More Like this

1. Basin structure from a dense nodal seismic array in Yangon, Myanmar: Contributions to seismic hazard estimates

   https://doi.org/10.1190/segam2020-3426695.1  

   Ghose, Ritu; Persaud, Patricia; Thant, Myo; Lin Kyaw, Zaw; Myint Oo, Tin; Myo Win, Zin; Phyo Lwin, Pyae; Chit Min, Aye; Thiha, Thiha; Naing Oo, Thet; et al (September 2020, SEG Technical Program Expanded Abstracts 2020)

   null (Ed.)

   Myanmar is surrounded by complex seismotectonic elements and threatened by a high seismic risk. The Central yanmar Basin (CMB) hosts the largest and fastest growing cities of Myanmar. The CMB is bounded by the Indo- Myanmar subduction zone to the west and the Sagaing fault to the east and is a seismically active tectonic block that has experienced large earthquakes (up to magnitude 8.0). A large earthquake in this region would affect Yangon and its surrounding population of around 8 million. Sedimentary basins have a significant contribution to seismic wave propagation, amplification and duration of ground shaking. Thus, to more accurately estimate the seismic hazard, a clear understanding of the detailed basin structures is required. The goal of our study is to map crustal structures, i.e. crustal thickness, crustal blocks, basin shape, size and depth, fault geometry, dipping layers and intra-crustal layers beneath the Yangon region. We will present receiver functions from a dense array of 168 nodal seismometers with the goal of revealing high-resolution seismic images of the basin. Our dense array will improve basin imaging by reducing uncertainties in receiver function interpretations. Developing a better understanding of basin structures will help our understanding of seismic amplification in the basin and thus will help to more accurately estimate the seismic hazard of this region. 

   more » « less
2. Spatial variability of site effects and its correlation with site response in Japan

   https://doi.org/10.3208/jgssp.v10.P2-25  

   Lorenzo-Velazquez, Cristina; Cabas, Ashly (January 2024, Japanese Geotechnical Society Special Publication)

   Local soil conditions depict an important role in regional seismic hazard assessments due to their influence on earthquake-induced ground shaking and deformation. The different levels of damage and site response at nearby locations correlate to site and geologic conditions variability, as has been reported after past earthquakes. Evaluating spatially variable ground motions (GMs) is key for earthquake reconnaissance efforts and regional seismic hazard assessments. This study focuses on the evaluation of spatial correlations in site parameters (e.g. time-averaged shear-wave velocity to a depth of 30 meters) at Kiban-Kyoshin Network (KiK-net), and their comparison to the observed spatial correlation residuals from ground motion intensity measures (IMs) from the Mw9.1 Tohoku earthquake. Current spatial correlation models treat site effects either as a fixed amplification factor or as randomized amplifications, but site effects are neither fixed nor random. Hence, geostatistical methods are used here to estimate spatial correlations between parameters that control site response and integrate their effects on resulting spatially variable ground motions. In this work, we evaluate the significance of the spatial correlation for different site parameters with respect to the GM amplification IMs residuals. 

   more » « less
3. Detecting Urban Earthquakes with the San Fernando Valley Nodal Array and Machine Learning

   https://doi.org/10.1785/0220250124  

   Omojola, Joses; Persaud, Patricia (August 2025, Seismological Research Letters)

   Abstract The San Fernando Valley (SFV), part of the Los Angeles metropolitan area, is a seismically active urban environment. Large-magnitude earthquakes, such as the 1994 Mw 6.7 Northridge event that occurred on a blind fault beneath the valley, caused significant infrastructure damage in the region, underscoring the need for enhanced seismic monitoring to improve the identification of buried faults and hazard evaluation. Currently, the Southern California Earthquake Data Center operates four broadband instruments within the valley; however, the network’s ability to capture small earthquakes beneath the region may be limited. To demonstrate how this data gap can be filled, we use recordings from the SFV array, comprised of 140 nodal instruments with interstation distances ranging from 0.3 to 2.5 km that recorded for one month. High-anthropogenic noise levels in urbanized areas tend to conceal earthquake signals; therefore, we applied a previously developed machine learning model fine-tuned on similar waveforms to detect events and pick seismic phases. In a two-step event association workflow, isolated phase picks were first culled, which eliminated false positive detections and reduced computational runtime. We located 62 events within a 209 km radius of our array with magnitudes ranging from ML 0.13 to 4, including 36 new events that were undetected by the regional network. One event cluster reveals a previously unidentified (5.3 km × 4 km) blind fault zone located ∼5 km beneath the southern part of the valley. Seismicity from this zone is rare in the regional catalog (<3 events per year), despite producing a Mb 4.4 event in 2014. Our results highlight the benefits of detecting small-magnitude seismicity for hazard estimation. Temporary nodal arrays can identify critical gaps in regional monitoring and guide site selection for permanent stations. In addition, our workflow can be applied to complement seismic monitoring in other urban settings. 

   more » « less
4. Ground‐Motion Amplification in Cook Inlet Region, Alaska, from Intermediate‐Depth Earthquakes, Including the 2018 Mw 7.1 Anchorage Earthquake

   https://doi.org/10.1785/0220190179  

   Moschetti, Morgan P.; Thompson, Eric M.; Rekoske, John; Hearne, Michael G.; Powers, Peter M.; McNamara, Daniel E.; Tape, Carl (November 2019, Seismological Research Letters)

   null (Ed.)

   Abstract We measure pseudospectral and peak ground motions from 44 intermediate‐depth Mw≥4.9 earthquakes in the Cook Inlet region of southern Alaska, including those from the 2018 Mw 7.1 earthquake near Anchorage, to identify regional amplification features (0.1–5  s period). Ground‐motion residuals are computed with respect to an empirical ground‐motion model for intraslab subduction earthquakes, and we compute bias, between‐, and within‐event terms through a linear mixed‐effects regression. Between‐event residuals are analyzed to assess the relative source characteristics of the Cook Inlet earthquakes and suggest a difference in the scaling of the source with depth, relative to global observations. The within‐event residuals are analyzed to investigate regional amplification, and various spatial patterns manifest, including correlations of amplification with depth of the Cook Inlet basin and varying amplifications east and west of the center of the basin. Three earthquake clusters are analyzed separately and indicate spatial amplification patterns that depend on source location and exhibit variations in the depth scaling of long‐period basin amplification. The observations inform future seismic hazard modeling efforts in the Cook Inlet region. More broadly, they suggest a greater complexity of basin and regional amplification than is currently used in seismic hazard analyses. 

   more » « less
5. Parsimonious Velocity Inversion Applied to the Los Angeles Basin, CA

   https://doi.org/10.1029/2021JB023103  

   Muir, Jack B.; Clayton, Robert W.; Tsai, Victor C.; Brissaud, Quentin (January 2022, Journal of Geophysical Research: Solid Earth)

   Abstract The proliferation of dense arrays promises to improve our ability to image geological structures at the scales necessary for accurate assessment of seismic hazard. However, combining the resulting local high‐resolution tomography with existing regional models presents an ongoing challenge. We developed a framework based on the level‐set method that infers where local data provide meaningful constraints beyond those found in regional models ‐ for example the Community Velocity Models (CVMs) of southern California. This technique defines a volume within which updates are made to a reference CVM, with the boundary of the volume being part of the inversion rather than explicitly defined. By penalizing the complexity of the boundary, a minimal update that sufficiently explains the data is achieved. To test this framework, we use data from the Community Seismic Network, a dense permanent urban deployment. We inverted Love wave dispersion and amplification data, from the Mw 6.4 and 7.1 2019 Ridgecrest earthquakes. We invert for an update to CVM‐S4.26 using the Tikhonov Ensemble Sampling scheme, a highly efficient derivative‐free approximate Bayesian method. We find the data are best explained by a deepening of the Los Angeles Basin with its deepest part south of downtown Los Angeles, along with a steeper northeastern basin wall. This result offers new progress toward the parsimonious incorporation of detailed local basin models within regional reference models utilizing an objective framework and highlights the importance of accurate basin models when accounting for the amplification of surface waves in the high‐rise building response band. 

   more » « less