Strong Ground Motion Data Research Articles

Seismic Performance of Bridge Expansion Joints with and without Viscous Dampers during the 6 February 2023 Kahramanmaraş Earthquakes

Expansion joints render bridge structures highly vulnerable to damage during strong ground motions. Failures of expansion joints triggered by earthquakes not only jeopardize the post-earthquake serviceability of the bridge but also have a significant impact on the bridgeâs overall seismic performance. Despite extensive investigations and efforts to integrate these measures into design specifications aimed at mitigating the consequences of relative movements between adjacent bridge spans, major earthquakes have still revealed instances of damage related to expansion joints. On 6 February 2023, strong earthquake sequences occurred in KahramanmaraÅ, Turkey, with magnitudes of M7.7 and M7.6. The fault lines and epicenters of these shallow earthquakes were near the city and town centers and caused severe structural damage to buildings and infrastructures. There are approximately 1000 railway and highway bridges in the earthquake-affected region. Although both highway and railway bridges have generally performed well, some bridges experienced structural damage during the KahramanmaraÅ earthquakes. A large number of damage on the bridges is due to pounding and opening relative movements in expansion joints. This paper presents a comprehensive seismic evaluation of expansion joint failure mechanisms on bridges without viscous dampers during the 2023 KahramanmaraÅ earthquake sequences and an in-depth investigation into the seismic performance of bridge expansion joints equipped with viscous dampers and shock transmission unit devices are implemented utilizing the strong ground motion data collected throughout the earthquake sequences. It can be stated that the near-fault induced significant directivity and fling effects, resulting in notable velocity pulses and permanent tectonic deformations, and that these effects contributed to the failures of expansion joints, viscous damper devices, pot bearings, and shear keys.

Performance of Single Degree of Freedom (SDOF) Systems Subjected to The Near-Fault Earthquakes

This paper aims to assess the structures' seismic response with a system of Single-degree-of-freedom exposed to near-fault earthquakes, taking into account the effect of pulse period, shear wave velocity (VS30), and fault mechanism. Strong ground motion data were taken for different events in different places around the world and the prism software program is used for the analysis of seismic response for structures recognized as single-degree-of-freedom systems. Results show that the ground motion with a higher value of (VS30) provides an acceleration response higher than that of the lower value of (VS30). However, the findings revealed that the peak displacement requirements are observed in a nearby of the pulse period limits. In addition, it is noticed that there is an obvious increase in spectrum demand with longer pulse periods. Finally, results show at short vibration periods (T? 0.6sec) for both types (strike slip and dip slip) comparable results while an increment is observed in the results of the strike-slip for vibration periods more than (0.6sec) of the acceleration response spectrum. Nonetheless, for the velocity response spectrum dip-slip continuous in flocculating with a significant increase.

Empirical models for Fourier amplitude spectrum of ground-motion calibrated on data from the Iranian plateau

Ground-motion models (GMMs) are frequently used in engineering seismology to estimate ground motion intensities. The majority of GMMs predict the response spectral ordinates (such as spectral acceleration) of a single-degree-of-freedom oscillator because of their common application in engineering design practices. Response spectra show how an idealized structure reacts to applied ground motion; however, they do not necessarily represent the physics of ground motion. The functional forms of the response spectra GMMs are built around ideas taken from the Fourier spectral concept. Assuming the validity of Fourier spectral concepts in the response spectral domain could cause physically inexplainable effects. In this study, using a mixed-effects regression technique, we introduce four models capable of predicting the Fourier amplitude spectrum that investigates the impact of incorporating random-effect event and station terms and variations in using a mixed-effects regression technique in one or two steps using truncated dataset or all data (nontruncated dataset). All data consists of 2581 three-component strong ground motion data resulting from 424 events with magnitude ranging from 4.0 up to 7.4, from 1976 to 2020, and 706 stations. The truncated dataset’s records, events, and stations are reduced to 2071, 408, and 636, respectively. As part of this study, we develop GMMs to predict the Fourier amplitude spectrum for the Iranian plateau within the frequency range of 0.3–30 Hz. We adopted simple, functional forms for four models, and we included a limited number of predictors, namely Mw (moment magnitude), Rjb (Joyner–Boore distance), and VS30 (time-averaged shear-wave velocity in the top 30 m). Due to statistical analyses, the style-of-faulting term was excluded from the final functional forms. The robustness of the derived models is indicated by unbiased residual variation with predictor variables.

Modeling of kappa factor using multivariate adaptive regression splines: application to the western Türkiye ground motion dataset

The recent seismic activity on Türkiye’s west coast, especially in the Aegean Sea region, shows that this region requires further attention. The region has significant seismic hazards because of its location in an active tectonic regime of North–South extension with multiple basin structures on soft soil deposits. Recently, despite being 70 km from the earthquake source, the Samos event (with a moment magnitude of 7.0 on October 30, 2020) caused significant localized damage and collapse in the Izmir city center due to a combination of basin effects and structural susceptibility. Despite this activity, research on site characterization and site response modeling, such as local velocity models and kappa estimates, remains sparse in this region. Kappa values display regional characteristics, necessitating the use of local kappa estimations from previous earthquake data in region–specific applications. Kappa estimates are multivariate and incorporate several characteristics such as magnitude and distance. In this study, we assess and predict the trend in mean kappa values using three–component strong–ground motion data from accelerometer sites with known VS30 values throughout western Türkiye. Multiple linear regression (MLR) and multivariate adaptive regression splines (MARS) were used to build the prediction models. The effects of epicentral distance Repi, magnitude Mw, and site class (VS30) were investigated, and the contributions of each parameter were examined using a large dataset containing recent seismic activity. The models were evaluated using well–known statistical accuracy criteria for kappa assessment. In all performance measures, the MARS model outperforms the MLR model across the selected sites.

Hybrid Empirical Ground-Motion Models for the Island of Hawaii Based on an Updated Strong Ground-Motion Database

ABSTRACT In this study, we develop ground-motion models (GMMs) for the Island of Hawaii. This area has been the site of several significant earthquake events with a growing database of strong ground-motion observations. Ground-motion modeling on the Island of Hawaii is challenging due to different anelastic attenuation characteristics, the volcanic origin of some of the events, and event depth distribution. Only a few GMMs have been developed for the Island of Hawaii. In this study, we apply a hybrid empirical method (HEM) to develop two separate GMMs for shallow (hypocentral depth ≤ 20 km) and deep (hypocentral depth > 20 km) earthquakes on the Island of Hawaii. We utilize the ratio of the stochastic point-source model in the target and host regions as an appropriate adjustment factor. We apply these adjustment factors to convert the GMMs from the host (western North America) to the target (Island of Hawaii) region. We considered five GMMs proposed in the Next Generation Attenuation Phase 2 project by the Pacific Earthquake Engineering Research Center to model ground motions in the host region. We developed GMMs to predict peak ground acceleration and 5%-damped pseudospectral acceleration at periods T = 0.01–10 s, for moment magnitudes (M) in the range of 3–7.5, and for Joyner–Boore distances in the RJB≤200 km range. The applicability of HEM to develop GMMs for the Island of Hawaii and the growing strong ground-motion data result in further improvements in the capability of GMMs.

The 2020 Mw 7.0 Samos (Eastern Aegean Sea) Earthquake: joint source inversion of multitype data, and tsunami modelling

SUMMARY We present a kinematic slip model and a simulation of the ensuing tsunami for the 2020 Mw 7.0 Néon Karlovásion (Samos, Eastern Aegean Sea) earthquake, generated from a joint inversion of high-rate GNSS, strong ground motion and InSAR data. From the inversion, we find that the source time function has a total duration of ∼20 s with three peaks at ∼4, 7.5 and 15 s corresponding to the development of three asperities. Most of the slip occurs at the west of the hypocentre and ends at the northwest downdip edge. The peak slip is ∼3.3 m, and the inverted rake angles indicate predominantly normal faulting motion. Compared with previous studies, these slip patterns have essentially similar asperity location, rupture dimension and anticorrelation with aftershocks. Consistent with our study, most published papers show the source duration of ∼20 s with three episodes of increased moment releases. For the ensuing tsunami, the eight available gauge records indicate that the tsunami waves last ∼18–30 hr depending on location, and the response period of tsunami is ∼10–35 min. The initial waves in the observed records and synthetic simulations show good agreement, which indirectly validates the performance of the inverted slip model. However, the synthetic waveforms struggle to generate long-duration tsunami behaviour in simulations. Our tests suggest that the resolution of the bathymetry may be a potential factor affecting the simulated tsunami duration and amplitude. It should be noted that the maximum wave height in the records may occur after the decay of synthetic wave amplitudes. This implies that the inability to model long-duration tsunamis could result in underestimation in future tsunami hazard assessments.

Site classification methodology using support vector machine: A study

The site effect is a crucial factor when analyzing seismic risk and establishing ground motion attenuation relationships. A number of countries have introduced building site classification into earthquake-resistant design codes to account for local site effects on ground motion. However, most site classification indicators rely on drilling data, which is often expensive and requires considerable manpower. As a result, the less detailed drilling data may lead to an undetermined site category of numerous stations. In this study, a Support Vector Machine (SVM) algorithm-based site classification model was trained to address this issue using strong ground motion data and site data from KiK-net and K-net. The classification model used the average HVSR curve of the labeled site and the combined inputs, including frequency, peak, “prominence, and “sharpness” extracted from the curve. The SVM classification model has an accuracy of 76.12% on the test set, with recall rates of 82.69%, 75%, and 63.64% for sites I, II, and III, respectively. The precision rates are 75.44%, 73.77%, and 87.50%, respectively, with F1 scores of 78.90%, 74.38%, and 73.68%. For sites without significant peaks in the HVSR curve, the HVSR curve value was used as the characteristic parameter (input), and the SVM-based site classification model was also trained. The accuracy of class I and II is 75.86%. The results of this study show higher recall and accuracy rates than those obtained using the spectral ratio curve matching method and GRNN method, indicating a better classification performance. Finally, the generalization ability of the model was verified using some basic stations in Xinjiang deployed by the “National Seismic Intensity Rapid Reporting and Early Warning Project”. The SVM-based site classification model that employs strong motion data can provide more reliable classification results for sites without detailed borehole information, and the site classification results can serve as a reference for probing ground motion attenuation relationships, ground motion simulation, and seismic fortification considering the site effect.

Destructive impact of successive high magnitude earthquakes occurred in Türkiye’s Kahramanmaraş on February 6, 2023

AbstractTwo successive earthquakes with moment magnitudes of Mw = 7.7 (focal depth = 8.6 km) and Mw = 7.6 (focal depth = 7 km) occurred approximately within 9 h on February 6, 2023, in Türkiye, respectively. The epicenters were the Pazarcık and Elbistan districts of Kahramanmaraş. Both earthquakes occurred in the East Anatolian Fault Zone, one of Türkiye’s two major active fault systems. Between these two severe earthquakes, there was one more big aftershock with a moment magnitude of 6.6, the epicenter of which was in the Nurdağı District of Gaziantep. Then, on February 20, 2023, another aftershock earthquake with a magnitude of Mw = 6.4 occurred in Yayladağı district of Hatay. As a result of the earthquakes, severe damage occurred in several provinces and districts with a population of around 15 million, and more than 50,000 people have lost their lives. This study presents on-site geotechnical and structural investigations by a team of researchers after the Kahramanmaraş earthquakes. It summarizes the performance of the building environments as a result of on-site assessments, taking into account observed structural damage, local site conditions, and strong ground motion data. The possible causes of the observed damage are addressed in detail. These earthquakes once again revealed the common deficiencies of existing reinforced concrete structures in Türkiye, such as poor material quality, poor workmanship, unsuitability of reinforcement detailing, and inadequate earthquake-resistant construction techniques. Precast concrete and masonry structures in the region were also severely damaged during the earthquakes due to insufficient engineering service, poor materials, deficiencies during construction, etc.

Subduction Interface Earthquake Rise-Time Scaling Relations

ABSTRACT The slip duration in a fault plane, also known as the rise time (Tr), is determined in finite-fault rupture models (FFRMs) through the analysis of seismic source inversions using strong ground-motion (SGM) records and teleseismic data. For subduction interface earthquakes (megathrust), models exist that provide estimates for Tr values. The finite-source rupture model database and National Earthquake Information Center databases include FFRMs that allow for the extension of source-scaling relations. Currently, Tr versus seismic moment (M0) scaling relations specifically derived for large megathrust earthquakes in the near-source region are scarce. The relationship between stress drop and M0 is not straightforward; therefore, the logarithmic distribution of stress drop among earthquakes of different magnitudes (Mw) appears to be constant or self-similar. This self-similarity refers to a symmetry of the time-dependent fields, which remain unchanged under certain scale transformations in space and time characterized by similarity exponents and a function of the scaled variable, called the scaling function. In this study, Tr scaling has been conducted using 45 FFRMs derived from large megathrust earthquakes (Mw≥7.3) obtained from the previously mentioned databases. The scaling relation derived from the FFRMs based on SGM records closely approximates log(Tr)=const+1/3log(M0), which agrees with the self-similarity assumption for earthquake ruptures. On the other hand, the scaling relation obtained from the teleseismic dataset exhibits a smaller slope, indicating that the teleseismic data may overestimate source time characteristics compared with SGM data from seismic stations located close to the source.

Stochastic strong-ground motion simulation in the Santiago metropolitan region considering an Mw 7.8 intraplate intermediate-depth earthquake

Large intraplate intermediate-depth (IID) events are the most destructive to Chilean structures and they occurred throughout the country. Cities located above the hypocenters of these large earthquakes have been completely destroyed. In recent years, only small- and moderate-magnitude IID events have been reported below Santiago, the most populated Chilean city; however, the occurrence of large-magnitude IID events cannot be ruled out. In this study, we investigated the strong-ground motion generated by large-magnitude earthquakes occurring below the Santiago metropolitan region. We used a stochastic methodology to simulate synthetic records, considering IID events of magnitude Mw 7.8. To validate this method, we simulated intermediate-depth events of magnitudes Mw ∼5-6 that occurred near Santiago. We further calibrate our results by reproducing the strong-ground motion data recorded during the 2005 Tarapacá Mw 7.8 Northern Chile IID earthquake. We observe that in some areas of the Santiago Basin, high PGA values can reach values close to 1 g, in which, in addition to directivity effects and takeoff angles, the rupture distances (∼100 km) and soil type (C) play a key role in amplifying strong-ground motion. Finally, our findings highlight the importance of reproducing high-frequency time histories as a proxy to re-evaluate the seismic hazard due to large IID earthquakes.

Ground motion prediction equations based on shallow crustal earthquakes in Georgia and the surrounding Caucasus

Strong ground motions caused by earthquakes with magnitudes ranging from 3.5 to 6.9 and hypocentral distances of up to 300 km were recorded by local broadband stations and three-component accelerograms within Georgia’s enhanced digital seismic network. Such data mixing is particularly effective in areas where strong ground motion data are lacking. The data were used to produce models based on ground-motion prediction equations (GMPEs), one benefit of which is that they take into consideration information from waveforms across a wide range of frequencies. In this study, models were developed to predict ground motions for peak ground acceleration and 5%-damped pseudo-absolute-acceleration spectra for periods between 0.01 and 10 s. Short-period ground motions decayed faster than long-period motions, though decay was still in the order of approximately 1/r. Faulting mechanisms and local soil conditions greatly influence GMPEs. The spectral acceleration (SA) of thrust faults was higher than that for either strike-slip or normal faults but the influence of strike-slip faulting on SA was slightly greater than that for normal faults. Soft soils also caused significantly more amplification than rocky sites.

On the development of region and site-specific ground motion prediction model for the region of I-lan, Taiwan

this study presents the development of a region- and -site specific ground motion model (GMM) based on ground motion data obtained from the I-lan alluvial basin in northeastern Taiwan. The development was performed by calibrating the ergodic Phung et al. (2020) (Ph20) GMM developed for Taiwan. The source of strong ground motion data includes events from shallow crustal and subduction zones with magnitudes (MW) from 4.0 to 7.6, records from distances shorter than 200 km, and focal depths up to 150 km. The resulting regional model accounts for peculiarities that are not captured by the ergodic Ph20 GMMs, such as (1) the difference in source type effects, (2) VS30-scaling from the local site effects, and (3) enhancement of long period spectral ordinates due to the deep sedimentary basins. The standard deviations of the local model are much lower than those of the ergodic model, particularly the component of the standard deviation that corresponds to the site-to-site variability (ϕS2S), indicating that better site characterization can significantly reduce the overall uncertainty in ground motion estimation.

Strong ground motion data of the 2015 Gorkha Nepal earthquake sequence in the Kathmandu Valley

Strong-motion records of earthquakes are used not only to evaluate the source rupture process, seismic wave propagation and strong ground motion characteristics, but also to provide valuable data for earthquake disaster mitigation. The Kathmandu Valley, Nepal, which is characterised by having soft sediments that have been deposited in an earthquake-prone zone, has experienced numerous earthquakes. We have operated four strong-motion stations in the Kathmandu Valley since 2011. These stations recorded the 2015 magnitude 7.8 Gorkha Nepal earthquake that occurred in the Himalayan continental collision zone. For several months after the mainshock, we deployed four additional temporary stations. Here, we describe the seismic data for 18 earthquakes over magnitude 5.0 collected by this array, including the 2015 magnitude 7.3 Dolakha earthquake of maximum aftershock and three large aftershocks of magnitude 6-class. These data are essential for validating the sedimentary structure of the basin and for evaluating the hazard and risk of future earthquakes in the Kathmandu Valley.

Seismological and engineering characteristics of strong motion data from 24 and 26 September 2019 Marmara Sea earthquakes

An MW 4.5 earthquake took place on September 24, 2019 in the Marmara Sea. Two days after, on September 26, 2019, Marmara region was rattled by an MW5.7 earthquake. With the intention of compiling an ample strong ground motion data set of recordings, we have utilized the stations of Istanbul Earthquake Rapid Response and Early Warning System operated by the Department of Earthquake Engineering of Boğaziçi University and of the National Strong Motion Network operated by AFAD. Altogether 438 individual records are used to calculate the source parameters of events; namely, corner frequency, radius, rupture area, average source dislocation, source duration and stress drop. Some of these parameters are compared with empirical relationships and discussed extensively. Duration characteristics are analysed in two steps; first, by making use of the time difference between P-wave and S-wave onsets and then, by considering S-wave durations and significant durations. It is observed that they yield similar trends with global models. PGA, PGV and SA values are compared with three commonly used ground motion prediction models. At distances closer than about 60 km, observed intensity measures mostly conform with the GMPE predictions. Beyond 60 km, their attenuation is clearly faster than those of GMPEs. A frequency-dependent Q model is developed by using both events. Its consistency with existing regional models is confirmed.

HVSR-based Site Classification Approach Using General Regression Neural Network (GRNN): Case Study for China Strong Motion Stations

ABSTRACT Seismic site classification, which is fundamental for site-specific seismic hazard assessment, also plays an important role in accurate interpretation of ground motion data. However, detailed borehole information is not always available in many countries, e.g., China. Therefore, this study investigated application of the generalized regression neural network (GRNN) method to seismic site classification using China strong motion stations as example case. First, stations from KiK-net in Japan were classified based on their borehole information and individually assigned to I, II, III, and IV site classes as defined in Chinese seismic code. Then, mean horizontal-to-vertical spectral ratio (HVSR) curves for each site class were calculated as reference patterns. The overall recall rates for I, II, and III sites could reach 66.60%, 67.57%, and 68.42%, respectively, regarding use of KiK-net stations. The GRNN site classification scheme was validated using borehole information of K-NET stations, with recall rates for I and II site classes reaching 68% and 60%, respectively. Finally, based on HVSR curves calculated using strong ground motion data acquired during 2007–2015 in China, the site conditions of 167 National Strong Motion Observation Network System stations were estimated using the GRNN classification scheme. The results were partially validated using borehole information of 73 stations. The similarity between the mean HVSR curves and reference pattern curves indicated that the GRNN seismic site classification scheme is robust and could produce plausible results succinctly.

Constraining families of dynamic models using geological, geodetic and strong ground motion data: The Mw 6.5, October 30th, 2016, Norcia earthquake, Italy

The 2016 Central Italy earthquake sequence is characterized by remarkable rupture complexity, including highly heterogeneous slip across multiple faults in an extensional tectonic regime. The dense coverage and high quality of geodetic and seismic data allow us to image intriguing details of the rupture kinematics of the largest earthquake of the sequence, the Mw 6.5 October 30th, 2016 Norcia earthquake, such as an energetically weak nucleation phase. Several kinematic models suggest multiple fault planes rupturing simultaneously, however, the mechanical viability of such models is not guaranteed.Using 3D dynamic rupture and seismic wave propagation simulations accounting for two fault planes, we constrain “families” of spontaneous dynamic models informed by a high-resolution kinematic rupture model of the earthquake. These families differ in their parameterization of initial heterogeneous shear stress and strength in the framework of linear slip weakening friction.First, we dynamically validate the kinematically inferred two-fault geometry and rake inferences with models based on only depth-dependent stress and constant friction coefficients. Then, more complex models with spatially heterogeneous dynamic parameters allow us to retrieve slip distributions similar to the target kinematic model and yield good agreement with seismic and geodetic observations. We discuss the consistency of the assumed constant or heterogeneous static and dynamic friction coefficients with mechanical properties of rocks at 3-10 km depth characterizing the Italian Central Apennines and their local geological and lithological implications. We suggest that suites of well-fitting dynamic rupture models belonging to the same family generally exist and can be derived by exploiting the trade-offs between dynamic parameters. Our approach will be applicable to validate the viability of kinematic models and classify spontaneous dynamic rupture scenarios that match seismic and geodetic observations as well as geological constraints.

Failures of structures during the January 24, 2020, Sivrice (Elazığ) Earthquake in Turkey

On January 24, 2020, a severe earthquake of magnitude Mw 6.8 hit the Sivrice district of Elazig province at 20:55 (17:55 GMT) local time. This earthquake caused significant damages, partial or total collapses in many buildings with 41 fatalities. A few days after the earthquake, our reconnaissance team visited city centers, districts and villages in the region and, then, carried out an investigation and assessments. The results and suggestions obtained after the earthquakes are very important in designing earthquake-resistant structures and reducing the casualties. This study aims to identify deficiencies and reveal the causes of damages by examining the failure mechanisms of structures. Firstly, the effect of the destructive seismic event is discussed and the historical earthquakes in the region are summarized. Then, strong ground motion data and the structural damages observed from different building types are evaluated. The damage patterns and failure mechanisms are analyzed and interpreted based on the Turkish Earthquake Codes.

Strong Ground Motion Sensor Network for Civil Protection Rapid Decision Support Systems.

Strong motion sensor networks deployed in metropolitan areas are able to provide valuable information for civil protection Decision Support Systems (DSSs) aiming to mitigate seismic risk and earthquake social-economic impact. To this direction, such a network is installed and real-time operated in Chania (Crete Island, Greece), city located in the vicinity of the seismically active south front of the Hellenic Subduction Zone. A blend of both traditional and advanced analysis techniques and interpretation methods of strong ground motion data are presented, studying indicative cases of Chania shaking due to earthquakes in the last couple years. The orientation independent spectral acceleration as well as the spatial distribution of the strong ground motion parameters such as the Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), Peak Ground Displacement (PGD) and Arias Ιntensity observed at the urban area of Chania are presented with the use of a Geographic Information System (GIS) environment. The results point to the importance of the strong ground motion networks as they can provide valuable information on earthquake hazards prior to and after detrimental seismic events to feed rapid systems supporting civil protection decisions for prevention and emergency response.

Sensitivity Analysis of the Interfrequency Correlation of Synthetic Ground Motions to Pseudodynamic Source Models

AbstractGiven the deficiency of recorded strong ground-motion data, it is important to understand the effects of earthquake rupture processes on near-source ground-motion characteristics and to develop physics-based ground-motion simulation methods for advanced seismic hazard assessments. Recently, the interfrequency correlation of ground motions has become an important element of ground-motion predictions. We investigate the effect of pseudodynamic source models on the interfrequency correlation of ground motions by simulating a number of ground-motion waveforms for the 1994 Northridge, California, earthquake, using the Southern California Earthquake Center Broadband Platform. We find that the cross correlation between earthquake source parameters in pseudodynamic source models significantly affects the interfrequency correlation of ground motions in the frequency around 0.5 Hz, whereas its effect is not visible in the other frequency ranges. Our understanding of the effects of earthquake sources on the characteristics of near-source ground motions, particularly the interfrequency correlation, may help develop advanced physics-based ground-motion simulation methods for advanced seismic hazard and risk assessments.

Contribution of Fault Geometry on Probabilistic Seismic Hazard Assessment in Intermontane Basin: An example from Kathmandu Valley

The intermontane basins of the Himalaya are prone to damaging earthquakes as they are located roughly 10-15 km above the Main Himalayan Thrust (MHT), a major seismogenic thrust fault in the Himalaya. After the Mw 7.8 2015 Gorkha earthquake, the geometry of the MHT has been investigated using different approaches. Two contrasting models with a single ramp and double ramp geometries are proposed. However, the contribution of these geometries on seismic hazard has not been investigated yet. In this contribution, therefore, a probabilistic seismic hazard assessment is carried out using both models for Kathmandu valley and the obtained results are compared with the measured strong ground motion data of main shock of the 2015 Gorkha seismic sequence at Kirtipur, Kathmandu (rock site). It is found that the areal sources have the least contribution indicating sole contribution of MHT to relatively higher level of seismic hazard in the valley located on the up-dip locked portion of the MHT. The Peak Ground Acceleration (PGA) of the main shock of the 2015 Gorkha earthquake and PGA for 760 yr (exposure period of 50 yr and probability of exceedance 6.36%) of return period adopting both single and double ramp models are approximately same with error level of ± 3.84%. The results indicate that the adopted seismic model fairly represents the seismo-tectonic of the region, particularly of MHT. Considering this as the best fit results, the spatial distribution of the seismic hazard is analysed using double ramp model. It is found that the PGA values in the valley for 760 yr return period vary from 0.24 g to 0.28 g. The PGA values are higher in the southern part and gradually decrease towards north. Such decrease in PGA is consistent with the decrease in locking level of the MHT towards north. The study, therefore, emphasizes detailed geometrical characterization of the MHT while carrying out the seismic hazard assessment in the Himalaya.