SM1.1

Teleseismic back-projection has emerged as a widely-used tool for understanding the rupture histories of large earthquakes. However, its application often suffers from artifacts related to the receiver array geometry, notably the `swimming' artifact. We present a teleseismic back-projection method with multiple arrays and combined P and pP waveforms. The method is suitable for defining arrays ad-hoc in order to achieve a good azimuthal distribution for most earthquakes.

We present a catalog of short-period rupture histories (0.5-2.0 Hz) containing 54 events from 2010 to 2021 (Mw ≥ 7.5), including recent and significant earthquake ruptures, e.g., 2021 Mw 8.3 South of Sandwich Islands, 2021 Mw 8.2 Chignik, 2021 Mw 8.1 Kermadec Islands, and 2020 Mw 7.8 Simeonof Island.

The method provides semi-automatic estimates of rupture length, directivity, speed, and aspect ratio, which are related to the complexity of large ruptures. We determined short-period rupture length scaling relations that are in good agreement with previously published relations based on estimates of total slip. Rupture speeds were consistently in the sub-Rayleigh regime for thrust and normal earthquakes, whereas strike-slip events propagated in the unstable supershear range. Many of the rupture histories exhibited complex behaviors such as rupture on conjugate faults (e.g., 2018 Mw 7.9 Gulf of Alaska), bilateral ruptures (e.g., 2017 Mw 7.8 Komandorsky Islands), and dynamic triggering by a P wave (e.g., 2016 Mw 7.9 Solomon Islands). For megathrust earthquakes, ruptures encircling asperities were frequently observed, with down-dip (e.g., 2021 Mw 8.1 Kermadec Islands), up-dip (e.g., 2016 Mw 7.8 Pedernales), double encircling (e.g., 2015 Mw 8.3 Illapel), and segmented (e.g., 2020 Mw 7.8 Simeonof Island) patterns. Although there is a preference for short-period emissions to emanate from central and down-dip parts of the megathrust, emissions up-dip of the main asperities are more frequent than suggested by earlier results.

How to cite: Vera, F., Tilmann, F., and Saul, J.: A decade of short-period earthquake rupture histories from multi-array back-projection, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2839, https://doi.org/10.5194/egusphere-egu22-2839, 2022.

MERMAIDs (Mobile Earthquake Recording in Marine Areas by Independent Divers) are seismic instruments which record local, regional and teleseismic earthquakes, and other signals, in the oceans. In the Southern Pacific Ocean, some fifty MERMAIDs are collecting acoustic pressure time series as part of the South Pacific Plume Imaging and Modeling (SPPIM) project. Deployed in 2018 and 2019 by members of the EarthScope-Oceans consortium, these instruments record continuous time series data on a one-year buffer and autonomously report a wealth of waveforms, selectively triggered mostly by teleseismic events, suitable for mantle tomography. 

Listening for signals while roughly 1.5 km below the ocean surface, MERMAIDs' primary mission is to detect and deliver records of P-waves generated by distant earthquakes, and collectively they have returned many thousands of seismograms corresponding to such signals. We present highlights from our earthquake catalog and discuss the changing character and causes of the background noise. Whilst the South Pacific fleet is programmed to only send short seismic records, corresponding to confident identifications of teleseismic first arrivals, some records contain later-arriving phases. In addition to P-waves, we present a miscellany of observations of other signals, including core phases, converted S- and surface waves, and T-phases. Furthermore, we illustrate that we are able to obtain other recorded data segments through buffer requests via satellite. 

Data from the MERMAIDs owned by Geoazur and Princeton University that we report on here are being archived by IRIS—those from three instruments is available without embargo. We highlight MERMAID waveform availability and its utility to the scientific community via examples of their modeling and preliminary interpretations that can be made regarding wavespeed heterogeneity in the dynamic mantle below the Pacific Ocean. 

How to cite: Irving, J., Simon, J., Pipatprathanporn, S., Simons, F., and EarthScope-Oceans Consortium, T.: MERMAIDs in the South Pacific Ocean: Observations, Measurements, Modeling, Data Availability, and First Hints at Mantle Structure, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4238, https://doi.org/10.5194/egusphere-egu22-4238, 2022.

Earth’s mantle transition zone (MTZ) is a possible global water reservoir and may be responsible for long-term (~100 Ma) ocean-mass regulation, driven by plate tectonics and mantle convection. Estimates of MTZ mineral water capacity exceed 1 wt%, far greater than that of rocks of either the upper- or lower-mantle. When water-rich material from the transition zone penetrates the upper or lower mantle, partial melting occurs due to the decrease in water capacity after phase transition, generating a reduction in seismic velocities. This process can add an additional low-velocity zone (LVZ) that can be imaged above(below) the 410(660)-km discontinuities, if melt is present. Depending on the melt fraction and wetting angle at mineral-grain boundaries, decreases in shear velocity of 0.5-2.6% can be generated. Seismic receiver functions have detected velocity reductions both above and below the MTZ, interpreted to be partial melting induced by high water content under the Alpine orogeny, in the deep Japan-slab subduction zone, and across the western United States. Since much of Earth lacks seismic stations, we apply SS precursors to conduct a global survey for such LVZs. The precursors to the SS phase reflect off interfaces near the source-receiver midpoint, so seismic stations are not required to be located above the target region. Detection and interpretation of LVZs surrounding sharp positive-velocity gradients, such as the 410- or 660-km discontinuity, is often complicated by side lobes, an artifact of common signal-processing routines. To address this challenge, we develop an SS precursor method based on the multitaper-correlation (MTC) technique. MTC allows for analysis at higher frequency, leading to finer depth resolution, and can increase the number of useful data records. We conduct MTC SS-precursor analysis for seismic waveforms recorded on the ~125 stations of the Global Seismographic Network to benchmark our new method and search for LVZs. Results will be compared to LVZs interpreted from previous seismic analysis.

How to cite: Frazer, W. and Park, J.: Searching for Mid-Mantle Water with Multitaper-Correlation SS Precursors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8833, https://doi.org/10.5194/egusphere-egu22-8833, 2022.

We use seismological data collected from a recently deployed seismic network around the Klyuchevskoy Volcanic Group (KVG) in Kamchatka to study the crustal structure and mantle anisotropy beneath the region. In order to improve and extend the data coverage, we combined this data set with data from previous temporary deployments and permanent stations to reach a total number of 145 stations covering a region defined in the geographic coordinates 150°-167°E and 50°-61°N.

We use receiver function (RF) analysis to study the crustal structure beneath the study area. P-RFs are migrated to depth and stacked to image seismic interfaces beneath the network of seismic stations. We used a recently published three-D seismic tomography model to migrate the RFs from time to space domain. The RF amplitudes are stacked in the space domain using the Common Conversion Point (CCP) approach. The stacked RF amplitudes provide a 3-D image of seismic interfaces. The use of the 3-D velocity model helps migrate the RF amplitude to correct depths so that the depth and geometry of subsurface interfaces are constrained more correctly.  Furthermore, we are able to better compare the 3-D CCP images with the 3-D tomography model. In addition, at stations with a sufficient number of RFs, we also tried to calculate Moho depth and mean Vp/Vs ratio using the single-station H-k stacking approach. This analysis provides a way to better identify the interfaces beneath different locations and verify and adjust the depths obtained using the CCP stacking. We found a relatively complex crustal structure in the entire region of the KVG that laterally merges to a simpler structure to the west. Seismic tomography images provide better lateral resolution of velocity anomalies while RF analysis provides better vertical resolution of vertical velocity constants. Our RF-CCP images reveal two main interfaces beneath the active volcanic region. The shallow interfaces with a limited lateral extent have depths varying between 20 and 30 km. The deeper interface occurs at depths 50-60 km with an east-to-west dipping direction. In comparison with the seismic tomography model, we infer that the shallow interface is related to a velocity increase from <6 km/s to >7 km/s, implying the presence of a shallow low-velocity zone beneath the volcanic group. The deeper interface that correlates with a velocity increase from <7 km/s to around 8 km/s might be related to the top of the subducting plate. 

In addition to the RF analysis for the crustal structure, we also perform splitting analysis of core-refracted shear waves (SKS) to study mantle seismic anisotropy as a proxy for the pattern of the mantle flow field. Our SKS-splitting analysis indicates a trench-normal mantle flow beneath the eastern edge of the Kamchatka peninsula that converts to a more complex pattern beneath the KVG region. We argue that this pattern of fast polarization direction suggests the rotational mantle flow that may be related to a slab gap at the junction between the Kuril-Kamchatka and Aleutian arcs.

How to cite: Kaviani, A., Rümpker, G., Koulakov, I., Sens‐Schönfelder, C., and Shapiro, N.: Crustal structure and mantle anisotropy beneath Klyuchevskoy Volcano and surrounding regions in Kamchatka, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2498, https://doi.org/10.5194/egusphere-egu22-2498, 2022.

We perform an adjoint waveform tomography using Rayleigh-wave empirical Green‘s functions (EGFs) at periods 10-50 s to improve a pre-existing 3-D velocity model of the crust and uppermost mantle beneath the Iranian plateau. The starting model was derived from a conventional surface-wave dispersion tomography based on high-frequency ray-theory assumption to invert of a quasi-3-D shear-wave velocity model. We use the EGFs from the same study that were derived from cross correlation of continuous seismic noise. Adjoint tomography refines the initial model by iteratively minimizing the frequency-dependent travel-time misfits between synthetic and observed EGFs measured in different period bands. Our new model covers the known tectonic units such as the Central Iranian Block, Zagros fold-and-thrust belt, Sanandaj-Sirjan metamorphic zone and Urumieh-Dokhtar magmatic arc.

Overall, the adjoint tomography provides images with better lateral resolution and depth sensitivity and more realistic absolute velocity values due to the inclusion of finite-frequency waveforms. The use the numerical spectral-element solver in adjoint tomography provides accurate structural sensitivity kernels, which helps to obtain more robust images rather than those generated by ray-theory tomography. The final model adjusts the shapes of velocity anomalies at crustal depth more specifically for the eastern Zagros. The final model significantly improves the initial model at the upper mantle depths and provides a higher resolution for the shape of velocity anomalies.

How to cite: komeazi, A., Kaviani, A., Yaminifard, F., and Rümpker, G.: An Improved shear velocity model beneath the Iranian plateau using adjoint noise tomography, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3017, https://doi.org/10.5194/egusphere-egu22-3017, 2022.

The Eifel region is a large volcanic system in the middle of European continent. From the Eifel teleseismic tomography experiment (8 months in 1997-1998), a mantle plume beneath the volcanic fields (down to 400 km depth) has been identified and further confirmed by receiver function and teleseismic surface wave dispersion analyses. A study in 2020 using dense geodetic observations leads to the conclusion that the Eifel region experiences a pronounced uplift encompassing the neighbouring countries Netherlands, Belgium, Luxembourg and France, which is attributed to the same buoyant mantle plume.

A detailed focus on the uppermost 30 km above the Moho has been missing until recently. However, a noteworthy recent seismological investigation showed the evidence of a deep magmatic recharge beneath the Laacher See Volcano in East Eifel between 2013 and 2018. Located at depth roughly between 40 and 10 km, low-frequency seismic swarms, which are typical of volcanic environment, convey the presence of magma movements and potential storage zones in the crust.  

The present study aims to bring additional information on this shallow active magmatic system using an Ambient Noise Tomography (ANT). Thanks to theoretical and technical developments over the two last decades, this approach has been increasingly popular for imaging Earth structure worldwide at different scales. We use here ambient noise data from archives of the 1997-1998 Eifel experiment and more recent (2019-2020) continuous seismic record. The group velocity dispersion of Rayleigh waves are estimated between station pairs from Noise Cross-correlation Functions (NCF) covering the secondary microseismic frequency band, which allows to sample the uppermost 10-20 km of the crust. Our contribution includes a complete description of the ANT/NCF processing (e.g., directivity of the noise sources, sensitivity tests) in order to better constrain the velocity anomalies observed in the Eifel region and around.

How to cite: Barrière, J. and Oth, A.: Imaging the uppermost layers of the Eifel volcanic system (Germany) using ambient microseismic noise, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7268, https://doi.org/10.5194/egusphere-egu22-7268, 2022.

A large volume of digital seismic data was recorded by six broadband seismic sensors equipped with GPS-clock timing in the Ghana Digital Seismic Network (GHDSN) between October 2012 and April 2014. For this period, no public seismicity catalog was reported by the global data centers, International Seismological Center (ISC), and United States Geological Survey (USGS) for southern Ghana. In this study, this database is processed to detect local earthquakes. To facilitate the challenging and time-consuming process of detecting the earthquakes and picking the arrival times of P and S phases, we utilize EQTransformer, a Deep Learning (DL) model deploying Hierarchical Attention Mechanism (HAM) for simultaneous earthquake detection and phase picking. This model utilizes global and local levels of attention mechanism for identifying earthquake and seismic phases deriving benefits from deep neural networks, including convolutional and recurrent neurons. The thresholding values of 0.2, 0.07, and 0.07 are set for earthquake detection, P-picking, and S-picking, respectively. As a result, a list of events for each station of the network with the associated time of detection, as well as P and S phase arrivals are obtained. Taking these arrival times into account, we have devised a so-called ”conservative strategy” to optimally extract all possible earthquakes in the data set, amenable to locate. Initially, a list of preliminary events recorded by at least two stations is created by comparing the earthquake occurrence and arrival times of the P and S phases for all stations regarding a 100 sec time threshold. The list in this step includes 317 events recorded by at least two stations. Eventually, an analyst controls the obtained waveforms in other stations assesses whether EQTranasformer misses the preliminary list of events in those stations. Consequently, a number of 533 picked phases (282 P and 251 S) recorded by a minimum of 3 stations are finalized. Incorporating these phases and removing the instrument response from the waveforms, the hypocentral parameters for 73 earthquakes with 2.5 ≤ M L ≤ 4.0 are estimated. The main concentration of events is on the intersection of the Akwapim fault zone and the coastal boundary fault, with some scattered seismicity along the Akwapim fault zone. The corresponding set of seismic phases is utilized to estimate an updated 1D crustal velocity model for the study area. This research contributes to the FCT-funded projects SHAZAM (Ref. PTDC/CTA-GEO/31475/2017), RESTLESS (Ref. PTDC/CTA-GEF/6674/2020), SIGHT (Ref. PTDC/CTA-GEF/30264/2017), and IDL (Ref. UIDB/50019/2020).

How to cite: Mohammadigheymasi, H., Tavakolizadeh, N., Mousavi, S. M., Silveira, G., and Fernandes, R.: Seismicity analysis in southern Ghana- I: Detecting local earthquakes by Deep Learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5860, https://doi.org/10.5194/egusphere-egu22-5860, 2022.

A small network of six broadband seismic sensors operated in southern Ghana between October 2012 and April 2014 (GHDSN). During this period, no seismicity was reported by the global data centers, however application of the Deep Learning algorithm EQTransformer resulted in the detection and subsequent location of 73 earthquakes. Preliminary constant crustal velocity models with  vp=5.55 km/s and vs=3.36 km/s have been utilized since 2002 to locate the local earthquakes in southern Ghana. Using this crude velocity model resulted in scattered seismicity, hinting into a likely inadequacy of these preliminary velocity parameters to represent the elastic properties of the area. In this study, we perform a joint-inversion for estimating an updated 1D crustal velocity model and the hypocentral parameters of the 73 recently detected local earthquakes. A grid search method is implemented and a 6-layer velocity model is defined, down to 45 km crustal depth. The space of velocity model parameters is searched by altering the upper depth of the layers (ud), P-wave velocity in each layer (vp), and the ratio of vp/vs. The optimized velocity model and hypocenteral parameters are evaluated by minimizing the RMS error function between the observed (533 picked phases consisting of 282 P and 251 S phases) and calculated arrival times. A two-step implementation is devised to increase the computational efficiency of the inversion process. Initially, the optimum  vp/vs is estimated by implementing a coarse grid search on vp and ud values. Then, incorporating the optimum vp/vs a fine grid search on vp and ud is applied.
The results yields layers with 1, 13, 8, 13 and 10 km thickness, with vp = 5.9, 6.1, 6.3, 6.5, 6.9 and 7.2 km/s, respectively. The updated velocities for the first and last layers are 6% and 26% percent higher than the previously reported constant velocity models. Furthermore, the updated vp/vs=1.70 is 0.03% higher than the corresponding value vp/vs=1.65 of the constant velocity model. The updated hypocentral locations of the 73 earthquakes with  2.5<ML<3.9 are concentrated on five major clusters. Two clusters are located on the AFZ, indicative of the active role of this structure in the seismicity of the region. Two other clusters, which have the highest rate of activity,  are positioned in the intersection between the AFZ and CBF. The last cluster consists of scattered earthquakes that coincide with mapped segments of the AFZ. Incorporating the updated velocity model for estimating the hypocentral parameters resulted in enhanced seismogenic source delineation in southern Ghana.  This research contributes to the FCT-funded projects SHAZAM (PTDC/CTA-GEO/31475/2017), RESTLESS (PTDC/CTA-GEF/6674/2020), SIGHT (PTDC/CTA-
GEF/30264/2017) and IDL (UIDB/50019/2020).

How to cite: Custódio, S., Mohammadigheymasi, H., Tavakolizadeh, N., Matias, L., and Silveira, G.: Seismicity analysis of Southern Ghana II: Updated crustal velocity model and hypocentral parameters, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5570, https://doi.org/10.5194/egusphere-egu22-5570, 2022.

Seismic event locations are usually performed by means of iterative, linearized arrival time inversion considering 1D velocity models with fixed data errors. Both the use of inaccurate velocity structure or data error estimates may however affect the quality of event location and uncertainty evaluation. Here, we test a 3D P- and S-wave velocity model built in a previous work for Metropolitan France (the part of France located in Europe) and we compare it with the “Auvergne” 1D velocity model used by BCSF-RéNaSS (Bureau Central Sismologique Français - Réseau National de Surveillance Sismique) using quarry blast data. The reason for using quarry blast data is that, to some extent, their epicentral location and depth are known, which is not the case for earthquakes. We first identify potential active quarries over the territory of Metropolitan France by comparing catalog quarry blast locations with those from quarries visible from satellite images. Relocation is achieved by means of a Hierarchical Bayesian inversion procedure in which not only the hypocentral parameters (longitude, latitude, depth, origin time) are inverted for, but also P- and S-wave arrival time errors. The area of interest is a 1° by 1° zone located between 4°E and 5°E in longitude and 44°N and 45°N in latitude, the region where the Le Teil earthquake occurred (Mw 4.9, 2019/11/11). We first demonstrate the ability of the algorithm to properly determine hypocentral parameters and data noise using two simple synthetic experiments. Then we apply it to real data and relocate 147 quarry blasts that occurred in the region between 1980 and 2020 and that were located wit the “Auvergne” 1D velocity model. Relocations obtained with the 1D and 3D model are rather similar. Estimated data errors are larger, in both cases, than the amplitude of picking uncertainties, meaning that both models could be improved, by seismic arrival time tomography for instance. They are larger in the 3D case, suggesting that, from that point of view, the 1D model is in better agreement with the data. Distances between relocated hypocenters and the closest known quarry are comparable but relocations with the 3D model are characterized by shallower hypocenters than those obtained with the 1D model, so they appear more consistent with the fact that events are quarry blasts. In both cases, some events are quite far away from the closest quarry, suggesting that some of them might be natural events.

How to cite: Arroucau, P., Mayor, J., Grunberg, M., Nayman, E., and Daniel, G.: Testing seismic velocity models with quarry blast data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8652, https://doi.org/10.5194/egusphere-egu22-8652, 2022.

A major earthquakes struck the north of Flores island, in Nusa Tenggara Timur, Indonesia, on 14  December 2021 at 10:20:22 local time, the hypocenter is 7.59°S, 122.26°E, depth 12.0 km, with moment magnitude Mw 7.4. The faulting orientation of the mainshock, fault plane was strike = 290°, dip = 89°, and rake = 177°, and the auxiliary plane was strike = 21°, dip = 87°, and rake = 1°, respectively, is possibly related to thrust fault in the sea. Focal mechanism solutions for the earthquakes indicate rupture occurred thrust fault with large dip angle. The mainshock was followed by low aftershocks productivity may due to homogeneous faulting systems and relatively uniform stress state in that region. We analyze aftershock hypocenter relocation and gravity anomaly, slip distribution, coulomb stress and seismic hazard (PSHA) to investigate the earthquake characteristics and seismic hazard analysis. The distribution of hypocenter relocations show that aftershock ruptured distribute between two block of high gravity anomaly, its indicate that it was not the new fault. The inversion of the source model shows several time periods of energy release with three main peaks. These temporal rupture suggest repetition of a large scale slip on the large asperity. The models of coulomb stress indicate that static stress transfer due to the Mw 7.4 earthquake is suitable with aftershock spatial distribution. We compute the probabilistic seismic hazard assessment in the Flores region for Earthquake mitigation

How to cite: Rohadi, S., Prakoso, T. A., Yatimantoro, T., Rahman, A., Sunardi, B., Adimarta, A., Riama, N. F., Adi, S. P., Adi Wibowo, B., and Karnawati, D.: The 14 December 2021, Mw 7.4 Flores Earthquake: Review of the hypocenter relocation, slip distribution, coulomb stress, and seismic hazard, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8366, https://doi.org/10.5194/egusphere-egu22-8366, 2022.

On December 14, 2021, the Mw 7.3 Flores Sea earthquake occurred approximately 100 km to the north of Flores Island, one of the most complex tectonic settings in Indonesia. The existence of the causative fault that generated this earthquake was not been previously known, therefore making further analysis crucial for assessing future seismic hazard in the region. In this study, we relocated the hypocenter of the mainshock and aftershocks using a double-difference method, determine focal mechanisms using waveform inversion, and then analyse stress changes to estimate the fault type and stress transfer caused by this earthquake. Our relocated hypocenters show that this earthquake sequence ruptured on at least three segments: the source mechanism of the mainshock exhibits dextral strike-slip motion (strike N288^oW and dip 78^o) that occurred on a West-East trending fault which we call the Kalaotoa Fault, while rupture of the other two segments located to the west and east of the mainshock (WSW-ESE directions, respectively) may have been triggered by this earthquake. The Coulomb stress change of the mainshock shows that areas to the northwest and southeast experienced an increase in stress, which is consistent with the observed aftershock pattern.

How to cite: Supendi, P., Rawlinson, N., Prayitno, B. S., Widiyantoro, S., Palgunadi, K. H., Simanjuntak, A., Kurniawan, A., Marliyani, G. I., Nugraha, A. D., Daryono, D., Fatchurochman, I., Sadly, M., Adi, S. P., Karnawati, D., Gunawan, M. T., and Arimuko, A.: Preliminary results of investigation of “unidentified fault” associated with the Mw 7.3 Flores Sea earthquake, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3794, https://doi.org/10.5194/egusphere-egu22-3794, 2022.

On September 27, 2021, an M_w=6.0 earthquake struck the central part of Crete Island (southern Greece) and in particular the Heraklion Region. This event was preceded by an extended foreshock sequence started on early July 2021 and it was followed by an Mw=5.3 aftershock on the following day.

Taking into account the spatial distribution of foreshocks and aftershocks and the focal mechanism of mainshock as well as the active faults of the earthquake-affected area, it is evident that the seismic activity is strongly related to the NNE-SSW striking W-dipping faults of the Kasteli fault zone located along the eastern margin of the Neogene to Quaternary Heraklion Basin. The latter has been filled with Miocene to Holocene post-alpine deposits.

A field reconnaissance conducted by the authors in the earthquake-affected area shortly after the mainshock revealed that the earthquake-triggered effects comprised mainly rockfalls and slides, as well as ground cracks within or close to landslide zones. These effects were located within the hanging-wall of the KFZ. The affected sites are mainly composed of Miocene deposits and they are characterized by pre-existing instability conditions and high susceptibility to landslides. Far field effects were also observed south of the earthquake-affected area and in particular in the southern coastal part of Heraklion Region.

In regards to the spatial distribution of the earthquake-induced building damage, the vast majority was caused in villages and towns founded on Miocene and Holocene deposits of the hanging-wall. Damage was not reported in settlements located in the footwall, which is composed of alpine formations.

The dominant building types of the earthquake-affected area comprise: (i) buildings with load-bearing masonry walls made of stones and bricks with clay or lime mortar, mainly constructed without any anti-seismic provisions and (ii) buildings with reinforced-concrete frame and infill walls constructed according to the applicable seismic codes. The former suffered the most severe structural damage including partial or total collapse in many villages founded on post-alpine deposits of the hanging-wall of KFZ. The latter responded satisfactory during the mainshock and were less affected with only non-structural damage including cracking, detachment of infill walls from the surrounding reinforced concrete frame, peeling of concrete and short-column failures.

From the abovementioned, it is concluded that the impact of the 2021 Arkalochori earthquake was limited to the hanging-wall of the causative fault zone and in particular to residential areas founded on post-alpine deposits and to slopes highly susceptible to failure within the Heraklion Basin.

How to cite: Mavroulis, S., Kranis, H., Lozios, S., Argyropoulos, I., Vassilakis, E., Soukis, K., Skourtsos, E., Lekkas, E., and Carydis, P.: The impact of the September 27, 2021, Mw=6.0 Arkalochori (Central Crete, Greece) earthquake on the natural environment and the building stock, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7994, https://doi.org/10.5194/egusphere-egu22-7994, 2022.

Post-earthquake reconnaissance missions are critical to understand the event characteristics, identify building and infrastructure vulnerabilities, and improve future construction practice. However, in-field missions can present logistic and safety challenges that do not make them viable in every post-disaster scenario. Remote sensing technique can be used to rapidly collect a large amount information that can be used to enrich the post-event learning process. While the possibility to deploy teams in the field remain a valuable asset for an integrated understanding of technical and socio-economic factors, a mix of remote and in-field reconnaissance activities can be a way forward in post-disaster management.

This work presents the results of a hybrid mission mobilised by the Earthquake Engineering Field Investigation Team (EEFIT) after the 2021 Haiti earthquake. On 14 August 2021, a 7.2 magnitude earthquake struck the Tiburon Peninsula in the Caribbean nation of Haiti, approximately 150km east of the capital Port au Prince. The event was followed by numerous aftershocks up to magnitude 5.7, and tiggered over 1000 landslides. Over 2000 people lost their lives, with over 15,000 injured and over 137,000 houses damaged or destroyed. The estimated economic impact is of the order of US$1.6 billion. Due the complex political and security situation in Haiti, coupled with the global pandemic, a full in field mission was not considered feasible, so a hybrid mission was designed instead.

First, open-source information was collected and used to characterise the seismic event, analyse the strong ground motion and compare to established national and international earthquake codes and standard. Second, remote sensing techniques including Interferometric Synthetic Aperture Radar (InSAR) and Optical/Multispectral imagery were used to understand the earthquake mechanism, the ground displacement distribution and the possibility to detect landslide on a regional scale. The general applicability of remote sensing technique in the context of post disaster assessment was also evaluated. Finally, the earthquake impact on different building typologies in Haiti was investigated through the damage assessment of over 2000 buildings comprising schools, hospitals, churches and housing. This was done in collaboration with the Structural Extreme Events Reconnaissance (StEER) team, who mobilised a team of local non-experts to rapidly record building damage.

This talk summarises the mission setup and findings, and discusses the benefits of and difficulties encountered during this hybrid reconnaissance.

How to cite: Whitworth, M., Giardina, G., Penney, C., Di Sarno, L., Adams, K., Kijewski-Correa, T., Macabuag, J., Foroughnia, F., Macchiarulo, V., Ojaghi, M., Orfeo, A., Pugliese, F., Dönmez, K., Black, J., and d Aktas, Y.: Remote Reconnaissance Mission to the 14th August 2021 Haiti Earthquake; remote sensing and building damage assessments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10192, https://doi.org/10.5194/egusphere-egu22-10192, 2022.