Stable Modification of Frequency–Magnitude Relation and Prospects for Its Application in Seismic Zoning

Izvestiya, Physics of the Solid Earth - A new composite model is suggested for the frequency–magnitude relation of the earthquakes. The new model statistically reasonably describes the...     

Probability estimation of rare extreme events in the case of small samples: Technique and examples of analysis of earthquake catalogs

The most general approach to studying the recurrence law in the area of the rare largest events is associated with the use of limit law theorems of the theory of extreme values. In this paper, we use the Generalized Pareto Distribution (GPD). The unknown GPD parameters are typically determined by the method of maximal likelihood (ML). However, the ML estimation is only optimal for the case of fairly large samples (>200–300), whereas in many practical important cases, there are only dozens of large events. It is shown that in the case of a small number of events, the highest accuracy in the case of using the GPD is provided by the method of quantiles (MQs). In order to illustrate the obtained methodical results, we have formed the compiled data sets characterizing the tails of the distributions for typical subduction zones, regions of intracontinental seismicity, and for the zones of midoceanic (MO) ridges. This approach paves the way for designing a new method for seismic risk assessment. Here, instead of the unstable characteristics—the uppermost possible magnitude M_max—it is recommended to use the quantiles of the distribution of random maxima for a future time interval. The results of calculating such quantiles are presented.     

Submarine Landslides on the Western Slope of the Kuril Basin,Sea of Okhotsk

Landslide processes on the western slope of the Kuril Basin were studied using bathymetry and seismic data obtained under the international KOMEX and SSGH projects. Slope areas containing landslides, landslide blocks and mass-transport deposits were distinguished. Large-scale landslides occupying an area of more than 100 km² are located in such areas of open continental margins as the slopes of the North Hokkaido Marginal Plateau and Terpeniya Ridge. Landslide blocks up to 2 km in size and mass-transport deposits are located in submarine canyons and fans in Terpeniya Bay. The age of landslides has been estimated as Middle Pleistocene–Holocene. Landslides are most likely triggered by seismic activity and gas saturation of sediments. Subsequent slope failure seems quite probable within the study area, and landslides capable of generating tsunamis may occur.     

Estimation of the probability of strongest seismic disasters based on the extreme value theory

This paper presents the review of the experience in applying the approach based on the limiting distributions of the extreme value theory (the generalized Pareto distribution, GPS, and generalized extreme value distribution, GEV) for deriving the distributions of maximal magnitudes and related ground accelerations from the earthquakes on the future time intervals of a given duration. The results of analyzing the global and regional earthquake catalogs and the ground peak accelerations during the earthquakes are described. It is shown that the magnitude of the strongest possible earthquake M _max (and analogous characteristics for other types of data), which is often used in seismic risk assessment, is potentially unstable. We suggest a stable alternative for M _max in the form of quantiles Q _q (τ) of the maximal possible earthquake, which could occur during the future time interval of length τ. The quantity of the characteristic maximal event M _c, which has been introduced in our previous publications, is another helpful robust scalar parameter. All the cases of approximation of the tails of empirical distributions, which were studied in our works, turned out to be finite (bounded); however, the rightmost point of these distributions, M _max, is often poorly detectable and unstable. Therefore, the M _max parameter has a low practical value.     

Submarine landside in the Bussol Graben: Structural and formation features

Analysis of geophysical data obtained during a study of the insular slope in the central Kuril?Kamchatka Trench during projects Kuriles-2005 and Kuriles-2006 promoted by the Presidium of the Russian Academy of Sciences revealed a large submarine landslide in this area. The landslide, located at the bottom of the transverse valley confined to the Bussol l Graben, resulted from the failure of the northeastern wall of a graben composed of sedimentary material. It exceeds 35 km³ in size, representing one of the large submarine landslides discovered to date on the slope of the Kuril?Kamchatka Trench in submarine canyonfan environments.     

Application of the Theory of Extreme Events to Problems of Approximating Probability Distributions of Water Flow Peaks

Statistically treated data of long-term observational series (>30 years) for 66 rivers are used to study the character of distribution of water flow maximums during rain-induced floods in Maritime Territory, Russia. Two probability models are discussed: generalized Pareto distribution (for the domain of very large values) and generalized distribution of extremums (for the rest of the range). The issue of optimal conjunction point of these distributions is discussed. The problem of increasing the accuracy of distribution parameter estimates through data grouping is considered.     

New Data on Seismotectonics of the Laptev Sea from Observations by Ocean Bottom Seismographs

Doklady Earth Sciences - The results of new local seismic observations in the Laptev Sea obtained using ocean bottom seismographs were compared with actual data from global and regional earthquake...     

Contourite Drifts in the Tartar Strait,Sea of Japan

Doklady Earth Sciences - Contourite drifts were first detected in the Tatar Strait in the framework of the Sakhalin Slope Gas Hydrates International Project (2012–2015). The number of...     

Statistical methods for river runoff prediction

Methods used to analyze one type of nonstationary stochastic processes—the periodically correlated process—are considered. Two methods of one-step-forward prediction of periodically correlated time series are examined. One-step-forward predictions made in accordance with an autoregression model and a model of an artificial neural network with one latent neuron layer and with an adaptation mechanism of network parameters in a moving time window were compared in terms of efficiency. The comparison showed that, in the case of prediction for one time step for time series of mean monthly water discharge, the simpler autoregression model is more efficient.Translated from Vodnye Resursy, Vol. 32, No. 2, 2005, pp. 133–145.Original Russian Text Copyright © 2005 by Pisarenko, Lyubushin, Bolgov, Rukavishnikova, Kanyu, Kanevskii, Saveleva, Demyanov, Zalyapin.