Unified Scaling Law For Earthquakes Research Articles

Green’s Function, Earthquakes, and a Fast Ambient Noise Tomography Methodology

Green’s function plays an important role in the relationship of a future strong earthquake epicenter to the average earthquake potential score. In the frame of the latter, the fractal dimension of the unified scaling law for earthquakes naturally arises. Here it is also shown to be a cornerstone for the development of a new ambient noise tomography methodology, which is applied for example to the west coast of Central Greece. In particular, we show that a fast and reliable 3D shear velocity model extraction is possible without the need for a large amount of data, great-circle propagation assumptions, or the intermediate step of inverting for group velocity maps. The tomography results are consistent with previous studies conducted in the neighboring region.

Regional seismic risk assessment based on the Unified Scaling Law for Earthquakes: The Lake Baikal railway system

Seismic hazard assessment (SHA) and evaluation of seismic risk (SR) require an adequate understanding of the actual distribution of earthquakes over magnitude, space, and time ranges. Neo-deterministic seismic hazard assessment (NDSHA) methodologies have been developed to improve the reliability and accuracy of reproducible seismic hazard maps. In the last decade, the application of NDSHA in many regions of the world has confirmed the availability of reliable and effective input for mitigating object-oriented earthquake risks NDSHA results have passed intensive testing by historical evidence and realistic modelling of scenario earthquakes. We used two NDSHA tools – (i) Unified Scaling Law for Earthquakes (USLE) and (ii) anisotropic propagation of the seismic effect – to evaluate SR for the Lake Baikal regional railroad system represented by Open Street Map (OSM) data of tracks, bridges and tunnels on the basis of seismic hazard maps of maximum macroseismic intensity expected in 50 years with 10%, 5%, and 1% probability of exceedance. We compare the achieved USLE−based results with the SR evaluations based on the General Seismic Zonation 2016 maps at identical levels of probability of exceedance.

Seismic risk assessment for the infrastructure in the regions adjacent to the Russian Federation Baikal–Amur Mainline based on the Unified Scaling Law for Earthquakes

The purpose of the analysis is to assess the risk of loss in performance of infrastructure facilities in the regions adjacent to the Russian Federation Baikal–Amur and Trans-Siberian Mainlines due to seismic events of maximum macroseismic intensity expected in a period of 50 years with a probability of 10%, 5% and 1%. In particular, we use earthquake data compiled at the Baikal Division of the Russian Geophysical Survey, which provides sufficiently complete earthquake determinations of M = 2.5 or larger events for the period 1994–2019 for a reliable mapping the Unified Scaling Law for Earthquakes coefficients at the seismically active cells of a regular grid. Based on these estimates, we present maps of the maximum expected magnitude in about 500, 1000 and 5000 years. Having described an anisotropic seismic effect model of seismic sites in the region, we conclude by characterizing the seismic hazard in traditional terms of macroseismic intensity and by estimating the associated seismic risk to selected infrastructures, i.e. Baikal–Amur Mainline and Trans-Siberian Railway.

Displacements Before and After Great Earthquakes: Geodetic and Seismic Viewpoints

Analysis of geodetic data obtained by the global positioning system (GPS) leads to better understanding of earthquake origins and helps to interpret their sequences. For this, we cross-compare the pre- and postseismic displacements associated with great earthquakes and derived from GPS observations and seismic catalogs. In a pilot study of the 2004 Sumatra–Andaman Mw9.2 earthquake in the Indian Ocean, the 2011 Tohoku Mw9.1 earthquake in Japan, the 2010 offshore Maule Mw8.8 and the 2015 Illapel Mw8.3 earthquakes in Chile, the 2018 Kodiak Mw7.9 earthquake in the Gulf of Alaska, and the 2016 Kaikoura Mw7.8 earthquake in New Zealand, we consider GPS data from stations of the Global Navigation Satellite System (GNSS) along with integral characteristics of the regional seismic regime, including the accumulated displacement derived from the catalogs of earthquake hypocenter parameters. We did not find any prominent transient pattern in the daily geodetic measurements registered before the six great earthquakes at the nearest GNSS stations. We found that (a) the six cases exhibit different GPS versus seismic displacement correlation patterns before and after the great earthquakes, (b) the observed high variability of the correlation between geodetic ρ(t) and seismic ∑(t) integrals appears indicative of a partial contribution of earthquakes to naturally haphazard sporadic movement of lithospheric blocks of different size, and (c) GPS data confirm the existence of intermittent long periods of regionally stable levels of seismic regime reflected in the control parameter of the Unified Scaling Law for Earthquakes that may change as a result of mid- or even short-term bursts of activity associated with catastrophic events.

Unified Scaling Law for Earthquakes: Space-Time Dependent Assessment in Friuli-Venezia Giulia Region

The concept of the Unified Scaling Law for Earthquakes (USLE), which generalizes the Gutenberg-Richter relationship making use of the fractal distribution of earthquake sources in a seismic region, is applied to seismicity in the Friuli-Venezia Giulia region, FVG (Northeastern Italy) and its surroundings. In particular, the temporal variations of USLE coefficients are investigated, with the aim to get new insights in the evolving dynamics of seismicity within different tectonic domains of FVG. To this purpose, we consider all magnitude 2.0 or larger earthquakes that occurred in 1995–2019, as reported in the catalog compiled at the National Institute of Oceanography and Applied Geophysics (OGS catalog), within the territory of its homogeneous completeness. The observed variability of seismic dynamics for three sub-regions of the territory under investigation, delimited based on main geological and tectonic features, is characterized in terms of several moving averages, including: the inter-event time,τ; the cumulative Benioff strain release, Ʃ; the USLE coefficients estimated for moving six-years time intervals, and the USLE control parameter,η. We found that: 1) the USLE coefficients in FVG region are time-dependent and show up correlated; 2) the dynamical changes ofτ, Ʃ, andηin the three sub-regions highlight a number of different seismic regimes; 3) seismic dynamics, prior and after the occurrence of the 1998 and 2004 Kobarid (Slovenia) strong main shocks, is characterized by different parameters in the related sub-region. The results obtained for the FVG region confirm similar analysis performed on a global scale, in advance and after the largest earthquakes worldwide. Moreover, our analysis highlights the spatially heterogeneous and non-stationary features of seismicity in the investigated territory, thus suggesting the opportunity of resorting to time-dependent estimates for improving local seismic hazard assessment. The applied methods and obtained parameters provide quantitative basis for developing suitable models and forecasting tools, toward a better characterization of future seismic hazard in the region.

Characterizing the Foreshock, Main Shock, and Aftershock Sequences of the Recent Major Earthquakes in Southern Alaska, 2016–2018

For each of three major M ≥ 7.0 earthquakes (i.e., the January 24, 2016, M7.1 earthquake 86 km E of Old Iliamna; the January 23, 2018, M7.9 earthquake 280 km SE of Kodiak; and the November 30, 2018, M7.1 earthquake 14 km NNW of Anchorage, Alaska), the study considers characterization of the foreshock and aftershock sequences in terms of their variations and scaling properties, including the behavior of the control parameterηof the unified scaling law for earthquakes (USLE), along with a detailed analysis of the surface wave records for reconstruction of the source in the approximation of the second moments of the stress glut tensor to obtain integral estimation of its length, orientation, and development over time. The three major earthquakes at 600 km around Anchorage are, in fact, very different due to apparent complexity of earthquake flow dynamics in the orogenic corner of the Pacific and North America plate boundary. The USLE generalizes the classic Gutenberg-Richter relationship taking into account the self-similar scaling of the empirical distribution of earthquake epicenters. The study confirms the existence of the long-term periods of regional stability of the USLE control parameter that are interrupted by mid- or even short-term bursts of activity associated with major catastrophic events.

The Unified Scaling Law for Earthquakes

This paper is a review of a long-continued research by many Russian and foreign scientists in the theory of self-organized criticality (SOC) in application to seismological data. We mean the Unified Scaling Law for Earthquakes (USLE). This law uses the spatial similarity of earthquake epicenters to derive a generalization of the classical Gutenberg–Richter relation. We discuss why this generalization is needed for practical problems that involve space–time parameters of seismicity, and we point out possible restrictions on practical applications. Several different methods are set forth for estimating the constants in USLE with examples of their practical use.

Unified Scaling Law for Earthquakes as Applied to Assessment of Seismic Hazard and Associate Risks

The distribution of the number of seismic events by magnitudes—the Gutenberg–Richter frequency–magnitude relation—is of paramount importance for seismic hazard assessment of a territory. The generalization of the Gutenberg–Richter relation—the Unified Scaling Law for Earthquakes (USLE) proposed in 1988 makes it possible to take into account the pattern of epicentral distribution of seismic events when changing the spatial scale of the analysis. This is extremely important for adequate downscaling of the frequency of occurrence into a smaller area within the territory under study (e.g., in the megalopolis). In 2002, Per Buck suggested a dual formulation of USLE where, instead of the number of earthquakes over a certain period of time, the reciprocal of their frequency of occurrence—the time between seismic events—is used. The same year, the Institute of Earthquake Prediction Theory and Mathematical Geophysics of the Russian Academy of Sciences developed a modified algorithm for robust estimation of USLE parameters referred to as Scaling Coefficients Estimation (SCE) for producing seismic hazard maps of territories prone to seismic effects. This brief review is focused on the use of the USLE approach to the assessment of seismic hazard and associated risk.

Распознавание образов в задачах оценки сейсмической опасности

Статья посвящена некоторым аспектам применения алгоритмов распознавания образов при решении задач определения мест возможного возникновения сильных землетрясений, что может быть использовано для оценки сейсмической опасности. Приведены основные принципы имеющего многолетнюю историю подхода к распознаванию мест сильных землетрясений (РМСЗ) рассматриваемого региона на базе схемы его морфоструктурного районирования с применением алгоритмов «Кора-3» и «Хемминг». Дан обзор полученных в этом направлении результатов и работ по разработке новых алгоритмов, основанных, в частности, на дискретном математическом анализе. Отмечено использование подходов распознавания образов для создания алгоритмов среднесрочного прогноза землетрясений, с помощью которых может быть получена оперативная оценка сейсмической опасности. Рассмотрено применение Общего закона подобия для землетрясений для оценки сейсмической опасности и рисков с учетом результатов РМСЗ. Приведен обзор результатов РМСЗ и оценки сейсмической опасности и рисков для региона Кавказа.

Aftershock Sequences of the Recent Major Earthquakes in New Zealand

The three clusters of the epicenters of the nine recent (1993–2018) earthquakes of magnitude 7.0 or larger in New Zealand are located in three different tectonic environments of the Australia–Pacific Plate boundary, including the southern part of the Kermadec Trench (showing rapid westward subduction), the oblique collision zone between the Pacific Plate and Indo-Australian Plate with the dominant Alpine Fault (showing right-lateral strike-slip movement), and the Puysegur Trench (showing eastward oblique subduction). From the viewpoint of the unified scaling law for earthquakes (USLE), these regions are characterized by different levels of seismic rate (A), earthquake magnitude exponent (B), and fractal dimension of epicenter loci (C). The recent major earthquakes exemplify different scenarios of aftershock sequences in terms of either the dynamics of interevent time (τ) or the USLE control parameter (η = τ × 10B×(5−M) × LC), where τ is the time interval between two successive earthquakes, M is the magnitude of the second one, and L is the distance between them. We find the existence, in the long term, of different, intermittent levels of rather steady seismic activity characterized by near-constant values of mean η (〈η〉), which, in the mid-term, switch between one another at times of critical transitions, including those associated with all but one magnitude 7.0 or larger earthquake. At such a transition, seismic activity may follow different scenarios with interevent time scaling of different kinds. Evidently, although these results based on analysis of an individual series do not support the presence of universality in seismic energy release, they provide constraints on modeling realistic seismic sequences for earthquake physicists and supply decision-makers with information for improving local seismic hazard assessments.

Earthquake hazard and risk assessment based on unified scaling law for earthquakes: Altai–Sayan Region

We apply the general concept of seismic risk analysis based on morphostructural analysis of the territory, pattern recognition of earthquake-prone nodes, and the Unified Scaling Law for Earthquakes, USLE, in another seismic region of Russia to the west from Lake Baikal, i.e., Altai–Sayan Region. The USLE generalizes the empirical Gutenberg–Richter relationship making use of apparently fractal distribution of earthquake sources of different size: $$ \log_{10} N\left( {M,L} \right)\, = \,A\, + \,B \cdot \left( {5\, - \,M} \right)\, + \,C \cdot \log_{10} L, $$ where N (M, L) is the expected annual number of earthquakes of a certain magnitude M within an seismically prone area of linear dimension L. The local estimates of A, B, and C allow determination of the expected maximum credible magnitude in a given time interval and the associated spread around ground shaking parameters (e.g., peak ground acceleration, PGA, or macroseismic intensity, I0). Compilation of the corresponding seismic hazard map of Altai–Sayan Region and its rigorous testing against the available seismic evidences in the past is used to model regional maps of specific earthquake risks for population, cities, and infrastructures.

Earthquake hazard and risk assessment based on Unified Scaling Law for Earthquakes: Greater Caucasus and Crimea

We continue applying the general concept of seismic risk analysis in a number of seismic regions worldwide by constructing regional seismic hazard maps based on morphostructural analysis, pattern recognition, and the Unified Scaling Law for Earthquakes (USLE), which generalizes the Gutenberg-Richter relationship making use of naturally fractal distribution of earthquake sources of different size in a seismic region. The USLE stands for an empirical relationship log10N(M, L) = A + B·(5 – M) + C·log10L, where N(M, L) is the expected annual number of earthquakes of a certain magnitude M within a seismically prone area of linear dimension L. We use parameters A, B, and C of USLE to estimate, first, the expected maximum magnitude in a time interval at seismically prone nodes of the morphostructural scheme of the region under study, then map the corresponding expected ground shaking parameters (e.g., peak ground acceleration, PGA, or macro-seismic intensity). After a rigorous verification against the available seismic evidences in the past (usually, the observed instrumental PGA or the historically reported macro-seismic intensity), such a seismic hazard map is used to generate maps of specific earthquake risks for population, cities, and infrastructures (e.g., those based on census of population, buildings inventory). The methodology of seismic hazard and risk assessment is illustrated by application to the territory of Greater Caucasus and Crimea.

Seismic hazard and risk assessment based on Unified Scaling Law for Earthquakes: thirteen principal urban agglomerations of India

The deterministic seismic hazard map of India with spatially distributed peak ground acceleration was used to estimate seismic risk using two data sets of the Indian population—the model population data set and the data set based on India’s Census 2011. Four series of the earthquake risk maps of the region based on these two population density sets were cross-compared. The discrepancy of the population data and seismic risks estimation were illuminated for the thirteen principal urban agglomerations of India. The confirmed fractal nature of earthquakes and their distribution in space implies that traditional probabilistic estimations of seismic hazard and risks of cities and urban agglomerations are usually underestimated. The evident patterns of distributed seismic activity follow the Unified Scaling Law for Earthquakes, USLE, which generalizes Gutenberg–Richter recurrence relation. The results of the systematic global analysis imply that the occurrence of earthquakes in a region is characterized with USLE: log10N (M, L) = A + B × (5 − M) + C × log10L, where N(M, L)—expected annual number of earthquakes of magnitude M within an area of liner size L, A determines seismic static rate, B—balance between magnitude ranges, and C—fractal dimension of seismic loci. We apply the seismic hazard and risk assessment methodology developed recently based on USLE, pattern recognition of earthquake-prone geomorphic nodes, and neo-deterministic scenarios of destructive ground shaking. Objects of risk are individuals (1) as reported in the 2011 National Census data and (2) as predicted for 2010 by Gridded Population of the World (model GPWv3); vulnerability depends nonlinearly on population density. The resulting maps of seismic hazard and different risk estimates based on population density are cross-compared. To avoid misleading interpretations, we emphasize that risk estimates presented here for academic purposes only. In the matter of fact, they confirm that estimations addressing more realistic and practical kinds of seismic risks should involve experts in distribution of objects of risk of different vulnerability, i.e., specialists in earthquake engineering, social sciences, and economics.

Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure.To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances.Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study region. The territorial heterogeneity of earthquakes clustering is in good agreement with spatial variability of scaling parameters identified by the USLE. In particular, the fractal dimension is higher to the west (about 1.2–1.4), suggesting a spatially more distributed seismicity, compared to the eastern parte of the investigated territory, where fractal dimension is very low (about 0.8–1.0).

Characterizing Aftershock Sequences of the Recent Strong Earthquakes in Central Italy

The recent strong earthquakes in Central Italy allow for a comparative analysis of their aftershocks from the viewpoint of the Unified Scaling Law for Earthquakes, USLE, which generalizes the Gutenberg–Richter relationship making use of naturally fractal distribution of earthquake sources of different size in a seismic region. In particular, we consider aftershocks as a sequence of avalanches in self-organized system of blocks-and-faults of the Earth lithosphere, each aftershock series characterized with the distribution of the USLE control parameter, η. We found the existence, in a long-term, of different, intermittent levels of rather steady seismic activity characterized with a near constant value of η, which switch, in mid-term, at times of transition associated with catastrophic events. On such a transition, seismic activity may follow different scenarios with inter-event time scaling of different kind, including constant, logarithmic, power law, exponential rise/decay or a mixture of those as observed in the case of the ongoing one associated with the three strong earthquakes in 2016. Evidently, our results do not support the presence of universality of seismic energy release, while providing constraints on modelling seismic sequences for earthquake physicists and supplying decision makers with information for improving local seismic hazard assessments.

Earthquake Hazard and Risk Assessment Based on Unified Scaling Law for Earthquakes: State of Gujarat, India

The Gujarat state of India is one of the most seismically active intercontinental regions of the world. Historically, it has experienced many damaging earthquakes including the devastating 1819 Rann of Kachchh and 2001 Bhuj earthquakes. The effect of the later one is grossly underestimated by the Global Seismic Hazard Assessment Program (GSHAP). To assess a more adequate earthquake hazard for the state of Gujarat, we apply Unified Scaling Law for Earthquakes (USLE), which generalizes the Gutenberg–Richter recurrence relation taking into account naturally fractal distribution of earthquake loci. USLE has evident implications since any estimate of seismic hazard depends on the size of the territory considered and, therefore, may differ dramatically from the actual one when scaled down to the proportion of the area of interest (e.g. of a city) from the enveloping area of investigation. We cross-compare the seismic hazard maps compiled for the same standard regular grid 0.2° × 0.2° (1) in terms of design ground acceleration based on the neo-deterministic approach, (2) in terms of probabilistic exceedance of peak ground acceleration by GSHAP, and (3) the one resulted from the USLE application. Finally, we present the maps of seismic risks for the state of Gujarat integrating the obtained seismic hazard, population density based on India’s Census 2011 data, and a few model assumptions of vulnerability.

Unified scaling law for earthquakes in Crimea and Northern Caucasus

This study continues detailed investigations on the construction of regional charts of the parameters of the generalized Guttenberg–Richter Law, which takes into account the properties of the spatiotemporal seismic energy scaling. We analyzed the parameters of the law in the vicinity of the intersections of morphostructural lineaments in Crimea and Greater Caucasus. It was shown that ignoring the fractal character of the spatial distribution of earthquakes in the southern part of the Russian Federation can lead to significant underestimation of the seismic hazard in the largest cities of the region.

Seismic hazard and seismic risk assessment based on the unified scaling law for earthquakes: Himalayas and adjacent regions

For the Himalayas and neighboring regions, the maps of seismic hazard and seismic risk are constructed with the use of the estimates for the parameters of the unified scaling law for earthquakes (USLE), in which the Gutenberg-Richter law for magnitude distribution of seismic events within a given area is applied in the modified version with allowance for linear dimensions of the area, namely, logN(M, L) = A + B (5 − M) + C logL, where N(M, L) is the expected annual number of the earthquakes with magnitude M in the area with linear dimension L. The spatial variations in the parameters A, B, and C for the Himalayas and adjacent regions are studied on two time intervals from 1965 to 2011 and from 1980 to 2011. The difference in A, B, and C between these two time intervals indicates that seismic activity experiences significant variations on a scale of a few decades. With a global consideration of the seismic belts of the Earth overall, the estimates of coefficient A, which determines the logarithm of the annual average frequency of the earthquakes with a magnitude of 5.0 and higher in the zone with a linear dimension of 1 degree of the Earth’s meridian, differ by a factor of 30 and more and mainly fall in the interval from −1.1 to 0.5. The values of coefficient B, which describes the balance between the number of earthquakes with different magnitudes, gravitate to 0.9 and range from less than 0.6 to 1.1 and higher. The values of coefficient C, which estimates the fractal dimension of the local distribution of epicenters, vary from 0.5 to 1.4 and higher. In the Himalayas and neighboring regions, the USLE coefficients mainly fall in the intervals of −1.1 to 0.3 for A, 0.8 to 1.3 for B, and 1.0 to 1.4 for C. The calculations of the local value of the expected peak ground acceleration (PGA) from the maximal expected magnitude provided the necessary basis for mapping the seismic hazards in the studied region. When doing this, we used the local estimates of the magnitudes which, according to USLE, corresponded to the probability of exceedance 1% and 10% during 50 years or, if the reliable estimate is absent, the maximal magnitudes reported during the instrumental period. As a result, the seismic hazard maps for the Himalayas and the adjacent regions in terms of standard seismic zoning were constructed. Based on these calculations, in order to exemplify the method, we present a series of seismic risk maps taking into account the population density prone to seismic hazard and the dependence of the risk on the vulnerability as a function of population density.

Seismic hazard and risk assessment based on the unified scaling law for earthquakes

The Unified Scaling Law for Earthquakes (USLE), that generalizes the Gutenberg–Richter recurrence relation, has evident implications since any estimate of seismic hazard depends on the size of territory that is used for investigation, averaging, and extrapolation into the future. Therefore, the hazard may differ dramatically when scaled down to the proportion of the area of interest (e.g. a city) from the enveloping area of investigation. In fact, given the observed patterns of distributed seismic activity the results of multi-scale analysis embedded in USLE approach demonstrate that traditional estimations of seismic hazard and risks for cities and urban agglomerations are usually underestimated. Moreover, the USLE approach provides a significant improvement when compared to the results of probabilistic seismic hazard analysis, e.g. the maps resulted from the Global Seismic Hazard Assessment Project (GSHAP). In this paper, we apply the USLE approach to evaluating seismic hazard and risks to population of the three territories of different size representing a sub-continental and two different regional scales of analysis, i.e. the Himalayas and surroundings, Lake Baikal, and Central China regions.

Estimation of seismic hazard and risks for the Himalayas and surrounding regions based on Unified Scaling Law for Earthquakes

To estimate seismic hazard, the basic law of seismicity, the Gutenberg–Richter recurrence relation, is applied in a modified form involving a spatial term: $$\log N\left( {M,\;L} \right) = A - B\left( {M - 5} \right) + C\log L$$ , where N(M,L) is the expected annual number of earthquakes of a certain magnitude M within an area of linear size L. The parameters A, B, and C of this Unified Scaling Law for Earthquakes (USLE) in the Himalayas and surrounding regions have been studied on the basis of a variable space and time-scale approach. The observed temporal variability of the A, B, and C coefficients indicates significant changes of seismic activity at the time scales of a few decades. At global scale, the value of A ranges mainly between −1.0 and 0.5, which determines the average rate of earthquakes that accordingly differs by a factor of 30 or more. The value of B concentrates about 0.9 ranging from under 0.6 to above 1.1, while the fractal dimension of the local seismic prone setting, C, changes from 0.5 to 1.4 and larger. For Himalayan region, the values of A, B, and C have been estimated mainly ranging from −1.6 to −1.0, from 0.8 to 1.3, and from 1.0 to 1.4, respectively. We have used the deterministic approach to map the local value of the expected peak ground acceleration (PGA) from the USLE estimated maximum magnitude or, if reliable estimation was not possible, from the observed maximum magnitude during 1900–2012. In result, the seismic hazard map of the Himalayas with spatially distributed PGA was prepared. Further, an attempt is made to generate a series of the earthquake risk maps of the region based on the population density exposed to the seismic hazard.