Characteristics of landslides triggered by the 2013 ML6.5 Nantou, Taiwan, earthquake

Earthquake-triggered landslides are common disasters of active mountain belts. Due to the lack of earthquake-triggered landslide inventory in Taiwan, it is not intuitive to observe spatial relationships and discover unique patterns between landslides and essential triggers. We examined strong earthquake events in Taiwan after the 1999 Mw7.6 Chi-Chi earthquake and targeted the 2013 ML6.5 Nantou earthquake to create the landslide inventory. We adopted two Landsat-8 satellite images before and after the event to detect landslides, and incorporated a 20-m DEM and rock type data of Taiwan to represent key factors triggering earthquake-induced landslides such as peak ground acceleration (PGA), lithology, slope roughness, slope, and aspect. Based on the analysis of the density of landslides, there are strong correlations between the landslide occurrence and seismic and geomorphic factors. Furthermore, we noticed that the landslide aspects have a systematic tendency towards the northeast, which is not correlated with the dip directions and wave propagation directions. Instead, we found that the northeastward landslide aspect is more associated with the westward–southwestward surface movement at the landslides. We found that the included angles between the landslide aspects and the displacement directions for all the landslides are ~ 100°–180°. The relationship indicated that the coseismic deformation of the Nantou earthquake may play a role in the landslide distribution. Graphical Abstract

Determination of earthquake prone zones at university of tadulako based on dominant periods and peak ground acceleration (PGA)

University of Tadulako is the largest State University in Palu City. When an earthquake with a magnitude of 7.4 Mw on September 28, 2018, occurred, many buildings were damaged and even collapsed at that time, even causing casualties due to the rubble. Research on the Local Site Effect is essential for the assessment of seismic hazard. In this study, the local site effect was analyzed using the HVSR method based on microtremor data. The predominant Period (To) ranges between 1.709 s to 3.816 s, indicates that this area consists of alluvium and has a very thick sediment layer. Another parameter calculated in this paper is the peak ground acceleration (PGA) with values from 0.914 g to 0.924 g. This value is the first indicated soil damage level due to ground motions. The results of this study can be used as a consideration in the development of regional spatial planning and building structures based on earthquake analysis.

NGA-Subduction research program

This article summarizes the Next Generation Attenuation (NGA) Subduction (NGA-Sub) project, a major research program to develop a database and ground motion models (GMMs) for subduction regions. A comprehensive database of subduction earthquakes recorded worldwide was developed. The database includes a total of 214,020 individual records from 1,880 subduction events, which is by far the largest database of all the NGA programs. As part of the NGA-Sub program, four GMMs were developed. Three of them are global subduction GMMs with adjustment factors for up to seven worldwide regions: Alaska, Cascadia, Central America and Mexico, Japan, New Zealand, South America, and Taiwan. The fourth GMM is a new Japan-specific model. The GMMs provide median predictions, and the associated aleatory variability, of RotD50 horizontal components of peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral acceleration (PSA) at oscillator periods ranging from 0.01 to 10 s. Three GMMs also quantified “within-model” epistemic uncertainty of the median prediction, which is important in regions with sparse ground motion data, such as Cascadia. In addition, a damping scaling model was developed to scale the predicted 5%-damped PSA of horizontal components to other damping ratios ranging from 0.5% to 30%. The NGA-Sub flatfile, which was used for the development of the NGA-Sub GMMs, and the NGA-Sub GMMs coded on various software platforms, have been posted for public use.

A Far-Field Ground-Motion Model for the North Australian Craton from Plate-Margin Earthquakes

ABSTRACT The Australian territory is just over 400 km from an active convergent plate margin with the collision of the Sunda–Banda Arc with the Precambrian and Palaeozoic Australian continental crust. Seismic energy from earthquakes in the northern Australian plate-margin region are channeled efficiently through the low-attenuation North Australian craton (NAC), with moderate-sized (Mw≥5.0) earthquakes in the Banda Sea commonly felt in northern Australia. A far-field ground-motion model (GMM) has been developed for use in seismic hazard studies for sites located within the NAC. The model is applicable for hypocentral distances of approximately 500–1500 km and magnitudes up to Mw 8.0. The GMM provides coefficients for peak ground acceleration, peak ground velocity, and 5%-damped pseudospectral acceleration at 20 oscillator periods from 0.1 to 10 s. A strong hypocentral depth dependence is observed in empirical data, with earthquakes occurring at depths of 100–200 km demonstrating larger amplitudes for short-period ground motions than events with shallower hypocenters. The depth dependence of ground motion diminishes with longer spectral periods, suggesting that the relatively larger ground motions for deeper earthquake hypocenters may be due to more compact ruptures producing higher stress drops at depth. Compared with the mean Next Generation Attenuation-East GMM developed for the central and eastern United States (which is applicable for a similar distance range), the NAC GMM demonstrates significantly higher short-period ground motion for Banda Sea events, transitioning to lower relative accelerations for longer period ground motions.

Modeling of Seismic Energy Dissipation of Rocking Foundations Using Nonparametric Machine Learning Algorithms

The objective of this study is to develop data-driven predictive models for seismic energy dissipation of rocking shallow foundations during earthquake loading using multiple machine learning (ML) algorithms and experimental data from a rocking foundations database. Three nonlinear, nonparametric ML algorithms are considered: k-nearest neighbors regression (KNN), support vector regression (SVR) and decision tree regression (DTR). The input features to ML algorithms include critical contact area ratio, slenderness ratio and rocking coefficient of rocking system, and peak ground acceleration and Arias intensity of earthquake motion. A randomly split pair of training and testing datasets is used for initial evaluation of the models and hyperparameter tuning. Repeated k-fold cross validation technique is used to further evaluate the performance of ML models in terms of bias and variance using mean absolute percentage error. It is found that all three ML models perform better than multivariate linear regression model, and that both KNN and SVR models consistently outperform DTR model. On average, the accuracy of KNN model is about 16% higher than that of SVR model, while the variance of SVR model is about 27% smaller than that of KNN model, making them both excellent candidates for modeling the problem considered.

Ergodic site response model for subduction zone regions

We present an ergodic site response model with regional adjustments for use with subduction zone ground-motion models. The model predicts site amplification of peak ground acceleration, peak ground velocity, and 5% damped pseudo-spectral accelerations of the orientation-independent horizonal component for oscillator periods from 0.01 to 10 s. The model depends on the time-averaged shear-wave velocity in the upper 30 m ( VS30), basin depth, and region and is independent of subduction earthquake type. It has three components: a linear site-amplification term in the form of VS30-scaling, a nonlinear term that depends on VS30 and shaking intensity parameterized by peak ground acceleration at the reference-rock velocity condition of 760 m/s, and a basin sediment-depth term for Japan and Cascadia conditioned on the depth to the 2.5 km/s shear-wave velocity isosurface ( Z2.5). A global VS30-scaling model is provided along with regional adjustments for Japan, Taiwan, South America, Alaska, and Cascadia. The nonlinear model is global, with a functional form that has often been used to fit nonlinear responses inferred from simulations, but here we calibrate it empirically. Relative to a prior model for shallow earthquakes in active tectonic regions, our subduction zone global VS30-scaling is comparable at short periods (<1.0 s) but weaker at long periods, while the nonlinear site response is generally less pronounced but extends to lower levels of shaking. Basin depth models are conditioned on the difference of the actual Z2.5 and a VS30-conditioned mean Z2.5. Sites with positive differential depths have increased long-period site responses and decreased short-period responses, with the opposite occurring for negative differential depths.

A Seismic Alert System for Oil & Gas Offshore Fields

Objectives/Scope This paper presents an innovative web tool developed for the seismic monitoring of critical infrastructure. As an example, we describe an application for the ENI offshore facilities, Jangkrik and Merakes Fields Development, offshore Indonesia. Methods, Procedures, Process The system monitors reported seismic activity in a project area, and issues warnings when earthquakes detected may have directly or indirectly impacted facilities. Notifications allow the owner to optimize decisions regarding post-earthquake asset surveys and maintenance, avoiding the need for inspections in areas not significantly affected. A system of email alerts and a web based GIS platform provide the end-user with a tool to control its own assets. Results, Observations, Conclusions The purpose of the tool is to indirectly monitor earthquakes in an area and identify those which may have damaged the Oil and Gas facilities of interest. This identification requires accurate near real-time earthquake data such as date, time, location, magnitude, and focal depth. To this end, the system retrieves earthquake data from a qualified set of public seismic agencies. The system computes the expected values of shaking at the specific offshore facilities (platforms, subsea structures, pipelines, etc.). Calculations are based on sets of Ground Motion Prediction Equations (GMPEs) selected to match the seismotectonic environment. The expected values of seismic acceleration generated by an earthquake are compared with threshold values and a warning message is issued to the facilities supervisors when the ground acceleration exceeds design values. Threshold values related to secondary seismic effects (e.g., seismically induced landslides, debris flow) which could affect facilities integrity are also considered in the alert system. Threshold values are defined considering project seismic and geohazard documents, to summarize strong ground motion parameters that could potentially trigger damaging seismic geohazards, and project design documents to collect all data about seismic design of the assets. Monitoring intervals are defined based on the documentation screening. Several alarm levels are selected, based on the potential severity of earthquake effects. The more severe levels of ground motion, with high damage potential, can trigger recommendation for inspection. Novel/Additive Information Asset integrity and safety are key drivers in the offshore petroleum industry. Safety performance with respect to earthquakes is a fundamental issue in all seismic prone areas. The seismic alert system presented highlights, in near real time, earthquakes that are potentially critical for structures in an Oil and Gas field. This allows the owners to make quick decisions and plan necessary intervention regarding assets affected directly or indirectly by earthquakes. Exploiting the wide background of knowledge in engineering and geoscience and the modern availability of global earthquake data, the tool can provide useful assistance in managing asset integrity, regardless of the availability of local seismic networks or strong motion stations.

Structural performance of buildings during the 30 November 2018 M7.1 Anchorage, Alaska earthquake

Southcentral Alaska, the most populous region in Alaska, was violently shaken by a Mw 7.1 earthquake on 30 November 2018 at 8:29 am Alaska Standard Time. This was the largest magnitude earthquake in the United States close to a population center in over 50 years. The earthquake was 46 km deep, and the epicenter was 12 km north of Anchorage and 19 km west of Eagle River. The event affected some 400,000 residents, causing widespread damage in highways, nonstructural components, non-engineered and older buildings, and structures on poorly compacted fills. A few isolated serious injuries and partial collapses took place. Minor structural damage to code-conforming buildings was observed. A significant percentage of the structural damage was due to geotechnical failures. Building stock diversity allows use of the region as a large test bed to observe how local building practices affected earthquake damage levels. The prevailing peak ground acceleration (PGA) was 0.2–0.32 g, causing shaking intensity at most sites of 50%–60% of the ASCE 7-16 design basis earthquake acceleration. Thus, the seismic vulnerability of building stock in the region was not truly tested. Reinforced concrete buildings had minor structural damage, except in a few cases of shear wall and transfer girder shear cracking. Fiber-reinforced polymer (FRP)-retrofitted buildings performed satisfactorily. Concrete-masonry-unit (CMU) masonry buildings experienced serious structural damage in many cases, including relatively newer buildings. The earthquake caused widespread structural damage in non-engineered buildings (primarily wood and CMU masonry) that exist widely in the region, especially in Eagle River. Of these, non-engineered single-family wood buildings had the heaviest structural damage. No structural damage could be observed in steel buildings. The aftershock sequence, which included 7 M5+ and 50 M4+ events, exacerbated structural damage in all types of buildings. The present study is based on the EERI field reconnaissance mission conducted by the authors following the earthquake. Based on the observed damage and structural performance, seismic risk mitigation recommendations are suggested.

Mobile home fragility curves

Seismic fragility of mobile (manufactured) homes is investigated. Compiled is a catalog of home performance in past earthquakes. Intensity measures causing damage are characterized by peak ground acceleration and velocity. Damage is defined as when the home is knocked out of position necessitating repairs and re-installation. Four categories of support conditions are identified: unanchored, tie-downs, proprietary systems, and perimeter wall foundations. Suggested fragility curves for unanchored homes and homes with tie-downs are derived from computer simulations. As a benchmark, a fragility curve for proprietary and perimeter wall systems is taken as the same as that for conventional wood homes. Shortcomings of using tie-down and proprietary systems in high seismic zones are discussed. The suggested fragility curves account for the different categories of support conditions thereby representing advancement to those in the Hazus national standardized risk modeling methodology.