NH4.3

Mechanisms of stress transfer and probabilistic models have been widely investigated to explain earthquake clustering features. However, these approaches are still far from being able to link individual events and to determine the number of earthquakes caused by a single event. An alternative approach based on proximity functions allows  to generate hierarchical clustering trees and to identify pairs of nearest-neighbours between consecutive levels of hierarchy. Then, the productivity of an earthquake is the number of events of the next level to which it is linked. To account for scale invariance in the triggering process we use a relative magnitude threshold ΔM. Recently it was shown that the relative productivity attached to each event is a random variable that follows an exponential distribution. The exponential rate of this distribution does not depend on the magnitude of triggering events and systematically decreases with depth. Here we test a hypothesis that this stochastic property of the earthquake productivity is a consequence of high spatial heterogeneity of the background event rates. The study was supported by Russian Science Foundation, project no. 20-17-00180.

How to cite: Shebalin, P., Baranov, S., Matochkina, S., and Krushelnitskiy, K.: Exponential earthquake productivity law, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8157, https://doi.org/10.5194/egusphere-egu21-8157, 2021.

We have created a new seismotectonic regionalization for Germany including a 200 km zone around its borders, based on a new concept which initially processes geological information separately from modern seismicity. The identification of a region as a distinct seismotectonic unit is estimated from past deformation, not the present one as represented by earthquakes. This has been done by analyzing fault density and displacements separately for six time slices from 300 Ma to the Present. The final regionalization results from overlaying the six deformation intensity maps and contrasts regions that deformed either repeatedly or very strongly in the geological past with others that suffered very little deformation. The new regionalization is significantly different from existing regionalizations. The existing ones mostly relied on modern seismicity for defining areas while using geological contacts of varying type (surface traces of faults, but also erosional edges of stratigraphic units as represented on geological maps) to trace boundaries.

The new, geology-based regionalization comprises comparatively few regions. Ubiquitous small faults (cm- to m-displacements) in the geological record suggest that earthquakes of low magnitude can occur anywhere and need not be tied to large faults. Our regionalization concurs with earlier ones in identifying the Cenozoic rifts – Upper Rhine Graben, Lower Rhine Graben and Eger Rift – as zones of increased hazard. A 100-150 km wide, NW-SE-trending belt of intense Mesozoic deformation runs across northwestern and central Germany from the Emsland to the Erzgebirge where it bifurcates into two branches that continue along the borders of the Bohemian Massif. This belt coincides reasonably well with the relatively sparse earthquakes in central and northern Germany. The Tornquist Fault Zone running NW-SE from northern Denmark to Bornholm is another belt of increased past deformation and elevated seismic activity on the northeastern border of our region. Areas of particularly low past deformation comprise the Brabant Massif, the Rhenish Massif and Münsterland Basin east of the Lower Rhine Graben, the Alpine foreland south of the Danube river and the Bohemian Massif southeast of the Eger Rift. Earthquake clusters occurring in stable areas such as the Brabant Massif or the Swabian Jura highlight geologically unexpected events. They can be added to the regionalization as separate zones or accounted for via a logic tree. They should not be used to assign increased hazard to the larger regions of the geology-based regionalization.

How to cite: Spies, T., Hahn, T., Kley, J., and Kaiser, D.: New seismotectonic regionalization for Germany: comparison with existing regionalizations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14356, https://doi.org/10.5194/egusphere-egu21-14356, 2021.

The Zagros mountains is a tectonically active Arabian-Eurasian plate convergence zone. The convergence direction changes along the strike of the belt, results in oblique faulting in the North-Western Zagros (NWZ) and the prevalence of pure reverse faulting in the South-Eastern Zagros (SEZ). The two regions undergo different convergence rates, (4 ± 2 mm yr −1) in NWZ and (9 ± 2 mm yr −1) in SEZ. These differences is partially accommodated by right-lateral strike-slip faulting throughout the Central Zagros (CZ), resulting in catastrophic earthquakes like 1972 Mw = 6.7 Qir and 1934 Mw = 6.3 Kazerun. This study presents the Probabilistic Seismic Hazard Assessment (PSHA) for the CZ region by integrating fault sources and seismological data. The seismological catalog data consists of 6504 events (2.5 < Mw < 6.7) during 1925-2020 and was compiled from the International Seismological Center (ISC) and the Iranian Seismological Center (IRSC). The faults with the history of Mw > 5.5 or geometrical potential of producing such an event were modeled. A Truncated Gutenberg–Richter (TGR) Magnitude-Frequency Distribution (MFD) for a range of magnitudes (5.5 < Mw < Mmax ) is evaluated by processing the geometrical parameters and slip rate of each fault source using the FiSH code. The Mmax is computed for each source by combining various Mmax estimates based on the faults geometry and observed Mmax if it is available. The catalog data was modeled as a grid source. A unique set of seismic activity rate parameters (for Mw > 4) in each grid is obtained by applying a modified smoothed seismicity approach. More precisely, a penalized likelihood-based methodwas utilized for the spatial estimation of the b-values, and a weighted smoothing method was implemented to calculate the spatial distribution of the a-values. The catalog events with Mw > 5.5 were excluded to avoid duplicated hazard estimation (modified earthquake catalog). Compiling the source models, the hazard computations were performed using the OpenQuake Engine. The Peak Ground Acceleration (PGA) is computed for the Probability Of Exceedance (POE) of 10% over 50 years for distributed seismicity obtained by the full catalog, and an aggregated model of active faults and distributed seismicity with the modified earthquake catalog. The distributed model produces an approximately uniform PGA with a maximum value of 0.185 g over CZ, while the aggregated model accents the PGA in the vicinity of the faults the maximum of 0.319 g observed around the Kazerun fault. The results show the competence of aggregating fault-based and distributed seismicity hazard assessments for applying comprehensive PSHA studies.

How to cite: Dolatabadi, N., Tavakolizadeh, N., Mohammadigheymasi, H., and Valentini, A.: A combined fault- and catalog-based hazard assessment for Central Zagros, Iran, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14411, https://doi.org/10.5194/egusphere-egu21-14411, 2021.

We investigate the source parameters of 87 local earthquakes (3.5 ≤ M_L ≤ 5.0) that occurred in West Brahmaputra basin and its neighbouring area, using body wave displacement spectra. Seismic moment, corner frequency, source dimension and static stress drop are estimated using a grid search method based on the model of circular source. The measured seismic moments, corner frequency and moment magnitude ranges from   to  N-m, 0.7 to 12.1 and 3.0 to 4.8, respectively. The average ratio of corner frequency of P - and S - waves is 2.21. The scaling relationship of seismic moment against corner frequency is also studied for various tectonics regimes separately. Median stress drop values of individual earthquake vary from ~ 0.1 to 38.5 MPa, with an average value of about ~ 6 MPa. Spatial variation of stress drop observed for different tectonic unit reveals a higher stress drop values associated with West Brahmaputra basin, Shillong-Mikir plateau and Indo-Myanmar subduction zone suggesting a higher stress accumulation that may increase the probability of higher magnitude earthquake. The empirical relationship between M_L and M_W scale is also derived for hazard assessment.

How to cite: Khan, P. K. and Baruah, B.: Estimation of Source Parameters and their scaling relationship of small to moderate magnitude earthquakes for northeast India, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1636, https://doi.org/10.5194/egusphere-egu21-1636, 2021.

The Mexican subduction zone, the Gulf of California spreading center, as well as the triple junction point around the Jalisco and the Michoacán Blocks, represents the most active seismogenic belts inducing seismic hazard in the Jalisco-Colima-Michoacán region. Herein, considering such seismotectonic setting, we have developed a new seismic source model for the surrounding of this zone to be used as an input to the assessment of the seismic hazard of the region.

This new model is based on revised Poissonian earthquake (1787-2018) and focal mechanism (1963-2015) catalogs, as well as crustal thickness data and all information about the geometry of the subducting slabs. The proposed model consists of a total of 37 area sources, comprising the three different possible categories of seismicity: shallow crustal, interface subduction, and inslab earthquakes. A special care was taken during the delimitation of the boundaries for each area source to ensure that they represent a relatively homogeneous seismotectonic region, and to include a relatively large number of earthquakes that enable us to compute, as reliable as possible, seismicity parameters.

Actually, the sources zones were delimited following the standard criteria of assessing a probabilistic seismic hazard, being characterized in terms of their seismicity parameters (annual rate of earthquakes above Mw 4.0, b-value, and maximum expected magnitude), mean seismogenic depth, as well as the predominant stress regime. The proposed seismic source model defines and characterizes regionalized potential seismic sources that can contribute to the seismic hazard at the Jalisco-Colima-Michoacán region, providing the necessary information for seismic hazard estimates.

How to cite: Peláez, J. A., Sawires, R., Santoyo, M. A., and Henares, J.: Development and characterization of a seismic source model for the Jalisco-Colima-Michoacán region, Western Mexico, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-411, https://doi.org/10.5194/egusphere-egu21-411, 2021.

In the present work, we examine the stress parameter values for the stochastic simulation modeling of shallow interface (h<45km) earthquakes in the southern Aegean Sea subduction zone. Using the extended-source model (EXSIM code), the stochastic stress parameter is estimated for several of these earthquakes, which are typically associated with thrust faulting. The assessment is performed using a Monte Carlo parametric search (non-linear optimization) of the stress parameter values, realized through an adapted neighborhood algorithm (Wathelet, 2008). In this approach, we estimate the stress parameter which minimizes the total root mean square (rms) misfit between observed and simulated Fourier Amplitude Spectra (FAS) for all records of each event available in the strong motion database. We also employ appropriate source and path parameters (e.g., moment magnitude, fault dimensions, high-frequency spectral attenuation, etc.), from previous works on strong-motion simulations, considering earthquakes in the range M4.4 to M6.6. For several recording stations, we employed site-specific transfer functions, derived from a generalized inversion of strong motion records, considering the seismic source and propagation path of the seismic events in terms of their frequency content (Drouet et al., 2008; Grendas et al., 2018). For the remaining stations, the assessment of site-effects on seismic motions was performed based on the Vs30 values available for all recording stations. Using these values, soil classes according to NEHRP (1994) have been assigned and we employed generic transfer functions for NEHRP site conditions A/B, C and D (together with the corresponding κ0 values), as these were available from previous work for Greece by several authors (Margaris and Boore, 1998, Margaris and Hatzidimitriou, 2002; Klimis et al., 1999, 2006). The final comparisons show that the FAS of the strong motion data can be adequately matched (in most cases) by the synthetic data from the EXSIM simulations, using stress parameter values less than 100bars. This value is quite different from results obtained for larger depth interface and inslab events of the Aegean Sea and Vrancea subduction zones (e.g., Sokolov et al., 2005; Kkallas et al., 2018), which show much larger stress parameters (>200bar) for M>6 events. These findings suggest that the event hypocentral depth is a critical factor regarding the observed stress parameter affecting accordingly the seismic hazard estimation. Strong Intermediate-depth events (h>45km) require large stress parameters, while shallow interface thrust events show rather similar stress parameter values with the typical shallow back-arc normal and strike-slip events of the Aegean region. This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning» in the context of the project “Reinforcement of Postdoctoral Researchers - 2nd Cycle” (MIS-5033021), implemented by the State Scholarships Foundation (ΙΚΥ).

How to cite: Kkallas, C., Papazachos, C., Margaris, B., Grendas, I., Theodoulidis, N., and Hatzidimitriou, P.: Investigation of the stress parameter values for the stochastic simulation of shallow (h<45km) interface earthquakes of the southern Aegean Sea subduction zone, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8034, https://doi.org/10.5194/egusphere-egu21-8034, 2021.

Fault displacement hazard assessment is based on empirical relationships derived from data of historical surface rupturing earthquakes. This approach is used for land use planning, sizing of lifelines or major sensitive infrastructures located in the proximity of active faults. These relationships provide the probability of occurrence of surface rupture and predict the amount of displacement, both for the main ruptures (principal) and for distributed ones appearing beyond.

Following the first version of the global database SURE 1.0 (Baize et al., 2019), we are continuing the effort to compile observations from well-documented historical and recent surface faulting events in order to feed and improve empirical relationships. The new SURE2.0 global database consolidates the previous version SURE 1.0 data, rejecting some poorly constrained cases, reviewing some cases already in, and adding well-documented new ones (e.g. Ridgecrest sequence, USA, 2019). In total, the SURE 2.0 database has 46 earthquakes, including 15 normal fault cases, 16 reverse fault cases and 15 strike-slip cases from 1872 to 2019. The magnitude range is from M4.9 to 7.9, with ruptures from 5 to 300 km long.

SURE 2.0 provides the geometric location and attribute information of rupture segments in a GIS environment and a spreadsheet reports the amplitude and characteristics of deformation, including data sources and its eventual geometric refinement during analysis. In this new version, we completed an essential task to derive attenuation relationships, by classifying each rupture segment and each slip measurement point, using a ranking scheme based on the pattern and amplitude of the observed rupture traces, and considering the structural context and the long-term geomorphology. This distinguishes the principal rupture (class 1), which is the main surface expression of the source of the earthquake. Typically, in the siting study, this class is assigned to the identified active fault. Class 2 features (distributed ruptures) are characterized by shorter lengths and smaller displacements that appear randomly close and around the main rupture. We introduced the distributed main fracture category (class 1.5), which corresponds to the relatively long minor fractures recognized on cumulative structures secondary to the main fault. Class 3 represents triggered slip evidences on remote active faults, clearly not connected with the earthquake causative fault (sympathetic ruptures).

As was done with reverse fault cases (Nurminen et al., 2020), this new SURE 2.0 version will be used to derive probabilities associated with the rupture distribution  during any type of earthquake.

How to cite: Baize, S., Blumetti, A. M., Boncio, P., Cinti, F. R., Civico, R., Guerrieri, L., and Nurminen, F.: A new release of the SURE database of earthquake surface ruptures suited to Fault Displacement Hazard Analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14182, https://doi.org/10.5194/egusphere-egu21-14182, 2021.

Seismic hazard assessment requires an adequate understanding the earthquake distribution in magnitude, space, and time ranges. Laking data for a period of several thousand years makes probabilistic approach to estimating the recurrence time of hazardous ground shaking unreliable and misleading. In spite of theoretical flaws and actual failures on practice, the probabilistic seismic hazard assessment (PSHA) maps keep being actively used both at global and national scales. In recent decades, alternative methodologies have been developed to improve the reliability and accuracy of reproducible seismic hazard maps that pass intensive testing by historical evidence and realistic modelling of scenario earthquakes. In particular, the neo-deterministic seismic hazard assessment (NDSHA) confirms providing reliable and effective input for mitigating object-oriented earthquake risks. The unified scaling law for earthquakes (USLE) is a basic part of NDSHA that generalizes application of the Gutenberg-Richter law (G-RL). The USLE states that the logarithm of expected annual number of earthquakes of magnitude M in an area of linear size L within the magnitude range [M– , M+] follows the relationship log N(M, L) = A + B×(5 − M) + C×log L, where A, B, and C are constants.  Naturally, A and B are analogous to the classical a- and b-values, while C compliments to G-RL with the estimate of local fractal dimension of earthquake epicentres allowing for realistic rescaling seismic hazard to the size of exposure at risk. USLE implies that the maximum magnitude MX expected with p% chance in T years can be obtained from N(MX, L) = p%, then used for estimating and mapping ground shaking parameters by means of the NDSHA algorithms. So far, the reliable USLE based seismic hazard maps tested by historical evidence have been plotted for a number of regions worldwide. We present the USLE based maps of MX computed at earthquake-prone cells of a regular grid, as well as the adapted NDSHA estimates of seismic hazard and risks for social and infrastructure exposures in the regions adjacent to the Russian Federation Baikal–Amur Mainline. The study supported by the Russian Science Foundation Grant No. 20-17-00180.

How to cite: Kossobokov, V. and Nekrasova, A.: Seismic hazard and risks for social and infrastructure exposures adjacent to the Baikal–Amur Mainline, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6254, https://doi.org/10.5194/egusphere-egu21-6254, 2021.

The broader Aegean area is one of the highest seismicity regions in Europe, with almost half of the European seismicity released in this region, often with damaging mainshocks, such as the recent M7.0 Samos event. While several Probabilistic Seismic Hazard Assessment (PSHA) studies have been performed for this area, an attempt to quantify the main factors controlling PSHA has not been performed. To study the effect that each input factor (seismic source model, GMPE, seismicity parameters, etc.) has on the seismic hazard calculations, an OFAT (One Factor at A Time) analysis has been conducted. For this analysis we considered two standard peak ground motion parameters, PGA and PGV, for a typical PSHA scenario, namely 10% probability of exceedance for a mean return period of 50 years (equivalent to a 476 yr return period). For the analysis the following factors were considered: a) Four (4) seismicity area-type source models for the broader Aegean area (Papazachos, 1990; Papaioannou and Papazachos, 2000; Woessner et al., 2015; Vamvakaris et al., 2016), as well as various uncertainties for the associated G-R seismicity parameters and active fault geometries of each seismic source, b) ten (10) Ground Motion Prediction Equations (GMPEs), which contain four NGA-West2 (Abrahamson et al., 2014; Boore et al., 2014; Campbell and Bozorgnia, 2014; Chiou and Youngs, 2014), two European (Bindi et al., 2011; Cauzzi and Faccioli, 2008) and four “Greek” (Theodulidis and Papazachos, 1992; Skarlatoudis et al., 2003; Danciu and Tselentis, 2007; Chousianitis et al., 2018) equations, as well as a variable number of sigma for each equation and, c) the minimum (Mmin) and maximum (Mmax) source magnitude of each seismic source. Tornado diagrams (Howard, 1988) were generated for 42 selected sites of seismological interest that span the study area, allowing to explore the extent of each factor’s effect on the PSHA results. The sensitivity analysis results suggest that the GMPE selection, as well as uncertainties in the G-R parameters a and b are the most critical factors, significantly affecting the PGA/PGV levels for all sites. They also reveal a strong correlation of PSHA sensitivity with other seismicity parameters. For example, the employed source model and Mmax play a more critical role for regions of low seismicity, while the least important factor is the selected Mmin. The spatial distribution of the PSHA sensitivity on the various factors considered was also examined through the generation of several maps, exposing regions of high and of low PSHA uncertainty. The results can be efficiently employed by scientists and engineers in order to focus research and application efforts for a targeted uncertainty minimization of the most critical factors (which may not be the same for all sub-regions of the examined Aegean area), as well as to evaluate the reliability and uncertainty of the current PSHA estimates that are employed in seismic design.

How to cite: Kerkenou, A., Papazachos, C., Margaris, B., and Papaioannou, C.: Identifying the main factors that control Probabilistic Seismic Hazard Assessment (PSHA) in the Aegean area: Results from OFAT (One Factor at A Time) analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7967, https://doi.org/10.5194/egusphere-egu21-7967, 2021.

Probabilistic Seismic Hazard Assessment (PSHA) attempts to forecast the fraction of sites on a hazard map where ground shaking will exceed the mapped value within some time period. Because the maps are probabilistic forecasts, they explicitly assume that shaking will exceed the mapped value some of the time. At a point on a PSHA map, the probability p that during t years of observations shaking will exceed the value on a map with a T-year return period is assumed to be described by the exponential cumulative density function: p = 1 – exp(-t/T). The fraction of sites, f, where observed shaking exceeds the mapped value should behave the same way. To assess the 2018 USGS National Seismic Hazard Model maps for California, we created the California Historical Intensity Mapping Project (CHIMP), a 162-yr long dataset that combines and consistently reinterprets seismic intensity information that has been stored in disparate and sometimes hard-to-access locations (Salditch et al., 2020). We use two performance metrics; M0 based on the fraction of sites where modeled ground motion is exceeded, and M1 based on of the difference between the mapped and observed ground motion at all sites. M0 is implicit in PSHA because it measures the difference between the predicted and observed fraction of site exceedances and is therefore a key indicator of map performance.

We explore these metrics for CHIMP. Assuming the dataset to be correct, it appears that the hazard maps overpredicted shaking even correcting for the time period involved. Assuming the model is also correct, a shaking deficit exists between the model and observations. Possible reasons for this apparent overprediction/shaking deficit include: 1) the observations in CHIMP are biased low; 2) the observation period has been less seismically active than typical – either by chance or temporal variability due to stress shadow effects; 3) the model overpredicts due to either the earthquake rupture forecast or the ground motion models. Similar overpredictions appear for past shaking data in Italy, Japan, and Nepal, implying that seismic hazards are often overestimated. Whether this reflects too-high models and/or biased data remains an important question.

How to cite: Salditch, L. and Stein, S.: Do PSHA maps overpredict or are there shaking deficits in the historic record?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12450, https://doi.org/10.5194/egusphere-egu21-12450, 2021.

The study of strong historical and early instrumental earthquakes is based almost exclusively on the use of their macroseismic data, which usually constrain the area that has suffered the heaviest damage. In the recent decades, strong-motion data have been also employed for the same purpose. We present a stochastic simulation approach to jointly model macroseismic and strong motion data for selected shallow strong (M≥6.0) earthquakes that occurred in the broader Aegean region between 1978 and 1995. For the simulations we employed the finite-fault stochastic simulation method, as realized by the EXSIM algorithm. We calibrated several parameters for the stochastic simulation modeling using a priori published information (e.g., moment magnitude, stress parameter). Other rupture zone information were collected from published works, such as fault plane solutions, relocated seismicity, etc. A Monte Carlo approach was adopted to perform a parametric search for the stress parameter and the modelling both independently and jointly the available macroseismic data and the strong motion instrumental recordings. The validity and the reliability of this semi-automated simulation approach was examined, to test if this method could be applied either in a fully automated manner, or for the study of the source properties of historical earthquakes. The results suggest that a joint-misfit minimization from the simultaneous simulation of macroseismic and strong motion data is a feasible target, that can be potentially employed for the simulation of older events, for which a limited number of instrumental data is often available. In general, a good agreement of the spatial distribution of the original and modeled macroseismic intensities is observed, showing that can reliably reconstruct the main features of the damage distribution for strong shallow mainshocks in the Aegean area using the proposed joint interpretation approach.

How to cite: Ravnalis, M., Kkallas, C., Papazachos, C., Margaris, B., and Papaioannou, C.: Joint interpretation of macroseismic and strong motion data for recent large shallow mainshocks of the Aegean area using a Monte Carlo optimization of finite-fault stochastic simulations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7969, https://doi.org/10.5194/egusphere-egu21-7969, 2021.

Marmara region is a tectonically active part of Turkey. Over the history, the Marmara region has been the site of numerous destructive earthquakes such as the 1509 Istanbul earthquake (Mw=7.5), 1766 Istanbul earthquake (Mw=5.63), 1953 Yenice-Gönen Depremi (Ms=7.2), 1999 Kocaeli (Mw=7.4) and Düzce (Mw=7.2) earthquakes. Many Electric power systems located in the Marmara region are exposed to the destructive effects of potential earthquakes. The serviceability and functionality of the electric power systems after a major earthquake are major concerns for people's wealth. Thus, the design of the electric power system requires site-specific seismic hazard assessment. Site-specific hazard analysis provides a uniform hazard spectrum used for the design of power structures. Response spectrums are presented for the seismically resistant design of the structures according to the Turkey Building Earthquake Regulation 2018 (TBDY2018) and Turkish Seismic Code 2007 (TSC2007) regulations. 
In this study, seismic hazard assessment of the Marmara region has been studied using the Openquake platform. Earthquake hazard has been investigated using the time-independent probabilistic (Poisson) models. Probabilistic seismic hazard assessment (PSHA) is conducted based on SHARE project ESHM13 model characteristics. The SHARE project has presented the 2013 European –Mediterranean seismic hazard model (ESHM13). ESHM13  models consist of all events with magnitudes Mw>=4.5 in the computation of seismic hazard and it covers the whole European territory including Turkey. The probabilistic seismic hazard assessment calculations take into account SHARE seismic source characterization. Akkar&Bommer(2010), Cauzzi&Faccioli(2008), Chiou&Youngs(2008), and Zhao et.al (2006) ground motion prediction models have been considered for active shallow crustal tectonic region. The study has developed uniform hazard spectrum and hazard maps of the Marmara Region with peak ground acceleration (PGA) and spectral accelerations (SA)’s at 0.2s and 1s periods corresponding to 10% and 2% probabilities of exceedance in 50 years. Obtained uniform hazard spectrums of electric power systems in the Marmara region have been compared with response spectrums of TBDY2018 and TSC-2007. The compatibility of SHARE model hazard analysis results with TBDY 2018 and TSC2007 has been assessed.

How to cite: Zulfikar, A. C. and Okuyan Akcan, S.: Seismic Hazard Assessment for the Energy Facilities in Marmara Region, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15353, https://doi.org/10.5194/egusphere-egu21-15353, 2021.

On October 30, 2020, an Mw=6.9 earthquake struck the eastern Aegean Sea. It was the largest earthquake in Europe and the deadliest worldwide in 2020, as it resulted in 119 fatalities (117 in Turkey, 2 in Greece) from partial or total building collapse. Moreover, it generated environmental effects and damage to the built environment in both countries. The primary earthquake environmental effects included permanent surface deformation and coseismic surface ruptures, while the secondary effects comprised tsunami, slope failures, liquefaction phenomena, hydrological anomalies and ground cracks.

Every time a strong earthquake strikes, disaster management plans for emergency response tested in drills are applied under real conditions and on large scale. Immediately after the 2020 Samos earthquake, Greek authorities launched the largest mobilization of resources for assisting the affected population since the initiation of the COVID-19 pandemic in Greece.

Public authorities from all administration levels, civil protection agencies as well as security and armed forces were mobilized. All emergency plans for protection of life, health and property of the affected population were applied according to the existing legislation framework. The immediate response comprised search and rescue operations, first-aid treatment and medical care, provision of emergency supplies, establishment of emergency shelters, building inspections and assessment of damage extent. Moreover, the Greek government announced immediate relief measures and financial assistance for reconstruction and repairs.

The local population and responders were exposed to geohazards including the earthquake, the subsequent tsunami and aftershocks among other effects and to the evolving COVID-19 pandemic. The situation was more serious as there were many contradicting issues in the emergency response phase. Actions usually applied in the pre-pandemic period are in contradiction with the main measures for preventing SARS-CoV-2 transmission. The novel coronavirus adds extra risk to these life-saving activities. Thus, these actions had to adapt to the newly introduced conditions and adopt provisional measures for mitigation and elimination of COVID-19 consequences.

This study focuses on the emergency response actions taken shortly after the earthquake amid the COVID-19 pandemic. They comprised establishment of the operational centres and emergency shelters in outdoor places, mandatory mask wearing indoors and outdoors at all times by all responders, immediate housing of homeless in hotels and touristic facilities in order to maintain social distancing, provision of protective equipment against COVID-19 transmission in responders and the affected population among others.

Based on the officially reported laboratory-confirmed daily COVID-19 cases in the earthquake-affected area during the pre- and post- disaster period, it is concluded that the impact of the natural hazards on the evolution of the pandemic in the affected area was negligible. The viral load was low and no increase of the infection rate was recorded.

From the aforementioned, it is concluded that the disaster management policy amid pandemic in Greece proved to be more efficient than thought with a well-planned and well-structured procedure for dealing not only with earthquakes amid pandemic, but also with other types of disasters induced by natural hazards. This approach could be used as a guide for similar compound emergencies worldwide.

How to cite: Mavroulis, S., Mavrouli, M., Thoma, T., Kourou, A., Manousaki, M., Karveleas, N., and Lekkas, E.: Lessons on COVID-19 pandemic and Earthquake Response: What we have learned from the October 30, 2020, Mw 6.9 Samos (Eastern Aegean, Greece) earthquake, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1722, https://doi.org/10.5194/egusphere-egu21-1722, 2021.

The first confirmed COVID-19 case was reported in December 2019. Over the first months of 2020, the novel SARS-CoV-2 virus was spread worldwide resulting in the declaration on March 11, 2020 of a global COVID-19 pandemic by the World Health Organization. The evolving pandemic has resulted in over 1900000 fatalities worldwide (as of January 8, 2021), while all sectors of the everyday life has been affected in numerous and varied ways. Natural hazards did not stop for the novel coronavirus. When the natural hazards cross the path of an evolving pandemic, compound emergencies emerge and are characterized by various effects and new unprecedented challenges.

Greece was no exception. Geological, hydrological and meteorological hazards took place in several parts of the country and they affected the local population, the natural and the built environment including buildings, infrastructures and lifelines. Among the most destructive effects in terms of human and economic losses was the March 21, 2020, Mw=5.7, Epirus (northwestern Greece) earthquake, the August 9, 2020, Evia (central Greece) flood, the September 17, 2020, Ianos medicane and the October 30, 2020, Mw=7.0, Samos (Eastern Aegean Sea) earthquake.

In order to identify the potential impact of the aforementioned disasters on the evolution of the COVID-19 pandemic in the disaster-affected areas, the officially reported laboratory-confirmed daily COVID-19 cases for the pre- and post- disaster periods from the disaster-affected areas were used. The impact of disasters in the evolution of the pandemic in the studied disaster-affected areas comprises increasing and decreasing trends and stability of the COVID-19 cases during the post-disaster period. More specifically, the geological and the hydrological hazards and the induced disasters negligibly affected the evolution of pandemic in the affected areas, while the hydrometeorological hazards resulted in increasing trends of the post-disaster reported COVID-19 cases in various affected areas.

The detected trends are strongly associated with the pre-existing viral load and infection rate in the disaster-affected areas, to the emergency response actions adapted to adopt provisional measures for the mitigation and elimination of COVID-19 consequences, to demographic features of the affected areas and to the intensity of the induced disasters and their effects on the local population (fatalities and injuries), the natural environment (primary and secondary environmental effects) and the built environment (structural damage to buildings, infrastructures and lifelines).

How to cite: Mavrouli, M., Mavroulis, S., and Lekkas, E.: Impact of natural hazards on the evolving COVID-19 pandemic: cases from Greece, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1731, https://doi.org/10.5194/egusphere-egu21-1731, 2021.

Across the world, health and disaster managers face the challenge of responding to natural hazards such as cyclones, floods, and droughts while minimizing the impacts of Covid-19. The tropical cyclones and floods affect vulnerable communities and result in losses of life and damages. The drought situations can weaken the agricultural economy and local livelihoods. How these impacts could be amplified by the Covid-19, mainly during the monsoon season, is of great importance for informed-planning. The present study aims to assess exposure to hydro-meteorological hazards (tropical cyclones, floods, and droughts) in terms of the number of people affected, economic activities exposed, and how these hazards superimposed over the Covid-19 pandemic could impact the different phases of disaster risk management cycle. The study focuses on three deltas, namely, Ganges-Brahmaputra-Meghna (GBM) delta spanning over India and Bangladesh, and Red River (RR) and Mekong River (MK) deltas in Vietnam.

Present research found that the GBM delta suffers from frequent cyclones and floods and less with coastal floods and droughts, whereas the MK delta suffers from riverine and coastal floods and droughts. The RR delta faces frequent tropical cyclones, riverine and coastal floods, and droughts. Populations living in Red delta (100%) exposed more to tropical cyclone as compared to GBM (2.22%) and the Mekong delta (0%) with 50-year return period (RP). Similarly, about 36.46 (0.28), 83.24 (47.23), and 72.76 (33.49) % population of the GBM, RR, and MK deltas are exposed to riverine (coastal) flood hazards with 10-year RP, respectively. During May-Aug 2020, a maximum of 0.76, 100, and 33.49 % population in a month was exposed to meteorological drought (SPI3 below -1) in the GBM, RR, and MK deltas, respectively.

The results include probabilistic exposure of urban area, cropland, livestock, and GDP to major hydro-meteorological hazards on a similar line. In the second part, the study explores the number of Covid-19 cases reported at the administrative level 2 and draws qualitative inferences on how tackling multi-hazards in the deltas could have become more challenging during the ongoing pandemic and vice versa.  The study recommends that the pandemic has resulted in an urgent need to incorporate health emergency disasters while designing hydro-meteorological disaster management plans.

How to cite: Pal, I., Udmale, P., Szabo, S., Pramanik, M., and Ganni, S. V. S. A. B.: Multi-hazard mitigation challenges during the Covid-19 crisis? Evidence from the tropical regions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13930, https://doi.org/10.5194/egusphere-egu21-13930, 2021.