Geologically, three active faults exist in West Timor, East Nusa Tenggara (NTT) Province, Indonesia, namely the Babau, Camplong, and Atambua faults. The audio-frequency magnetotelluric (AMT) data is used to model the electrical subsurface of the Camplong Fault’s southwestern part. The AMT profile that comprised 15 AMT observation points over a length of 26 km running in an NW–SE direction was subjected to a phase tensor analysis. The results suggest that the studied area has a regional strike of N25°E and that 2-D inverse modelling on the AMT profile was possible. The inverse modelling result indicates the presence of two conductive boundaries (C1: ρ ≤ 5 Ωm and C2: ρ ≤ 5 Ωm) in the central and the southeastern parts of the AMT profile that separates the R1 (ρ = 10–50 Ωm) and R2 (ρ = 10–50 Ωm) as well as R2 and R3 (ρ = 5-100 Ωm) zones, respectively. The R1, R2, and R3 are located in the northwestern, central and southeastern parts, respectively. We suggest that the C2 is possibly the damaged zone of the fault in this study area. We also conducted forward modelling and examined the seismic activity and geological background, the results of which aligned with the inverse modelling.

ABSTRACT Understanding the structure of the Opak fault in Yogyakarta, Indonesia, is crucial for accurate seismic hazard assessment. Despite identifying nearby local faults, the whole structure of the Opak fault remains unclear. Our detailed study reveals that the Opak fault and its surrounding faults are interconnected within a single fault system. This new insight will improve disaster mitigation efforts in Yogyakarta. Our approach integrates tomography, focal mechanism analysis, receiver functions (RFs), and seismicity data to provide a comprehensive understanding of the shallow crustal layer beneath an active fault. We deployed a mini regional network around the fault, combined with data from InaTEWS BMKG and a GTF (the German task force for earthquake) network, totalling 114 stations. Analyzing 3079 earthquakes with P-wave phases of 16,894 and S-wave phases of 14,422 enabled us to achieve higher-resolution seismic tomography than earlier studies, leading to more precise resolution of complex fault interactions. Our results show that the Opak fault and its neighboring faults are connected at a depth of around 12 km. In addition, at a depth of about 9 km, we observed that the P-wave velocity (VP), S-wave velocity (VS), and VP/VS ratio indicate the presence of the Opak, Ngalang, and Oyo faults, corroborated by lithological mapping. Understanding these crustal features is crucial for understanding the region’s geodynamic evolution and refining seismic hazard models. However, a detailed crustal model of Yogyakarta is still lacking. In this study, we present a new map of crustal thickness and bulk VP/VS ratios derived from P-wave RFs. Crustal thickness ranges from approximately 27 km beneath Bantul and the foothills of Mount Merapi to about 36 km under the Eastern Mountains. Using the common conversion point method applied in Bantul reveals a thin crust and a low-velocity zone extending down to about 15 km, with the Moho located between 30 and 40 km and a slab extending from 90 to 100 km. The presence of parallel faults near Yogyakarta may increase the risk of earthquakes if they were to rupture altogether. The interconnected Opak, Ngalang, and Oyo faults could significantly influence the seismic hazards faced by Yogyakarta.

The Yogyakarta area and its surroundings have a reasonably high population density and disaster vulnerability. Appropriate mitigation is essential to reduce the impact of earthquakes in this region caused by co-seismic activity around active faults in the future. One step towards earthquake disaster mitigation in a particular area is to understand the fault systems of its seismic zones so that the earthquake characteristics in that region can be well understood. This study applies a seismological model consisting of an updated 1-D velocity model and hypocenter relocation based on the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) seismic network. The relocated hypocenter results show that the original catalog's fixed depth (10 km) has been successfully relocated, spreading across seismogenic zones under the faults. The results indicate an earthquake distribution most located east of the Ngalang Fault (a source of the 2006 destructive earthquake) or along the southern prolongation of the Nglipar Fault, potentially dipping toward the northwest. This study also incorporates surface geological data to model the fault system associated with the co-seismic and post-seismic activities of the 2006 Yogyakarta earthquake. Based on this joint analysis, we propose that the Opak, Ngalang, and Nglipar faults formed an NE-trending parallel strike-slip fault network dipping toward the northwest. Moreover, fault planes that dip to the northeast are seen along the Oyo Fault, connecting the southern Opak and Ngalang faults.

The Timor region yields to an area for geologists that sits in a transitionalzone which is the boundary between subduction and collision zones. In this study, the goal is to better understand the tectonic conditions by imaging the subsurfacestructures in the region, especially in the upper mantle area. The study uses teleseismic tomography, a method that is particularly good at capturing deep structural features, making it ideal for tectonic research. The tomographic imaging was carried out using the FMTOMO code, which uses the fast-marching method for ray tracing and subspace inversion for the actual imaging process. To check the accuracy of the model, a checkerboard resolution test was performed, showing that reliable interpretation begins at a depth of 100 km. Horizontal cross-sections in the depth of 100 km, 200 km, and 300 km and Vertical cross-sections at longitude of 122°E and 124°E reveal a high-velocity area that represents the subducting Indo-Australian Plate, providing insight into the subduction structure in the region.

The earthquake striking Yogyakarta in 2006 with a magnitude Mw 6.4 stands out as one of Indonesia's most devastating inland seismic events. Within a few days post-event, the German Task Force for Earthquakes (GTF) mission strategically deployed 16 seismic stations to capture aftershocks, providing crucial insights into the earthquake's characteristics. In previous investigations, these aftershocks were useful in delineating the seismic structures beneath the earthquake zone. Notably, the study successfully identified the Ngalang Fault as the mainshock source of the 2006 Yogyakarta earthquake. The Ngalang Fault's orientation aligns with that of the Opak Fault, situated approximately 10 km to the east. This study unveils the results of relocating the aftershock hypocenters recorded by the seismic network and their correlation with the static and dynamic stress generated by co-seismic activity. Using an updated 1-D velocity model, we relocated 2141 hypocenters out of 2170 earthquakes. Daily seismicity patterns reveal that aftershocks from the Yogyakarta earthquake occurred along three active faults. Apart from the Ngalang Fault, which served as the primary source of the earthquake, additional aftershocks were observed on the southern segment of the Opak Fault and the Oyo Fault, connecting the two faults from the south. The static stress distribution indicates elevated values in the Oyo Fault and the southern segment of the Opak Fault, correlating with heightened seismic activity in these regions. Using the dynamic rupture model, the transient shear stress changes generated by the mainshock raise the stress on the Oyo and Opak Faults through dynamic rupture branching and jumping mechanisms, respectively. Consequently, seismic activity in the surrounding faults was influenced by the 2006 Yogyakarta earthquake, leading to the propagation of its aftershocks towards the two faults adjacent to the mainshock.

The western Java region is situated along the Sunda Arc, which is formed by subduction of the Indo-Australian Plate beneath the Eurasian Plate. The subduction process causes seismic activity in the Wadati-Benioff zone of the descending slab, produces a chain of active volcanoes, and forms numerous faults in the terrestrial and backarc region of the overriding plate. This study examines the region's tectonic system via seismic tomography, in which the most recent earthquake catalog from the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) is utilized. Body wave travel time from 4561 local-regional earthquakes recorded by 78 seismic stations produces a 3-D Vp and Vp/Vs ratio model. The subducting Indo-Australian Plate slab is characterized mainly by high Vp and low Vp/Vs anomalies and exhibits steeper subduction than the Slab2 model. Partial melting zones, which serve as magma sources for several volcanoes, are observed at depths of about 90-100 km, characterized by low Vp and high Vp/Vs anomalies. The Lembang and Cimandiri fault lineaments are visible at 10 km depth and are characterized by negative Vp and positive Vp/Vs anomalies. This study also successfully demonstrates that the source of the damaging 2022 Cianjur earthquake occurred in a region dominated by low Vp and high Vp/Vs. These anomalies most likely relate to fluids or molten material in the fault zone. This study again highlights the importance of the BMKG seismic network for understanding tectonic systems on a local-regional scale, in this case, through the lens of seismic tomography.

Simeulue Island sits near the northern subduction margin of the Sumatran Megathrust, which is characterized by high tectonic activities and earthquakes. The oblique subduction along this margin has developed a complicated crustal deformation on the island, including faulting, uplifting and crustal segmentation. In the subduction zone, crustal anisotropy is often caused by stress-induced anisotropy in which the anisotropy direction is parallel to the stress direction. However, the complex crustal structure around the study area may produce a complicated anisotropy pattern. Here, we measure crustal seismic anisotropy from shear wave splitting analysis using the seismic data recorded at eight temporary stations spread across Simeulue Island. We apply the 2-D tomographic inversion and spatial averaging technique to map the splitting anisotropy patterns around the region. This research allows us to gain new insight into the crustal deformation pattern and its relationship with the complicated crustal structure beneath the island. The splitting result shows variations of anisotropy pattern around the study area. The spatially averaged fast directions at the northern region are trench-parallel, consistent with the strike of the geological features resulting from the strain partitioning deformation of the oblique convergence. Higher strength anisotropy is also observed in this area, indicating that the local fault system may strongly contribute to the crustal anisotropy. In the southern part of the island, the spatial averaging of fast direction gives a consistent pattern with the maximum regional stress direction, suggesting that anisotropy is mainly associated with stress-aligned microcracks. The central part of the island exhibits different splitting directions, marking the boundary of the geological structures between the areas in the north and south of the island. This pattern is also accompanied by high-strength anisotropy, suggesting that the source may be associated with the subducting geological structures beneath the area playing a significant role in the rupture barrier of the great events, as suggested by several previous studies.

Ultra-low frequency (ULF) geomagnetic analysis is a robust method for earthquake (EQ) forecasting. We conducted a simultaneous study of EQ precursors around the western part of Java Island in 2020 using wavelet transform (WT) and detrended fluctuation analysis (DFA) methods. ULF geomagnetic data (March to December 2020, 16:00–21:00 UTC or 23.00–04.00 LT) from Lampung Selatan (LPS) geomagnetic station were used to assess the precursors. We analyzed four EQs with an epicenter distance (R) of around 100 km from LPS station and a magnitude (M) greater than 5 Mw. We analyzed changes in the SZ/SG values and α values from the WT and DFA analyses against the threshold (µ±2σ) to identify anomalies related to the EQs. The result showed that SZ/SG anomalies occurred simultaneously with a decrease in α values several weeks prior to probable source EQ when there was a very low geomagnetic activity (Dst ≤ -30 nT). The Mw5.4 (07/07/2020) EQ might be the main source that led to the appearance of the precursor since it had the highest magnitude and KLS values compared to others. The combined WT and DFA results showed anomalies 1.5–13 weeks before the Mw5.4 (07/07/2020) EQ. The results suggest that WT and DFA are suitable methods for detecting EQ precursors but more work is needed to link the precursors to specific EQs.

The earthquake, which occurred in Yogyakarta, Indonesia, on May 26, 2006, at 22:53:58 UTC with Mw similar to 6.4, was one of the most destructive earthquakes in Indonesia. The earthquake caused thousands of fatalities, tens of thousands of injuries, and hundreds of thousands of house damages in the Yogyakarta area and its surroundings at a loss of billions of dollars. Previous studies from seismic tomography and satellite radar imaging hypothesized that the earthquake was caused by activating a so far unknown fault east of the Opak Fault. Although, in the beginning, the Opak fault was suspected to be the source of the Yogyakarta earthquake in 2006. This assumption was made because the damage was maximum in the Bantul area west of the Opak Fault. This study demonstrates that our seismic tomography achieved a higher resolution than the previous study and could resolve a failed complex fault system. We utilized more aftershocks (2170 events) and smaller grid sizes for seismic tomography inversion. Four focal mechanisms from aftershocks for Mw >= 4.5 were also conducted to support structure interpretation in the study area. Our results successfully delineate the Opak Fault and the second fault, namely the Ngalang Fault, parallel to the eastern part of the fault at a depth of 9 km. Two faults could be indicated by the velocity contrast of Vp, Vp/Vs ratio, and Vs from a horizontal section tomogram. Our focal mechanisms also support seismic tomography, revealing two fault planes in our study area. The results show that the two faults are connected by the Oyo Fault, which is ruptured in the opposite direction compared to the two faults.

Eastern Indonesia's tectonic setting is well known for its complexity and intense seismic activity. Controlled by several major and minor plates, including the Eurasian, Australian, and Pacific plates, this region is famous for its U-shaped subduction system beneath the Banda Arc. To better understand the architecture of the underlying structure in this region, we performed body-wave travel time tomography using ten years of catalog data provided by the Indonesian Agency for Meteorology, Climatology, and Geophysics. We utilize 9729 events in total, from which 46,446 P-wave arrival times were extracted. We used a double difference method to relocate the initial event catalog, which produced a pattern of seismicity consistent with a curved subduction system. Our tomographic model reveals a high velocity band between 90 and 240 km depth in the upper mantle, which is interpreted to be a concave dipping lithospheric slab that is parallel to the present-day Banda arc. Our results also show that lithosphere subducting from the north and south starts to collide at a depth of 300-350 km and becomes shallower further east. Apparent discontinuities in the high velocity band and a corresponding lack of seismicity supports the presence of a slab tear to the west of Seram. A dipping high velocity structure that is present from south to north beneath the island of Timor represents a subducting slab that dips more steeply beyond a depth of 150-200 km, which appears consistent with slab roll-back. Our tomographic model also shows evidence of back arc thrusting to the north of Sumbawa and Flores Islands in the form of a south-dipping higher velocity band at shallow depth. Furthermore, our tomographic models also reveal the possible presence of underthrust continental forearc in the form of a thin higher velocity anomaly that connects the backarc thrust and northward dipping lithosphere slab in the Timor area. Finally, a zone of low velocity above the higher velocity slab is clearly seen beneath Seram Island at a depth of similar to 100 km and may represent a partial melting zone.

The present study examines the underlying structures and Moho depth's geological implications in Central Sulawesi. Comprehending the underlying features of this area is essential for evaluating seismic risks and geological mechanisms. From the World Gravity Map 2012 (WGM 2012), we used a 2D radially-averaged power spectrum analysis of Bouguer gravity anomalies. The Moho depth is around 31 km in the northwest and northeast, with significant fluctuations in the middle and eastern regions. Although the northeastern and northwestern regions have similar depths, the center region has a lower Moho depth. On the other hand, the Palu-Koro Fault limit is marked by the eastern area, which corresponds to the Matano Fault, mirroring the center region. Furthermore, substantial orogenesis inside the Eastern Tokorondo Complex is suggested by Moho depth thinning, especially in the central, eastern, and southern portions. Our research emphasizes Central Sulawesi's complicated geological structures, marked by variable Moho depth and underlying formations. With implications for earthquake risk assessment and hazard reduction, these insights advance our knowledge of the region's geological processes.

We investigated the accurate locations of 443 explosion earthquakes that happened at Sinabung Volcano, North Sumatra, between October 2014 and June 2017. The explosion earthquakes were concentrated at shallow depths of approximately 1-5 km from the active crater. We used seismic tomography imaging to track the magma migration. Low Vp anomalies with low seismicity at shallow depths indicate that molten material originated from the shallow magma chamber. The presence of a shallow magma chamber of the Sinabung volcano was also revealed. The magma chamber with a volume of 2 km3 is located at a depth of 1.5-3.5 km below the summit. The magma plumbing system at shallow depths of approximately 1-5 km beneath the active crater was successfully imaged in detail.

The tsunami disaster in Palu, Indonesia, on September 28, 2018, caused many casualties and damage along Palu Bay, Indonesia. Prior to the tsunami, an earthquake was recorded 25 km northeast of Donggala. The analysis suggests that the tsunami was triggered by a landslide beneath the waters of Palu Bay. The investigation then focused on the earthquake's impact on the tsunami. This study conducts simulations to discern the dominant causes of tsunamis, comparing the effects of landslides with earthquakes. Three distinct tsunami sources were identified: earthquake-only (T-E), earthquake and submarine landslide (T-EL), and submarine landslide-only (T-L). Interpretation of tsunami source parameters for underwater landslides is carried out accurately. A nesting grid numerical method was employed to increase resolution and accuracy in the simulations. This study accurately interprets tsunami source parameters using data from the Bathymetry National Data-Geospatial Information Agency (185 meters resolution) and the field survey data from Baruna Jaya IV-BPPT Research Vessel Indonesia (25 meters resolution), thereby contributing to the creation of a tsunami inundation model map. This map serves to inform preparedness efforts and guide recommendations for infrastructure development in the Palu Bay area. The tsunami inundation model map is verified with field data and estimated using tide gauge monitoring data. The characteristics of the tsunami waves on September 28, 2018, reflect a T-EL-type tsunami source, while the T-L type source produces tsunami waves with longer periods compared to earthquake-generated tsunamis (T-EL). The T-E type, located on land, had minimal influence in causing the tsunami, despite the destructive potential of the shallow-depth M7.5 earthquake.

Abstract The history eruption of the Banda volcanoes was recorded in 1632, 1816, and 1988 and was preceded by significant earthquakes. In the eruption in 2017, there were 28 volcanic earthquakes, indicating a rock cracking process due to the movement of magma in the form of gas, liquid, and rock solids. We suspect that when the earthquake occurs, the rock-cracking process upon the eruption will potentially trigger the volcano flank to collapse into the sea and generate a tsunami in the Banda Naira and surrounding area. We contribute to modeling the travel time and tsunami inundation resulting from the flank collapse of Banda Volcano. BATNAS bathymetry data is used to run tsunami simulations. We use aerial photography from field survey data to interpret Banda Volcano failure parameters, including diameter, direction of sliding of the collapse, and slope of the collapse of the side of the Banda Volcano. Based on the tsunami simulation, the volcano flank collapse source on Banda Volcano produced a maximum tsunami in Banda Naira as high as 6.2 meters, and the tsunami will arrive around 6 – 8 minutes. While in AI Island, tsunami inundation reached 55.87 m and arrived in 4 minutes. Meanwhile, the maximum elevation of Banda Naira Island is 3.5 meters, with a population of 21,000 people in March 2024. Tsunami inundation has the potential to submerge entire residential areas in Banda Neira.

A series of earthquakes occurred on Bali Island, Indonesia, on December 13, 2022. The United States Geological Survey (USGS) recorded four shallow earthquakes around Karangasem - Bali with magnitude (M) > 4 at that time. The largest was the M 5.2 earthquake, which occurred at 10:38:21.67 UTC with 10 km of depth. We analyzed the anomalous geomagnetic activities during these earthquakes by utilizing the geomagnetic data from the Bayan geomagnetic station located on Lombok Island, less than 100 km from the earthquake's epicenters. We conducted the polarization ratio analysis by applying the Fast Fourier Transform (FFT) on the five hours of night geomagnetic data (16:00 - 21:00 UTC). The spectral power values of X, Y, and Z geomagnetic data at frequencies 0.04 - 0.06 Hz were calculated and compared with the disturbance storm time (Dst) to find their correlation. The Pearson correlation analysis indicates that they are significantly uncorrelated. Finally, we calculated the S-Z/S-G to analyze the geomagnetic anomalies and found them 6 - 11 days before the earthquakes at frequencies 0.04 - 0.06 Hz. We consider that these anomalies are possibly caused by the M 5.2 earthquake since it had the highest magnitude, E-S, and K-LS values.

Abstract The tail of a seismogram record, the coda, usually comes from the high-order scattered waves from some heterogeneities in the earth’s crust. Coda waves can be used to estimate the earthquake attenuation, site amplification and to determine the magnitudes. This preliminary study investigates the seismic attenuation property around the Yogyakarta region, Indonesia, from the Meramex temporary network. The Meramex network was installed from May to October 2004. We estimated the coda wave attenuation using the back-scattering model. We presented results from two station measurements (AJ1 and AI1) in this preliminary study. We analyzed shallow earthquakes (<40km) with distances less than 3 degrees. We bandpass filter the data with central frequencies of 1, 2, 4, 6, 8, 10, 12, and 14 Hz. The coda window begins from twice the S-wave arrival time with a window length between 20 and 80 seconds. We estimated the coda quality factor (Qc) for each central frequency. The Qc at reference frequency 1 Hz yields the estimation for Q0 and the frequency-dependent factor (η) of 64 - 134 and 1.14-0.95, respectively. The Q0 value increased significantly in the window length of 20 to 30 seconds and was relatively stable in the window length of 30 seconds, but the η value is the contrary. The rise of the Q0 and decrease of η is apparently due to the heterogeneity of the earth’s crust, and the flat may be associated with the uniformity of the upper mantle.

Traces of past landslides were found on the seabed of Palabuhanratu Bay, West Java. This landslide is thought to have generated a tsunami, but has never been investigated before. This bay is located around the western part of the Cimandiri Fault which is an active horizontal fault with a length of 100 km. Therefore, it is necessary to study the potential impact of a tsunami in the Palabuhanratu Bay area caused by a combination of local earthquakes and underwater landslides around the bay. Evidence of past landslides was revealed through side-scan sonar data from the underwater research vessel Baruna Jaya IV in Palabuhanratu Bay, Indonesia, in 2020. The data from this survey provides evidence of debris flows (historical landslide data) at the survey site. We simulated 29 tsunami scenarios from combined landslide earthquake sources by solving shallow water nonlinear equations numerically. Tsunami sources from earthquakes are classified into three types, e.g., land faults, sea faults, and combinations of land and sea faults. While the source of the tsunami from the landslide is divided by volume. Combination of the earthquake magnitudes range from M6.80 to M7.85, and the landslide volume ranged from 3.06 × 105 m3 to 2.5 × 108 m3. This study concludes that in our scenario, the M8.12 type T7 earthquake generates the largest tsunami in the study area, followed by the T6L5 scenario with M7.85 from the Cimandiri Fault and landslide with a total volume of 2.5 × 108 m3.

Abstract Sumatra Island is located in the subduction zone between Indo-Australian and Eurasian Plates. The tectonic activity has resulted in an active region. Hence, it may cause more heterogeneous crust in the region. To understand the relationship between the attenuation factor and the tectonic setting, we apply coda wave attenuation study Sumatra Island. This preliminary result focuses at the northern Aceh from observation at LHMI station. A total of about 123 earthquake waveforms of local distance (less than 3°) with depth less than 40 km is analyzed in this study. We employ a back-scattering model assumption to determine the attenuation of coda waves. Our coda wave quality factor (Qc ) estimation covers frequencies from 1 to 8 Hz. Onset of the coda window is determined by considering twice the arrival time of shear wave, with varying window lengths between 20 and 120 s. The Q0 (Qc at frequency 1 Hz) varies from 65.84 ± 5.50 to 183.09 ± 7.17. We observe a decrease in the factor of frequency dependence (η) between 1.14 ± 0.06 and 1.04 ± 0.03. Depth dependent of coda wave attenuation can be seen from the increase of Q0 (which is Qc at 1 Hz) with window length. We suggest that the Low Q0 (< 200) and high η (> 1) may be associated with high tectonic activity in this region.

Abstract The Mentawai segment, which is located on the western coast of Sumatra, Indonesia, is characterized by the convergence of the Indo-Australian Plate and the Sunda Plate. The complex interactions between these two tectonic plates have given rise to numerous earthquakes and deformations. After the devastating earthquake (Mw 7.8) in 2010 followed by a tsunami, this segment remains locked and has the possibility to produce a great earthquake. This study aims to determine precise earthquake locations and analyze the pattern of seismic distribution along with the deformation analysis from continuous GPS observations to understand the plate dynamics. We use the earthquake catalog data from the Agency for Meteorology, Climatology and Geophysics (BMKG) of the Indonesian earthquake network during the time period April 2009-December 2021. To improve the accuracy of the hypocenter, we relocated 1,130 events consisting of 10,994 P- and 3,414 S-wave phases and update the minimum 1-D velocity model simultaneously using the Joint Hypocenter Determination Method. Our results show that the intense seismicity occurred at a depth of less than 50 km. At deeper depths, the earthquake is distributed along the subducting plate to a depth of ~200 km in north and ~250 km in the south. Our findings strongly support the inference that the plate interface lies at a depth of 20 km. This conclusion is substantiated by the sharp increase in seismic velocity at that particular depth, which is indicative of a significant boundary between distinct geological layers. Furthermore, our investigation has uncovered a prominent aseismic zone beneath the forearc basin, situated approximately 100 km away from the trench line. The plate velocity derived from continuous GPS observations confirmed the stable movement of subducting Indo-Australian place towards the Sunda plate along the Mentawai segment. Finally, the results of this study are addressed to conduct further three-dimensional velocity inversion studies.

North Sumatra region is located at the plate boundary of Indo-Australian and Eurasian Plates. The plate boundary is characterized by high seismicity due to the subduction and Sumatra fault zones. One of the main tourist attractions in North Sumatra is Lake Toba, a large caldera formed due to Mt. Toba eruption. In recent years, it has become one of the most attractive destinations in Indonesia. Due to rapid development around this region, it is necessary to understand the seismic risk for hazard mitigation. First, Microzonation analysis is carried out from the installed temporary short-period seismometers around Lake Toba region. Then we estimate the peak ground acceleration (PGA) from the obtained horizontal-vertical spectral ratio (HVSR) using four ground motion equations. We use three earthquake sources (Mw 6.7 2011, Mw 6.3 2020, and Mw 5.7 2022) that occurred in North Sumatra to calculate the PGA. We obtained that the ground motion equations give different values of PGA. The highest PGAs ∼110 gal were estimated from Mw 5.7 2022 earthquake using Tong and Katayama ground motion equation at an epicenter distance of 15 km. However, further analysis are still needed, especially from strong motion data observations to verify our observation. We hope this preliminary result may provide information for future analysis for disaster risk reduction.