NH5.1

Subaerial landslides are among the most complex sources for tsunamis, as several complex processes occur simultaneously in various regimes, with multiple phases interacting. The simulation and prediction of these events is respectively difficult.

We will present a three-dimensional multiphase model (granules, air, water) that considers the  effects and properties that we deem most important: (i) a sharp water-air interface with low diffusivity, (ii) granular rheology for the landslide, (iii) differentiation between effective pressure and pore pressure, as well as (iv) porosity, dilatancy and permeability. No depth-integration or other form of simplification is applied. The resulting mathematical model is solved with the fluid dynamics toolkit OpenFOAM.

Many effects and processes that are lost in depth-integrated models are directly simulated in our approach. This allows the simulation of complex events with a relatively simple model, however for a large computational cost. The model parameters are widely intrinsic material parameters, which promises a prediction of events without significant parameter optimizations.

We will show results for small scale experiments as well as for a well documented real scale event and will give an outlook on further developments and remaining problems.

How to cite: Rauter, M., Viroulet, S., Gylfadóttir, S. S., Løvholt, F., and Fellin, W.: Granular porous landslide tsunami modelling with OpenFOAM, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4804, https://doi.org/10.5194/egusphere-egu22-4804, 2022.

Fjord environments are subject to submarine mass wasting events due to their steep slopes, high sedimentation rates, and tectonic activity driven by glacial-isostatic rebound. In specific cases, these events can generate tsunami waves whose coastal heights are strongly influenced by the physiography, both subaerial and submarine, of the fjord. Here we present modeling simulations of a potential tsunami initiated by a submarine landslide in Pangnirtung Fjord, eastern Baffin Island (Nunavut, Canada). Pangnirtung Fjord, a 43 km long, 1 to 3 km wide, and 165 m deep fjord, is fed by numerous rivers that transport sediment from the surrounding high-relief, partially glaciated landscape. Collapse of the Kolik River delta, situated directly across from the hamlet of Pangnirtung, is the likely cause of the largest submarine landslide (2.1 km²) identified in the fjord using multibeam bathymetric data and 3.5 kHz sub-bottom profiles collected in 2019. The mapped landslide extends across the flat basin and features a blocky deposit directly downslope of the delta. The landslide dynamics, the consequent water waves generation and propagation were simulated by means of codes developed by the Tsunami Research Team of Bologna University. The landslide parameters characterizing the downslope motion have been retrieved by matching the landslide dynamics with the observed deposit. As the landslide impulses to the water column are considered, the propagation of the waves inside the fjord is determined through the shallow water approximation of the Navier-Stokes set of equations. The waves reach the hamlet (3.5 km from the landslide source) in 200 s, and the surrounding fjord coasts in approximately 800 s. Maximum wave height values of approximately 2 m were modeled and used to construct an inundation map for the area, over a 2 m regularly spaced grid for the hamlet of Pangnirtung.

How to cite: Gallotti, G., Sedore, P., Armigliato, A., Normandeau, A., Maselli, V., and Zaniboni, F.: Submarine landslide tsunamis in fjord environments: the case of Pangnirtung Fjord, eastern Baffin Island (Nunavut, Canada), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8236, https://doi.org/10.5194/egusphere-egu22-8236, 2022.

Depth-averaged models, such as the Savage-Hutter model with Coulomb or Pouliquen friction laws, are usually considered to simulate aerial and submarine avalanches. In particular,  submarine avalanches can be the source of a tsunami. These models are presented in local coordinates over the topography or a reference bottom. We show in this work that  classical models do not in some cases preserve the physical threshold of motion. On the one hand, the simulated granular mass can start to flow  even if the slope angle of its free surface is lower than the repose angle of the granular material involved. On the other hand, the granular mass can stay at rest being the slope angle of the free surface higher than the repose angle of the material. Several numerical tests are presented  to illustrate these problems related to classical depth averaged models. In this work we also propose an initial correction which ensures that the model preserves, up to the second order, the physical threshold of motion defined by the repose angle of the material. Several numerical tests are presented, by comparing also with experimental data to illustrate the effect of the proposed correction.

How to cite: Fernandez-Nieto, E., Bouchut, F., Delgado Sánchez, J. M., Narbona-Reina, G., and Mangeney, A.: A bed pressure correction for depth-averaged granular flow models to ensure the physical threshold of motion, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12471, https://doi.org/10.5194/egusphere-egu22-12471, 2022.

Studies of the influence of coast roughness on run-up height have numerous applications to tsunami problem. It happens when tsunami propagates over the urban area and houses and coastal structures represent roughness elements, which help to dissipate wave energy and reduce maximum tsunami inundation and at the same time can break due to tsunami loading. In this paper we focus on this topic from both points of view and study experimentally and numerically reduction of wave run-up height due to the bed roughness and corresponding wave loading on roughness elements.

Experiments have been performed in a 307 m long, 7 m deep and 5 m wide Large Wave Flume in Hannover, Germany. The experimental setup contained a 251 m long section of the constant depth, which was kept at the depth of h = 3.5 m during all tests, and a 1:6 slope section. A total of 16 wave gauges were mounted along the flume to reconstruct the incident wave field and to study its nonlinear deformation. During the tests, two video cameras and a capacitance probe were used to measure wave run-up on a sloping beach. Two cameras were set up to film the surf zone. One video record was used to calibrate the run-up data measured by the capacitance probe. An additional video record was used to determine the shape of the water surface, which was illuminated by a laser sheet along the direction of wave propagation.

Logs with rectangular 10×10 cm cross-section were used as roughness elements and the force acting on logs was recorded. Two logs were equipped with force transducers; one located at the unperturbed shoreline 272 m and the one located at 276 m mark. Four roughness configurations were considered, with logs every 1 m, 2 m, and 4 m which was compared to the smooth, zero log baseline condition. Waves of different height, period and shape have been used as input signals.

Experimentally shown, that run-up height has a strong non-linear dependence on the amplitude of incident wave and the number of roughness elements. Force acting on the roughness elements is related to the amplitude of the incident wave during the run-up phase and is defined by the flowing down near-slope layer when the bulk of the fluid recedes. At higher wave amplitudes, the average force (total momentum) imposed by roughness elements on the fluid is directed up the slope

Described experiments have been used to validate two numerical models (nondispersive shallow water model and dispersive model based on modified Peregrine equations) and to evaluate the potential of these models to simulate wave attenuation due to sea bed roughness. To model the bottom friction, we used both Manning’s and Chezy’s roughness laws. The results of this work are also discussed.

How to cite: Didenkulova, I., Abdalazeez, A., Dutykh, D., and Denissenko, P.: Effects of coastal roughness on long wave runup, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8520, https://doi.org/10.5194/egusphere-egu22-8520, 2022.

On July 9^th, 551 AD, a destructive earthquake, estimated magnitude 7.5, impacted the Phoenician coast, nowadays Lebanon, Easternmost Mediterranean. Historical accounts describe a sudden withdrawal of the sea from Berytus (Beirut at the time) and other towns along the Phoenician littoral, for a distance of two miles and then return to its normal position, causing many casualties. Critical reading of the historic descriptions raises questions regarding the possible seismogenic and tsunamigenic sources of this catastrophe. Previous researchers presumed inland and offshore seismogenic sources, and submarine earthquake and submarine landslide as tsunami triggers.

Lebanon lies along the Yammouneh restraining bend of the left-lateral Dead Sea Transform (DST), the boundary between the Sinai Sub-Plate (Africa) and Arabia Plate. The bend resulted from a right stepping offset of the DST and thus induces transpressional deformation formed of several thrust faults, such as the recently identified Mount Lebanon thrust (MLT). On the base of extensive geological investigation, marine survey and submarine study (e.g., Elias et al. 2007), the MLT was found to be an active fault that underlies Lebanon and was interpreted to crop out at the seabed, just offshore the coast. It was thus proposed as the source for both the earthquake and the tsunami. Yet, we were puzzled how the significant retreat of the sea and the return to its original state without noticed inundation, conforms inundation expected from near offshore thrust fault.

First, we constructed a grid of the SRTM Lebanon topography merged with the EMODnet bathymetry of the northeastern Mediterranean Basin, and modified the present-day Beirut coastline so as to reflect its pattern at the time. We then modelled the coseismic deformation of an M7.5 thrust earthquake on the MLT, constraining the vertical offset according to evidence of uplifted marine-cut terraces along the Lebanese coast. The calculated seafloor deformation was used for tsunami wave generation, and non-linear shallow water equation for numerical modelling of tsunami propagation and inundation.

Preliminary assessment shows that, as expected, the simulated scenario exhibits a series of waves. However, the general effect of the simulation is a notable drawdown and minimal inundation, which in our eyes is compatible with the historical observations. The results also suggest that the modelled M7.5 MLT offshore scenario, can explain the 551 AD tsunami description with no need to consider secondary submarine and/or subaerial landslide sources. The review of historical events is thus an important tool to characterize earthquake and tsunami hazards in this area. While further elaboration is certainly needed, we already learnt the need to consider coseismic deformation in tsunami inundation modelling. This effect is critical in the case of near-shore sources leading to coseismic subsidence of coastal areas, which in turn can amplify the expected inundation.

How to cite: Salamon, A., Omira, R., and Baptista, M. A.: Modern Eyes on the Historical 551 AD Earthquake and Tsunami Offshore Phoenicia, Lebanon of Today, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4840, https://doi.org/10.5194/egusphere-egu22-4840, 2022.

The last major events in the Sea of Japan were in 1983 and 1993. There were the 1983 Nihonkai-Chubu Earthquake (M_w 7.8) and the 1993 Hokkaido Nansei-Oki Earthquake (M_w 7.7). These earthquakes caused tsunamis, which we are studying in this research. I use numerical modelling to reproduce and study effects for the Russian coast. The tsunami waves were stimulated by the TUNAMI numerical model. The bottom topography was created using GEBCO database (30 arc seconds), SRTM data, digitized Russian navigational charts and NOAA Center data. The tsunami source was calculated using Okada's formulas. To better resolve local resonant properties arising from local topography and tsunami run-up, calculations were carried out with nested grids. Using nested grids made it possible to obtain significant agreement with the observational data. Since the seismic source of the 1993 earthquake has a complex structure, three different models were analyzed: USGS, Harvard-model and Takahashi et al. 1995. This study focuses on an examination of the Russian coast. Vladivostok, Posyet and Nakhodka were considered in the most detail. Comparison of the model with the observations was done for both the tsunami waveforms and their spectra. Also, a tsunami wave height map was built for the entire Russian coast of the Sea of Japan. The maximum tsunami wave height on the Russian coast in 1993 was more than 5 m.

How to cite: Tsukanova, E.: The 1983 and 1993 tsunamis on the coast of the Sea of Japan: observations and numerical modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-166, https://doi.org/10.5194/egusphere-egu22-166, 2022.

On the 12^th of August 2021 at 18:32:54 and 18:35:20 (UTC) a doublet of reverse faulting earthquakes of magnitude M_w 7.5 and 8.1 were recorded by seismic observatories. These earthquakes were located on the South Sandwich Islands (UK) subduction zone, in the south Atlantic Ocean at 25.032°W/57.567°S and 25.327°W/58.451°S respectively (USGS locations). Initially, their temporal proximity (2’26”) made clear distinction of the two events impossible and a tsunami warning was issued by the PTWC after the first earthquake only. In fact, a tsunami was clearly recorded ~800 km north-westward of the epicentre on nearby King Edward Point coastal gauge (South Georgia Island, UK) ~1.5 hours after the shaking, showing a maximum amplitude of ~74 cm. While tsunami waves were recorded by neighbouring gauges located in the south Atlantic Ocean and the south-west Indian Ocean, numerical simulations of wave propagation show that this tsunami appears likely to have reached far-field regions not only in the Atlantic Ocean, but also in the Indian and Pacific Oceans using oceanic ridges like the Mid-Atlantic and Atlantic-Indian ridges as waveguides. Analysis of 33 records from gauges located within the maximum amplitude lobes of the simulated tsunami validates the modelling and the nearly worldwide spread of this tsunami. Further tsunami simulations using high-resolution nested grids to refine the bathymetry around the gauges (e.g. La Réunion Island, Cocos, Hillary Harbour) are used to constrain the source model via tsunami waveform inversion, comparing the calculated results and the real records. Consequently, we highlight that this tsunami reached many places including the Canary Islands, Cape Verde and the Azores in the northern Atlantic Ocean, and French Polynesia, New Zealand, Hawaii and as far as the Aleutian Islands in the Pacific Ocean, making this subduction zone a source for further consideration in tsunami hazard assessments of these distant regions, especially in the case of a more energetic rupture. Although the largest known event in the instrumental period is the 27 June 1929 M_PAS 8.3 earthquake, geological knowledge of the region suggests that this ~1000 km long convergence zone between the South American and the South Sandwich plates with a convergence rate of 69-78 mm yr⁻¹, is potentially able to produce a M_w 9.0 earthquake. This is supported by recent studies showing that the sediment thickness of 2-3 km at the trench and the ~150 km wide subduction interface shallow dipping (< 20° in the forearc part) are positive factors for generation of earthquakes M_w > 8.5. Results of simulation of M_w 9.0+ scenarios rupturing most of the subduction zone are discussed as well as the particular role of the oceanic ridges in the tsunami propagation. Our research aims to improve understanding of tsunami hazard posed by this subduction zone, especially for southern hemisphere coastlines.

How to cite: Roger, J., Hebert, H., Jamelot, A., Gusman, A., Power, W., and Hubbard, J.: The South Sandwich circum-Antarctic tsunami of August 12, 2021: widespread propagation using oceanic ridges, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-904, https://doi.org/10.5194/egusphere-egu22-904, 2022.

On June 17, 2017, a 40 Mm³ rock avalanche generated a tsunami that impacted several coastal communities in Karrat Fjord, Central West Greenland. The tsunami run-up was 10-12 m high in the nearest village 30 kilometres away from the rock avalanche and caused four fatalities. The two villages most heavily affected are still evacuated. In the aftermath of this event, several unstable rock slopes have been discovered proximal to the 2017 rock avalanche. One of these volumes, coined Karrat 1, has a volume of about 0.5 km³ and is hence at least an order of magnitude larger than the volume involved in the 2017 event. To put this in perspective, it has a volume 2-3 times larger than the 2018 Anak Krakatau tsunami that led to more than 400 fatalities in Sunda Strait, Indonesia (which is also much more heavily populated). Hence, the Karrat 1 worst case scenario poses a threat to a much larger area than the event that took place in 2017 and could potentially affect the whole fjord system. In this study, we quantify the tsunami hazard from this unstable rock slope as well as the 2017 event. We first provide a set of landslide tsunami simulations using a frictional-collisional Voellmy type model coupled to a tsunamis model for the event in 2017 and compare it with observations. We found that the model results agree closely with observations of the tsunami run-up heights, observations of the tsunami arrival times, and the wave periods. The 2017 tsunami model was then used to calibrate the landslide source model for the future hazard, simulating the Karrat 1 landslide tsunami with an included uncertainty range. Extreme run-up heights (10-70 m) are found for the nearest villages, as well as complete inundation of entire low-lying villages, some more than 100 km away from the landslide release area. The large modelled run-up heights, involving extreme run-up heights and relatively short arrival times for the nearby villages, demonstrate the need for better understanding of the risk as well as risk-reducing measures. With few or no previous subaerial events that have taken place historically of this scale, the possible implications of a catastrophic release are widespread, but they also imply substantial uncertainties.

How to cite: Løvholt, F., Glimsdal, S., Harbitz, C., Svennevig, K., Keiding, M., and Møller, J. J.: Tsunami propagation and high-resolution inundation modelling of the 2017 Karrat rock avalanche and potential future tsunamis from proximal slope failures, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10261, https://doi.org/10.5194/egusphere-egu22-10261, 2022.

A tsunami numerical inundation modeling in the Ambon city was developed by considering large earthquakes along the Ambon bay strike-slip fault and triggering submarine landslide as the tsunami source. 
The simulation was conducted using Comcot (Cornell Multi-grid Coupled Tsunami model) with a nested grid system in the spherical coordinate system. The four different spatial grid sizes of 60 (layer 1), 15 (layer 2), 3.75 (layer 3), and 0.9375 (layer 4) arc-sec were used in the computation. The linear shallow-water theory with bottom friction was applied for layers 1 -3, meanwhile, layer 4 used the non-linear shallow-water theory with manning roughness coefficient and detail bathymetry data. 
The single segmentation of earthquake scenarios with magnitudes Mw 7.2 was assumed. The earthquake then triggers submarine landslides in some areas around Ambon city. The landslide area was approached by Peak Ground Acceleration (PGA) value and historical data.
The results showed that in Ambon city the first tsunami wave arrived 18 min after the earthquake with a maximum flow depth of 7.4 m and inundation distance around 1.2 km. These results show that Ambon city has a risk of tsunami threat from earthquakes and submarine landslides. Therefore, it is necessary the tsunami hazard preparedness by the government and communities.

How to cite: Yatimantoro, T., Harvan, M., Anugrah, S. D., Daryono, D., Prayitno, B. S., and Adi, S. P.: Numerical Tsunami Inundation Modeling in Ambon City, Indonesia for Potential Earthquake and Landslide at Ambon bay, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11303, https://doi.org/10.5194/egusphere-egu22-11303, 2022.

Historical earthquake records suggest that the Alboran Sea seismicity is mostly triggered by strike-slip faults with little or no vertical throw preventing significant tsunami formation. Although in the North Alboran Sea the Averroes fault may have a tsunamigenic potential, the main active fault system responsible of the last three major earthquakes (Mw ≥ 6) in the South Alboran Sea, the Al-Idrissi fault, has no significant vertical component. This points to submarine landslides as the main potential source of tsunamis for the southern sector of the basin. Our study deals with the tsunamigenic potential of submarine landslides in the southern Alboran Sea, where several deposits are stacked within the last million year of sedimentary cover. We have identified up to 67 landslide events with volumes between 0.01 to 15 km³. The probability of landslide occurrence has been analysed with a logistic regression describing the relationship between a binary response variable (existence or absence of landslide) and a set of predictor variables such as high seafloor gradients and presence of active faults. The analysis of the severity of a given landslide has been investigated based on the estimation of the probability that the landslide reaches a certain (high) level (e.g. tsunami run-up or submarine cable breaks) giving that it has occurred through the extreme value analysis. We have used the Shaltop code simulating landslide run-out on the basis of a depth-averaged model based on the hydrostatic Saint Venant equations and Coulomb-type basal friction considering a Bingham rheology. Our tsunami simulations include Shaltop output scenarios as a source of the generated tsunami through hydrodynamic simulations using the hydrostatic 3D Navier-Stokes code Freshkiss3d. We found that tsunamis waves triggered by submarine landslides on the South Alboran Sea would be no higher than two meters. However, the tsunami would include wavelengths of tens of kilometres translating into important water volumes flooding several areas of around the Alboran coast. 

How to cite: Rabaute, A., Lafuerza, S., Thomas, M., Sainte-Marie, J., El Baz, A., Mangeney, A., d'Acremont, E., Basquin, E., Mercier, D., Creach, A., and Gorini, C.: Tsunami hazard along the Alboran Coast triggered by submarine landslides, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6439, https://doi.org/10.5194/egusphere-egu22-6439, 2022.

Eastern Indonesia is exposed to significant tsunami hazards induced by its complex tectonic setting characterized by several curved subduction zones, multiple active volcanoes, as well as submarine landslides. Therefore, the region experiences tsunami from various types of sources (earthquake, landslide and volcano). Here, we study the great tsunami hazards in Eastern Indonesia through analyzing two recent real tsunamis that occurred in this region namely the 14 November 2019 Molucca Sea tsunami following an M_w 7.2 earthquake, and the 16^th of June 2021 tsunami following an M_w 5.9 earthquake.

For the 2019 Molucca Sea tsunami, we analyzed 16 tide gauge records and 69 teleseismic data to characterize the tsunami and the earthquake. The maximum zero-to-crest tsunami amplitude was 13.6 cm recorded at Bitung. A combination of aftershocks analysis, forward tsunami simulations and teleseismic inversions were applied to obtain the tsunami source. It is found that the best results are obtained using a rupture velocity of 2.0 km/s and a high-angle reverse fault with a dip angle of 55^o. The source model has a maximum slip of 2.9 m, and an average slip of 0.64 m. The seismic moment associated with this final slip model is 7.64 × 10¹⁹ N·m, equivalent to M_w 7.2. By comparing the results with other similar events in the region, such as the November 2014 event (Mw 7.1) with a reverse mechanism and a high dip angle of 65^o, we may conclude that the Molucca Sea region is prone to splay faulting.

The 16^th June 2021 tsunami was observed on the southern coast of Seram Island following an M_w 5.9 earthquake. The tsunami’s maximum wave amplitude was approximately 50 cm on the Tehoru tide gauge whereas the other two nearby stations showed amplitudes of less than 4 cm. Such a relatively large tsunami (50 cm in Tehoru) is normally unexpected from an earthquake of M_w 5.9 having a normal faulting mechanism. It is likely that a plausible secondary tsunami source, such as a submarine landslide, was involved. For the case of the 2021 Seram tsunami, here we apply numerical modelling and bathymetric analysis to examine the veracity of it being generated by a submarine landslide. Modeling of earthquake sources of the tsunami confirmed that that the simulated tsunamis were only a few centimeters in height and thus cannot reproduce the 50 cm waves observed in Tehoru. However, we were able to reproduce the tsunami observations using potential landslide sources.

This research is funded by The Royal Society (the United Kingdom), grant number CHL/R1/180173.   

How to cite: Heidarzadeh, M., Hilmann Natawidjaja, D., Hananto, N. D., Kongko, W., Sabeti, R., Daryono, M. R., Putra, P., Patria, A., and Gusman, A. R.: Tsunami hazards in Eastern Indonesia from earthquake, landslide and volcanic sources: Seram Island (June 2021) and Molucca Sea (November 2019) tsunamis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1559, https://doi.org/10.5194/egusphere-egu22-1559, 2022.

We present a refined methodological procedure for computationally efficient local SPTHA based on regional SPTHA.  The adopted procedure extracts from the regional SPTHA the most impacting tsunami sources at the investigated site, and reconstructs hazard curves on high-resolution topobathymetric models based on a reduced set of inundation simulations. This procedure enhances the original workflow for local SPTHA quantification described by Volpe et al. (2019), applying some significant upgrades to simplify its application and improve the accuracy of the results. In particular, the description of local sources has been refined through a more detailed discretization of the natural variability (aleatory uncertainty), eventually reducing the epistemic uncertainty. Then, a more efficient filtering procedure, based on the strategy proposed by Williamson et al. (2020), is adopted to select a subset of scenarios to be modelled at high resolution, eventually reducing the epistemic uncertainty introduced by this selection. This allows to perform only coarse-grid simulations after the regional source filtering and local source refinement, and then combine coarse-grid results with fine-grid topography. Overall, the resulting method simplifies the original one, improving accuracy and decreasing uncertainty. The newly developed procedure is applied to an illustrative case study for the harbour of Ravenna (Northern Adriatic Sea, Italy).

How to cite: Baglione, E., Brizuela, B., Volpe, M., Armigliato, A., Zaniboni, F., Tonini, R., and Selva, J.: An improved workflow to efficiently compute local seismic probabilistic tsunami analysis (SPTHA): a case study for the harbour of Ravenna (Italy), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3949, https://doi.org/10.5194/egusphere-egu22-3949, 2022.

Meteotsunamis (or meteorological tsunamis) are long, progressive sea waves triggered by external forcings due to meteorological events as e.g., air pressure disturbances, wind gusts and fast-moving storms that are observed in beaches of enclosed basins and/or in ocean waves entering the harbors and bays. The atmospheric disturbance in open sea generates near the surface water the localized waves, that travel at the same speed but with a period ranging from a few minutes to two hours. The waves propagate toward the shore amplifying near the coast due to resonance mechanisms related to the bathymetric characteristics of the waterbody and the topography of the coastal line. Therefore, a meteotsunamis results from two resonance effects: an external resonance between the air pressure disturbance and the long sea waves in the open sea, followed by an internal resonance between the incoming long waves and the harbor/bay eigenmodes.

Meteotsunamis have been observed all around the globe, but the most destructive events happened at a limited number of sites where meteorological and resonance conditions (i.e., intense resonant amplification due to the harbor/bay geomorphology, dynamic instability, frontal passages, gales, squalls, storms, tornadoes, convection cells, and atmospheric gravity waves) are satisfied at the same time. Examples of these sites are the North-East Adriatic Sea, the Balearic Islands (Spain) and the Sicily Strait (Marrobbio). Over the years, this natural phenomenon recorded an increase (higher frequency of Medicanes) and it has caused structural damages to properties and infrastructures along the coastal areas, as well as human casualties.

In the last fifteen years, numerous studies have addressed the issue of producing statistics and hazard estimates for meteotsunamis, even though in situ data are scarce and often available with a low spatial and temporal resolution. Numerical atmospheric-ocean models, mostly running with simulated air-pressure disturbance and calibrated over data of real events, were therefore carried out seeking to establish a shared approach for hazard estimation and meteotsunamis short-term forecast. Selecting appropriate models for this natural phenomenon is important in the view of planning coastal intervention in danger areas and quantifying the hazard in the harbor/bay in relation to geomorphological changes. In this light the PMO-GATE project (Preventing, Managing and Overcoming Natural-Hazards Risks to mitiGATE economic and social impact project) in the framework of the Interreg V Italy-Croatia 2014-2020 Program aims to develop a joint innovative methodology to strengthen and consolidate the collaboration against natural disasters specific to the NUTS Italy-Croatia in order to increase the level of protection, resilience and prevention of natural disasters through shared management methodologies and multi-risk overcoming of extreme events, such as meteotsunamis, to deal with natural risk with greater awareness and effectiveness.

In particular, it is crucial to understand whether and how the hazard estimate would be modified due to coastal changes brought about by the rise in the sea level expected as a consequence of climate changes.

How to cite: Visentin, C., Prodi, N., Benvenuti, E., Marrocchino, E., and Vaccaro, C.: Meteotsunamis: the hazard in the coastal areas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7194, https://doi.org/10.5194/egusphere-egu22-7194, 2022.

The Black Sea is located in the Anatolian sector of the Alpine-Himalayan orogenic system. In this region the African and Arab plates are moving to the north and to the west colliding with the Eurasia tectonic plate. In this study we focused on the northern Bulgarian Black Sea coast, where devastating earthquakes occurred in the past, during the I^st century BC, 543 AD, 1444 and 1901, all of them with estimated magnitudes M>7.0 causing tsunami waves. An evaluation of the possible seismic sources and maximum credible earthquake magnitude is made to build tsunami hazard scenarios for the northern Bulgarian coastline, including Shabla-Kaliakra seismic zone. The numerical code UBO-TSUFD is used for the tsunami simulations, coupled with bathymetry and relief data. The initial conditions of the generated tsunami waves are calculated using the method proposed by Okada supplemented with focal mechanisms information and fault geometry. We consider three seismic sources (SS I, SS II and SS III) which are tested for three different earthquake magnitudes M7.0, M7.5 and M8.0. To increase the resolution of the results we use nested grids, as the finest one (space resolution 50 m) is focused on the coastline between the city of Varna and Cape Kaliakra. We built simplified local tsunami hazard maps based on the computed water column on the coast for all nine tsunami scenarios in the studied region. The potentially threatened inundation zones are marked with different colors and vary between 0 and 5 m, depending on the selected magnitude. SS I poses the highest risk of potential tsunami flooding with the calculated water column for the northern part of the Bulgarian coast reaching more than 1.5 m, even for M7.0. When M7.5 is considered, the tsunami heights rise to 2.3 m and assuming M8.0, the water column exceed 4 m. The gulf of Bourgas is partially protected by Cape Emine, located to the north. It should be noted that the Romanian coast and more precisely the shores to the north of Constanta are seriously affected by the modelled scenarios, as the calculated inundation heights exceed 2.5 m for M8.0. The results for SS III show the lowest values of the vertical water column inland. The modeling estimates the sea level variations in certain points computing synthetic mareograms. Virtual mareograms near Varna, Balchik and Albena resort displays the evolution of the initiated tsunami heights in time. SS II and SS III have similar behavior for all three magnitudes. The dominant tsunamigenic source with extremely high waves is SS I.

In addition, the impact of these three seismic sources on the entire Black Sea coast is examined through the coarse grid of 500 m, the propagation field and the maximum computed tsunami heights.

This study is funded by the Bulgarian National Science Fund, grant number CP-06-COST-7/24.09.2020. LD contributed to the European Cooperation in Science and Technology COST project “AGITHAR-Accelerating Global science In Tsunami HAzard and Risk analysis”.

How to cite: Raykova, R. and Dimova, L.: Tsunami hazard scenarios for the northern Bulgarian Black Sea coast, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9174, https://doi.org/10.5194/egusphere-egu22-9174, 2022.

Probabilistic tsunami hazard and risk analysis (PTHA/PTRA) is an emerging scientific discipline within the tsuanmi community and allows potentially to incorporate the diverse sources of uncertainty into disaster prevention, preparedness, and mitigation activities. While there are a number of successful applications of this paradigm, it is still an emerging field with a number of unresolved research questions. 

In a collaborative effort members of the COST Action AGITHAR assessed the existing research gaps for PTHA/PTRA and identified almost 50 different topics worth of further research. An ad hoc expert judgement was conducted to weight these open questions with respect to their expected impact on the quality of the PTHA/PTRA results and their difficulty to be answered. The results of this collaborative effort will be reported highlighting the most challenging and most severe research gaps.

The presentation is based on the following publication:
J. Behrens, F. Løvholt, F. Jalayer, et al. (2021): Probabilistic Tsunami Hazard and Risk Analysis – A Review of Research Gaps, Frontiers in Earth Science, 9:114, DOI:10.3389/feart.2021.628772.

How to cite: Behrens, J., Løvholt, F., Jalayer, F., Lorito, S., Salgado-Gálvez, M. A., and Sørensen, M. and the AGITHAR Team: Assessing research gaps in probabilistic tsunami hazard and risk analysis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6282, https://doi.org/10.5194/egusphere-egu22-6282, 2022.

As tsunamis propagate across open oceans, they remain largely unseen due to the lack of
adequate sensors. To help better mitigate the tsunami risk, we use a detection method that takes
advantage of the efficient coupling of tsunami waves with the atmosphere. Tsunami-induced
internal gravity waves thus travel upward in the atmosphere, where amplitude amplifies by several
orders of magnitude as the air density decreases with altitude. Once the waves reach the
ionosphere, they put charged particles into motion, creating propagative phenomena known as
Traveling Ionospheric Disturbances (TIDs). Thanks to the Global Navigation Satellites Systems
(GNSS), such disturbances can be monitored and observed using the Total Electron Content (TEC)
derived from the delay that the ionosphere imposes in the electromagnetic signals transmitted to
the Earth’s surface by the GNSS satellites. Here we show ionospheric TEC signatures following the
passage of three ocean-wide tsunami events: the two tsunamis triggered by the March 4th, 2021
8.1 Mw Kermadec Islands, New Zealand, and the July 29th, 2021 8.2 Mw Perryville, Alaska
earthquakes, as well as across the southern Atlantic following the tsunami generated by the
August 12th, 2021 8.1 Mw Sandwich Islands earthquake. We classify the observed TEC signatures
based on detection reliability and the potential connection to the tsunami wavefield. In addition,
we utilize an analytical model to investigate the source of these identified TEC signatures. Thus, we
ensure their gravity-waves origin and assess the characteristics (wavelength, period, etc.) of such
gravity waves, which is necessary to confirm they originate from the tsunami. Finally, to better
map the tsunami amplitude at the ocean level in various configurations, we examine, compare,
and contrast the amplitude of the identified tsunami-induced TEC signatures from geographically
sparse regions. We account for multiple parameters such as the local magnetic field, the azimuth,
and the distance to the tsunami source. They all affect the TEC signature detection and the
retrieval of the tsunami wavefield and, thus, potentially, the estimated risk.

How to cite: Munaibari, E., Rolland, L., Sladen, A., and Delouis, B.: Tsunami Ionospheric Monitoring Across the Pacific Ocean and the Southern Atlantic, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5324, https://doi.org/10.5194/egusphere-egu22-5324, 2022.

Innovative deep ocean monitoring technologies are crucial to catalyzing fundamental improvements in mitigating natural disasters, reducing human vulnerabilities, and understanding environmental threats. An attractive but untapped resource is the global submarine fiber optic cable network, which carries over 95% of international internet traffic. Key components of undersea fiber optic cable systems are repeaters, which are placed every 60-100 km along the cable to provide optical signal amplification. Integrating environmental sensors, including seismic, pressure, and temperature sensors, would enable real-time data collection for environmental and infrastructure threat reduction, natural disaster mitigation, and cable system monitoring. 

A unique technology that will revolutionize the utility of these cables is the SMART (Sensor Monitoring And Reliable Telecommunications) cable concept. Although the concept has been evaluated for over 10 years by an international suite of agencies and institutions, developing a SMART repeater requires substantial investment in research and development to validate a technology that could transform an industry. To date, no commercial manufacturer has allocated the resources to produce a prototype SMART repeater. To bridge this gap, we have obtained support by the National Science Foundation’s Small Business Innovation Research (SBIR) program to develop a benchtop prototype SMART repeater. As part of an international effort to help develop a SMART Cable system for the New Caledonia - Vanuatu region, we also have received support from the Gordon and Betty Moore Foundation as part of a team led by the University of Hawai`i.

Best-in-class SMART repeater sensors include a 3-axis accelerometer, absolute pressure gauge, and temperature sensor. Included with the sensors are data acquisition circuits with suitable dynamic range and precision, integration around a common communications module, an interface suitable for fiber optic cable spans up to 120 km in length, the software and firmware necessary to support the data path from the sensors to data storage servers, and precision timing for both time-stamps and frequency reference. The SMART repeater sensor system design is modular, thereby containing branch points for different sensors, as well as incorporation in different repeater housings or as standalone units. 

SMART Cables will be particularly well suited for providing essential tsunami monitoring data, particularly from the seismic and pressure sensors. More specifically, SMART repeaters provide a unique opportunity to develop significantly more extensive sensor networks of real-time ocean bottom monitoring, filling in critical near-field and azimuthal gaps frequently encountered in earthquake monitoring. Further, our SMART repeater sensor system design includes the option for either acceleration or velocity monitoring, thereby enabling better measurement of amplitudes of tsunamigenic subduction zone earthquakes while providing a lower noise sensor in ocean basins. Further, data from SMART Cables will facilitate the detection of other tsunamigenic sources, including underwater landslides. We will present the results of our sensor development efforts and upcoming opportunities for SMART Cable installations.

How to cite: Fouch, M., Lentz, S., Howe, B., and Avenson, B.: SMART Cables: Integration of Environmental Sensors Into Submarine Telecommunications Cables for Improved Ocean Monitoring, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10756, https://doi.org/10.5194/egusphere-egu22-10756, 2022.

Seismic instrumentation is critical for instantaneous tsunami early warning systems as well as assessing long-term risk of tsunami activity in areas with high seismic hazard. Ocean Bottom Seismometer (OBS) systems provide real-time data in areas with appropriate infrastructure or batch data from offline temporary autonomous stations.

OBS systems detect ground motion from seismic waves significantly before detecting any pressure change in the water column from an associated tsunami due to the order of magnitude difference in wave velocity. Güralp’s OBS systems combine seismic and pressure detection in both permanent cabled networks and temporary non-cabled systems utilising near-real-time acoustic transmission. All seismic sensors used in Güralp systems are sensitive to both earthquakes as well as other tsunami-triggering events such as landslides (e.g. Anak Krakatau, 2018) or volcanic eruptions (e.g. Hunga Tonga–Hunga Haʻapai, 2022).

Cabled systems provide obvious benefits of real-time data, confidence of installation and flexibility to add additional instrumentation without power consideration. For example, Güralp Orcus and Maris cabled OBS systems are both deployed off the western coast of North America monitoring volcanic and tectonically induced earthquakes that have potential to cause tsunamis. Seismometers at these stations coupled with pressure gauges allow for immediate notification of a threat and subsequent refinement of hazard estimates using surrounding assets such as dedicated DART buoys.

Both Orcus and Maris allow for multiple auxiliary systems to be incorporated into the system while maintaining as well as providing additional installation flexibility for operators. Orcus has facility for both strong & weak motion seismometers in addition to auxiliary sensors while Maris has the unique feature of operating at any angle without the need for a gimbal mechanism, simplifying installation and network design considerations.

The Güralp Aquarius is the latest generation autonomous OBS for short-to-medium term or rapid response campaigns to monitor areas with increased seismic and tsunami hazard. Aquarius also uses omnidirectional capabilities as well as acoustic communication of seismic data to the surface to improve operator confidence of installation. Acoustic communication also allows for near-real-time communication with land-based warning systems after a significant seismic event in anticipation of a tsunami. This can be verified and communicated after the initial seismic wave using onboard pressure gauges. In areas where surface communication is not required, intelligent battery systems optimise deployment lengths beyond 18 months for maximum data/cost benefit.

Güralp is also pioneering the use of seismic sensors and auxiliary equipment within Science Monitoring And Reliable Telecommunications (“SMART”) cables which have already been shown to be useful in incorporating pressure gauges to detect tsunami events. These cables utilise regular telecommunication cables making uses of their natural communication and power source qualities to improve sensor network coverage. Güralp is currently manufacturing a demonstration system to be deployed in the Ionian Sea, monitoring seismic and volcanic activity with the aim of indicating practicality and data quality using this installation method.

How to cite: Barbara, R., Cilia, M., Reis, W., Watkiss, N., Mohr, S., Hill, P., and Whealing, D.: Utilising ocean bottom seismometer platforms for tsunami early warning and hazard assessment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8075, https://doi.org/10.5194/egusphere-egu22-8075, 2022.

Tsunamis have the potential to cause widespread damage and loss of life over large swaths of coastal areas. To mitigate their effects, both in the long term and during emergency situations, an accurate, detailed and timely assessment of the hazard is essential. Here, an enhanced method for estimating tsunami time series using a uni-dimensional convolutional neural network model is presented, with the aim of reducing the time and computing capacity required by a high-resolution numerical modeling. While the use of deep learning for this problem is not new,  most of existing research has focused on the determination of the capability of a network to reproduce inundation values. However, for the context of Tsunami Early Warning, it is equally relevant to assess whether the networks can predict the absence of inundation. Hence, the network model was adjusted for the bays of Valparaíso, Viña del Mar and Coquimbo in central Chile, based on a set of 6800 scenarios with Mw 8.0-9.2. Tentative models were trained with time series from low- and high-resolution numerical modeling, to recreate the tsunami time series of control points on land. The objective was to reproduce the inundation high resolution time series, when the network was fed with low resolution offshore data. The approach considered 1075 (15%) scenarios to test the model, and 5783 (85%) scenarios to adjust (train and validate) the model. Different performance metrics are employed, particularly the RMSE measured with respect to peak flow depth and arrival times. Critically, the number of false alerts and alerts not issued was analyzed, which was considered a relevant performance owing to the wide range of magnitudes tested that led to an unbalance between scenarios that inundate and the ones that not. A notable outcome in this study shows the network is capable of reproducing inundation, either for small or large amplitudes, and also of no inundation. To further assess the performance, the model was tested with three existing tsunamis and compared with actual inundation metrics at three cities with different hydrodynamic response. The results obtained are promising, and the proposed model could become a reliable alternative for the calculation of tsunami intensity measures (TIMs) in a near to real time manner, with a network model forecasting where sea surface and geodetic data are not readily available, as occurs in many countries. This could complement existing early warning systems to reduce uncertainties involved in the decision making process.

How to cite: Catalan, P. A., Núñez, J., Valle, C., Zamora, N., and Valderrama, A.: Estimating Time Series of Tsunami Inundation using One-Dimensional Convolutional Neural Networks for Early Warning., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10179, https://doi.org/10.5194/egusphere-egu22-10179, 2022.

Tsunami warning systems currently focus on the first parameters of the earthquake, based on a 24-hour monitoring of earthquakes, seismic data processing (Magnitude, location), and tsunami risk modelling at basin scale.

The French Tsunami Warning Center (CENALT) runs actually two tsunami modelling tools where the water height at the coast is not calculated (i.e., Cassiopee based on a pre-computed database, and Calypso based on real time simulations at basin scale). A complete calculation up to the coastal impact all along the French Mediterranean or Atlantic coastline is incompatible with real time near field or regional forecast, as nonlinear models require fine topo-bathymetric data nearshore and indeed a considerable computation time (> 45 min). Predicting coastal flooding in real time is then a major challenge in near field context, the aim being a rapid determination of shoreline amplitude and real time estimation of run-up and currents. A rapid prediction of water heights at the coast by amplification laws or derived transfer function can be used to linearly approximate the amplitude at the coastline, with error bars on calculated values within a factor 2 at best. However, such approach suffers from a limited consideration of local effects and no run-up estimation.

The goal is there to add complexity to the predicted models through deep learning techniques, which are newly explored approaches for rapid tsunami forecasting. Several architectures, treatments and settings are being explored to quickly transform a deep ocean simulation result into a coastal flooding model. The models provide predictions of maximum height and run-up, maximum retreat, and currents in 1 second. However, such approach is dependent of a large scenario base for learning. This work presents preliminary comparisons of the coastal impact captured from nonlinear time consuming tsunami simulations (ground truth) with predicted localised tsunami responses provided by rapid forecasting deep learning approaches at 10 m resolution along the French Mediterranean, for several earthquake scenarios.

How to cite: Andraud, P., Gailler, A., Sprunck, T., and Vayatis, N.: Deep learning models  exploration for rapid forecasting of coastal tsunami impact in near field context – application to the French Mediterranean coastline., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12716, https://doi.org/10.5194/egusphere-egu22-12716, 2022.

One of the most critical part of tsunami warning systems is the so-called “last mile”, i.e., informing promptly residents and tourists about a possible impending inundation.

In Italy, one of the most recent activities to reach this goal is the implementation of the Tsunami Ready (TR) Program, developed under the aegis of UNESCO and achieved in synergy between INGV, ISPRA and the Italian Civil Protection Department (the three components of the Italian Tsunami Warning System - SiAM).

In 2020, the path towards the TR recognition has started in three Italian pilot municipalities: Minturno, Palmi, Marzamemi. The response of local authorities has been enthusiastic in all three cases, despite numerous bureaucratic obstacles to involvement and membership.

Italy as a NEAM member aims to reach the goal of 100% of communities at risk of tsunami prepared for and resilient to tsunamis by 2030 through the implementation of the UNESCO/IOC Tsunami Ready Programme.

Several developments are going on because all participants are aware that TR is a virtuous model for dealing with tsunami risk, with numerous implications in terms of education and responsibilities for the harmful consequences of a tsunami.

First of all, the direct involvement of citizens in the education and information process represents a significant step change of TR. It is achieved through the participation of citizens’ representatives in the TR Local Board, which is responsible for monitoring the development of procedures and certifying that a suite of 12 target parameters identified in the TR guidelines have been accomplished.

It is important to remind that the recognition as Tsunami Ready community must be also approved by the National TR Board and by the UNESCO ICG.

Secondly, the existence of internationally accredited guidelines (IOC UNESCO n. 74 and its ongoing updates) represents a reliable parameter for determining the behavior to be adopted by public decision-makers.  In case of harmful events, the compliance with these parameters can contribute to mitigating the (possible) criminal reproach against civil protection officers charged in risk management.

How to cite: Valbonesi, C.: Tsunami Ready Programme in NEAM region: strategies, responsibilities and further advancements to protect communities from tsunamis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11876, https://doi.org/10.5194/egusphere-egu22-11876, 2022.

The tsunami that occurred on the Southern Coast of West Java and Central Java resulted in 802 people killed, 498 people injured, and 1623 houses heavily damaged. The total economic loss and damage to infrastructure due to this disaster reached US$55 million. The impact of this disaster in Jetis Village, Cilacap, Central Java was 12 people died, Jetis Beach tourist facilities were damaged, transportation infrastructure was destroyed, and hundreds of houses collapsed. The Jetis area and its surroundings are very close to vital national infrastructures such as the Cilacap steam power plant that supplies electricity to southern Java and the Cilacap container port. In addition, this area is a tourist attraction visited by thousands of people per year. Therefore, the purpose of this research is to create a tsunami disaster mitigation map and evacuation route in Jetis Village to anticipate future casualties and economic losses. The method used in this study is scoring to create a tsunami mitigation map and Dijkstra's algorithm to determine the fastest evacuation route. The results depict that there are five zones of tsunami vulnerability, namely high impact potential, moderately high, moderate, moderately low, and low impact potential. The most vulnerable tsunami is the South Jetis area that has low elevation, is near the coast, fairly gentle slope, and is close to the river. Meanwhile, the northern part of Jetis is the safest zone of tsunami hazard. It has a high elevation, far from the coastline and river, and a steep slope. The distance of the evacuation route from the high-impact zone to the safe evacuation zone is 683 m. This study concludes that the high-impact to moderate-impact zone needs to be avoided in the event of a tsunami. If the community is within that range zone, then an evacuation route should be followed.

How to cite: Laksono, A. T., Widagdo, A., Aditama, M. R., Fauzan, M. R., and Kovacs, J.: Tsunami Mitigation Map and Evacuation Route Modeling on the Jetis Beach, Cilacap Regency, Indonesia using Scoring Method and Dijkstra’s Algorithm, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1273, https://doi.org/10.5194/egusphere-egu22-1273, 2022.