Browse
Submit Data
Databases
API
Help

Dataset Information

22 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Forecasting the magnitude of the largest expected earthquake.

ABSTRACT: The majority of earthquakes occur unexpectedly and can trigger subsequent sequences of events that can culminate in more powerful earthquakes. This self-exciting nature of seismicity generates complex clustering of earthquakes in space and time. Therefore, the problem of constraining the magnitude of the largest expected earthquake during a future time interval is of critical importance in mitigating earthquake hazard. We address this problem by developing a methodology to compute the probabilities for such extreme earthquakes to be above certain magnitudes. We combine the Bayesian methods with the extreme value theory and assume that the occurrence of earthquakes can be described by the Epidemic Type Aftershock Sequence process. We analyze in detail the application of this methodology to the 2016 Kumamoto, Japan, earthquake sequence. We are able to estimate retrospectively the probabilities of having large subsequent earthquakes during several stages of the evolution of this sequence.

SUBMITTER: Shcherbakov R

PROVIDER: S-EPMC6731311 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Forecasting the magnitude of the largest expected earthquake.

Shcherbakov Robert R Zhuang Jiancang J Zöller Gert G Ogata Yosihiko Y

Nature communications 20190906 1

The majority of earthquakes occur unexpectedly and can trigger subsequent sequences of events that can culminate in more powerful earthquakes. This self-exciting nature of seismicity generates complex clustering of earthquakes in space and time. Therefore, the problem of constraining the magnitude of the largest expected earthquake during a future time interval is of critical importance in mitigating earthquake hazard. We address this problem by developing a methodology to compute the probabilit ...[more]

PMID: 31492839

Similar Datasets

The largest prospective warfarin-treated cohort supports genetic forecasting.

Project description:Genetic variants of cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase (VKORC1) are known to influence warfarin dose, but the effect of other genes has not been fully elucidated. We genotyped 183 polymorphisms in 29 candidate genes in 1496 Swedish patients starting warfarin treatment, and tested for association with response. CYP2C9*2 and *3 explained 12% (P = 6.63 x 10(-34)) of the variation in warfarin dose, while a single VKORC1 SNP explained 30% (P = 9.82 x 10(-100)). No SNP outside the CYP2C gene cluster and VKORC1 regions was significantly associated with dose after correction for multiple testing. During initiation of therapy, homozygosity for CYP2C9 and VKORC1 variant alleles increased the risk of over-anticoagulation, hazard ratios 21.84 (95% CI 9.46; 50.42) and 4.56 (95% CI 2.85; 7.30), respectively. One of 8 patients with CYP2C9*3/*3 (12.5%) experienced severe bleeding during the first month compared with 0.27% of other patients (P = .066). A multiple regression model using the predictors CYP2C9, VKORC1, age, sex, and druginteractions explained 59% of the variance in warfarin dose, and 53% in an independent sample of 181 Swedish individuals. In conclusion, CYP2C9 and VKORC1 significantly influenced warfarin dose and predicted individuals predisposed to unstable anticoagulation. Our results strongly support that initiation of warfarin guided by pharmacogenetics would improve clinical outcome.

| S-EPMC2630264 | biostudies-literature

Physics-based forecasting of man-made earthquake hazards in Oklahoma and Kansas.

Project description:Reinjection of saltwater, co-produced with oil, triggered thousands of widely felt and several damaging earthquakes in Oklahoma and Kansas. The future seismic hazard remains uncertain. Here, we present a new methodology to forecast the probability of damaging induced earthquakes in space and time. In our hybrid physical-statistical model, seismicity is driven by the rate of injection-induced pressure increases at any given location and spatial variations in the number and stress state of preexisting basement faults affected by the pressure increase. If current injection practices continue, earthquake hazards are expected to decrease slowly. Approximately 190, 130 and 100 widely felt M???3 earthquakes are anticipated in 2018, 2019 and 2020, respectively, with corresponding probabilities of potentially damaging M???5 earthquakes of 32, 24 and 19%. We identify areas where produced-water injection is more likely to cause seismicity. Our methodology can be used to evaluate future injection scenarios intended to mitigate seismic hazards.

| S-EPMC6158231 | biostudies-literature

Forecasting of the first hour aftershocks by means of the perceived magnitude.

Project description:The majority of strong earthquakes takes place a few hours after a mainshock, promoting the interest for a real time post-seismic forecasting, which is, however, very inefficient because of the incompleteness of available catalogs. Here we present a novel method that uses, as only information, the ground velocity recorded during the first 30?min after the mainshock and does not require that signals are transferred and elaborated by operational units. The method considers the logarithm of the mainshock ground velocity, its peak value defined as the perceived magnitude and the subsequent temporal decay. We conduct a forecast test on the nine M ???6 mainshocks that have occurred since 2013 in the Aegean area. We are able to forecast the number of aftershocks recorded during the first 3 days after each mainshock with an accuracy smaller than 18% in all cases but one with an accuracy of 36%.

| S-EPMC6609666 | biostudies-literature

Complexity-based approach for El Nino magnitude forecasting before the spring predictability barrier.

Project description:The El Niño Southern Oscillation (ENSO) is one of the most prominent interannual climate phenomena. Early and reliable ENSO forecasting remains a crucial goal, due to its serious implications for economy, society, and ecosystem. Despite the development of various dynamical and statistical prediction models in the recent decades, the "spring predictability barrier" remains a great challenge for long-lead-time (over 6 mo) forecasting. To overcome this barrier, here we develop an analysis tool, System Sample Entropy (SysSampEn), to measure the complexity (disorder) of the system composed of temperature anomaly time series in the Niño 3.4 region. When applying this tool to several near-surface air temperature and sea surface temperature datasets, we find that in all datasets a strong positive correlation exists between the magnitude of El Niño and the previous calendar year's SysSampEn (complexity). We show that this correlation allows us to forecast the magnitude of an El Niño with a prediction horizon of 1 y and high accuracy (i.e., root-mean-square error = 0.23° C for the average of the individual datasets forecasts). For the 2018 El Niño event, our method forecasted a weak El Niño with a magnitude of 1.11±0.23° C. Our framework presented here not only facilitates long-term forecasting of the El Niño magnitude but can potentially also be used as a measure for the complexity of other natural or engineering complex systems.

| S-EPMC6955339 | biostudies-literature

Predicting the Maximum Earthquake Magnitude from Seismic Data in Israel and Its Neighboring Countries.

Project description:This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluated on a catalog of 9,042 earthquake events, which took place between 01/01/1983 and 31/12/2010 in the area of Israel and its neighboring countries. The data was obtained from the Geophysical Institute of Israel. Each earthquake record in the catalog is associated with one of 33 seismic regions. The data was cleaned by removing foreshocks and aftershocks. In our study, we have focused on ten most active regions, which account for more than 80% of the total number of earthquakes in the area. The goal is to predict whether the maximum earthquake magnitude in the following year will exceed the median of maximum yearly magnitudes in the same region. Since the analyzed catalog includes only 28 years of complete data, the last five annual records of each region (referring to the years 2006-2010) are kept for testing while using the previous annual records for training. The predictive features are based on the Gutenberg-Richter Ratio as well as on some new seismic indicators based on the moving averages of the number of earthquakes in each area. The new predictive features prove to be much more useful than the indicators traditionally used in the earthquake prediction literature. The most accurate result (AUC = 0.698) is reached by the Multi-Objective Info-Fuzzy Network (M-IFN) algorithm, which takes into account the association between two target variables: the number of earthquakes and the maximum earthquake magnitude during the same year.

| S-EPMC4727930 | biostudies-literature

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

Project description: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 ([Formula: see text]) 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 [Formula: see text] 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 [Formula: see text]. It is to monitor the exceedance probability of an assumed [Formula: see text] in real time by monitoring the seismogenic index, a quantity that characterizes the intensity of the fluid-induced seismicity per unit injected volume.

| S-EPMC8568929 | biostudies-literature

Early magnitude estimation for the MW7.9 Wenchuan earthquake using progressively expanded P-wave time window.

Project description:More and more earthquake early warning systems (EEWS) are developed or currently being tested in many active seismic regions of the world. A well-known problem with real-time procedures is the parameter saturation, which may lead to magnitude underestimation for large earthquakes. In this paper, the method used to the MW9.0 Tohoku-Oki earthquake is explored with strong-motion records of the MW7.9, 2008 Wenchuan earthquake. We measure two early warning parameters by progressively expanding the P-wave time window (PTW) and distance range, to provide early magnitude estimates and a rapid prediction of the potential damage area. This information would have been available 40 s after the earthquake origin time and could have been refined in the successive 20 s using data from more distant stations. We show the suitability of the existing regression relationships between early warning parameters and magnitude, provided that an appropriate PTW is used for parameter estimation. The reason for the magnitude underestimation is in part a combined effect of high-pass filtering and frequency dependence of the main radiating source during the rupture process. Finally we suggest only using Pd alone for magnitude estimation because of its slight magnitude saturation compared to the τc magnitude.

| S-EPMC4209451 | biostudies-other

Unbiased logic-tree data for earthquake-induced landslide hazard maps for low-to-moderate magnitude events.

Project description:Land-use planning in regard of earthquake-triggered landslides is usually implemented by means of the production of hazard maps. The well-known Newmark rigid block methodology is the most frequent used approach for this purpose. In this method, slope stability is evaluated by the estimation of the Newmark displacement, which is used to set different categories of hazard. This methodology presents limitations due to the difficulty of incorporating the variability of the used variables. For that reason, the logic-tree approach has been used in order to incorporate the epistemic uncertainties and compute probabilistic seismic-landslide hazard maps. However, the used weights in the logic-tree are usually set for each branch based on an expert judgement or subjective criteria. This article provide data obtained from the use of logic-tree methodology; this dataset is useful for deriving the unbiased weights to use in such methodology and in moderate-to-low magnitude scenarios. The data presented here are related to the article entitled "Obtaining suitable logic-tree weights for probabilistic earthquake-induced landslide hazard analyses" (Rodríguez-Peces et al., 2020) [1].

| S-EPMC7358656 | biostudies-literature

Maternal exposure to a high-magnitude earthquake during pregnancy influences pre-reading skills in early childhood.

Project description:Exposure to an adverse prenatal environment can influence fetal development and result in long-lasting changes in the offspring. However, the association between maternal exposure to stressful events during pregnancy and the achievement of pre-reading skills in the offspring is unknown. Here we examined the association between prenatal exposure to the Chilean high-magnitude earthquake that occurred on February 27th, 2010 and the development of early reading precursors skills (listening comprehension, print knowledge, alphabet knowledge, vocabulary, and phonological awareness) in children at kindergarten age. This multilevel retrospective cohort study including 3280 children, of whom 2415 were unexposed and 865 were prenatally exposed to the earthquake shows substantial evidence that maternal exposure to an unambiguously stressful event resulted in impaired pre-reading skills and that a higher detrimental effect was observed in those children who had been exposed to the earthquake during the first trimester of gestation. In addition, females were more significantly affected by the exposure to the earthquake than their male peers in alphabet knowledge; contrarily, males were more affected than females in print knowledge skills. These findings suggest that early intervention programs for pregnant women and/or children exposed to prenatal stress may be effective strategies to overcome impaired pre-reading skills in children.

| S-EPMC8084950 | biostudies-literature

Near-surface softening and healing in eastern Honshu associated with the 2011 magnitude-9 Tohoku-Oki Earthquake.

Project description:The near-surface part of the crust, also called the skin of the earth, is the arena of human activity of which the stiffness is of great concern to engineers in infrastructure construction. The stiffness reduction of near-surface geomaterials also plays a vital role in geohazards triggering. However, the physical mechanism behind the material softening is still not fully understood. Here, we report a coseismic shear-wave velocity reduction in the near surface by up to a few tens of percent during the strongest shaking from the 11 March 2011 Tohoku-Oki Earthquake and a subsequent two-stage healing process including a rapid recovery within a few minutes and a slow recovery over many years. We also present a theoretical contact model between mineral grains in geomaterials containing multiple metastable contacts at small separations due to the oscillatory hydration interaction, which can explain the emergence of different stages in the healing process.

| S-EPMC7900222 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data