Preliminary Seismic Hazard Analyses for the Ugandan Region

Uganda is situated between the two seismically active branches of the East African Rift Valley System, which are characterized by high levels of seismicity. A probabilistic approach has been used to assess the seismic hazard for Uganda and the surrounding areas. A probabilistic seismic hazard analysis requires the availability of an earthquake catalog, relevant ground motion prediction equations, and an outline of how the hazard calculations will be conducted. Using online sources, an earthquake catalog for Uganda and the immediate areas around Uganda was compiled spanning 108 years, from 1912 to 2020. This catalog was homogenized to moment magnitude to match with the selected ground motion prediction equations from Toro and Idriss. A logic tree accounting for the two ground motion prediction equations and dividing the study region into four seismic zones was used for calculating the seismic hazard. As an example, the seismic hazard results at two sites close to each other showed how different seismic hazards can be. Results from the probabilistic seismic hazard analyses was expressed through seismic hazard maps for peak ground acceleration at 10% probability of exceedance in 5, 10, 20, 50, 100 and 500 years, corresponding to return periods of 50, 100, 200, 500, 1000 and 5000 years, respectively. The seismic hazard map for 10% probability of exceedance in 5 years calculated PGAs from 0.02 to 0.10 g and 0.10 to 0.27 g outside of and within the western branch of the East African Rift Valley System, respectively. The estimated PGAs from previous studies at a similar probability of exceedance level are within the range of these findings, although the ranges calculated herein are wider.

b-value of what? Complex behavior of the magnitude distribution during and within the 2016–2017 central Italy sequence

The Magnitude–Frequency-Distribution (MFD) of earthquakes is typically modeled with the (tapered) Gutenberg–Richter relation. The main parameter of this relation, the b-value, controls the relative rate of small and large earthquakes. Resolving spatiotemporal variations of the b-value is critical to understanding the earthquake occurrence process and improving earthquake forecasting. However, this variation is not well understood. Here we present unexpected MFD variability using a high-resolution earthquake catalog of the 2016–2017 central Italy sequence. Isolation of seismicity clusters reveals that the MFD differs in nearby clusters, varies or remains constant in time depending on the cluster, and features an unexpected b-value increase in the cluster where the largest event will occur. These findings suggest a strong influence of the heterogeneity and complexity of tectonic structures on the MFD. Our findings raise the question of the appropriate spatiotemporal scale for resolving the b-value, which poses a serious obstacle to interpreting and using the MFD in earthquake forecasting.

A Detailed Earthquake Catalog for Banda Arc–Australian Plate Collision Zone Using Machine-Learning Phase Picker and an Automated Workflow

The tectonic setting of Timor–Leste and Eastern Indonesia comprises of a complex transition from oceanic lithosphere subduction to arc-continental collision. To better understand the deformation and convergent-zone structure of the region, we derive a new catalog of earthquake hypocenters and magnitudes from a temporary deployment of five years of continuous seismic data using an automated processing procedure. This includes a machine-learning phase picker, EQTransformer, and a sequential earthquake association and location workflow. We detect and locate ∼19,000 events during 2014–2018, which demonstrates that it is possible to characterize earthquake sequences from raw seismic data using a well-trained machine-learning picker for a complex convergent plate setting. This study provides the most complete catalog available for the region for the duration of the temporary deployment, which includes a complex pattern of crustal events across the collision zone and into the back-arc, as well as abundant deep slab seismicity.

Box Counting Fractal Dimension and Frequency Size Distributon of Earthquakes in the Central Himalaya Region

To establish the relations between b-value and fractal dimension (D0) for the earthquake distribution, we study the regional variations of those parameters in the central Himalaya region. The earthquake catalog of 989 events (Mc = 4.0) from 1994.01.31 to 2020.10.28 was analyzed in the study. The study region is divided into two sub-regions (I) Region A: 27.3°N -30.3°N and 80°E -84.8°E (western Nepal and vicinity) and (II) Region B: 26.4°N -28.6°N and 84.8°E -88.4°E (eastern Nepal and vicinity). The b-value observed is within the range between 0.92 to 1.02 for region A and 0.64 to 0.74 for region B showing the homogeneous nature of the variation. The seismic a-value for those regions ranges respectively between 5.385 to 6.007 and 4.565 to 5.218. The low b-values and low seismicity noted for region B may be related with less heterogeneity and high strength in the crust. The high seismicity with average b-values obtained for region A may be related with high heterogeneity and low strength in the crust. The fractal dimension ≥1.74 for region A and ≥ 1.82 for region B indicate that the earthquakes were distributed over two-dimensional embedding space. The observed correlation between D0 and b is negative for western Nepal and positive for eastern Nepal while the correlation between D0 and a/b value is just opposite for the respective regions. The findings identify both regions as high-stress regions. The results coming from the study agree with the results of the preceding works and reveal information about the local disparity of stress and change in tectonic complexity in the central Himalaya region.

SEISMICITY of the ARCTIC in 2015

The article provides an overview and analysis of seismicity within the boundaries of the Arctic region for 2015, a description of seismic station networks, and processing methods. The catalog of earthquakes in the Arctic region was compiled on the basis of catalogs of several organizations and seismological centers. In total, 334 earthquakes are included in the earthquake catalog. Most of the earthquakes that occurred in 2015, including all the strongest earthquakes, were located within the mid-ocean ridges of Mon, Knipovich and Gakkel. In the offshore territories, most of the earthquakes were confined to the Svalbard archipelago, in particular, to the seismically active zone in the Sturfjord strait. The renewal of instrumental seismological observations in 2011 (station ZFI) on Alexandra Land Island in the Franz Josef Land archipelago made it possible to record weak earthquakes in the north of the shelf of the Barents and Kara Seas. For twelve earthquakes, the focal mechanism parameters are presented according to the Global CMT catalog.

A New Smoothed Seismicity Approach to Include Aftershocks and Foreshocks in Spatial Earthquake Forecasting: Application to the Global Mw ≥ 5.5 Seismicity

Seismicity-based earthquake forecasting models have been primarily studied and developed over the past twenty years. These models mainly rely on seismicity catalogs as their data source and provide forecasts in time, space, and magnitude in a quantifiable manner. In this study, we presented a technique to better determine future earthquakes in space based on spatially smoothed seismicity. The improvement’s main objective is to use foreshock and aftershock events together with their mainshocks. Time-independent earthquake forecast models are often developed using declustered catalogs, where smaller-magnitude events regarding their mainshocks are removed from the catalog. Declustered catalogs are required in the probabilistic seismic hazard analysis (PSHA) to hold the Poisson assumption that the events are independent in time and space. However, as highlighted and presented by many recent studies, removing such events from seismic catalogs may lead to underestimating seismicity rates and, consequently, the final seismic hazard in terms of ground shaking. Our study also demonstrated that considering the complete catalog may improve future earthquakes’ spatial forecast. To do so, we adopted two different smoothed seismicity methods: (1) the fixed smoothing method, which uses spatially uniform smoothing parameters, and (2) the adaptive smoothing method, which relates an individual smoothing distance for each earthquake. The smoothed seismicity models are constructed by using the global earthquake catalog with Mw ≥ 5.5 events. We reported progress on comparing smoothed seismicity models developed by calculating and evaluating the joint log-likelihoods. Our resulting forecast shows a significant information gain concerning both fixed and adaptive smoothing model forecasts. Our findings indicate that complete catalogs are a notable feature for increasing the spatial variation skill of seismicity forecasts.

Spatial and time variations of seismicity before strong earthquakes in the southern part of the Balkans

A retrospective analysis of the spatial and time variations of three main statistical parameters of the seismicity before recent 4 stronger earthquakes (2015 – 2020) in the southern Balkans is presented. The modern extended software package ZMAP with various advanced seismological functions for earthquake catalog analysis is used for estimating the spatial-time variations in a- value (seismic activity), b-value (slope of the recurrence graph) and z-value (parameter of the relative seismic quiescence). The catalog data from constantly updated catalog of the University of Athens for the period 1964-2020 and spatial window 32° - 44° N and 10° – 30° E are used for the various statistical interpretations. The main result of the whole analysis is that the abnormally low b-values and high z-values, defining the zones of relatively seismic quiescence, may be an indicator of imminent release of more significant stress in areas adjacent to the zones of relatively high a-values. Thus, the result of the proposed joint interpretation of the spatial-time variations of these three statistical parameters of seismicity could be considered as a kind of predictor of the stronger recent seismic events in the southern part of Balkans.

Quantitative Analysis of Shallow Earthquake Sequences and Regional Earthquake Behavior: Implications for Earthquake Forecasting

<p>This study is a quantitative investigation and characterization of earthquake sequences in the Central Volcanic Region (CVR) of New Zealand, and several regions in New Zealand and Southern California. We introduce CURATE, a new declustering algorithm that uses rate as the primary indicator of an earthquake sequence, and we show it has appreciable utility for analyzing seismicity. The algorithm is applied to the CVR and other regions around New Zealand. These regions are also compared with the Southern California earthquake catalogue. There is a variety of behavior within these regions, with areas that experience larger mainshock-aftershock (MS-AS) sequences having distinctly different general sequence parameters than those of more swarm dominated regions. The analysis of the declustered catalog shows that Lake Taupo and at least three other North Island regions have correlated variations in rate over periods of ~5 years. These increases in rate are not due to individual large sequences, but are instead caused by a general increase in earthquake and sequence occurrence. The most obvious increase in rate across the four North Island subsets follows the 1995-1996 magmatic eruption at Ruapehu volcano. The fact that these increases are geographically widespread and occur over years at a time suggests that the variations may reflect changes in the subduction system or a broad tectonic process. We examine basic sequence parameters of swarms and MS-AS sequences to provide better information for earthquake forecasting models. Like MS-AS sequences, swarm sequences contain a large amount of decay (decreasing rate) throughout their duration. We have tested this decay and found that 89% of MS-AS sequences and 55% of swarm sequences are better fit with an Omori's law decay than a linear rate. This result will be important to future efforts to forecast lower magnitude ranges or swarm prone areas like the CVR. To look at what types of process may drive individual sequences and may be associated with the rate changes, we examined a series of swarms that occurred to the South of Lake Taupo in 2009. We relocated these earthquakes using double-difference method, hypoDD, to obtain more accurate relative locations and depths. These swarms occur in an area about 20x20 km. They do not show systematic migration between sequences. The last swarm in the series is located in the most resistive area of the Tokaanu geothermal region and had two M =4.4 earthquakes within just four hours of each other. The earthquakes in this swarm have an accelerating rate of occurrence leading up to the first M = 4.4 earthquakes, which migrate upward in depth. The locations of earthquakes following the M = 4.4 event expand away from it at a rate consistent with fluid diffusion. Our statistical investigation of triggering due to large global (M ≥ 7) and regional earthquakes (M ≥ 6) concludes that more detailed (waveform level) investigation of individual sequences will be necessary to conclusively identify triggering, but sequence catalogs may be useful in identifying potential targets for those investigations. We also analyzed the probability that a series of swarms in the central Southern Alps were triggered by the 2009 Dusky Sound Mw = 7.8 and the 2010 Darfield Mw = 7.1 earthquake. There is less than a one-percent chance that the observed sequences occurred randomly in time. The triggered swarms do not show a significant difference to the swarms occurring in that region at other times in the 1.5-year catalog. Waveform cross-correlation was performed on this central Southern Alps earthquake catalog by a fellow PhD student Carolin Boese, and reveals that individual swarms are often composed of a single waveform family or multiple waveform families in addition to earthquakes that did not show waveform similarities. The existence of earthquakes that do not share waveform similarity in the same swarm (2.5 km radius) as a waveform family indicates that similar waveform groups may be unique in their location, but do not necessarily necessitate a unique trigger or driver. In addition to these triggered swarms in the Southern Alps we have also identified two swarms that are potentially triggered by slow-slip earthquakes along the Hikurangi margin in 2009 and 2010. The sequence catalogs generated by the CURATE method may be an ideal tool for searching for earthquake sequences triggered by slow-slip.</p>

Quantitative Analysis of Shallow Earthquake Sequences and Regional Earthquake Behavior: Implications for Earthquake Forecasting

<p>This study is a quantitative investigation and characterization of earthquake sequences in the Central Volcanic Region (CVR) of New Zealand, and several regions in New Zealand and Southern California. We introduce CURATE, a new declustering algorithm that uses rate as the primary indicator of an earthquake sequence, and we show it has appreciable utility for analyzing seismicity. The algorithm is applied to the CVR and other regions around New Zealand. These regions are also compared with the Southern California earthquake catalogue. There is a variety of behavior within these regions, with areas that experience larger mainshock-aftershock (MS-AS) sequences having distinctly different general sequence parameters than those of more swarm dominated regions. The analysis of the declustered catalog shows that Lake Taupo and at least three other North Island regions have correlated variations in rate over periods of ~5 years. These increases in rate are not due to individual large sequences, but are instead caused by a general increase in earthquake and sequence occurrence. The most obvious increase in rate across the four North Island subsets follows the 1995-1996 magmatic eruption at Ruapehu volcano. The fact that these increases are geographically widespread and occur over years at a time suggests that the variations may reflect changes in the subduction system or a broad tectonic process. We examine basic sequence parameters of swarms and MS-AS sequences to provide better information for earthquake forecasting models. Like MS-AS sequences, swarm sequences contain a large amount of decay (decreasing rate) throughout their duration. We have tested this decay and found that 89% of MS-AS sequences and 55% of swarm sequences are better fit with an Omori's law decay than a linear rate. This result will be important to future efforts to forecast lower magnitude ranges or swarm prone areas like the CVR. To look at what types of process may drive individual sequences and may be associated with the rate changes, we examined a series of swarms that occurred to the South of Lake Taupo in 2009. We relocated these earthquakes using double-difference method, hypoDD, to obtain more accurate relative locations and depths. These swarms occur in an area about 20x20 km. They do not show systematic migration between sequences. The last swarm in the series is located in the most resistive area of the Tokaanu geothermal region and had two M =4.4 earthquakes within just four hours of each other. The earthquakes in this swarm have an accelerating rate of occurrence leading up to the first M = 4.4 earthquakes, which migrate upward in depth. The locations of earthquakes following the M = 4.4 event expand away from it at a rate consistent with fluid diffusion. Our statistical investigation of triggering due to large global (M ≥ 7) and regional earthquakes (M ≥ 6) concludes that more detailed (waveform level) investigation of individual sequences will be necessary to conclusively identify triggering, but sequence catalogs may be useful in identifying potential targets for those investigations. We also analyzed the probability that a series of swarms in the central Southern Alps were triggered by the 2009 Dusky Sound Mw = 7.8 and the 2010 Darfield Mw = 7.1 earthquake. There is less than a one-percent chance that the observed sequences occurred randomly in time. The triggered swarms do not show a significant difference to the swarms occurring in that region at other times in the 1.5-year catalog. Waveform cross-correlation was performed on this central Southern Alps earthquake catalog by a fellow PhD student Carolin Boese, and reveals that individual swarms are often composed of a single waveform family or multiple waveform families in addition to earthquakes that did not show waveform similarities. The existence of earthquakes that do not share waveform similarity in the same swarm (2.5 km radius) as a waveform family indicates that similar waveform groups may be unique in their location, but do not necessarily necessitate a unique trigger or driver. In addition to these triggered swarms in the Southern Alps we have also identified two swarms that are potentially triggered by slow-slip earthquakes along the Hikurangi margin in 2009 and 2010. The sequence catalogs generated by the CURATE method may be an ideal tool for searching for earthquake sequences triggered by slow-slip.</p>