult from these imagery data, since this requires to estimate the altitudes, which may be possible using a stereographic approach, with a couple of images, but high-resolution digital elevation models (DEMs) are rarely available in remote areas.

Here we aim at providing additional tsunami characteristics in the area of the Nusa Kambangan island, that encompasses the maximum tsunami impact in the Permisan area, using, first, SPOT images with a resolution from 20 m (SPOT2, multispectral) to 10 m (SPOT5, multispectral), and second, a Quickbird image with a resolution of 2.4 m (multispectral) and 0.6 m (panchromatic) for refined analyses. These images allow us to define the impacted areas on the Nusa Kambangan island. The image's processing involved orthorectification, coregistration and, for Quickbird images, pan-sharpening to combine panchromatic and multispectral contents, thus allowing a facilitated analysis. The coastline has been digitized from both SPOT or Quickbird sources.

2.2 Estimation of the impact on the Nusa Kambangan island

The SPOT2 image from 2006 June 26 was the only one available, acquired only a few weeks prior to the 2006 July 17 event, and is thus used as the pre-event reference for this study. With a 60 × 60 km ² spatial extent and a 20 m resolution, it offers a regional view of the Java coast near Pangandaran, which can be easily studied through the near infrared channel ( Fig. 3, top panel). The post-event SPOT5 image from 2006 July 22 has a 10 m resolution in near-infrared, and does not cover the easternmost extremity of the island as did the SPOT2 image ( Fig. 3, centre). However the Quickbird images from 2006 November 14 and 27 partly overcome this missing zone ( Fig. 3, bottom panel).

The SPOT5 image allows defining four areas impacted by the tsunami between 108°48′E and 108°52′E ( Fig. 4). The pre-event image does not reveal any cleared areas close to the coast, even near 108°49′E where the cloud cover seems more important and could be interpreted as a plough or bare soil. However the post-event image clearly exhibits four coastal areas where the vegetation has been cleared, and where the soil is bare (marked in green in Fig. 4, bottom panel), each of these places corresponding to small bays, and probably to river mouths. The horizontal distance from the shore to the forest border ranges from 100 to 300 m. Near 108°52′E, the impact seems to be more limited since the forest is only partially cleared and several trees remain. This kind of impact has been marked in blue in Fig. 4.

Near the longitude 108°52′E, using Quickbird images allows refining the impact estimated from the SPOT5 image ( Fig. 6). As previously observed on the SPOT5 image ( Fig. 4), the original forest appears as destructed, but several clumps remain standing. The Quickbird image confirms the extent of the inundation, and even defines a larger impact zone characterized by sparse trees, more or less following riverbeds, especially in the western and the eastern parts of this area. Besides, most of the cleared zones on the Nusa Kambangan island seem to correspond to river mouths, as also evidenced further east near longitude 108°56′E where, again, inundation distances amount to 100-200 m, reaching 300 m along riverbeds ( Fig. 7).

Without any further information on local elevation values, but assuming average ground slopes similar to Permisan, these first results provide minimum values for the run-up that are actually close to the ones surveyed in the area of the prison. Before synthetizing them in these terms, we first focus on the Permisan area with higher resolution imagery.

2.3 Focus on the impact on the Permisan area

The pre-event SPOT2 image shows that the Permisan prison was surrounded by dense vegetation, with however a possible less thick cover that could correspond to places cleared before the tsunami ( Fig. 8), similar to what is also observed elsewhere on the pre-event scene on Fig. 5. For the prison, the SPOT5 image underlines the forest widely cleared after the tsunami, the prison being reached by the tsunami waves, in agreement with field survey observations ( Fritz et al. 2007). The possibly pre-existing cleared fields are located within the tsunami impact zone, as also evidenced on the Quickbird scene, which allows identifying the field borders. These fields have been defined as amplified through anthropogenic activities, and marked in light orange ( Fig. 8, bottom).

The Quickbird image also provides a likely impact in the forest not previously cleared, and which was marked in dark green in Fig. 8. These places are beyond the assumed pre-existing trimline and may reflect higher altitudes. However their extent even seems to exceed the limit of the extreme measured run-up values ( Fritz et al. 2007), which correspond very well to the trimline identified on the SPOT5 scene from 2006 July 22 ( Fig. 8, top right panel). Since the Quickbird scene dates back from 2006 November, we cannot rule out that 4 months after the event, the debris could have been cleaned and the dead trees cut, so that the zones appearing as washed by the tsunami may actually correspond to some more recent human activities. Prisoners serving as workers were indeed involved in removing the debris early 2006 August ( Fritz, personal communication, 2011).

All in all, the area near the Permisan prison was heavily struck by tsunami waves, and inundation distances reach about 400 m inland, perpendicular to the shoreline.

2.4 Distribution of tsunami heights

The analysis of satellite imagery reveals long inundation distances all along the Nusa Kambangan shoreline, at several places likely related to the presence of riverbeds. These results confirm the large impact of the tsunami on this island, not only close to the prison, but also at several other places where the inundated area was similar to the one of Permisan. The measured inundation distances range from 100 to 500 m. These results broaden the measures taken on this specific island where access was restricted, and where only one site could be surveyed in the days following the tsunami ( Fritz et al. 2007).

3 Method and Data Used for Tsunami Modelling

We use numerical modelling to compute tsunami initiation, propagation and run-up on different coastal places. Different seismological sources are tested to model the sea bottom coseismic deformation triggering the tsunami. We compare our modellings with the outstanding video recording of the wave arrival in the PLTU Power Plant east of Cilacap that was converted into a tide gauge record ( Lavigne et al. 2007). Run-up computations are then focused on the Permisan area where a refined DEM has been established thanks to satellite imagery.

3.1 Method

The method used to model tsunami waves follows the approach solving the hydrodynamic equations under the non-linear shallow water (NLSW) assumption ( Heinrich et al. 1998; Hébert et al. 2001, 2007). The method solves the depth-averaged NLSW hydrodynamic equations with a finite difference scheme working on staggered grids that describe for each gridpoint the propagation velocity , where g is the gravity acceleration and h the water depth. The tsunami initiation comes from the perturbation of the sea bottom in response to the displacement due to the earthquake. This initial deformation is computed through a model of elastic dislocation ( Okada 1985) constrained with seismological parameters of the rupture that verify the expression of moment magnitude M ₀ = μULW, where μ is the rigidity, U the average slip amount, L the length and W the width of the fault plane (e.g. Kanamori & Anderson 1975). When taking into account a finite rupture propagation, which is worth being tested for slow tsunami earthquakes, the contribution of each subfault is computed at the corresponding rise time, and added to the ongoing wavefield.

The hydrodynamical equations are:

where h is the sea depth and η the water elevation above mean sea level, v the depth-averaged horizontal velocity vector, g the gravity acceleration. Equations of continuity (1) and motion (2) are solved in spherical coordinates by means of a finite-difference method, centred in time and using an upwind scheme in space. Under the shallow water theory dispersive effects are neglected. Close to the coasts the phase velocity c = ( gh)1/2 drastically decreases, leading to the tsunami wave amplification.

The decreasing of tsunami wavelengths implies the need for finer bathymetric grids when the tsunami approaches the coasts. To properly model the tsunami arrival at the local scale we usually consider a series of five levels of nested bathymetric grids characterized by an increasing resolution, from a few kilometres in deep ocean (encompassing the source area) down to 5-15 m in bays and harbours. Open free boundary conditions are ascribed to the boundaries of the larger grid, and wave heights and velocities along the boundaries of a fine grid are spatially interpolated at each time step from the values computed in the coarse grid containing the fine grid.

3.2 Building a DEM

To compare tsunami observations with modelling, we took the opportunity to have high-resolution images in the area of the prison to build a detailed DEM essential for refined tsunami modelling. To this aim we needed a couple of high-resolution images taken after the tsunami, to map the area on both scenes, and without vegetation. We added a Quickbird image from 2006 December 7 to the previous image from 2006 November 27 to build a stereoscopic pair taken at different incidences. The first image (November 27) was taken with a 106° azimuth and a 69.9° incidence, while the second image (December 7) had a 275° azimuth and a 72.1° incidence, thus this couple offers an optimal stereoscopic view, with a base to height ratio of = 0.7.

About 450 tie points have been manually identified on both images ( Fig. 10), first close to the shore where the ground without vegetation was available, then on most of the cleared places. Then the relative altitudes were computed through the parallax estimation between both scenes. Since QuickBird images are orthorectified with a constant mean height DEM (ortho-ready products), the parallax Δ p along the epipolar direction between the images is related to the relative altitude to the orthorectification mean height Δh by:

K being an unknown bias related to the global misregistration of the images. The few relative heights obtained within the forest have been corrected from a standard palm tree height taken to 13 m. The obtained values have also been cautiously adjusted to the available run-up values obtained in the area ( Fritz et al. 2007), which also provide altitudes at the surveyed places. The final interpolation was carried out with additional data taken from SRTM values above the 20 m altitude.

Concerning bathymetric data, no detailed nautical chart was available. We chose the trend from the GEBCO 30″ data ( IOC, IHO & BODC 2003) that were progressively re-interpolated close to the studied site, to produce a complete computational grid imbricated to a series of five regular grids, from a 1′ (about 1800 m) grid encompassing the earthquake source, down to the final 15 m grid focusing on the Permisan area. In the following we show the results of tsunami modelling towards this place, as well as towards the area of PLTU Power Plant east to Cilacap.

3.3 Bathymetric grids for this study

We based our bathymetric grids on the global bathymetry now made available at a 30″ cell size (GEBCO data, IOC, IHO & BODC 2003). The first grid level (extent of Fig. 1) was built from a 1′ sampling of these data, enough to discretize the source rupture area and to enable rapid computations. Then subsequent grid levels have been synthetized using interpolations of containing values and more refined data sets. The grids 2 (extent displayed in Fig. 2), 3 and 4 focus on the Permisan area down to a 15 m grid cell corresponding to DEM data constructed from stereoscopic imagery ( Fig. 10). While these topographic data are here well detailed, no refined bathymetric data were available off the Permisan area. We added bathymetric contours from the GEBCO 30″ data to ensure a proper focusing and imbrication of the bathymetric grids. However it has to be noted that, while the average slope offshore is probably well modelled this way, the detailed local coastal features are not taken into account in this grid.

Concerning the PLTU area, a 45 m grid was built based on additional data for the Cilacap harbour, provided by local authorities. At the PLTU site, available pictures of the water supply channel and observations reported by field surveys ( Lavigne et al. 2007) allowed digitizing a bathymetric data set that was interpolated into a 15 m grid to model the channel. Although this is a rather coarse approach, and topographic data were not considered here (their trend was taken from SRTM data), the overall dimensions and depth of this basin appearing in the video recording are well reproduced using direct witnesses reports ( Lavigne, personal communication, 2006).

3.4 Earthquake sources

We chose to test available seismological sources for the 2006 earthquake, first a source computed through an inversion of Rayleigh waves confirming the slow rupture and the directivity towards an azimuth of 109°E ( Ammon et al. 2006), and second, a source based on the inversion of tsunami waveforms recorded at several places in the Indian Ocean ( Fujii & Satake 2006). This kind of tsunami data inversion has proved to be consistent with seismological models retrieved from inversions of seismic data, and are able to produce similar patterns of coseismic slip heteorogeneities for large earthquakes ( Sladen & Hébert 2008); besides joint inversions using both tsunami and seismic data sets are nowadays frequently carried out to produce consistent coseismic models, as for the 2011 Tohoku earthquake (e.g. Yokota et al. 2011).

The first model used here ( Ammon et al. 2006) involves a very low rigidity of 10 GPa consistent with a rupture within the sedimentary accretionary wedge, a common characteristic inferred for tsunami earthquakes ( Polet & Kanamori 2000), and the rupture velocity is retrieved to 1.25 km s −1. Distributed over 975 subfaults with an average slip of 8-15 m, this model yields a seismic moment of 7.0 10 ²⁰ Nm.

The tsunami waveform inversion ( Fujii & Satake 2006) yields, first, the area of the source rupture, and, second, a slip distribution over 10 subfaults. By letting both the rupture velocity and the slip distribution vary, the resulting source model consists of average slips from 0.5 to 2.5 m, assuming a rigidity of 30 GPa.

4 Results from Tsunami Modelling

4.1 On the regional scale

Modelling results at the regional scale ( Fig. 12) confirm the great values of tsunami heights obtained using the Ammon model. For this source indeed, maximum tsunami heights computed offshore reach 2 m and more for three distinct areas: the whole margin off Pangandaran, the island of Nusa Kambangan and the bay of Cilacap. Actually two of these maximum lobes already originate farther offshore, from the source, beyond the main margin slope, and they are eastwards shifted when a finite rupture velocity is considered (model B). As expected, using a rupture velocity can change the tsunami pattern offshore, as already shown for example for the 2004 tsunami ( Geist et al. 2007), and this can change the definition of areas at risk. However, for the 2006 tsunami, as the studied area is in the near field, the impact seems to be only marginally shifted from a few kilometres. The three maximum lobes evidenced here are also correlated with three shallower parts of the breaking slope, hence low-velocity zones acting as focusing lenses, where tsunami heights are more amplified.

A similar tsunami pattern is obtained for the Fujii source (models C and D), even though with smaller amplitudes. In the latter case however, the finite rupture even yields larger amplitudes off PLTU than off the prison, for an unclear reason. Except for this area, the amplitudes computed offshore do not exceed 1 m.

All conducted models allow defining the area from Pangandaran to east Cilacap as the most impacted area. This portion of the coastline also seems to correspond to a wider margin shelf (between 108.5°E and 109.5°E), seemingly less steep than the other coastal shelves farther westwards and eastwards. This pattern may be able to keep the tsunami energy and even to efficiently amplify it before reaching the coast for the whole impacted area.

4.2 Comparison with observations in PLTU

The video recording in the PLTU basin was converted in a sea level temporal variation ( Lavigne et al. 2007) and can be compared with modelling results. All the source models yield a very satisfying waveform for the gauge located where the sea level was observed on the record.

Using static source models ( Fig. 13, bottom) yields first arrival times slightly in advance with respect to the observation, with a shift from 5 min (Fujii source) to 4 min (Ammon source). The modelled amplitudes are larger than the observed one for the Ammon source (5 m compared to about 3 m), while the Fujii source is too small with a factor of about 2. However, the waveform is satisfactorily close to the one recorded, and the models predict a second wave arriving about 12 min after the first one. This wave was indeed reported by several witnesses in the area of Cilacap.

Using a finite rupture increases the modelled amplitudes with the Fujii model, as for the model in the Permisan area, while the Ammon source similarly exceeds the observation ( Fig. 13, top). The arrival times are also closer to the observed ones, especially for the Ammon model: as expected from the source directivity, the kinematic models increase the arrival times of about 2-3 min. For all models the computed duration of the first arrival is about 8 min, to be compared to the observed 10 min duration. Subsequent waves were not reported from the video recording, while the models indicate further arrivals of smaller amplitude about 12 min after. It is also worth stressing that the very abrupt inception of the wave is well modelled and similar to the observed one.

These results illustrate the efficiency of the Ammon source, and to a lesser extent of the Fujii source, to match the tide gauge observations. Even though the used DEM is approximate, the basin geometry has been cautiously designed to be consistent with the actual one, allowing to properly model tsunami amplitudes. However since the approach of the basin may be more inaccurate, this could account for the time shift observed between the synthetic and actual signal. Such shifts are not unusual in detailed tsunami modellings and synthetics are often earlier than observations since the velocity model does not account accurately for the shoaling effect in the last metres, where this is the most influent.

4.3 Detailed study in the Permisan area

Using a kinematic model does not change the flooding pattern that significantly, except for the Fujii source. The Ammon source (B) is very similar to the static source (A), apparently more restricted close to the prison. Using the Fujii source (D) increases the flooded area obtained with the static source, reaching the run-up measurement points, but the overall amplitudes are still low, and the flow depths do not exceed 1-2 m.

However, in any case, none of these earthquake source models is able to produce tsunami heights comparable with the ones available from field surveys ( Fritz et al. 2007) that reached about 10 m of flow depth over the inundated area of Permisan. This underlines a need for a secondary source able to fill this gap for this portion of the coastline.

4.4 Modelling the tsunami heights distribution

The distribution of tsunami run-up data along the coastline shown in Fig. 9 can also provide indications on the tsunami source process, especially as it concerns the ratio between the maximum amplitudes and the lateral extent of the distribution along the shore ( Okal & Synolakis 2004). This ratio is indeed greatly increased from 10 −5-10 −4 for most of the earthquake sources to 10 −3 at least for assumed landslide sources (for instance 1946, Aleutian; 1998, Papua New Guinea, both events characterized by an earthquake followed by a large submarine landslide). Following the quantitative description of this behaviour proposed by Okal & Synolakis (2004), we attempted here to model the 2006 distribution using their dimensionless parameters, namely a (lateral extent of sustained run-up along the coast), b (maximum run-up height), defining as the aspect ratio of the distribution, and,

1. 1
for an earthquake, where Δ u is the fault slip,

2. 2
for a landslide, , where η₋ is the initial depression of the sea surface.

For the 2006 data, the overall distribution is well modelled using a = 200 km, b = 8 m and Δ u∼ 6 m. This yields log( I ₁) = 0.1 and log( I ₂) =−4.4, thus in the upper category of the series of modelling results displayed in Okal & Synolakis (2004) study, consistent with tsunami earthquakes such as in 1994 (Java) or 1992 (Nicaragua). The corresponding red line displayed in Fig. 15 obviously cannot explain the peak amplitudes of the Nusa Kambangan island. An additional source described by a = 8 km, b = 12 m and = 9 m, corresponds to log( I ₂) =−2.8 and log( I ₃) = 0.1, and again belongs to an extremity of the modelling results of the referred study. The corresponding blue line in Fig. 15 allows to propose a very narrow run-up distribution which, added to the previous one, is able to properly explain the overall distribution reaching about 20 m in its centre (pink line in Fig. 15). This is consistent with the additional source already proposed ( Fritz et al. 2007), that we finally also proposed from the modelling results presented in the previous sections.

5 Discussion and Conclusions

5.1 Discussion on the uncertainties

While satellite imagery provided a clear horizontal mapping of the flooded areas, we saw that the uncertainties on the average ground slope are not large enough to discard a striking anomaly in the run-up distribution along the coast. Tsunami modelling can also be associated with uncertainties, especially concerning the source model used and the flooding parameters. However tsunami studies relying on modelling are generally efficient to discuss the characteristics of an event based on run-up data, or tide gauge data when available. For instance, tsunami modelling can efficiently explain observed sea level anomalies in the far distances, provided accurate bathymetry is available in the harbour, and all the more as an accurate model of the slip heterogeneities is used (examples in La Réunion, Hébert et al. 2007, or in French Polynesia, Hébert et al. 2009). A single source model is however rarely relevant (see for instance Poisson et al. 2011), and the definition of the source parameters also depends on the propagation model used: source components of shorter wavelength may require a model taking into account frequency dispersion. In our study, close to the source, such dispersion cannot be significant, and the source wavelengths are long enough to avoid a dispersive model.

Nevertheless, high-resolution bathymetric data are necessary to improve models near Permisan. In this study, in designing an elevation model from satellite imagery, we achieved to produce tsunami models using realistic earthquake sources. These input parameters remain at the origin of the first-order uncertainties in the results, as shown using either the Ammon or the Fujii source. Even with a more realistic source accounting for the 2006 low seismic rupture, such results in the near field are not significantly changed. Such an effect is expected to be more influencing in the far field, when maximum tsunami energy can be significantly shifted in the direction of the seismic rupture ( Geist et al. 2007; Poisson et al. 2011).

The modelling of flooding is very sensitive to various parameters of the models. However, generally, models tend to overestimate the flooding because they lack physical dissipation due to the ground friction. In our case, this is unlikely to occur, because the extent of the flooding is not questionable, and by the way is rather well modelled. Instead these are the overall modelled flow depths that remain too low by a factor 2 at least, with respect to observations, thus again stressing the need for a more complex source.

5.2 A possible secondary source

Coarse modelling results obtained using the earthquake source from Ammon et al. (2006) are also displayed in Fig. 15 (green line). They are taken along the 5 m bathymetric contour, and exhibit amplitudes from 2 to 6 m, in line with the overall data distribution. These figures are consistent with coastal amplitudes reaching finally 10 m and even more, once the shoaling effect is taken into account. However the peaks obtained in this coarse modelling do not indicate a specific relative amplification towards Nusa Kambangan, but rather towards Pangandaran and PLTU sites, which were indeed heavily impacted ( Lavigne et al. 2007).

Whenever an additional tsunami source has to be invoked, as already suggested in previous studies ( Fritz et al. 2007; Lavigne et al. 2007), our study confirms that it should have occurred directly off Nusa Kambangan, where it may have doubled the final tsunami amplitudes along a portion of the coastline not exceeding 20-30 km in length. Following the analysis presented, a tsunamigenic landslide with an initial depression close to 10 m could have been triggered there. This scenario is significantly smaller than a similar sequence (earthquake followed by a submarine landslide) in 1998 in Papua New Guinea ( Heinrich et al. 2001) that produced extreme run-up values along about 20 km of the shoreline, while tsunami heights barely reached 1-2 m, 20 km away from this extreme height. To a less extent, the tsunami triggered in 1979 by a submarine failure off the Nice airport (French Riviera) produced extreme tsunami heights (at least 5 m) at the airport, while it was unnoted on a tide gauge located 15 km away in Mandelieu ( Labbé 2012). On the contrary in 2006, the earthquake source alone still contributes to high tsunami waves more than 50 km from the maximum amplitude point.

Such a secondary source off Nusa Kambangan could therefore have contributed to increase run-up on the Nusa Kambangan island only, while other places would have been impacted by the tsunami essentially due to the earthquake, which, as a tsunami earthquake, produced large water heights for this level of magnitude. Also, in the case of this 2006 tsunami earthquake, which is supposed to have radiated low-frequency seismic waves, with a soft ground shaking, the triggering of a landslide should have occurred in submarine slopes either very steep and/or very unstable. One could also remark that in 2006 May a strong earthquake shook central Java with magnitude M w 6.2, less than 200 km away from the 2006 July earthquake. Submarine sedimentary layers on steep slopes could have increased their instability at the occasion.

The recent synthesis of bathymetric data in Indonesia ( Brune et al. 2010) reveals important submarine landslides, one of them offshore Java, with an assumed 3 km ³ volume, but far eastwards of Pangandaran near 110°30′, thus not realistically related to the 2006 July tsunami. According to Brune et al. (2010), submarine landslidings are frequent off Indonesia, and the important sedimentary deposition may even be oversteepened by tectonic processes due to subduction, especially off Java.

In any case, only a detailed in situ investigation off Pangandaran and Nusa Kambangan (high-resolution bathymetry and subbottom profiler) could complete the surveys presented in this synthesis of landslides identified off Java ( Brune et al. 2010), and confirm whether such an event may have occurred in 2006. This would also be fruitful to better characterize the submarine slopes off Nusa Kambangan, and the capacity of the submarine relief to focus or defocus tsunami energy. The available bathymetric data from global data sets do not reveal any tsunami-focusing feature, such as a localized submarine ridge. The impact of this kind of structure is however important for high water depths (a few hundreds of metres), where more important relative velocity contrasts are more efficient in focusing and defocusing the tsunami energy. The continuous improvement of the global bathymetry data sets makes rather unlikely that such a structure could be nowadays discovered.

5.3 Concluding remarks

In this study we have been able, thanks to satellite imagery, to image the horizontal extent of the 2006 tsunami on the Nusa Kambangan island, the area where the impact was the highest. Given average ground slopes, these extents confirm extreme run-up values from 15 to 20 m for the whole Nusa Kambangan island, thus not only on the Permisan prison. These satellite data are extremely important to be gathered in the first days after the event, not only to guide rescuing operations, but also to assess damage and to propose DEMs, provided a recent pre-event image is available.

Tsunami modelling carried out for two detailed areas, in the Permisan prison and the PLTU Power Plant, provides contrasted results with respect to available observations, rather underestimated in the highly impacted Permisan site, while rather in good agreement in the PLTU location. Using two published seismological sources, accounting for finite or infinite seismic rupture, these differences cannot be simply explained by modelling uncertainties. However, they confirm that the tsunami was high on all the impacted area, for the magnitude level of the vent, as is expected for a tsunami earthquake. Besides although the dissemination and communication systems have been improved in Indonesia, as well as the automatic estimation of the magnitude in the first minutes after the main shock ( Hanka et al. 2010), this 2006 event stresses the difficulty of handling slow earthquakes in the near field in Warning Systems, which must be able to detect the slow seismic rupture involved in such earthquakes, using seismic wave analyses at longer period ( Kanamori & Kikuchi 1993).

Following a previous study ( Fritz et al. 2007), and together with the overall analysis of the tsunami observations along the coastline, our results finally supports that an additional source, possibly due to a submarine landslide, may have increased the tsunami impact off Nusa Kambangan. Only a detailed offshore mapping of the submarine slopes off this region of Java could help confirming such a landlslide source, and would provide essential parameters to compare future landslide modellings with available data.

Acknowledgments

This work has been supported by the French Agence Nationale de la Recherche, under the contract Cattell TSUMOD ANR-05-CATT-016-01, and then under the contract RiskNat MAREMOTI ANR-08-RiskNat-05. It also initially benefited from the support of the Délégation Interministérielle chargée de l'aide Post-Tsunami (DIPT) set up by the French Ministry of Foreign Affairs after the catastrophic 2004 Indian Ocean tsunami. We thank Hermann Fritz and an anonymous reviewer for their constructive remarks, and the Editor Saskia Goes for her in-depth analysis to improve the clarity of the paper.

References

.

The 1994 Java tsunami earthquake and its "normal" aftershocks

,

,

, doi:10.1029/2002GL016806.

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2006 July 17 Java (Indonesia) tsunami from satellite imagery and numerical modelling: a single or complex source?

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The M w 7.8 2006 July 17 earthquake off the southern coast of Java, Indonesia, has been responsible for a very large tsunami causing more than 700 casualties. The tsunami has been observed on at least 200 km of coastline in the region of Pangandaran (West Java), with run-up heights from 5 to more than 20 m.

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From Wikipedia, the free encyclopedia

An earthquake occurred on July 17, 2006 at along a subduction zone off the coast of west and central Java, a large and densely populated island in the Indonesian archipelago. The shock had a moment magnitude of 7.7 and a maximum perceived intensity of IV (Light) in Jakarta, the capital and largest city of Indonesia. There were no direct effects of the earthquake's shaking due to its low intensity, and the large loss of life from the event was due to the resulting tsunami, which inundated a 300 km (190 mi) portion of the Java coast that had been unaffected by the earlier 2004 Indian Ocean earthquake and tsunami that was off the coast of Sumatra. The July 2006 earthquake was also centered in the Indian Ocean, 180 kilometers (110 mi) from the coast of Java, and had a duration of more than three minutes.

An abnormally slow rupture at the Sunda Trench and a tsunami that was unusually strong relative to the size of the earthquake were both factors that led to it being categorized as a tsunami earthquake. Several thousand kilometers to the southeast, surges of several meters were observed in northwestern Australia, but in Java the tsunami runups (height above normal sea level) were typically 5-7 meters (16-23 ft) and resulted in the deaths of more than 600 people. Other factors may have contributed to exceptionally high peak runups of 10-21 m (33-69 ft) on the small and mostly uninhabited island of Nusa Kambangan, just to the east of the resort town of Pangandaran, where damage was heavy and a large loss of life occurred. Since the shock was felt with only moderate intensity well inland, and even less so at the shore, the surge arrived with little or no warning. Other factors contributed to the tsunami being largely undetected until it was too late, and although a tsunami watch was posted by an American tsunami warning center and a Japanese meteorological center, no information was delivered to people at the coast.

The island of Java is the most densely populated island on Earth, and is vulnerable to both large earthquakes and volcanic eruptions, due to its location near the Sunda Trench, a convergent plate boundary where the Australian tectonic plate is subducting beneath Indonesia. Three great earthquakes occurred in the span of three years to the northwest on the Sumatra portion of the trench. The 2004 M9.15 Sumatra-Andaman, the 2005 M8.7 Nias-Simeulue, and the 2007 M8.4 Mentawai earthquakes produced the largest release of elastic strain energy since the 1957/ 1964 series of shocks on the Aleutian/Alaska Trench.[9]

The southeastern (Java) portion of the Sunda Trench extends from the Sunda Strait in the west to Bali Basin in the east. The convergence of relatively old oceanic crust is occurring at a rate of 6 centimeters (2.4 in) per year in the west portion and 4.9 cm (1.9 in) per year in the east, and the dip of the Benioff Zone (the angle of the zone of seismicity that defines the down-going slab at a convergent boundary) is around 50° and extends to a depth of approximately 600 kilometers (370 mi). Pre-instrumental events were the large to very large events of 1840, 1867, and 1875, but unlike the northwestern Sumatra segment, no megathrust earthquake has occurred on the Java segment of the Sunda Trench in the last 300 years.[10]

The earthquake was the result of thrust faulting at the Sunda Trench. A rupture length of approximately 200 kilometers (120 mi) (and an unusually low rupture velocity of 1-1.5 km (0.62-0.93 mi) per second) resulted in a duration of about 185 seconds (just over three minutes) for the event. The shock was centered 50 kilometers (31 mi) from the trench, and about 180 kilometers (110 mi) from the south coast of the island. A comparison was made with the earlier 2002 Sumatra earthquake, a M7.5 submarine earthquake of a similar size that also occurred along the Sunda Arc and at a shallow depth, but one that did not result in a tsunami.[4][9]

The large and damaging tsunami that was generated was out of proportion relative to the size of the event, based on its short-period body wave magnitude. The Indonesian Meteorological, Climatological, and Geophysical Agency assigned a magnitude of 6.8, and the United States Geological Survey (USGS) reported a similar value of 6.1 (both body wave magnitude) that were calculated from short-period seismic waves (1-2 seconds in the case of the USGS). The USGS then presented a moment magnitude of 7.2 that was calculated from 5-100-second surface waves, and Harvard University subsequently revealed that a moment magnitude of 7.7 had been resolved based on even longer 150-second surface waves.[4]

In tsunami prone regions, strong earthquakes serve as familiar warnings, and this is especially true for earthquakes in Indonesia. Previous estimates of the tsunami hazard for the Java coastline may have minimized the risk to the area, and to the northwest along the Sumatran coast, the risk is substantially higher for tsunami, especially near Padang. Previous events along the coast of Java in 1921 and again in 1994 illustrate the need for an accurate assessment of the threat. The July 2006 earthquake had an unusually slow rupture velocity which resulted in minor shaking on land for around three minutes, but the intensity was very light relative to the size of the tsunami that followed.[7]

The earthquake produced shaking at Pangandaran (where the M6.3 2006 Yogyakarta earthquake was felt more strongly) of intensity III-IV ( Weak- Light), intensity III at Cianjur, and II ( Weak) at Yogyakarta. Further inland and farther from the epicenter, intensity IV shaking made tall buildings sway in Jakarta, but at some coastal villages where many of the casualties occurred, the shaking was not felt as strong. An informal survey of 67 people that were present at the time revealed that in at least eight cases, individuals stated that they did not feel the earthquake at all (a typical M7.7 earthquake would have been distinctly noticed at those distances). The unusually low felt intensities, along with the short period body wave magnitudes, were components of the event that narrowed its classification into that of a tsunami earthquake.[6]

Tsunami earthquakes can be influenced by both the presence of (and lack of) sediment at the subduction zone, and can be categorized as either aftershocks of megathrust earthquakes, like the M7 June 22, 1932 Cuyutlán event in Mexico, or as standalone events that occur near the upper portion of a plate interface. Northwestern University professor Emile Okal imparts that in the aftershock scenario, they can occur as a result of stress transfer from a mainshock to an accretionary wedge or a similar environment with "deficient mechanical properties", and as standalone events they can occur in the presence of irregular contacts at the plate interface in a zone that lacks sediment.[11]

One of the initial characterizations of tsunami earthquakes came from seismologist Hiroo Kanamori in the early 1970s, and additional clarity materialized following the 1992 Nicaragua earthquake and tsunami, which was evaluated to have a surface wave magnitude of 7.0 when analyzing short period seismic signals. When longer period signals of around 250 seconds were investigated, the shock was reevaluated to have a moment magnitude of 7.6, with a hypothesis that the slow nature of the slip of the event may have concealed its substantial extent. Sediment was thought to have contributed to a slower rupture, due to a lubrication effect at the plate interface, with the result being an earthquake signature that had abundant long period seismic signals, which could be an important factor in the tsunami-generation process.[4]

A tsunami warning system was not in operation at the time of the shock, but the Pacific Tsunami Warning Center (operated by the National Oceanic and Atmospheric Administration in Hawaii) and the Japan Meteorological Agency posted a tsunami watch, based on the occurrence of a M7.2 earthquake. The bulletin came within 30 minutes of the shock, but there was no means to transmit the warning to the people on the coast that needed to know. Many of those who felt the earthquake responded by moving away from the shore, but not with any urgency. The withdrawal of the sea that exposed an additional 5-10 meters (16-33 ft) of beach created an even more significant warning sign, but in some locations wind waves on the sea effectively concealed the withdrawal that signalled the approach of the tsunami.[12][13]

The earthquake and tsunami came on a Monday afternoon, a day after many more people were present on the beach, due to a major national holiday. The waves came a few tens of minutes after the shock (and were a surprise, even to lifeguards) and occurred when the sea level was approaching low tide which, along with the wind waves, masked the initial withdrawal of the sea as the tsunami drew near. Most portions of the south Java coast saw runup heights of 5-7 meters (16-23 ft), but evidence on the island of Nusa Kambangan indicated that a peak surge measuring 21 meters (69 ft) had occurred there, suggesting to researchers that the possibility of a submarine landslide had contributed to the magnitude of the tsunami in that area.[14]

A 300 km (190 mi) portion of the southwest and south-central Java coast was affected by the tsunami, and resulted in around 600 fatalities, with a high concentration in Pangandaran. Two thousand kilometers (1,200 mi) to the southeast at the Steep Point area of western Australia, a runup of 2 m (6 ft 7 in) was measured, which was comparable to a similar runup in northern Oman from the 2004 Indian Ocean earthquake and tsunami, though in that case it was at a much greater distance of 5,000 kilometers (3,100 mi). Within three weeks of the event, scientists from five different countries were on the ground in Java performing a survey of the affected areas, including gathering runup (height above normal sea level) and inundation (distance the surge moved inland from the shore) measurements.[13]

The island of Nusa Kambangan (30 km × 4 km (18.6 mi × 2.5 mi)) sits on the south coast of Java and is separated from the main island by a narrow strait. It is a large and mostly uninhabited nature reserve, and is referred to as the Alcatraz of Indonesia, due to the three high security prisons that are located at the town of Permisan. Of all the measurements taken during the post-tsunami survey, the highest runup heights (10-21 m (33-69 ft)) were seen on the island behind a beach, where hibiscus and pandanus plants, and large coconut trees were mangled and uprooted up to 1,500 m (4,900 ft) from the shore. The (sea floor) bathymetry in the area supported a proposition that a canyon slope failure or an underwater landslide may have contributed to or focused the tsunami energy at that location. Nineteen farmers and one prisoner were killed there, but the deep water port of Cilacap (just to the east) was protected by the island, although one large moored vessel made ground contact during the initial 1.5 m (4 ft 11 in) withdrawal.[13]

Since the earthquake caused only minor ground movement, and was only lightly felt, all the damage that occurred on the island was due to the tsunami. Types of buildings that were affected were timber/ bamboo, brick traditional, and brick traditional with reinforced concrete. Semi-permanent timber or bamboo structures that were based on a wooden frame were the most economical style of construction that were assessed following the disaster. A tsunami flow depth of 2 m (6 ft 7 in) usually resulted in complete destruction of these types of structures. A group of scientists that evaluated the damage considered the unreinforced brick construction as weak, because the performance of homes constructed in that style did not fare much better than the timber/bamboo variety. Hotels and some houses and shops that were of reinforced brick construction were far better off, because units that were exposed to a flood depth of 3-4 meters (9.8-13.1 ft) were considered repairable.[8]

Many wooden cafes and shops within 20 meters (66 ft) of the shore were completely removed by the tsunami at Pangandaran, and severe damage still occurred to unreinforced masonry that was within several hundred meters, but some hotels that were constructed well held up better. The villages of Batu Hiu and Batu Kara, both to the west of Pangandaran, experienced similar damage. Other severe damage was seen at Marsawah village, Bulakbenda, where all buildings had been removed down to their foundation within 150 meters (490 ft) of the water line, and even 300-500 m (980-1,640 ft) further inland there were many buildings that were totally destroyed. Witnesses reported that waves were breaking several hundred meters inland at that location.[12]

Officials in Indonesia received information regarding the tsunami in the form of bulletins from the Pacific Tsunami Warning Center and the Japan Meteorological Agency, but wanted to avoid panic, and did not attempt to disseminate the advisories to the public. Virtually no time was available to make that sort of effort (had the intention been to communicate the danger with the public) because some community leaders were sent text messages with pertinent information only minutes prior to the arrival of the first waves. The tsunami affected the coast of Java comprising mostly fishing villages and beach resorts that were unscathed following the 2004 Indian Ocean tsunami, and was also only several hundred kilometers distant from the region that saw heavy destruction just several months prior during the 2006 Yogyakarta earthquake.[15]

Trained research teams were already on the ground on Java responding to the May earthquake and began a survey of more than one hundred Muslim farmers, plantation laborers, and fishermen (or those with fishing-related occupations) that were affected by the tsunami. Almost two thirds of the group reported that they lived in permanent structures made of wood, brick, or cement, while the remainder lived in semi-permanent facilities made from earth or stone. The government was cited as the first responder for water, relocation and medical assistance, and helping with the deceased. For rescue, shelter, clothing, and locating missing people, individuals were listed as the primary provider, but 100% of those surveyed replied that the government should be responsible for relief. Most of those requiring aid stated that they were given effective assistance within 48 hours and that they were satisfied with the help.[15]

1. ^ Ammon, C. J.; Kanamori, H.; Lay, T.; Velasco, A. A. (2006), "The 17 July 2006 Java tsunami earthquake" (PDF), Geophysical Research Letters, 33 (24): 1, Bibcode:2006GeoRL..3324308A, doi:10.1029/2006gl028005

2. ^ ISC (2016), ISC-GEM Global Instrumental Earthquake Catalogue (1900-2009), Version 3.0, International Seismological Centre

3. ^ Mori et al. 2010, p. 202

4. ^ Kuenza, K.; Soon-Hoe, C. (2010), "Anatomy of the 17 July 2006 Java Earthquake Reveals Its Tsunamigenic Nature", Seismological Research Letters, 81 (1): 99-101, doi:10.1785/gssrl.81.1.99

5. ^ Muhari, A.; Diposaptono, S.; Imamura, F. (2007), "Toward an integrated tsunami disaster mitigation: Lessons learned from previous tsunami events in Indonesia" (PDF), Journal of Natural Disaster Science, 29 (1): 15, doi:10.2328/jnds.29.13

6. Mori et al. 2010, p. 203

7. Yulianto, E.; Setja Atmadja, C. M. (2009), "Predecessors of the 2006 South Java Tsunami", Estimating the recurrence interval and behavior of tsunamis in the Indian Ocean via a survey of tsunami-related sedimentation, Tsukuba International Congress Center: National Research Institute for Earth Science and Disaster Prevention, p. 19

8. Reese, S.; Cousins, W. J.; Power, W. L.; Palmer, N. G.; Tejakusuma, I. G.; Nugrahadi, S. (2007), "Tsunami vulnerability of buildings and people in South Java - field observations after the July 2006 Java tsunami" (PDF), Natural Hazards and Earth System Sciences, 7 (5): 573, 580-582, Bibcode:2007NHESS...7..573R, doi:10.5194/nhess-7-573-2007

9. Yeats, R. (2012), Active Faults of the World, Cambridge University Press, pp. 457, 462-464, ISBN 978-0-521-19085-5

10. ^ Irsyam, M.; Dangkua, D. T.; Hendriyawan; Hoedajanto, D.; Hutapea, B. M; Kertapati, E. K.; Boen, T.; Petersen, M. D. (2008), "Proposed seismic hazard maps of Sumatra and Java islands and microzonation study of Jakarta city, Indonesia" (PDF), Journal of Earth System Science, 117 (2): 868, 869, Bibcode:2008JESS..117..865I, doi:10.1007/s12040-008-0073-3, S2CID 129933598

11. ^ Okal, E. A. (2012), "The south of Java earthquake of 1921 September 11: a negative search for a large interplate thrust event at the Java Trench" (PDF), Geophysical Journal International, 190 (3): 1657-1659, Bibcode:2012GeoJI.190.1657O, doi:10.1111/j.1365-246x.2012.05570.x

12. Mori et al. 2010, p. 204

13. ^ Fritz, H. M.; Kongo, W.; Moore, A.; McAdoo, B.; Goff, J.; Harbitz, C.; Uslu, B.; Kalligeris, N.; Suteja, D.; Kalsum, K.; Titov, V.; Gusman, A.; Latief, H.; Santoso, E.; Sujoko, S.; Djulkarnaen, D.; Sunendar, H.; Synolakis, C. (2007), "Extreme runup from the 17 July 2006 tsunami", Geophysical Research Letters, 34 (12): L12602, Bibcode:2007GeoRL..3412602F, doi:10.1029/2007gl029404, S2CID 129647228

14. ^ Georgia Institute of Technology (June 18, 2007). "Scientists report study results from 'stealth' tsunami that killed 600 in Java last summer" (Press release). Eurekalert!.

15. Bliss, D.; Campbell, J. (2007), The immediate response to the Java tsunami: Perceptions of the affected (PDF), Fritz Institute, pp. 2-6, archived from the original (PDF) on 2019-11-05

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Mori, J.; Mooney, W. D.; Afnimar; Kurniawan, S.; Anaya, A. I.; Widiyantoro, S. (2010), "The 17 July 2006 Tsunami Earthquake in West Java, Indonesia" (PDF), Seismological Research Letters, 78 (2): 201-207, doi:10.1785/gssrl.78.2.201

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2006 Pangandaran earthquake and tsunami - Wikipedia

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Toggle the table of contents From Wikipedia, the free encyclopedia An earthquake occurred on July 17, 2006 at along a subduction zone off the coast of west and central Java, a large and densely populated island in the Indonesian archipelago.

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The 2006 Java, Indonesia tsunami caused significant economic impacts including damage to infrastructure, loss of property, disruption of economic activities, decrease in GDP, increase in unemployment, and an increase in public debt.

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The 2006 Java, Indonesia tsunami caused significant economic impacts including damage to infrastructure, loss of property, disruption of economic activities, decrease in GDP, increase in unemployment, and an increase in public debt.

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 there is no information available about significant environmental impacts caused by the 2006 Java, Indonesia tsunami, but in general Tsunami cause Coastal erosion,Habitat destruction,Contamination of soil and water, Damage to marine ecosystems and fisheries, Coastal flooding and destruction of wetlands, Introduction of invasive species, Damage to coral reefs and other underwater habitats, Destruction of mangrove forests, Loss of biodiversity, Soil and water salinization.

# data[].attributes.subject
 there is no information available about significant environmental impacts caused by the 2006 Java, Indonesia tsunami, but in general Tsunami cause Coastal erosion,Habitat destruction,Contamination of soil and water, Damage to marine ecosystems and fisheries, Coastal flooding and destruction of wetlands, Introduction of invasive species, Damage to coral reefs and other underwater habitats, Destruction of mangrove forests, Loss of biodiversity, Soil and water salinization.

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The 2006 Java, Indonesia tsunami affected coastal areas, including the city of Pangandaran.

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The 2006 Java, Indonesia tsunami affected coastal areas, including the city of Pangandaran.

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The 2006 Java, Indonesia tsunami was caused by a 7.7 magnitude earthquake.

# data[].attributes.subject
The 2006 Java, Indonesia tsunami was caused by a 7.7 magnitude earthquake.

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resulted in significant damage to coastal areas, including the city of Pangandaran. It caused 668 deaths, over 9,000 injuries, and over 100,000 people displaced.

# data[].attributes.subject
resulted in significant damage to coastal areas, including the city of Pangandaran. It caused 668 deaths, over 9,000 injuries, and over 100,000 people displaced.

# data[].attributes.headline
The 2006 Java, Indonesia tsunami was caused by a 7.7 magnitude earthquake.

# data[].attributes.subject
The 2006 Java, Indonesia tsunami was caused by a 7.7 magnitude earthquake.

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 located off the southern coast of Java, Indonesia. 

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 located off the southern coast of Java, Indonesia. 