Liquefaction Vulnerability Analysis using N-SPT Value and Grain Size Analysis on Gumbasa Irrigation Canal in the Post-Disaster Petobo Area, Sulawesi

Strong earthquakes occurred in Central Sulawesi, Indonesia, in late 2018, causing an inheritance disaster, soil liquefaction on Gumbasa Irrigation Canal at Petobo, Sulawesi. Soil liquefaction is a phenomenon of a decreasing soil bearing capacity triggered by strong vibrations in certain soil conditions. It immediately changes the soil characteristic from solid to liquid. Liquefaction vulnerability analysis was done using Idriss-Boulanger’s simplified procedure based on SPT value in several spots. The Petobo liquefaction zone has seven boreholes, five of which are located near the Gumbasa Irrigation Canal. The soil sample at those boreholes was taken to the laboratory for further soil testing using grain size analysis. The simplified procedure is intended to calculate the safety factor using Cyclic Resistance Ratio, Cyclic Stress Ratio, and Magnitude Scaling Factor. The liquefaction vulnerability analysis resulted in the AB 1 – AB 3 area near Gumbasa Irrigation Canal, which liquefied. Meanwhile, LP 1 and LP 4 are contrary. LP 1 is located upstream of the canal, whereas LP 4 the downstream. Grain size analysis yields a consistent result that AB 1 – AB 3 soil is quite scattered inside the liquefiable constraint.

CPTu-based approaches for cyclic liquefaction assessment of alluvial soil profiles

Over the years, methods to assess cyclic liquefaction potential based on piezocone penetration tests (CPTu) have been developed. This paper presents a comparative study between three CPTu-based methodologies, mainly in terms of the normalization procedures of overburden stresses, equivalent clean sand resistance, and magnitude scaling factor (MSF). Four CPTu profiles from a pilot site in southwest Portugal are thoroughly analysed with different methods, in terms of factor of safety against liquefaction, the Liquefaction Potential Index (LPI), and the Liquefaction Severity Number (LSN). The site presents very heterogeneous soil profiles, composed of alluvial deposits. Due to the presence of significant sand-silt–clay interbedded layers, the influence of transition zones and the use of different soil behaviour type index (Ic) cut-off values were also considered. From these analyses, a set of recommendations is presented for CPTu-based liquefaction assessment. Based on the extensive database of CPTu results in the pilot site area, a new classification relating LPI and LSN is proposed to assess liquefaction severity and damage.

Earthquake Magnitude Estimation using Precise Point Positioning

An accurate estimation of an earthquake magnitude plays an important role in targeting emergency services towards affected areas. Along with the traditional methods using seismometers, site displacements caused by an earthquake can be monitored by the Global Navigation Satellite Systems (GNSS). GNSS can be used either in real-time for early warning systems or in offline mode for precise monitoring of ground motion. The Precise Point Positioning (PPP) offers an optimal method for such purposes, because data from only one receiver are considered and thus not affected by other potentially not stable stations. Precise external products and empirical models have to be applied, and the initial convergence can be reduced or eliminated by the backward smoothing strategy or integer ambiguity resolution. The product for the magnitude estimation is a peak ground displacement (PGD). PGDs observed at many GNSS stations can be utilized for a robust estimate of an earthquake magnitude. We tested the accuracy of estimated magnitude scaling when using displacement waveforms collected from six selected earthquakes between the years 2016 and 2020 with magnitudes in a range of 7.5–8.2 Moment magnitude MW. We processed GNSS 1Hz and 5Hz data from 182 stations by the PPP method implemented in the G-Nut/Geb software. The precise satellites orbits and clocks corrections were provided by the Center for Orbit Determination in Europe (CODE). PGDs derived on individual GNSS sites formed the basis for ground motion parameters estimation. We processed the GNSS observations by the combination of the Kalman filter (FLT) and the backward smoother (SMT), which significantly enhanced the kinematic solution. The estimated magnitudes of all the included earthquakes were compared to the reference values released by the U. S. Geological Survey (USGS). The moment magnitude based on SMT was improved by 20% compared to the FLT-only solution. An average difference from the comparison was 0.07 MW and 0.09 MW for SMT and FLT solutions, respectively. The corresponding standard deviations were 0.18 MW and 0.22 MW for SMT and FLT solutions, which shows a good consistency of our and the reference estimates.

A Big Problem for Small Earthquakes: Benchmarking Routine Magnitudes and Conversion Relationships with Coda Envelope-Derived Mw in Southern Kansas and Northern Oklahoma

ABSTRACT Earthquake magnitudes are widely relied upon measures of earthquake size. Although moment magnitude (Mw) has become the established standard for moderate and large earthquakes, difficulty in reliably measuring seismic moments for small (generally Mw<4) earthquakes has meant that magnitudes for these events remain plagued by a patchwork of inconsistent measurement scales. Because of this, magnitudes of small earthquakes and statistics derived from them can be biased. Furthermore, because small earthquakes are much more numerous than large ones, many applications, such as seismic hazard modeling, depend critically on analysis of events characterized by magnitudes other than Mw. To assess this problem, we apply coda envelope analysis to reliably determine moment magnitudes for a case study of small earthquakes from northern Oklahoma and southern Kansas. Not surprisingly, we find significant differences among ML, mbLg, and Mw for M ∼2–4 earthquakes examined here. More troublingly, we find that relations designed to convert other magnitudes to Mw, which are relied upon for important applications such as seismic hazard analysis, often increase rather than decrease this bias for our dataset. In our case study, we find that converted magnitudes can result in a systematic bias sometimes exceeding 0.5 magnitude units, a difference that typically corresponds to a factor of ∼3 in seismicity rate. Moreover, we find a correspondingly large bias in Gutenberg–Richter b-values, controlled primarily by inaccurate magnitude scaling in the conversion relationships. Although this study focuses on a relatively small geographic area, we can expect that similar issues exist with varying severity in other regions. Therefore, magnitudes of small earthquakes and their associated statistics, including seismicity rates and b-values, should be treated with caution.

NGA-subduction global ground motion models with regional adjustment factors

We develop semi-empirical ground motion models (GMMs) for peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral accelerations for periods from 0.01 to 10 s, for the median orientation-independent horizontal component of subduction earthquake ground motion. The GMMs are applicable to interface and intraslab subduction earthquakes in Japan, Taiwan, Mexico, Central America, South America, Alaska, the Aleutian Islands, and Cascadia. The GMMs are developed using a combination of data inspection, data regression with respect to physics-informed functions, ground-motion simulations, and geometrical constraints for certain model components. The GMMs capture observed differences in source and path effects for interface and intraslab events, conditioned on moment magnitude, rupture distance, and hypocentral depth. Site effect and aleatory variability models are shared between event types. Regionalized GMM components include the model constant (that controls ground motion amplitude), anelastic attenuation, magnitude-scaling break point, linear site response, and sediment depth terms. We develop models for the aleatory between-event variability [Formula: see text], within-event variability [Formula: see text], single-station within-event variability [Formula: see text], and site-to-site variability [Formula: see text]. Ergodic analyses should use the median GMM and aleatory variability computed using the between-event and within-event variability models. An analysis incorporating non-ergodic site response should use the median GMM at the reference shear-wave velocity condition, a site-specific site response model, and aleatory variability computed using the between-event and single-station within-event variability models. Epistemic uncertainty in the median model is represented by standard deviations on the regional model constants, which facilitates scaled-backbone representations of model uncertainty in hazard analyses.

A Ground-Motion Prediction Equation for the Western and the Southwestern Parts of China Based on Local Strong-Motion Records and an Overseas Reference Model for the Vertical Component

ABSTRACT A ground-motion prediction equation for the vertical ground motions from the western and the southwestern parts of China (referred to as SWC) is presented in this study. Based on the Xing and Zhao (2021) study, the Zhao et al. (2017) model (referred to as ZHAO2017) for the shallow crustal earthquakes in Japan was used as the reference model. We used a bilinear magnitude-scaling function hinged at a moment magnitude (Mw) of 7.1. The magnitude-scaling rate for events with Mw>7.1 was determined by records from the SWC dataset and the large events in the Pacific Earthquake Engineering Research Center Next Generation Attenuation-West2 dataset. Site classes (SCs) were used as the site response proxy. All other parameters were derived from the SWC dataset only. The magnitude-scaling rates for events with Mw≤7.1 in this study are larger than in the ZHAO2017 model at most periods. The absolute values of the geometric attenuation rates are larger, and the absolute values of the anelastic attenuation rates are smaller than in the ZHAO2017 model. The between-event standard deviations are smaller than in the ZHAO2017 model at short periods, and the within-event standard deviations are larger than in the ZHAO2017 model at all periods. The differences in the between-site standard deviations vary significantly from one SC to another. We also find that the between-event and within-event residuals are almost independent of magnitude and source distance. The response spectrum attenuates less rapidly than in the ZHAO2017 model at distances less than 30 km.

Near-Source Magnitude Scaling of Spectral Accelerations: Analysis and Update of Kotha et al. (2020) Model

Ground-motion models (GMMs) are often used to predict the random distribution of spectral accelerations (SAs) at a site due to an earthquake at a distance. In probabilistic seismic hazard and risk assessment, large earthquakes occurring close to a site are considered as critical scenarios. GMMs are expected to perform well for such rare scenarios i.e., to predict realistic SAs with low prediction uncertainty. However, the datasets used to regress GMMs are usually deficient of data from rare/critical scenarios. The Kotha et al. (2020) GMM developed from the Engineering Strong Motion (ESM) dataset was found to predict decreasing short-period SAs with increasing \({M}_{W}\ge {M}_{h}=6.2\), and with large within-model uncertainty at near-source distances \({R}_{JB}\le 30km\). In this study, we analysed and updated the parametrisation of the GMM based on non-parametric and parametric analyses of ESM and the NEar Source Strong motion (NESS) datasets. By reducing \({M}_{h}\) to 5.7, we could rectify the \({M}_{W}\) scaling issue, while also reducing the within-model uncertainty on predictions at \({M}_{W}\ge 6.2\). We then evaluated the updated GMM against NESS data, and found that the SAs from a few large, thrust-faulting events in California, New Zealand, Japan, and Mexico are significantly higher than GMM median predictions. However, near-source recordings of these events were mostly made on soft-soil geology and contain anisotropic pulse-like effects. A more thorough non-ergodic treatment of NESS was not possible because most sites sampled unique events in very diverse tectonic environments. Therefore, for now, we provide an updated set of GMM coefficients, within-model uncertainty, and heteroskedastic variance models.

​Slip modes and interaction in a simplified strike-slip fault system with increasing geometrical complexity

<p>The release of elastic energy along an active fault is accommodated by a wide range of slip modes. It ranges from long-term slow slip events (SSEs) and creep to short-term tremors and earthquakes. They vary not only in their characteristic duration but also in their magnitude, spatial exten<span><span>t</span></span> and slip velocities. The exact relationship is unclear, as in some regions many slip modes occur simultaneously (e.g. Tohoku-Oki) and in others certain slip modes are completely absent (e.g. Cascadia).</p><p>One of the driving factors in the generation of this large variety of slip modes is the interplay of fault heterogeneity and geometrical complexity of the fault system. We test various settings in terms of fault heterogeneity and geometrical complexity with a scaled physical model. The experimental results are then validated and benchmarked through multi-scale numerical simulations. We describe <span><span>the</span></span> system using <span><span>a</span></span> rate-and-state frictional framework and introduce on-fault heterogeneity with variable frictional properties. All properties are the same for analogue and numerical simulation as far as they can be determined or realized experimentally (a-b, v<sub>load</sub>, S<sub>hmax</sub>, S<sub>hmin</sub>, etc...). As analogue material we use segmented, decimetre sized neoprene foam blocks in multiple configurations (e.g. biaxial shear at forces <1 kN) to simulate the elastic upper crust. The contact surfaces are spray-painted with acrylic paint to generate velocity weakening characteristics in between the blocks which is similar to the frictional behaviour of natural faults. We add heterogeneity to the fault surface by varying the fault area that is velocity weakening using grease. Geometrical complexity is implemented using conjugated or parallel sets of additional faults with the same characteristics.</p><p>We are able to reliably generate frequent stick-slip events of variable size and recurrence intervals. The slip characteristics, such as slip distribution, are in good agreement with analytical solutions of fault slip in elastic media. In a geometrically simple strike-slip model the recurrence behaviour and magnitude follows straightforward scaling relations in accordance with existing studies. If geometrical complexity is added to the model we observe clustering and variable recurrence that differ from the simpler geometry. Additionally, we are going to give an outlook on the interaction behaviour of multiple faults in dependence of their geometric configuration and the generation of power-law type magnitude scaling relations.</p>