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.

Types of strong earthquake precursor behavior obtained from world and regional catalogs of earthquakes

Typical features of seismicity inherent to the period prior to the strong earthquake occurrence are examined using the regional and world-wide earthquake catalogs by the method of construction of the Generalized vicinity of a large earthquake (GVLE). These features are foreshock power-law cascade, the weak long-term background increase in seismic activity, and the definite clustering of the main events. Worth to note, that all these features appear to indicate the loss of a stability of a system, without any reference to the physical mechanism of development of the instability. Thus, these features are expected to occur in connection with the bifurcation points in systems of other physical nature, examples of such behavior are given. Besides, a tendency of a decrease in earthquakes depth in the close GVLE vicinity was found. This precursor feature has a specific character and evidences in favor of a fluid involvement in the mechanism of earthquake occurrence.

Magnitude and nucleation time of the 2017 Pohang Earthquake point to its predictable artificial triggering

A damaging Mw5.5 earthquake occurred at Pohang, South Korea, in 2017, after stimulating an enhanced geothermal system by borehole fluid injections. The earthquake was likely triggered by these operations. Current approaches for predicting maximum induced earthquake magnitude ($${M}_{\max }$$ M max ) consider the volume of the injected fluid as the main controlling factor. However, these approaches are unsuccessful in predicting earthquakes, such as the Pohang one. Here we analyse the case histories of induced earthquakes, and find that $${M}_{\max }$$ M max scales with the logarithm of the elapsed time from the beginning of the fluid injection to the earthquake occurrence. This is also the case for the Pohang Earthquake. Its significant probability was predictable. These results validate an alternative to predicting $${M}_{\max }$$ M max . It is to monitor the exceedance probability of an assumed $${M}_{\max }$$ M max in real time by monitoring the seismogenic index, a quantity that characterizes the intensity of the fluid-induced seismicity per unit injected volume.

A Consistent Geological-Seismological Model For Earthquake Occurrence in New Zealand

<p>For the development of earthquake occurrence models, historical earthquake catalogues and compilations of mapped, active faults are often used. The goal of this study is to develop new methodologies for the generation of an earthquake occurrence model for New Zealand that is consistent with both data sets. For the construction of a seismological earthquake occurrence model based on the historical earthquake record, 'adaptive kernel estimation' has been used in this study. Based on this method a technique has been introduced to filter temporal sequences (e.g. aftershocks). Finally, a test has been developed for comparing different earthquake occurrence models. It has been found that the adaptive kernel estimation with temporal sequence filtering gives the best joint fit between the earthquake catalogue and the earthquake occurrence model, and between two earthquake occurrence models obtained from data from two independent time intervals. For the development of a geological earthquake occurrence model based on fault information, earthquake source relationships (i.e. rupture length versus rupture width scaling) have been revised. It has been found that large dip-slip and strike-slip earthquakes scale differently. Using these source relationships a dynamic stochastic fault model has been introduced. Whereas earthquake hazard studies often do not allow individual fault segments to produce compound ruptures, this model allows the linking of fault segments by chance. The moment release of simulated fault ruptures has been compared with the theoretical deformation along the plate boundary. When comparing the seismological and the geological earthquake occurrence model, it has been found that a 'good' occurrence model for large dip-slip earthquakes is given by the seismological occurrence model using the Gutenberg-Richter magnitude frequency distribution. In contrast, regions dominated by long strike-slip faults produce large earthquakes but not many small earthquakes and the occurrence of earthquakes on such faults should be inferred from the dynamic fault model.</p>

A Consistent Geological-Seismological Model For Earthquake Occurrence in New Zealand

<p>For the development of earthquake occurrence models, historical earthquake catalogues and compilations of mapped, active faults are often used. The goal of this study is to develop new methodologies for the generation of an earthquake occurrence model for New Zealand that is consistent with both data sets. For the construction of a seismological earthquake occurrence model based on the historical earthquake record, 'adaptive kernel estimation' has been used in this study. Based on this method a technique has been introduced to filter temporal sequences (e.g. aftershocks). Finally, a test has been developed for comparing different earthquake occurrence models. It has been found that the adaptive kernel estimation with temporal sequence filtering gives the best joint fit between the earthquake catalogue and the earthquake occurrence model, and between two earthquake occurrence models obtained from data from two independent time intervals. For the development of a geological earthquake occurrence model based on fault information, earthquake source relationships (i.e. rupture length versus rupture width scaling) have been revised. It has been found that large dip-slip and strike-slip earthquakes scale differently. Using these source relationships a dynamic stochastic fault model has been introduced. Whereas earthquake hazard studies often do not allow individual fault segments to produce compound ruptures, this model allows the linking of fault segments by chance. The moment release of simulated fault ruptures has been compared with the theoretical deformation along the plate boundary. When comparing the seismological and the geological earthquake occurrence model, it has been found that a 'good' occurrence model for large dip-slip earthquakes is given by the seismological occurrence model using the Gutenberg-Richter magnitude frequency distribution. In contrast, regions dominated by long strike-slip faults produce large earthquakes but not many small earthquakes and the occurrence of earthquakes on such faults should be inferred from the dynamic fault model.</p>

Existing and Emerging Students’ Alternative Ideas on Geodynamic Phenomena: Development, Controlling Factors, Characteristics

This paper studies Greek junior high school students’ alternative ideas, both initial and synthetic, on geodynamic phenomena. It comments in detail on students’ concepts on Earth structure, earthquake occurrence, volcano formation, and relief change. Additionally, it attempts to trace and interpret how and why these ideas form (concept development), presenting that initial and synthetic ones are indissolubly attached and utterly directed by environmental interaction. Data analysis verifies that curriculum inadequacy and false scientific terminology in textbooks enforce the generation of alternative ideas. New synthetic alternative ideas on geodynamic phenomena are presented which are mainly characterized by intermittent and fragmentary perspective. Furthermore, the characteristics of both initial and synthetic alternative ideas are outlined, giving emphasis on the facts that students represent geodynamic phenomena as instantaneous events and that they are able to describe the repeatability of the phenomena, but they show difficulty in capturing their continuity. Finally, more factors that control alternative idea development on geodynamic phenomena are highlighted—such as (i) lack of continuous thinking, (ii) distribution, intensity and frequency of geodynamic phenomena, and (iii) current affairs (i.e., pollution, technology evolution, human intervention)—hoping that their revelation will lead to alternative ideas’ decomposition and thus to pure scientific knowledge.

A Safe Zone SMOTE Oversampling Algorithm Used in Earthquake Prediction Based on Extreme Imbalanced Precursor Data

Earthquake prediction based on extreme imbalanced precursor data is a challenging task for standard algorithms. Since even if an area is in an earthquake-prone zone, the proportion of days with earthquakes per year is still a minority. The general method is to generate more artificial data for the minority class that is the earthquake occurrence data. But the most popular oversampling methods generate synthetic samples along line segments that join minority class instances, which is not suitable for earthquake precursor data. In this paper, we propose a Safe Zone Synthetic Minority Oversampling Technique (SZ-SMOTE) oversampling method as an enhancement of the SMOTE data generation mechanism. SZ-SMOTE generates synthetic samples with a concentration mechanism in the hyper-sphere area around each selected minority instances. The performance of SZ-SMOTE is compared against no oversampling, SMOTE and its popular modifications adaptive synthetic sampling (ADASYN) and borderline SMOTE (B-SMOTE) on six different classifiers. The experiment results show that the quality of earthquake prediction using SZ-SMOTE as oversampling algorithm significantly outperforms that of using the other oversampling algorithms.

Application of fuzzy modelling to predict the earthquake damage degree of buildings based on field data

Prediction of structural damage prior to earthquake occurrence provides an early warning for stakeholders of building such as owners and urban managers and can lead to necessary decisions for retrofitting of structures before a disaster occurs, legislating urban provisions of execution of building particularly in earthquake prone areas and also management of critical situations and managing of relief and rescue. For proper prediction, an effective model should be produced according to field data that can predict damage degree of local buildings. In this paper in accordance with field data and Fuzzy logic, damage degree of building is evaluated. Effective parameters of this model as an input data of model consist of height and age of the building, shear wave velocity of soil, plan equivalent moment of inertia, fault distance, earthquake acceleration, the number of residents, the width of the street for 527 buildings in the city. The output parameter of the model, which was the damage degree of the buildings, was also classified as five groups of no damage, slight damage, moderate damage, extensive damage, and complete damage. The ranges of input and output classification were obtained based on the supervised center classification (SCC-FCM) method in accordance with field data.