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Intensity prediction equations for Central Asia
Abstract
In this study, new intensity prediction equations are derived for Central Asia, considering about 6000 intensity data points from 66 earthquakes encompassing the surface-wave magnitude range of 4.6–8.3. The suitability of the functional form used for constructing the model is assessed by comparing its predictions with those achieved through a non-parametric model. The parametric regressions are performed considering different measures of the source-to-site distance, namely the hypocentral, epicentral and the extended distance metrics. The latter is defined as the minimum distance from the site to a line crossing the epicentres, oriented along the strike of the earthquake and having a length estimated from the event's magnitude. Although the extended distance is introduced as a preliminary attempt to improve the prediction capability of the model by considering the finiteness of the fault extension, the standard deviation of the residual distribution obtained considering the extended distance (σ= 0.734) does not show an improvement with respect to the results for the epicentral distance (σ= 0.737). The similarity of the two models in term of average residuals is also confirmed by comparing the interevent errors obtained for the two regressions, obtaining very similar values for all earthquakes but the 1911, M 8.2 Kemin event. In particular, different evidences suggest that the magnitude of this event could be overestimated by about half a magnitude unit. Regarding the variability of the residual distribution, all the three considered components (i.e. interevent, interlocation and record-to-record variances) are not negligible, although the largest contribution is related to the record-to-record variability, suggesting that both source and propagation as well as site effects not captured by the considered model influence the spatial variability of the intensity values.
... Equations that predict seismic intensity as a function of magnitude and distance (Intensity Prediction Equations, or IPEs) are useful tools for seismic hazard and risk assessments. We compare our intensity data with various IPEs derived for western North America and Central Asia (Bindi et al., 2011) (Fig. 11). The equations presented in Atkinson et al. (2014) are based on the database of USGS 'Did You Feel It' (Wald et al., 1999) MMI values from 2000 to 2013. ...
... c5 -1.77 and c6 = -0.383. The equations developed in Bindi et al. (2011) consider 6000 intensity data points from 66 earthquakes encompassing the surface-wave magnitude range of 4.6-8.3. The work of the authors follows a standard regression approach where the parameters of the considered model are determined by evaluating the best least-squares fit to the set of observed intensities. ...
... where I is intensity, M is the moment magnitude, R H is the hypocentral distance, and the determined source coefficient terms are a1 = 1.071, a2 = 1.003, a3 = 2.621, and a4 -5.567*10 -4 . We assume that the I value of Bindi et al. (2011) is comparable to an MMI. Our results are consistent with all prediction equations within 0-30 km of observed intensities for a MMI range of 5 to 10. Asperity III is the region of greatest slip (max 6.5 m) located directly within Palu basin, just south of Palu Bay, and is shown in Fang et al. (2019). ...
A devastating Mw 7.5 earthquake and tsunami struck northwestern Sulawesi, Indonesia on 28 September 2018, causing over 4000 fatalities and severe damage to several areas in and around Palu City. Severe earthquake-induced soil liquefaction and landslides claimed hundreds of lives in three villages within Palu. The mainshock occurred at 18:03 local time at a depth of 10 km on a left-lateral strike-slip fault. The hypocenter was located 70 km north of Palu City and the rupture propagated south, under Palu Bay, passing on land on the west side of Palu City. The surface rupture of the earthquake has been mapped onshore along a 30 km stretch of the Palu-Koro fault. We present results of field surveys on the effects of the earthquake, tsunami and liquefaction conducted between 1–3 and 12–19 of October 2018. Seismic intensities on the Modified Mercalli Intensity (MMI) scale are reported for 375 sites and reach a maximum value of 10. We consolidate published tsunami runup heights from several field studies and discuss three possible interrelated tsunami sources to explain the variation in observed tsunami runup heights. Due to limited instrumentation, PGA and PGV values were recorded at only one of our field sites. To compensate, we use our seismic intensities and Ground Motion to Intensity Conversion Equations (GMICEs) and Ground Motion Prediction Equations (GMPEs) developed for similar tectonic regions. Our results indicate that the maximum predicted PGAs for Palu range from 1.1 g for GMICEs to 0.6 g for GMPEs.
... Intensity prediction equation (IPE) is important to analyze the decay of macroseismic intensity with distance (Pasolini et al. 2008). Many computer codes are compatible with intensity-based risk calculation (Silva et al. 2014) (OpenQuake, HAZUS, CAPRA) and in many countries, even the building codes account for the seismic excitation in terms of macroseismic intensity (among many others, Bindi et al. 2011). In addition, the macroseismic intensity is useful in communicating with the public to inform them about the potential earthquake impact (Lagomarsino and Giovinazzi 2006) and in preparing seismic hazard map where strong motion accelerometer data is sparse . ...
... Iif we consider Dhaka's distance from these fault zones, only an event from CTFB can be felt in Dhaka within the 300-km distance. Szeliga et al.'s (2010) and Bindi et al.'s (2011) relation portrays similar characteristics compared to the previous Fig. 4. Chandler and Lam's (2002) relation shows sharp decay in attenuation (with standard deviation * 0.92). This might be due to the close proximity to the epicentral area. ...
... It can be said by observing the curves and probable values that with a decreasing magnitude the difference between the minimum values of the intensities among attenuation relations increase. For example, the relation of Bindi et al. (2011) tends to give very small intensity values at 900 km. Szeliga et al. (2010) and Bindi et al. (2011) have also been applied (Fig. 6) for Naga thrust fault and Dauki fault considering maximum estimated earthquake by Yu and Sieh (2013). ...
An effort has been made through this study to evaluate the existing intensity attenuation model (IPE) for the potential seismotectonic regimes in and around Bangladesh. To reach the goal, the seismicity of the concerned tectonic regimes has been analyzed. Apart from evaluating the appropriate intensity model, this research has also assessed the predictive performance of epicentral intensity estimation. Different magnitude types have been made uniform by converting into moment magnitude and subsequently into the Modified Mercalli Intensity scale (MMI). The epicentral intensity conversion following Li in Chinese Earthquakes (Seismological Press, Beijing, 1980) fits best for the study area among the utilized four predictive equations. The epicentral intensity conversion from the moment magnitude shows that small to moderate earthquakes get significantly overestimated. Suitable attenuation models have been applied to the different tectonic regimes based on the criteria of using the IPEs. Among all the utilized IPEs, the relation of Bakun et al. (Bull Seismol Soc Am 93:190–202, 2003) exhibits the highest standard deviation (σ = 1.61) in attenuation with distance. Although the Szeliga et al.’s (Bull Seismol Soc Am 100(2):570–584, 2010) attenuation relation has a standard deviation of 1.22, the intensity decay is little even for the greater distance (~ 800–900 km). Up to Mw 7.0, the IPE of Bindi et al. (Geophys J Int 187(1):327–337, 2011) shows realistic attenuation scenario (with σ = 1.3); however, at lower magnitude range (< Mw 7.0), the intensity starts to decay sharply. Still, the IPE of Bindi et al. (2011) is more realistic in comparison of the shakemaps of the past and in terms of convincible intensity decay with greater distance (~ 500–900 km). However, the intensity close to the epicenter gets very high MMI (XI or larger) value for the major events (Mw ≥ 8.5). Although the IPE of Chandler and Lam (J Asian Earth Sci 20(7):775–790, 2002) has distance constraints, its performance is acceptable considering the attenuation scenario with distance along with the lowest standard deviation (~ 0.92). Considering the seismic events from the only strike-slip Churachandpur Mao fault of the study area, Bakun and Wentworth (Bull Seismol Soc Am 87(6):1502–1521, 1997) relation has been applied to determine the attenuation pattern.
The article is available as 'Online First':
http://link.springer.com/article/10.1007/s00024-019-02230-3
... Contouring of individual intensities is avoided when using intensity data points (IDPs). IPEs based on IDP data have been presented, among others, by Stromeyer and Grünthal (2009) for parts of Germany, France, the Netherlands, and the Czech Republic in central Europe, Sørensen et al. (2009) for the Sea of Marmara region in Turkey, Bindi et al. (2011) for central Asia and Allen et al. (2012) for shallow active tectonic crust worldwide. Many IPEs have been presented for Italy, or parts of it, including those by Peruzza (1996), Gasperini (2001), Albarello and D'Amico (2004), Gómez (2006), Faccioli and Cauzzi (2006), Pasolini et al. (2008a, b) and Sørensen et al. (2010). ...
... Depth estimates are not always given in the existing IDP databases. A single value may be taken to represent a regional average depth (e.g., Bindi et al. 2011), or it may be determined as an additional regression parameter (e.g., Sørensen et al. 2010). Depth errors are investigated in the later sections. ...
... So-called half-intensity values (7-8 is replaced by 7.5) are sometimes used when deriving IPEs (e.g., Stromeyer and Grünthal 2009;Sørensen et al. 2010;Bindi et al. 2011), although it is understood that this practice compromises the integer character of intensity. The new classes between integer values may be less dispersed but are less reliable (Peruzza 1996), and the practice suggests that the intensity scale has 23 degrees instead of twelve (Musson 1998). ...
The present investigation focuses on the effect of input data properties on the estimation of seismic intensity prediction equation (IPE) coefficients. Emphasis is placed on small-to-moderate magnitude earthquakes. Synthetic intensity data points (IDPs) are created using a given IPE, assuming independence of azimuth. Extensive simulations are performed for single earthquakes and a synthetic database. Tests of single earthquakes show that increasing the sample size narrows the range of obtained coefficients. The larger the difference between the shortest and longest distance of IDPs from the epicentre, the narrower is this range. A short radius of perceptibility is more rapidly saturated with new data points than a long one. The synthetic database is used to examine the effect of magnitude and depth errors. The performance of synthetic data gives a model with which the real data can be compared. The attenuation coefficient appears stable against magnitude errors of ± 0.2 units, but starts to be overestimated as magnitude errors increase. Assuming an erroneous regional depth easily leads to intensity differences of 1 degree. The mean coefficient values deviate from the correct ones and tend to increase with depth. The results resemble the synthetic ones, but imply larger uncertainties. The attenuation coefficient, ν, appears to be the least sensitive coefficient to errors. Real data from seven post-1965 earthquakes in the magnitude range of 4.0–5.2 were retrieved from the intensity database of the United Kingdom.
... and PGA) as input variables. A similar approach has been used by Bindi et al. [2011] for deriving intensity prediction equations for Central Asia. ...
... Similar to Bindi et al. [2011], we model the ground motion input variable under consideration with the following relation: ...
... For each event-station pair, the lth distance bin is chosen such that rl ≤ Rrup < rl+1, and the weights are given by wl = (Rrup -rl)/(rl+1 -rl) such that the attenuation curve is linearized between the distances rl and rl+1. Finally, Gj is a site response term for station j [not included in the analysis of Bindi et al., 2011]. The above system of equations is solved using a one-step least-squares inversion approach [Oth et al., 2011b]. ...
One of the key parameters for earthquake source physics is stress drop since it can be directly linked to the spectral level of ground motion. Stress drop estimates from moment-corner frequency analysis have been shown to be extremely variable, and this to a much larger degree than expected from the between-event ground motion variability. This discrepancy raises the question whether classically determined stress drop variability is too large, which would have significant consequences for seismic hazard analysis. We use a large high-quality dataset from Japan with well-studied stress drop data to address this issue. Non-parametric and parametric reference ground motion models are derived and the relation of between-event residuals for JMA equivalent seismic intensity and peak ground acceleration with stress drop is analyzed for crustal earthquakes. We find a clear correlation of the between-event residuals with stress drops estimates; however, while the island of Kyushu is characterized by substantially larger stress drops than Honshu, the between-event residuals do not reflect this observation, leading to the appearance of two event families with different stress drops levels yet similar range of between-event residuals. Both the within-family and between-family stress drop variations are larger than expected from the ground motion between-event variability. A systematic common analysis of these parameters holds the potential to provide important constraints on the relative robustness of different groups of data in the different parameter spaces and to improve our understanding on how much of the observed source parameter variability is likely to be true source physics variability.
... The choice of an attenuation model is very important for the hazard assessment because of its great influence on the final results. A modified version of the Bindi et al. [2011] IPE for Central Asia is used in this work. This modification is made to consider depth dependency of events in the IPE. ...
... This modification is made to consider depth dependency of events in the IPE. The same dataset of Bindi et al. [2011] is used for this modification. In its mathematical form, the IPE derived in this study can be written as: (7) where the intensity I is expressed in the MSK-64 scale, R is the epicentral distance and h is the hypocentral depth. ...
... Although the results of the latest study on the region, GSHAP [Giardini 1999], who published a homogenized seismic hazard map in terms of peak ground acceleration at a 10% probability of exceedance in 50 years, have been a major step towards a cross-border approach for the entire region, the conducted PSHA, employing a rather homogeneous distribution in terms of PGA for large parts of Central Asia, might be assumed to be outdated for several reasons (Figure 20). This includes the fact that much progress has been made in the development of region-specific ground motion prediction equations [e.g., Bindi et al. 2011], the treatment of uncertainties within a PSHA has been improved, and new model ideas have been developed. Figure 20 shows the seismic hazard calculated in GSHAP project in terms of 10% probability of exceedance in 50 years, converted from pga to macroseismic intensity using the relationship of Tselentis and Danciu [2008]. ...
Central Asia is one of the seismically most active regions in the world.
Its complex seismicity due to the collision of the Eurasian and Indian
plates has resulted in some of the world’s largest intra-plate events over
history. The region is dominated by reverse faulting over strike slip and
normal faulting events. The GSHAP project (1999), aiming at a hazard
assessment on a global scale, indicated that the region of Central Asia
is characterized by peak ground accelerations for 10% probability of
exceedance in 50 years as high as 9 m/s2. In this study, carried out within
the framework of the EMCA project (Earthquake Model Central Asia),
the area source model and different kernel approaches are used for a
probabilistic seismic hazard assessment (PSHA) for Central Asia. The
seismic hazard is assessed considering shallow (depth < 50 km) seismicity
only and employs an updated (with respect to previous projects)
earthquake catalog for the region. The seismic hazard is calculated in
terms of macroseismic intensity (MSK-64), intended to be used for the
seismic risk maps of the region. The hazard maps, shown in terms of
10% probability of exceedance in 50 years, are derived by using the
OpenQuake software [Pagani et al. 2014], which is an open source software
tool developed by the GEM (Global Earthquake Model) foundation.
The maximum hazard observed in the region reaches an intensity
of around 8 in southern Tien Shan for 475 years mean return period.
The maximum hazard estimated for some of the cities in the region,
Bishkek, Dushanbe, Tashkent and Almaty, is between 7 and 8 (7-8),
8.0, 7.0 and 8.0 macroseismic Intensity, respectively, for 475 years mean
return period, using different approaches. The results of different methods
for assessing the level of seismic hazard are compared and their underlying
methodologies are discussed.
... In this study, a nonparametric approach is followed (e.g. Bindi et al. 2011;Oth et al. 2011), where the intensity values are expressed in terms of a source (α) and attenuation (β) term ...
... The models show a reasonable agreement and only the model derived considering the ISC depths shows an early saturation at short distances. In addition, Fig. 5 shows that the non-parametric models agree well with the parametric attenuation function (blue line) recently obtained for Central Asia by Bindi et al. (2011). The latter has been derived considering a catalogue of 66 earthquakes, including the calibration and validation earthquakes considered in this study and considering the magnitudes and locations according to the CASRI catalogue. ...
... To be consistent in the assumptions made in this study (e.g. assumed depth value, number of bootstrap replications, etc.), we derived an intensity prediction equation (IPE) using the data set analysed by Bindi et al. (2011) without considering the 1985 Xinjiang earthquake. It is composed of 70 earthquakes (Fig. A1) with locations and magnitudes taken from the CASRI catalogue. ...
In this study, we estimate the location and magnitude of Central Asian earthquake from macroseismic
intensity data. A set of 2373 intensity observations from 15 earthquakes is analysed
to calibrate non-parametric models for the source and attenuation with distance, the distance
being computed from the instrumental epicentres located according to the International
Seismological Centre (ISC) catalogue. In a second step, the non-parametric source model
is regressed against different magnitude values (e.g. MLH, mb, MS, Mw) as listed in various
instrumental catalogues. The reliability of the calibrated model is then assessed by applying
the methodology to macroseismic intensity data from 29 validation earthquakes for which
bothMLH and mb are available from the Central Asian Seismic Risk Initiative (CASRI) project
and the ISC catalogue. An overall agreement is found for both the location and magnitude of
these events, with the distribution of the differences between instrumental and intensity-based
magnitudes having almost a zero mean, and standard deviations equal to 0.30 and 0.44 for
mb and MLH, respectively. The largest discrepancies are observed for the location of the 1985,
MLH = 7.0 southern Xinjiang earthquake, whose location is outside the area covered by the
intensity assignments, and for the magnitude of the 1974, mb = 6.2 Markansu earthquake,
which shows a difference in magnitude greater than one unit in terms of MLH. Finally, the
relationships calibrated for the non-parametric source model are applied to assign different
magnitude-scale values to earthquakes that lack instrumental information. In particular, an
intensity-based moment magnitude is assigned to all of the validation earthquakes.
... To this aim, an intensity prediction equation (IPE) is applied to the epicentral information (magnitude and location) available through a parametric catalog. In this study we apply the equations recently derived for central Asia by Bindi et al. [8]. ...
... The set of felt intensities at each site is completed using virtual intensities [11]. To this aim, the Intensity Prediction Equation developed for Central Asia [8] using the same macroseismic catalog are applied to the seismic catalog collected within CASRI project and composed by about 8400 earthquakes with hypocentral depth less than 40 km [8]. Finally, examples of felt histories for 4 large towns in Central Asia are shown in Fig. 3, considering both observed (red) and virtual (black) intensities. ...
... The set of felt intensities at each site is completed using virtual intensities [11]. To this aim, the Intensity Prediction Equation developed for Central Asia [8] using the same macroseismic catalog are applied to the seismic catalog collected within CASRI project and composed by about 8400 earthquakes with hypocentral depth less than 40 km [8]. Finally, examples of felt histories for 4 large towns in Central Asia are shown in Fig. 3, considering both observed (red) and virtual (black) intensities. ...
In the process of updating existing PSHA maps in Central Asia, a first step is the evaluation of the seismic hazard in terms of macroseismic intensity by applying a data driven method. Following the Site Approach to Seismic Hazard Assessment (SASHA) [11], the evaluation of the probability of exceedance of any given intensity value over a fixed exposure time, is mainly based on the seismic histories available at different locations without requiring any a-priori assumption about seismic zonation. The effects of earthquakes not included in the seismic history can be accounted by propagating the epicentral information through a Intensity Prediction Equation developed for the analyzed area. In order to comply with existing building codes in the region that use macroseismic intensity instead of PGA, we evaluated the seismic hazard at 2911 localities using a macroseismic catalog composed by 5322 intensity data points relevant to 75 earthquakes in the magnitude range 4.6-8.3. The results show that for most of the investigated area the intensity having a probability of at least 10% to be exceeded in 50 years is VIII. The intensity rises to IX for some area struck by strong earthquakes in the past, like the Chou-Kemin-Chilik fault zone in northern Tien-Shan, between Kyrgyzstan and Kazakhstan, or in Gissar range between Tajikistan and Uzbekistan. These values are about one intensity unit less than those evaluated in the Global Seismic Hazard Assessment Program (GSHAP: Ulomov, The GSHAP Region 7 working group [29]). Moreover, hazard curves have been extracted for the main towns of Central Asia and the results compared with the estimates previously obtained. A good agreement has been found for Bishkek (Kyrgyzstan) and Dushanbe (Tajikistan), while a lower probability of occurrence of I=VIII has been obtained for Tashkent (Uzbekistan) and a larger one for I=IX in Almaty (Kazakhstan).
... They also derived an IPE using the intermediate depth Vrancea earthquakes which are valid for the shallow, crustal seismicity in Romania (Sorensen et al., 2010b). New intensity prediction equations developed by Bindi et al. (2011) for Central Asia, considering about 6000 intensity data points from 66 earthquakes in magnitude range of 4.6-8.3 based on the hypocentral, epicentral and the extended distance measures. ...
... Among all of models used in comparison, lower prediction of intensities value is obtained by the proposed equations of this study. Consequently, the predicted curves by the proposed models are far from those of Sorensen et al., 2009, Sorensen et al., 2010and Bindi et al., 2011 models at distances less than 70 km from the source. The results of proposed model with Eq. (4) are close to other models when the distance parameter is increasing. ...
Macroseismic intensity data plays an important role in the process of seismic hazard analysis as well in developing of reliable earthquake loss models. This paper presents a physical-based model to predict macroseismic intensity attenuation based on 560 intensity data obtained in Iran in the time period 1975–2013. The geometric spreading and energy absorption of seismic waves have been considered in the proposed model. The proposed easy to implement relation describes the intensity simply as a function of moment magnitude, source to site distance and focal depth. The prediction capability of the proposed model is assessed by means of residuals analysis. Prediction results have been compared with those of other intensity prediction models for Italy, Turkey, Iran and central Asia. The results indicate the higher attenuation rate for the study area in distances less than 70km.
... Because our main focus is on the above-mentioned cities, we defined a target zone for the hazard assessment (see Fig. 1) as the rectangular region enclosing the cities and a 0.5°g reat-circle distance buffer zone around them. For an event of moment magnitude M w 8, which is larger than any observed event in the study's region (M w 7.5), using an intensity attenuation relation (Bindi et al., 2011), we expect the macroseismic intensity to drop below an intensity VI (slightly damaging) on average within an epicentral distance of around 185 km. Thus, we define a seismic source-model region ( Fig. 1) as the rectangular region around the cities with a 3°great-circle distance buffer. ...
... For the second cluster b, we chose Gasperini et al. (2010) because it consistently ranked higher than Pasolini et al. (2008). In cluster d, Bindi et al. (2011) was chosen because only LLH would rank Allen et al. (2012) higher. From the single IPE clusters (c and d), we implement only Chandler and Lam (2002) because, although Le Goff et al. (2014) fits well for smaller events, it is applicable only to M w ≤ 6:2 and, as Figure 4f shows, it strongly overestimates the intensity for large M w . ...
This data publication includes the DESERVE Earthquake Catalogue of historical and recent earthquakes and the DESERVE Macroseismic Intensity Dataset.
The DESERVE Earthquake Catalogue is a catalog of historical earthquakes in the region around the Dead Sea. It was compiled from several sources, including recent events (> Mw 3) for the region between 24.55° and 37.80° N and between 29.95° and 40.80° E. The catalogue includes events that occurred between the year 23 C.E. and 2014 C.E. and their magnitude was harmonized to moment magnitude. Details on how duplicates were removed, which magnitude conversions were applied, about the original data sources and the catalog completeness can be found in Haas et al. (2016).
The DESERVE Macroseismic Intensity Data set consists of macroseismic intensity observations for historical earthquakes in the region around the Dead Sea. It was compiled from several sources, including seismic events (Mw 4.2 - 7.9) that occurred between the year 23 C.E. and 1995 C.E for the region between 23.78° and 41.01° N and between 24.81° and 50.16°. Details on the the original sources can be found in Haas et al. (2016).
Both datasets are available in csv format and accompanied by explanatory files.
... Because our main focus is on the above-mentioned cities, we defined a target zone for the hazard assessment (see Fig. 1) as the rectangular region enclosing the cities and a 0.5°g reat-circle distance buffer zone around them. For an event of moment magnitude M w 8, which is larger than any observed event in the study's region (M w 7.5), using an intensity attenuation relation (Bindi et al., 2011), we expect the macroseismic intensity to drop below an intensity VI (slightly damaging) on average within an epicentral distance of around 185 km. Thus, we define a seismic source-model region ( Fig. 1) as the rectangular region around the cities with a 3°great-circle distance buffer. ...
... For the second cluster b, we chose Gasperini et al. (2010) because it consistently ranked higher than Pasolini et al. (2008). In cluster d, Bindi et al. (2011) was chosen because only LLH would rank Allen et al. (2012) higher. From the single IPE clusters (c and d), we implement only Chandler and Lam (2002) because, although Le Goff et al. (2014) fits well for smaller events, it is applicable only to M w ≤ 6:2 and, as Figure 4f shows, it strongly overestimates the intensity for large M w . ...
We derive a probabilistic seismic-hazard model for the Dead Sea region to allow for seismic risk estimation, which will be part of a subsequent study. This hazard model relies as much as possible on data-driven approaches, utilizing a seismic catalog compiled for the region by integrating data from different sources. We derive seismicity models using two different smoothing approaches and estimate a hypocentral depth distribution from historical observations. We do not include paleoseismological evidence apart from the observed seismicity. Because ground-motion records are sparse in the region, we formulate the model in the European Macroseismic intensity scale from 1998. However, the collected macroseismic intensity data are still too few to derive a local intensity prediction equation (IPE). Thus, we choose among existing equations derived for different regions and combine them in a logic tree. Here, motivated by Scherbaum et al. (2010), we propose a two-step approach to select the IPEs for the logic tree. First, we cluster a set of 10 candidate IPEs to identify groups of models that can be considered similar with respect to the distribution of the predicted values for a selection of the explanatory variables (i.e., magnitude and distance), using a k-mean approach (Steinhaus, 1956). Then, we apply different ranking techniques (Scherbaum et al., 2009; Kale and Akkar, 2013) to identify within each cluster the most suitable model to be included in the logic tree. The resulting hazard models are consistent with existing probabilistic seismic-hazard models for the region. We estimate a moderate-to-high hazard of intensity grade VII–VIII with 10% probability of exceedance within 50 years in close vicinity to the Dead Sea transform fault, the dominant seismogenic structure in this region.
... Considering the statement of Gu16 about the role of site effects, we also investigated the influence of site effects in deriving a ground motion prediction equation specifically for Central Asia. We started from the intensity assignments for 66 earthquakes considered by Bindi et al. (2011b) to derive an IPE for Central Asia without including any specific parameter in the regression that accounts for site effects. We used a random effect approach (Bates et al., 2014;Stafford, 2014;Kotha et al., 2016) where the site effects are included as a random effect on the offset. ...
... where M is the magnitude (considering the M LH scale, see Bindi et al., 2011b), R the epicentral distance, h the depth, the residual distribution, k the random effects on the offset parameter e 1 , with k=1,..,N, where N is the number of the considered vs30 categories. The random effects k describe the systematic deviations with respect to the median prediction of each group of observations relevant to any considered vs30 class. ...
... The considered catalogue contains information about 2700 documented intensities spanning an area of about 1.9 ×10 6 km² covering Kyrgyzstan and Tajikistan and part of Uzbekistan, Kazahkstan and China (see Figure 1). Following the approach described by Albarello e D'Amico [7], [8], a probabilistic hazard model has been computed over a two-dimensional grid (with resolution of 0.2×0.2 degrees) of virtual points covering the considered area. ...
... In following this methodology, first the seismic history at each site is first constructed from the available macroseismic information. For the case of earthquakes lacking direct observations in terms of felt intensity, the probability of exceeding a given intensity value (virtual assignments) can be estimated from the epicentral information and applying an Intensity Prediction Equation derived for the area [8]. Then, the probability of exceedance over a regular grid of sites is computed, starting from the intensity observations available for the same earthquake at neighboring localities and applying the Bayes's equation. ...
... In the framework of EMCA, a new generation of seismic hazard maps is foreseen in terms of macro seismic intensity, that, as anticipated above, are in turn used to assess seismic risk in the region. Previous studies, carried out as part of the EMCA activities, new Intensity Prediction Equation (IPE) for the region (Bindi et al 2011) were developed based on an updated earthquake catalog. A first seismic hazard assessment was carried out following the so called site-approach (Bindi et al 2012). ...
... A modified version of the Intensity Prediction Equation developed by Bindi et al (2011) for central Asia is used for this study. In mathematical form, the IPE can be written as: ...
In this study, the results of a probabilistic seismic hazard assessment for Central Asia from two different approaches, one using area sources and the other one based on smooth seismicity, are presented. In order to carry out the calculation, the OpenQuake platform (Pagani et al., 2014), which is an open source software tools developed by the GEM foundation, was used. For the smooth seismicity approach, the Frankel (1995) method with adaptive kernel of Stock and Smith (2002), and the Woo (1996) method are used. Regarding the area source model approach, the analyzed region is first divided into "super zone" for evaluating the completeness of the catalog and to assign the maximum magnitude. Then, smaller area sources are introduced based on tectonic regionalization, seismicity distribution and prominent faults structures in the region. The regional seismic hazard is estimated in terms of macroseismic intensity with 10% probability of exceedance in 50 years. The logic tree approach is applied to account for the epistemic uncertainty in the estimation of the maximum magnitude, the focal mechanism and the b-value. The highest seismic hazard is found to affect the Pamir Hindukush region which shows intensities as high as 9. The obtained results when compared with those of the GSHAP project, after their conversion to Intensity. Although the spatial variation of hazard is consistent, the level of expected intensity differs; with the new calculations providing in general lower hazard values. Finally, an example PSHA assessment for spectral acceleration accounting for empirical site effects is provided for Bishkek. In this case, the Vs30 estimated from array analysis of seismic noise and response spectral ratios obtained by the analysis of earthquake recordings are used to account for site modification of the ground motion. While, the maximum estimated hazard for Bishkek, when describing the site amplification through vs30 is observed to reach 0.69g at 0.3s, much higher values are derived (e.g.1.43g at 0.5s) when the site is described through response spectra ratio coefficients
... 5), would indeed propagate into ∆I. However, it should be considered that the intensity prediction equation yielding I ref in Eq. 1 ) does carry its own uncertainty term, which comprises epistemic and aleatory variabilities, including the uncertainties related to site response (see also Bindi et al. 2011;Baumont et al. 2018). It is not straightforward to disentangle such uncertainties from other sources of variability (path-and source-related); indeed, most IPEs currently available in the literature do not explicitly model local site amplification (e.g. ...
The spatial estimation of the soil response is one of the key ingredients for the modelling of earthquake risk. We present a ground motion amplification model for Switzerland, developed as part of a national-scale earthquake risk model. The amplification model is based on local estimates of soil response derived for about 240 instrumented sites in Switzerland using regional seismicity data by means of empirical spectral modelling techniques. These local measures are then correlated to continuous layers of topographic and geological soil condition indicators (multi-scale topographic slopes, a lithological classification of the soil, a national geological model of bedrock depth) and finally mapped at the national scale resorting to regression kriging as geostatistical interpolation technique. The obtained model includes amplification maps for PGV (peak ground velocity), PSA (pseudo-spectral acceleration) at periods of 1.0, 0.6 and 0.3 s; the modelled amplification represents the linear soil response, relative to a reference rock profile with VS30 (time-averaged shear-wave velocity in the uppermost 30 m of soil column) = 1105 m/s. Each of these amplification maps is accompanied by two layers quantifying its site-to-site and single-site, within event variabilities, respectively (epistemic and aleatory uncertainties). The PGV, PSA(1.0 s) and PSA(0.3 s) maps are additionally translated to macroseismic intensity aggravation layers. The national-scale amplification model is validated by comparing it with empirical measurements of soil response at stations not included in the calibration dataset, with existing city-scale amplification models and with macroseismic intensity observations from historical earthquakes. The model is also included in the Swiss ShakeMap workflow.
... According to the currently available peer-reviewed studies, IPEs strongly depend on the selected data, and they differ in the approaches employed for the statistical analysis, such as the regression technique (e.g., Sørensen et al., 2009, among others) or the fully probabilistic method (e.g., . Because of the regional dependency of seismic characteristics, several studies developed regional or local intensity attenuation relations (e.g., Bakun, 2006;Bakun and Scotti, 2006;Stromeyer and Grünthal, 2009;Bindi, Parolai, et al., 2011;Baumont et al., 2017;Oros et al., 2019), among others for different regions of the world. ...
Italy has a long tradition of studies on the seismic history of the country and the neighboring areas. Several archives and databases dealing with historical earthquake data—primarily intensity data points—have been published and are constantly updated. Macroseismic fields of significant events are of foremost importance in assessing earthquake effects and for the evaluation of seismic hazards. Here, we adopt the U.S. Geological Survey (USGS)-ShakeMap software to calculate the maps of strong ground shaking (shakemaps) of 79 historical earthquakes with magnitude ≥6 that have occurred in Italy between 1117 and 1968 C.E. We use the macroseismic data published in the Italian Macroseismic Database (DBMI15). The shakemaps have been determined using two different configurations. The first adopts the virtual intensity prediction equations approach (VIPE; i.e., a combination of ground-motion models [GMMs] and ground-motion intensity conversion equations [GMICEs]; Bindi, Pacor, et al., 2011; Oliveti et al., 2022b). The second exploits the intensity prediction equations (IPE; Pasolini, Albarello, et al., 2008; Lolli et al., 2019). The VIPE configuration has been found to provide more accurate results after appraisal through a cross-validation analysis and has been applied for the generation of the ShakeMap Atlas. The resulting maps are published in the Istituto Nazionale di Geofisica e Vulcanologia (INGV) ShakeMap (see Data and Resources; Oliveti et al., 2023), and in the Italian Archive of Historical Earthquake Data (ASMI; see Data and Resources; Rovida et al., 2017) platforms.
... The 100 latter were ranked and four of them (Table 1) were then selected to represent the body, center and range of intensity data. (Baumont et al., 2018) Bindi2011RHypo (with conversion to moment magnitude Mw) 0.2 (Bindi et al., 2011) Finally, some adjustments were carried out in the aleatory uncertainty modelling of the IPEs and GMMs. For the former, it 105 was decided to use the intra-and inter-event sigma of the Baumont et al. (2018) model, since the other functions do not distinguish into intra-and inter-event components, which is important for risk analyses. ...
Understanding seismic risk at both the national and sub-national levels is essential for devising effective strategies and interventions aimed at its mitigation. The National Earthquake Risk Model of Switzerland (ERM-CH23), released in early 2023, is the culmination of a multidisciplinary effort aiming to achieve, for the first time, a comprehensive assessment of the potential consequences of earthquakes on the Swiss building stock and population. Having been developed as a national model, ERM-CH23 relies on very high-resolution site-amplification and building exposure datasets, which distinguishes it from most regional models to-date. Several loss types are evaluated, ranging from structural/nonstructural and contents economic losses, to human losses, such as deaths, injuries and displaced population. In this paper, we offer a snapshot of ERM-CH23, summarize key details on the development of its components, highlight important results and provide comparisons with other models.
... Statistical bootstrapping has been successfully utilized by researchers in many areas of seismology. For example, bootstrapping was used to determine the standard deviation of the parameters of the GMPE model and the estimation of confidence intervals [11][12][13][14][15][16][17]. Another application of bootstrapping in seismology is for determining the uncertainty of estimated seismic deformations [18], determining the confidence intervals of the location of historical earthquakes [19], calculating the horizontal component of the seismic slowness vector [20], calculating the b parameter of the Gutenberg-Richter law [21], as well as estimating the uncertainty of the values describing seismic magnitude attenuation function [22]. ...
Induced seismicity has been a serious problem for many coal mines in the Upper Silesian Coal Basin in Poland for many decades. The occurring mining tremors of the rock mass generate seismic vibrations that cause concern to the local population and in some rare cases lead to partial damage to buildings on the surface. The estimation of peak ground acceleration values caused by high energy mining seismic tremors is an important part of seismic hazard assessment in mining areas. A specially designed bootstrapping procedure has been applied to estimate the ground motion prediction model and makes it possible to calculate the confidence intervals of these peak ground acceleration values with no assumptions about the statistical distribution of the recorded seismic data. Monte Carlo sampling with the replacement for 132 seismic records measured for mining seismic tremors exceeding 150 mm/s2 have been performed to estimate the mean peak ground acceleration values and the corresponding upper limits of 95% confidence intervals. The specially designed bootstrap procedure and obtained ground motion prediction model reflect much better the observed PGA values and therefore provide more accurate PGA estimators compared to the GMPE model from multiple regression analysis. The bootstrap analysis of recorded peak ground acceleration values of high-energy mining tremors provides significant information on the level of seismic hazard on the surface infrastructure. A new tool has been proposed that allows for more reliable determination of PGA estimators and identification in the areas in coal mines that are prone to high-energy seismic activity.
... The epicentral intensity I0 of the events in the LEQ377 database is given by the Shake-Maps. The magnitude (M)/depth (D) pair is converted to I0 by adjusting an intensity prediction equation using the functional form as follow (e.g., Atkinson and Wald 2007;Bindi et al. 2011): where a, b and c are the regression coefficients and σ is the standard deviation. Four relationships are derived, considering different classes of magnitude: [5; 6[, [6; 7[, [7; 8] and [5; 8]. ...
This work aims to construct a synthetic database of human and economic seismic losses. For weak-to-moderate magnitude and older earthquakes, the catalogs of losses are incomplete, which limits the creation of probabilistic based loss models. Furthermore, the number of earthquakes involving losses has increased in recent years, following a non-stationary Poisson distribution with a rate proportional to the exposed population and GDP. First, this study involved defining a series of empirical models (from definition of magnitude to losses) tested by the likelihood method applied to data from 377 earthquakes with variables related to exposure (exposed population and exposed GDP) and consequences (economic losses, number of fatalities and injuries). For these 377 earthquakes, the spatial variation of the hazard was deduced from USGS ShakeMaps and the social and economic losses evaluated were made stationary by taking into account exposure evolving over time. We then built a synthetic database of seismic losses from the ISC-GEM catalog of epicenters, which is assumed to be complete and homogeneous since 1967 for magnitudes > 5. The combination of the 377 events and the synthetic data indicates that earthquakes of magnitudes [5.5; 6.9] represent 36% of all economic losses, 56% of all fatalities, and 71% of injuries. An occurrence model was then designed to predict the evolution of losses over the next years.
... For comparison, I included attenuation curves obtained for magnitude-6.0 earthquakes in other seismically active regions of the world (Musson, 2005;Musson et al., 2010;Nazarov and Shebalin, 1975;Bindi et al., 2011). ...
... It is consequently important to determine the specific local attenuation relation for each region. Several studies have developed intensity attenuation relation (Allen et al. 2017;Ambraseys 1985;Baumont et al. 2018;Bindi et al. 2011;Chandler and Lam 2002;D. and Benouar 1994;Dowrick 1992;Haque et al. 2019;Le et al. 2014;Sørensen et al. 2010) for different regions around the world. ...
Macroseismic intensity data play an important role in seismic hazard analysis and in developing reliable earthquake loss models. This paper adopts an ellipse model to predict the macroseismic intensity attenuation in both the long-axis and the short-axis directions based on 136 earthquakes recorded throughout western China during 1970–2012. The geometric spreading and energy release of seismic waves are considered in the models proposed in this study. The proposed relation describes the macroseismic intensity simply as a function of the surface wave magnitude, source-to-site distance, and focal depth. This study adopts the focal depth that is not often considered in the current intensity prediction equations in China and uses different functional forms in the long- and short-axis directions. Based on residual analysis and evaluation, a more suitable macroseismic intensity predictive equation was established for western China, and it was compared and discussed with macroseismic intensity prediction equations of other researchers.
... Попытки учета особенностей проявления сейсми ческих воздействий, обусловленных различной глуби ной заложения очага землетрясения, описаны в ряде работ. Так, например, в работе Д. Бинди [Bindi et al., 2011] по территории Центральной Азии зависимость затуха ния макросейсмической интенсивности с расстоянием определяется уравнением: где Для коэффициентов данной зависимости на основе макросейсмических данных по ЦентральноАзиатскому региону методом наименьших квадратов получены сле дующие числовые значения: а 1 =0.898; а 2 =1.215; а 3 =1.809; а 4 =3.447•10 ...
Seismic intensity assessment in points of a macroseismic scale plays an important role for researching the seismic history of areas characterized by active seismicity, as well as for construction (and updating) of seismic zoning maps in various scales. Macroseismic scale points are generally referred to in construction standards applied in the majority of post-Soviet states. In our study aimed to model the macroseismic field of earthquakes, a large volume of macroseismic data on Central Asia was analyzed, and coefficients used in Blake–Shebalin and Covesligeti equations were aligned. This article presents a generalized dependence model of macroseismic intensity attenuation with distance. The model takes into account seismic load features determined by various depths of earthquakes. The ratios of small and big axes of the ellipse, that approximates real isoseists, are estimated with respect to seismic scale points, earthquake depths and magnitudes. The East Uzbekistan area is studied as an example to investigate whether seismic hazard assessment values may differ depending on a chosen law of seismic influence intensity attenuation with distance.
... Douglas (2011) has created a review-like report which represents the several attenuation models for different seismic provinces created between 1964 and 2010. Of the recent researches in the literature, Bindi et al. (2014) and Bindi et al. (2011) have given extensive predictive attenuation models for central Asia. Various researches were made similar for the USA (Atkinson and Kaka 2007;Bakun 2006;Bakun et al. 2003;Bakun and Wentworth 1997). ...
In this study, we propose new attenuation relations for use in possible future macroseismicity-based analyses for Turkey. The most significant difference of the new relationships is that they are specifically designed for use in the full extent of Turkey. Besides, this paper supplies an extensive macroseismic database larger than ever collected for Turkey. To this end, a modifiable MATLAB program, which is fully presented in the electronic supplement to this paper, was written to analyze the collected isoseismal maps that were first geo-rectified and then gridded by dividing them into 0.02° arrays. The epicentral distances belonging to each point intersected with the pertinent isoseism were compiled in an event-based log. Then, all subsets were merged into a single dataset, which is presented in the electronic supplement. Required strong ground motion parameters were taken from an improved earthquake catalog recently given by Kadirioğlu et al. (B Earthq Eng 1:2, 2016). For modeling the relations, the early relations were mostly selected as patterns for our candidate attenuation models. Of all candidate models, the statistically significant ones were individually tested whether or not they were able to detect the best fitting model to our database. The predicted error margins of the proposed models were compared to those of early models using data-driven statistical tests. In conclusion, considering the usability limits, the estimation capabilities of proposed relationships were found to be useful to some extent than those of the early models developed for Turkey.
... assessment is also required to take into account macroseismic intensity (e.g., Grünthal 1998;Garcia-Mayordomo et al. 2004;Grünthal et al. 2006;Tyagunov et al. 2006;Capera et al. 2010;Cua et al. 2010;Zare 2017). Macroseismic intensity databases are used in seismic hazard assessment because they represent a fundamental input for calibrating intensity prediction equations, spanning over a longer time window (e.g., Stromeyer and Grünthal 2009;Bindi et al. 2011). Particularly, such equations are used worldwide and are based on post-1900 catalogs, especially where parameters based on recorded data are not available (Cua et al. 2010). ...
Our work is intended to present the new macroseismic intensity database for the Republic of Georgia—hereby named GeoInt—which includes earthquakes from the historical (from 1250 B.C. onwards) to the instrumental era. Such database is composed of 111 selected earthquakes and related 3944 intensity data points (IDPs) for 1509 different localities, reported in the Medvedev-Sponheuer-Karnik scale (MSK). Regarding the earthquakes, the MS is in the 3.3–7 range and the depth is in the 2–36 km range. The entire set of IDPs is characterized by intensities ranging from 2–3 to 9–10 and covers an area spanning from 39.508° N to 45.043° N in a N-S direction and from 37.324° E to 48.500° E in an E-W direction, with some of the IDPs located outside the Georgian border, in the (i) Republic of Armenia, (ii) Russian Federation, (iii) Republic of Turkey, and (iv) Republic of Azerbaijan. We have revised each single IDP and have reevaluated and homogenized intensity values to the MSK scale. In particular, regarding the whole set of 3944 IDPs, 348 belong to the Historical era (pre-1900) and 3596 belong to the instrumental era (post-1900). With particular regard to the 3596 IDPs, 105 are brand new (3%), whereas the intensity values for 804 IDPs have been reevaluated (22%); for 2687 IDPs (75%), intensities have been confirmed from previous interpretations. We introduce this database as a key input for further improvements in seismic hazard modeling and seismic risk calculation for this region, based on macroseismic intensity; we report all the 111 earthquakes with available macroseismic information. The GeoInt database is also accessible online at http://www.enguriproject.unimib.it and will be kept updated in the future.
... (A) Plot of the distribution of fault strikes measured in the field and on high-resolution satellite images (total = 434; Y axis), vs. the distance from the HFF prolongation in meters (X axis). Such distance is defined as the minimum distance from the surface projection of the fault (e.g., Bindi et al., 2011). Below the graph, rose diagrams with fault strike distribution are provided. ...
We present a detailed field structural survey of the area of interaction between the active NW-striking transform Husavik-Flatey Fault (HFF) and the N–S Theystareykir Fissure Swarm (TFS), in North Iceland, integrated by analog scaled models. Field data contribute to a better understanding of how transform faults work, at a much higher detail than classical marine geophysical studies. Analog experiments are conducted to analyse the fracture patterns resulting from different possible cases where transform faulting accompanies or postpones the rift motions. Different tectonic block configurations are also considered and results are compared with field data in order to study as thoroughly as possible the interaction between the HFF and the TFS as well as the possible prolongation of the HFF into the TFS. West of the intersection between the transform fault (HFF) and the rift zone (TFS), the former splays with a gradual bending giving rise to a leading extensional imbricate fan. The westernmost structure of the rift, the N–S Gudfinnugja Fault (GF), is divided into two segments: the southern segment makes a junction with the HFF and is part of the imbricate fan; north of the junction instead, the northern GF appears right-laterally offset by about 20 m. Southeast of the junction, along the possible prolongation of the HFF across the TFS, the strike of the rift faults rotates in an anticlockwise direction, attaining a NNW–SSE orientation. Moreover, the TFS faults north of the HFF prolongation are fewer and have smaller offsets than those located to the south. Through the comparison between the structural data collected in the field at the HFF–TFS connection zone and a set of scaled experiments, we confirm a prolongation of the HFF through the rift, although here the transform fault has a much lower slip-rate than west of the junction. Our data suggest that transform fault terminations may be more complex than previously known, and propagate across a rift through a modification of the rift pattern.
... Macroseismic intensity (Grünthal, 2011) is a useful tool for purposes such as loss estimation (e.g., Eguchi et al., 1997;Grünthal et al., 2006;Wyss, 2008), communication of earthquake effects to the public (e.g., Wald, Quitoriano, Heaton, et al., 1999), and SHAs in regions with abundant historical earthquake records and moderate seismicity but sparse seismometer coverage (e.g., Musson, 2000;Bindi et al., 2011). Because the evaluation of building vulnerability is part of both macroseismic investigation and risk assessment, it is a natural advantage for intensity as the basis of risk assessment, leading to the continual popularity of the use of intensity for this purpose. ...
The engineering seismology community has recently recognized the importance of validating the performance of predictive models for seismic hazard by independent observations, yielding a number of studies on the relative performance of ground-motion prediction equations. The validation of intensity prediction equations (IPEs) has attracted less attention.We fill this gap by validating eight Italian IPEs plus one global IPE using five sets of Italian macroseismic intensity data, of which three are prospective and two retrospective to the models. We implemented multiple scoring methods to validate the models and found that the simple score of mean absolute error is sufficient to measure the general model performance. Good models consistently perform well under multiple methods and datasets, showing robustness. Models with physical functional forms are found to perform better. The global IPE performed well for Italian data, implying insignificant regional differences for IPEs. This result encourages grouping intensity data collected from multiple geographic regions, both from the Internet and traditional surveys, into a larger dataset for the use of future model development and validation.
... Within the EMCA project, Bindi et al. [2012] carried out an uniform assessment of the seismic hazard in Central Asia mainly guided by the observed seismic histories without any a-priori assumption on seismic zonation or on the model of time recurrence. The application of such an approach to cross-border catalogues and considering intensity prediction equations developed for the investigated area [Bindi et al. 2011], allowed to obtain a systematic and homogeneous evaluation of the hazard as well as the evaluation of the probability of exceedance of any given intensity value over a fixed exposure time over the entire analyzed area of different Central Asian countries. ...
Central Asia is one of the most exposed regions in the world to landslide hazard. The large variability of local geological materials, together with the difficulties in forecasting heavy precipitation locally and in quantifying the level of ground shaking, call for harmonized procedures to better quantify the hazard and the negative impact of slope failures across the Central Asian countries. As a first step towards a quantitative landslide hazard and risk assessment, a landslide susceptibility analysis at regional scale has been carried out, by benefitting of novel seismic hazard outcomes reached in the frame of Earthquake Model Central Asia (EMCA) project. By combining information coming from diverse potential factors, it is possible to detect areas where a potential for landslides exists. Initial results allow the identification of areas that are more susceptible to landslides with a level of accuracy greater than 70%. The presented method is, therefore, capable of supporting land planning activities at the regional scale in places where only scarce data are available © 2015 by the Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved
... Fig. 7 presents the seismic hazard map of the territory of Tajikistan in values of MSK-64 scale. The intensity prediction equation proposed in (Bindi et al., 2011) was used for calculation. The next step for seismic hazard assessment of the area of Tajikistan is to create the probabilistic seismic hazard map based on the up-to-date technics and methodology. ...
... Fig. 7 presents the seismic hazard map of the territory of Tajikistan in values of MSK-64 scale. The intensity prediction equation proposed in (Bindi et al., 2011) was used for calculation. The next step for seismic hazard assessment of the area of Tajikistan is to create the probabilistic seismic hazard map based on the up-to-date technics and methodology. ...
... Por ejemplo, la información del tamaño de un sismo histórico es generalmente proporcionada en términos de intensidad macrosísmica a la que se le asocia diferentes tipos de escalas como, Intensidad de Mercalli Modificada (MMI), la internacional Medvedev-Sponheuer-Karnik (MSK-64) y su posterior actualización a Escala Macrosísmica Europea (EMS-98). En importantes países, los códigos de construcción representan las "excitaciones sísmicas" en términos de la intensidad macrosísmica (Bindi, et al., 2012). ...
Este trabajo muestra la afinación del software ShakeMap en Panamá. La compañia OSOP ha implementado ShakeMap en conjunto con SeisComP para obtener mapas de intensidad sísmica instrumental a partir de los valores pico del movimiento del suelo (PGV, PGA y PSA). Los resultados de este trabajo muestran los tipos de modelos predictivos de movimiento del suelo propuestos por importantes investigadores, que pueden ser usados en ShakeMap para el territorio de Panamá.
... That is, the IPE is derived considering earthquakes different from those used to calibrate the BW97 attenuation model. We consider the same functional form used by Bindi et al. (2011). The distribution of the residuals, computed as observed minus predicted values, is decomposed into inter-(or between-) and intra-(or within-) event distribution of errors (Al Atik et al. 2010), which are assumed to be independent and normally distributed, with a zero mean. ...
We apply the Bakun and Wentworth (Bull Seism Soc Am 87:1502–1521, 1997) method to determine the location and magnitude of earthquakes occurred in Central Asia using MSK-64 intensity assignments. The attenuation model previously derived and validated by Bindi et al. (Geophys J Int, 2013) is used to analyse 21 earthquakes that occurred over the period 1885–1964, and the estimated locations and magnitudes are compared to values available in literature. Bootstrap analyses are performed to estimate the confidence intervals of the intensity magnitudes, as well as to quantify the location uncertainty. The analyses of seven significant earthquakes for the hazard assessment are presented in detail, including three large historical earthquakes that struck the northern Tien-Shan between the end of the nineteenth and the beginning of the twentieth centuries: the 1887, M 7.3 Verny, the 1889, M 8.3 Chilik and the 1911, M 8.2 Kemin earthquakes. Regarding the 1911, Kemin earthquake the magnitude values estimated from intensity data are lower (i.e. MILH = 7.8 and MIW = 7.6 considering surface wave and moment magnitude, respectively) than the value M = 8.2 listed in the considered catalog. These values are more in agreement with the value M
S = 7.8 revised by Abe and Noguchi (Phys Earth Planet In, 33:1–11, 1983b) for the surface wave magnitude. For the Kemin earthquake, the distribution of the bootstrap solutions for the intensity centre reveal two minima, indicating that the distribution of intensity assignments do not constrain a unique solution. This is in agreement with the complex source rupture history of the Kemin earthquake, which involved several fault segments with different strike orientations, dipping angles and focal mechanisms (e.g. Delvaux et al. in Russ Geol Geophys 42:1167–1177, 2001; Arrowsmith et al. in Eos Trans Am Geophys Union 86(52), 2005). Two possible locations for the intensity centre are obtained. The first is located on the easternmost sub-faults (i.e. the Aksu and Chon-Aksu segments), where most of the seismic moment was released (Arrowsmith et al. in Eos Trans Am Geophys Union 86(52), 2005). The second location is located on the westernmost sub-faults (i.e. the Dzhil'-Aryk segment), close to the intensity centre location obtained for the 1938, M 6.9 Chu-Kemin earthquake (MILH = 6.9 and MIW = 6.8).
... This method has gained considerable attention as a lowcost tool (Picozzi et al., 2009;De Siena et al., 2010;Pilz et al., 2012) and will also be carried out for the urban area of Dushanbe. In combination with already existing regional seismic intensity studies (Bindi et al., 2011(Bindi et al., , 2013, which did not allow a conclusion to be drawn about the existence of any possible regional dependency in the intensity-attenuation characteristics, such highly detailed site information is crucial when assessing seismic risk, which is defined as the probability of occurrence of economic and social losses as a consequence of an earthquake. As shown by Figure 2, this is particularly important for the city of Dushanbe, the political and economic center of Tajikistan, which is experiencing steady demographic growth. ...
The country of Tajikistan is located in the Asia–India continental collision zone where the northward‐moving Indian plate indents the Eurasian plate (Molnar and Tapponnier, 1975). The Asian lithosphere being impinged upon by the shallow northward underthrusting Indian lithosphere has resulted in high‐mountain topography, which is subject to active deformation and contemporary faulting, and, consequentially, frequent earthquakes (e.g., Gubin, 1960; Burtman and Molnar, 1993). According to the Global Seismic Hazard Map (Giardini, 1999), almost the entire country exhibits a high‐hazard level with intensities of VIII–IX for a 5% exceedance in 50 years. Most of the earthquakes that occur in these fault zones are crustal events with dominating thrust faulting along the Pamir front, whereas on the eastern edge of the Pamir the style of deformation is generally characterized by oblique thrusting with a component of strike‐slip motion. Thrust‐type events beneath the Tadjik Depression, a compressional intermountain basin in the western part of the country, indicate that both the sedimentary rocks and the basement are involved in shortening (Fan et al., 1994; Delvaux et al., 2013).
Although archaeological remnants........
Central Asia is an area characterized by complex tectonic and active deformation, largely due to the relative convergent motion between India and Arabia with Eurasia. The resulting compressional tectonic regime is responsible for the development of significant seismic activity, which, along with other natural hazards such as mass movements and river flooding, contributes to increased risk to local populations. Although several studies have been conducted on individual perils at the local and at national levels, the last published regional model for the whole Central Asia, developed under the EMCA project ("Earthquake Model of Central Asia"), is almost ten years old. With the goal of developing a new comprehensive multi-risk model, that is uniform and consistent across the five Central Asian countries of Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan, the European Union, in collaboration with the World Bank and the Global Facility for Disaster Reduction and Recovery (GFDRR), funded the regional program SFRARR ("Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia"). The activity was led by a consortium of scientists from international research institutions, from both the public and private sectors, with contribution from experts of the local scientific community. This study presents the main results of a probabilistic seismic hazard analysis (PSHA) conducted as part of the SFRARR program to develop the new risk model for Central Asia. The proposed PSHA model was developed using state-of-the-art methods and calibrated based on the most up-to-date information available for the region, including a novel homogenized earthquake catalog compiled from global and local sources and a database of active faults with associated slip rate information.
We derived new, reversible relationships between macroseismic intensity (I), expressed in either the European Macroseismic (EMS-98) or the Mercalli–Cancani–Sieberg (MCS) scales and peak ground acceleration (PGA), peak ground velocity (PGV) and the spectral acceleration (SA) at 0.3, 1.0 and 3.0 s [SA(0.3), SA(1.0) and SA(3.0)] for Italy. We adopted the orthogonal distance regression technique to fit a quadratic function. This research aims to improve ground motion and intensity estimates for earthquake hazard applications, and for the calculation of shakemaps in Italy. To this end, the recently published INGe data set was used (https://doi.org/10.13127/inge.2). The new relations are:
$$\begin{equation*} I = 3.01 \pm 0.12 + 0.86 \pm 0.04 \log ^2 \mathrm{ PGA},~\sigma = 0.30,~~\sigma _{\mathrm{ PGA}} = 0.25,~~\sigma _{I} = 0.16 \end{equation*}$$
$$\begin{equation*} I = 4.31 \pm 0.15 + 1.99 \pm 0.18 \log \mathrm{ PGV} + 0.58 \pm 0.18 \log ^2 \mathrm{ PGV},~\sigma = 0.34,~~\sigma _{\mathrm{ PGV}} \\ = 0.31,~~\sigma _{I} = 0.15 \end{equation*}$$
$$\begin{equation*} I = 2.77 \pm 0.15 + 0.68 \pm 0.03 \log ^2 \mathrm{ SA}(0.3),~\sigma = 0.31,~~\sigma _{\mathrm{ SA}(0.3)} = 0.28,~~\sigma _{I} = 0.14 \end{equation*}$$
$$\begin{equation*} I = 3.00 \pm 0.28 + 0.91 \pm 0.55 \log \mathrm{ SA}(1.0) + 0.51 \pm 0.20 \log ^2 \mathrm{ SA}(1.0),~\sigma = 0.40,~~\sigma _{\mathrm{ SA}(1.0)} \\ = 0.38,~~\sigma _{I} = 0.14 \end{equation*}$$
$$\begin{equation*} I = 4.04 \pm 0.20 + 1.63 \pm 0.19 \log \mathrm{ SA}(3.0) + 0.66 \pm 0.20 \log ^2 \mathrm{ SA}(3.0),~\sigma = 0.38,~~\sigma _{\mathrm{ SA}(3.0)} \\ = 0.35,~~\sigma _{I} = 0.14 \end{equation*}$$
where PGA and SAs are expressed in cm s⁻² and PGV is expressed in cm s⁻¹. Tests performed to assess the robustness and the accuracy of the results demonstrate that adoption of quadratic relationships for this regression problem is a suitable choice within the range of values of the available data set. Comparison with similar published regressions for Italy evidences that the proposed relations provide statistically significant improved fits to the data. The new relations are also tested by inserting them in the ShakeMap system of the Italian configuration evidencing a significant improvement when compared to those implemented
Based on macroseismic survey data for strong earthquakes in Central Asia, the coefficients of attenuation of seismic intensities with distance in the Blake-Shebalin- and Kovesligethy -type equations were refined. A new generalized dependence of macroseismic intensity attenuation on distance, taking into account the depth of the earthquake hypocentre, were obtained. Relations between the minor and major axes of the ellipse approximating real isoseists depending on the shaking strength, source depth and earthquake magnitude were found. With the example of the territory of eastern Uzbekistan, the influence of the choice of the law of seismic intensity attenuation with distance on the obtained seismic hazard assessments is investigated.
A correct seismic hazard assessment and intensity-based shake maps of a seismic zone depend on the determination of parameters that emphasize the distribution and the macroseismic intensity attenuation for that seismogenic zone. Due to the reduced number of strong ground motion records, macroseismic intensity information available for previous earthquakes which have occurred in studied area were the only source of information utilized for developing attenuation relationship for that zone. The aim of this paper is to test the existing equations published for various crustal seismic sources and develop a new macroseismic intensity attenuation law for the Vrancea crustal seismic source. The Vrancea crustal seismogenic zone had experienced moderate earthquakes in the past with magnitudes which did not exceed 5.9 [1] and macroseismic maralps had been constructed by various authors for these earthquakes representing intensity pattern and decrease of this parameter with distance on different azimuths. Some of the selected attenuation laws were tested for different values of epicentral intensity and with reference to eight directions. The input data consist of macroseismic intensities collected for 4 small and moderate earthquakes (Mw ≥ 3.9) that had occurred during the last hundred years with epicentral/maximum intensity in the range IV to VI MSK degrees. The seismic events used to verify the attenuation laws were selected based on the magnitude and number of macroseismic observations collected for each event. Using this data, attenuation relationships of macroseismic intensity with distance will be tested and modified. The deduced attenuation equation might be used for rapid intensity assessment of the potential future earthquakes occurred in this seismic zone.
In this study, we have evaluated the probabilistic and deterministic seismic hazard for the city of Almaty, the largest city in Kazakhstan, which has a population of nearly two million people. Almaty is located in the Tien Shan belt, a low-strain-rate environment within the interior of the Eurasian plate that is characterized by large infrequent earthquakes. A robust assessment of seismic hazard for Almaty is challenging because current knowledge about the occurrence of large earthquakes is limited, due to the short duration of the earthquake catalog and only partial information about the geometry, rupture behavior, slip rate, and the maximum expected earthquake magnitude of the faults in the area. The impact that this incomplete knowledge has on assessing seismic hazard in this area can be overcome using both probabilistic and deterministic approaches and integrating the results. First, we simulate ground-shaking scenarios for three destructive historical earthquakes that occurred in the northern Tien Shan in 1887, 1889, and 1911, using ground-motion prediction equations (GMPEs) and realistic fault-rupture models based on recent geomorphological studies. We show that the large variability in the GMPEs results in large uncertainty in the ground-motion simulations. Then, we estimate the seismic hazard probabilistically using a Monte Carlo-based probabilistic seismic hazard analysis and the earthquake catalog compiled from the databases of the International Seismological Centre and the British Geological Survey. The results show that earthquakes of M w 7.0-7.5 at Joyner-Boore distances of less than 10 km from the city pose a significant hazard to Almaty due to their proximity. These potential future earthquakes are similar to the 1887 Verny earthquake in terms of their magnitude and distance from Almaty. Unfortunately, this is the least well understood of the destructive historical earthquakes that have occurred in the northern Tien Shan.
The systematic study of the ore Zhitikara region held since the beginning of the 60s of the last century. In the course of exploration work on titanium was found Churchite presence of mineralization. Studies have shown that the occurrence of residual deposits of titanium, yttrium, rare earths and manganese in the strata in Marinovsk formation was due to intense crust formation in the Mesozoic. The Marinovsk section is divided into three horizons - the upper quartzite-shale, average substantially amphibolite and lower gneiss. It was found that yttrium and rare earths tend most to melanocratic schist, concentrated mainly in the garnet, biotite, as well as accessory minerals - apatite and orthite. Churchite at the time of this ore region was considered the only mineral that is associated with the rare-earth mineralization. The results of subsequent studies have shown that only a small proportion of rare earths concentrate directly to Churchite. It became necessary to study the gross clay rock weathering crust. Therefore, to assess the content of yttrium and rare earths used data from only those wells for which the determination of the amount of oxides was carried out on all argillaceous rocks. Since 2011, the thematic papers obtained detailed geological information on wells - column describing rocks at depth, the results of testing of ore intervals on rare earth metals. To determine the geophysical criteria for allocation of ore intervals measurements were performed in wells of electrical (apparent resistivity and natural polarization) and radioactive (natural gamma radiation) properties of rocks. The unique link between the industrial maintenance intervals of Churchite and increased values of natural radioactivity on curves gamma logging has not been established. Recommended testing and continuation of geophysical research methods of artificial wells nuclear field (gamma, neutron methods). © National Academy of Sciences of the Republic of Kazakhstan, 2017.
Rapidly expanding urban areas in Central Asia are increasingly vulnerable to seismic risk; but at present, no earthquake early warning (EEW) systems exist in the region despite their successful implementation in other earthquake-prone areas. Such systems aim to provide short (seconds to tens of seconds) warnings of impending disaster, enabling the first risk mitigation and damage control steps to be taken. This study presents the feasibility of a large scale cross-border regional system for Central Asian countries. Genetic algorithms are used to design efficient EEW networks, computing optimal station locations and trigger thresholds in recorded ground acceleration. Installation of such systems within 3 years aims to both reducing the endemic lack of strong motion data in Central Asia that is limiting the possibility of improving seismic hazard assessment, and at providing the first regional earthquake early warning system in the area. © 2015 by the Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved.
A new macroseismic intensity prediction equation is derived for the central and eastern United States and is used to estimate the magnitudes of the 1811-1812 New Madrid, Missouri, and 1886 Charleston, South Carolina, earthquakes. This work improves upon previous derivations of intensity prediction equations by including additional intensity data, correcting magnitudes in the intensity datasets to moment magnitude, and accounting for the spatial and temporal population distributions. The new relation leads to moment magnitude estimates for the New Madrid earthquakes that are toward the lower range of previous studies. Depending on the intensity dataset to which the new macroseismic intensity prediction equation is applied, mean estimates for the 16 December 1811, 23 January 1812, and 7 February 1812 mainshocks, and 16 December 1811 dawn aftershock range from 6.9 to 7.1, 6.8 to 7.1, 7.3 to 7.6, and 6.3 to 6.5, respectively. One-sigma uncertainties on any given estimate could be as high as 0.3-0.4 magnitude units. We also estimate a magnitude of 6.9 +/- 0.3 for the 1886 Charleston, South Carolina, earthquake. We find a greater range of magnitude estimates when also accounting for multiple macroseismic intensity prediction equations. The inability to accurately and precisely ascertain magnitude from intensities increases the uncertainty of the central United States earthquake hazard by nearly a factor of two. Relative to the 2008 national seismic hazard maps, our range of possible 1811-1812 New Madrid earthquake magnitudes increases the coefficient of variation of seismic hazard estimates for Memphis, Tennessee, by 35%-42% for ground motions expected to be exceeded with a 2% probability in 50 years and by 27%-35% for ground motions expected to be exceeded with a 10% probability in 50 years.
The last edition of a Manual of Seismological Observatory Practice dates back to 1979. It covered analog techniques only and is out of print. Since that time, computer and communication technologies as well as the availability of modern broadband sensors have revolutionized seismological observatory practice. Related know-how is chiefly available in industrial countries only. Besides this, classical university curricula do not provide suitable education and training of observatory personnel. Therefore, the IASPEI Commission on Practice has launched an initiative to produce within the next few years a New Manual of Seismological Observatory Practice (NMSOP). It will be developed as an electronic database and will be freely accessible, together with the old manual, via the Internet. The systematic tutorial body of the manual, complemented by the use of hypertext features which will guide the user to additional resources, will assist station operators and analysts in their daily work and enable them to retrieve relevant pieces of information or teaching/ training modules tailored to their specific needs. When finished, the NMSOP will also be available as a CD-ROM, and the publication of a condensed version as a text book is being considered. This paper outlines the philosophy, structure, and list of contents of the NMSOP and demonstrates it using several examples.
The S-wave attenuation characteristics beneath the Vrancea region in Romania are analyzed from the spectra (frequency range 0.5–20 Hz) of more than 850 recordings at 43 accelerometric stations of 55 intermediate-depth earthquakes (M 4:0–7:1) that occurred in the Vrancea seismogenic zone. The method commonly chosen for this type of investigation in the case of crustal earthquakes is the generalized inversion technique (GIT) (e.g., Andrews, 1986; Castro et al., 1990). Yet the Vrancea dataset is entirely different from common crustal datasets. Because of the strong clustering of the hypocenters within a very small focal volume, there are only few crossing ray paths from sources to receivers. As a consequence, inhomogeneities in the attenuation properties are not averaged out, which leads to unphysical results if the standard GIT approach is adopted. The problem is discussed qualitatively by performing tests with synthetic data and solved quantitatively by adapting the GIT technique in view of these peculiarities.With the optimally adapted inversion scheme, it is possible to unravel differences in the attenuation characteristics between two (or more) sets of stations. The results show that the attenuation of seismic waves is roughly comparable in the low frequency range (<4–5 Hz) but stronger by up to an order of magnitude at higher frequencies within the Carpathian mountain arc as compared with the foreland area. Modeling this strongly frequency-dependent lateral variation of seismic attenuation by a significantly lower Q beneath Vrancea (1) provides a very good fit of observed strong-motion characteristics, (2) sheds new light on the distribution of intensities of the previous strong earthquakes, (3) will have strong implications for future hazard assessment, and (4) is fully compatible with structural models from deep seismic sounding, tomography, and teleseismic attenuation. Published 2482–2497 4.2. TTC - Scenari e mappe di pericolosità sismica JCR Journal
The size of local and regional earthquakes in the former Soviet Union (USSR) has been given by the energy class ( K -class) system since the late 1950s. K -class was originally developed as a rapid and simple means of estimating the radiated energy ( E ) from an earthquake and was defined as
K = log10 E (in joules).
The nature, origin, and methodology of this system are poorly known to Western seismologists studying Soviet and Russian seismological data, and yet are of great interest and importance to those conducting detailed research on the seismicity of the former USSR. Since its inception, K -class has been the primary means of quantifying the size of small events in the former USSR and continues to be used for that purpose today. In most of this region, scientists employed the method of Rautian (1960), using the maximum horizontal (for the S wave) and vertical (for the P wave) amplitudes, which became the standard for local and regional networks in the early 1960s. In this paper, we describe the origins and basic principles of the energy class system, as well as the methodology generally used today by the regional networks (figure 1) of the states of the former USSR.
Shortly after World War II, between 1946 and 1949, three large earthquakes occurred in Soviet Central Asia and triggered an intense study of seismicity. After the magnitude 7.4 Khait earthquake of 10 July 1949, the Geophysical Institute (now the Institute of Physics of the Earth) of the USSR dispatched an expedition to Garm, Tajikistan (figure 1), to deploy a temporary network around the epicentral region. This Complex Seismological Expedition (CSE), which included the senior authors of this paper (Khalturin and Rautian) at its inception, became permanent in 1954.
The study of regional seismicity was not well-developed …
The use of ground-motion-prediction equations to estimate ground shak- ing has become a very popular approach for seismic-hazard assessment, especially in the framework of a logic-tree approach. Owing to the large number of existing published ground-motion models, however, the selection and ranking of appropriate models for a particular target area often pose serious practical problems. Here we show how observed ground-motion records can help to guide this process in a sys- tematic and comprehensible way. A key element in this context is a new, likelihood based, goodness-of-fit measure that has the property not only to quantify the model fit but also to measure in some degree how well the underlying statistical model assumptions are met. By design, this measure naturally scales between 0 and 1, with a value of 0.5 for a situation in which the model perfectly matches the sample dis- tribution both in terms of mean and standard deviation. We have used it in combi- nation with other goodness-of-fit measures to derive a simple classification scheme to quantify how well a candidate ground-motion-prediction equation models a par- ticular set of observed-response spectra. This scheme is demonstrated to perform well in recognizing a number of popular ground-motion models from their rock-site- recording subsets. This indicates its potential for aiding the assignment of logic-tree weights in a consistent and reproducible way. We have applied our scheme to the border region of France, Germany, and Switzerland where the Mw 4.8 St. Dieearth- quake of 22 February 2003 in eastern France recently provided a small set of ob- served-response spectra. These records are best modeled by the ground-motion- prediction equation of Berge-Thierry et al. (2003), which is based on the analysis of predominantly European data. The fact that the Swiss model of Bay et al. (2003) is not able to model the observed records in an acceptable way may indicate general problems arising from the use of weak-motion data for strong-motion prediction.
The number of different macroseismic scales that have been used to express earthquake shaking in the course of the last 200 years is not known; it may reach three figures. The number of important scales that have been widely adopted is much smaller, perhaps about eight, not counting minor variants. Where data sets exist that are expressed in different scales, it is often necessary to establish some sort of equivalence between them, although best practice would be to reassign intensity values rather than convert them. This is particularly true because difference between workers in assigning intensity is often greater than differences between the scales themselves, partic-ularly in cases where one scale may not be very well defined. The extent to which a scale guides the user to arrive at a correct assessment of the intensity is a measure of the quality of the scale. There are a number of reasons why one should prefer one scale to another for routine use, and some of these tend in different directions. If a scale has many tests (diagnostics) for each degree, it is more likely that the scale can be applied in any case that comes to hand, but if the diagnostics are so numerous that they include ones that do not accurately indicate any one intensity level, then the use of the scale will tend to produce false values. The purpose of this paper is chiefly to discuss in a general way the principles involved in the analysis of intensity scales. Conversions from different scales to the European Macroseismic Scale are discussed.
Several different attenuation models have recently been proposed for the Italian region to characterize the decay of macroseismic intensity with the distance from the source. The significant scatter between these relationships and some signif-icant drawbacks that seem to characterize previous approaches (described in a com-panion article by Pasolini et al., 2008) suggest that the problem needs to be reconsidered. As a first step toward more detailed analyses in the future, this study aimed at developing an isotropic attenuation relationship for the Italian area. Because this attenuation relationship has to be used primarily in probabilistic seismic hazard assessment, major attention was given to evaluating the attenuation relationship in its complete probabilistic form. Another important aspect of this study was the prelimi-nary evaluation of the intrinsic (i.e., independent of the specific attenuation relation-ship to be used) scattering of data, which represents the lowest threshold for the residual variance that cannot be explained by the attenuation relationship. Further-more, the peculiar formal features of intensity data and relevant uncertainties were considered carefully. To reduce possible biases, the completeness of the available database was checked and a suitable data selection procedure was applied. Since epi-central intensity cannot be defined unambiguously from the experimental point of view, the attenuation relationship was scaled with a new variable that is more repre-sentative of the earthquake dimension. Several criteria were considered when evalu-ating competing attenuation formulas (explained variance, Bayesian information criteria, Akaike information criteria, etc.). Statistical uncertainty about empirical pa-rameters was evaluated by using standard approaches and bootstrap simulations. The performance of the selected relationship with respect to a control sample was analyzed by using a distribution-free approach. The resulting equation for the expected intensity I at a site located at epicentral distance R is I I E
0:0086 0:0005
D h
1:037 0:027ln
D ln
h; where D R 2 h 2 p , h
3:91 0:27 km, and I E is the average expected inten-sity at the epicenter for a given earthquake that can be computed from the intensity data (when available) or by using empirical relationships with the moment magnitude M w or the epicentral intensity I 0 reported by the Italian seismic catalog I E
5:862 0:301
2:460 0:055M w ; I E
0:893 0:254
1:118 0:033I 0 : Comparison of the model standard deviation (S.D.) (0.69 intensity degrees) with the intrinsic one (0.62) indicates that this attenuation equation is not far from being optimal.
We critically analyze the results on seismic intensity attenuation in Italy derived by Albarello and D'Amico (2004) and Gasperini (2001). We demonstrate that, due to the inadequacy of certain underlying assumptions, the empirical relationships determined in those studies did not best reproduce the decay of intensity as the dis-tance from the source increases. We reconsidered some of the relevant concepts and assumptions used in these intensity-attenuation studies (macroseismic epicenter, epi-central intensity, data completeness) to suggest some useful recipes for obtaining un-biased estimates. In particular, we suggest that (1) data for distances from the source at which an intensity below the limit of diffuse perceptibility (≤ IV) is expected should be excluded from attenuation computations because such data are clearly incomplete, (2) attenuation equations that include a term proportional to the epicentral intensity I 0 with a coefficient different from 1.0 must not be used because they imply a variable offset between I 0 and the intensity expected at the epicenter, and (3) epicentral in-tensities must be recomputed consistently with the attenuation equation because those reported by the Italian catalog do not generally correspond with the intensity predicted at the epicenter by the attenuation relationships so far proposed. Following these sug-gestions produces a significant reduction in the standard deviation of the model that might lead to a corresponding reduction of the estimates of seismic hazard.
New probabilistic seismic hazard and Arias Intensity maps have beendeveloped for the territory of the Kyrgyz Republic and bordering regions.Data were mainly taken from the seismic catalogue of Kyrgyzstan and partlyfrom the world seismic catalogue. On the base of seismicity and activetectonics, seismic zones were outlined over the area. For these,Gutenberg-Richter laws were defined using mainly instrumental data, butregarding also historical events. Attenuation of acceleration inside the targetarea could not be determined experimentally since existing strong motiondata are insufficient. Therefore, empirical laws defined for other territories,principally Europe and China, were applied to the present hazardcomputations. Final maps were calculated with the SEISRISKIII programaccording to EUROCODE8 criteria, i.e. for a period of 50 years with90% probability of non-exceedance. For long-term prediction, 100 yearsmaps with 90% probability of non-exceedance have been developed. Theprocedure used for seismic hazard prediction in terms of PGA (PeakGround Acceleration) was also applied to Arias intensities in order to beable to define regional seismogenic landslide hazard maps.
The European Union has been promoting an homogenisation of the design rules for earthquake resistant structures through the
Eurocode 8, which will soon become the official standard (CEN, 2003). However, the zonation for the basic earthquake ground
motion will remain in the national authorities competence. Hence, it is important to outline differences and similarities
in the `official' seismic hazard assessments (SHA) used by national seismic codes to define seismic zones and levels of seismic
actions. The different SHA in 16 European countries were analysed taking into account a selection of comparative ingredients:
date of the SHA, earthquake scale, definition of seismogenic zones, maximum earthquake estimation, attenuation relation, hazard
calculation and hazard descriptor. Most of the official European SHAs were made more than 5 years ago, in terms of macroseismic
intensity, taking into account seismogenic zones, estimating maximum earthquakes from historical records, making use of attenuation
relationships for macroseismic intensity and assuming that earthquake occurrences follow a Poisson process. Most of the countries
(11/16) depict hazard for a ∼475 year return period; seven of them use peak ground acceleration and four MSK intensity. There
is also an important fraction relating the hazard to a different return period (3/16) or expressing it in a deterministic
way (2/16). A general updating and homogenisation in many of the national SHA is recommended.
Source parameters for historical earthquakes worldwide are compiled to develop a series of empirical relationships among moment magnitude (M), surface rupture length, subsurface rupture length, downdip rupture width, rupture area, and maximum and average displacement per event. The resulting data base is a significant update of previous compilations and includes the additional source parameters of seismic moment, moment magnitude, subsurface rupture length, downdip rupture width, and average surface displacement. Each source parameter is classified as reliable or unreliable, based on our evaluation of the accuracy of individual values. Only the reliable source parameters are used in the final analyses. In comparing source parameters, we note the following trends: (1) Generally, the length of rupture at the surface is equal to 75% of the subsurface rupture length; however, the ratio of surface rupture length to subsurface rupture length increases with magnitude; (2) the average surface displacement per
The aim of this study is to assess and map the seismic risk for Germany, restricted to the expected losses of damage to residential buildings. There are several earthquake prone regions in the country which have produced M<sub>w</sub> magnitudes above 6 and up to 6.7 corresponding to observed ground shaking intensity up to VIII?IX (EMS-98). Combined with the fact that some of the earthquake prone areas are densely populated and highly industrialized and where therefore the hazard coincides with high concentration of exposed assets, the damaging implications from earthquakes must be taken seriously. In this study a methodology is presented and pursued to calculate the seismic risk from (1) intensity based probabilistic seismic hazard, (2) vulnerability composition models, which are based on the distribution of residential buildings of various structural types in representative communities and (3) the distribution of assets in terms of replacement costs for residential buildings. The estimates of the risk are treated as primary economic losses due to structural damage to residential buildings. The obtained results are presented as maps of the damage and risk distributions. For a probability level of 90% non-exceedence in 50 years (corresponding to a mean return period of 475 years) the mean damage ratio is up to 20% and the risk up to hundreds of millions of euro in the most endangered communities. The developed models have been calibrated with observed data from several damaging earthquakes in Germany and the nearby area in the past 30 years.
The territory under review is the north part of Central Asia including five republics of the former Soviet Union — Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan, and Turkmenistan. It is a very complicated region in its geological-tectonic aspect, and it is at present one of the most highly seismic geostructural areas in the world. Much research work in various scientific fields has been directed towards studying the nature of earthquakes, the assessment of seismic hazard, and the development of methodologies for forecasting large earthquakes. A large amount of material has been collected on the different aspects of geology, tectonics, and seismic activity of the region, which shows the high level of seismic hazard in most parts of the republics, including the capital cities.
We investigated the Suusamyr, Kyrgyzstan, earthquake of 19 August 1992, using aftershock data, teleseismic body-wave modeling, and field observations. Aftershocks were recorded by the IRIS Kyrgyzstan broadband network, a temporary six-station aftershock network, and a regional network operated by the Kyrgyz Institute of Seismology. The aftershocks, which range in depth from the surface to 18 km, defined a 50 ±10-km-long rupture zone that dips 50° ±13° to the south and strikes roughly east-west. The base of the eastern end of the aftershock zone shallowed to the east along strike and may represent a lateral ramp. The surface ruptures also had an east-west strike and dipped south, but the total length (less than 4 km) was much shorter than the aftershock zone. A teleseismic body-wave inversion, using a point source and a directivity correction, yields a focal mechanism with a strike of 221°, dip of 46°, and a slip of 43°. We obtained a moment of 4.1 × 1019 N-m with a centroid depth between 5 and 21 km. The rupture propagated along an azimuth of 330° ±60°, which matches the relative location of the mainshock with respect to the aftershock zone. The results of the aftershock study and teleseismic inversion yield a clear picture of the fault geometry of a large-thrust earthquake.
The 1911 Ms =8.2 Kemin (Kebin) earthquake in the northern Tien Shan (Kazakhstan, Kyrgyzstan) formed a complex system of surface ruptures nearly 190 km long and numerous landslides and rock avalanches up to tens of millions of cubic meters in volume. Judging from their distribution, six fault segments of the Kemin-Chilik and the Aksu fault zones with different strikes, dips, and kinematics were activated. The Kemin earthquake was one of the strongest events of a sequence of seismic catastrophes that affected the Kungei and Trans-iii-Alatau mountain ranges between 1887 and 1938. The effects of the Kemin earthquake are well documented in a monograph published soon after the event by K. I. Bogdanovich. In the framework of the European INCO·COPERNICUS program, the surface ruptures, landslides, and rockslides associated with this earthquake have been reexamined in detail. In addition, the large-scale tectonic setting of the Kemin-Chilik and Aksu fault zones has been re-evaluated, and their segments have been identified and described. The whole system forms a sinistral transpressional structure, which controls the formation of the mountain ranges between the Issyk-Kul' depression and the Kazakhstan block. The surface ruptures of the 1911 earthquake can presently be observed in the field over a total length of nearly 100 km and :generally reactivate longer-term cumulative paleoseismic fault scarps. The presence of well-expressed paleoseismic fault scarps and several tremendous ancient landslides in the Chon-Kemin, Chon-Aksu, and Aksu valleys can be considered as evidence for strong prehistoric earthquakes. Active fault, landslides, 1911 Kemin earthquake, Tien Shan, Kyrgyzstan
A risk scenario for Bishkek, capital of the Kyrgyz Republic, is evaluated by considering a magnitude 7.5 earthquake occurring over the Issyk-Ata fault. The intensity values predicted through the application of an attenuation relationship and a recently compiled vulnerability composition model are used as inputs for seismic risk assessment, carried out using the Cedim Risk Estimation Tool (CREST) code. Although the results of this study show a reduction by as much as a factor of two with respect to the results of earlier studies, the risk scenario evaluated in this paper confirms the large number of expected injuries and fatalities in Bishkek, as well as the severe level of building damage.Furthermore, the intensity map has also been evaluated by performing stochastic simulations. The spectral levels of the ground shaking are converted into intensity values by applying a previously derived conversion technique. The local site effects are empirically estimated considering the spectral ratios between the earthquakes recorded by a temporary network deployed in Bishkek and the recordings at two reference sites. Although the intensities computed via stochastic simulations are lower than those estimated with the attenuation relationship, the simulations showed that site effects, which can contribute to intensity increments as large as 2 units in the north part of the town, are playing an important role in altering the risk estimates for different parts of the town.
This report is the first, as well as the most complete, summary of data on earthquakes in the USSR and neighboring regions to be published in English. The first (Russian) edition of the "New Catalog,' which contained data only through 1974, was modified by the editors for the present publication with substantial additions and revisions. Data for strong earthquakes in 1975-77 have been included, as well as additional information from published sources that became available to the editors after 1976.
Из сравнения различных опубликованных кривых амплитудB(Δ) и соотношенияB/T(Δ) вытекает, что у значенийB/T рассеяние меньше и поэтому они более удобные для определенияM. На наклон кривых влияет преобладающий период колебаний и выделяются интервалы интерференции волн и перехода максимальной энергии с одной волновой группы на другую (Δ=100–200 км и 500–700 км). Сравнение дает возможность определить приблизительно средние калибровочные кривые дляM близких землетрясений. © 1962, Nakladatelstvi Československé akademie věd. All rights reserved.
Prediction equations for macroseismic intensity are the backbone of seis-mic hazard assessment, of source parameter estimation, and of shake map generation in cases where an output in terms of intensity is desired. This is especially required when a direct relation to the damage associated with ground shaking is of interest or if ground shaking estimates will be used for informing nonseismologists such as emer-gency response teams or the general public. In the current study we derive ground-motion prediction equations for macroseismic intensity valid for the Marmara Sea region, northwest Turkey. The relations have a physical basis and are easy to imple-ment for the user. In one relation, the finite extent of the fault rupture is accounted for by defining distance as the Joyner–Boore distance leading to the relation I S 0:376M w 5:913 2:656 log R 2 JB h 2 h 2 r 0:0020 R 2 JB h 2 q h ; where M w is the moment magnitude, R JB is the Joyner–Boore distance, and h is the hypocentral depth. Furthermore, a relation based on the epicentral distance (R epi) is derived for application in cases where the extent of the fault plane is unknown: I S 0:793M w 3:417 2:157 log R 2 epi h 2 h 2 s 0:0065 R 2 epi h 2 q h : The relations are valid for the ranges 5 ≤ I ≤ 10, 5:9 ≤ M w ≤ 7:4, and R ≤ 350 km. It is shown that inclusion of the rupture dimensions leads to an improvement in the ability of the relation to fit observations in the near field for large earthquakes. Com-parison to already existing intensity prediction equations for the region shows that the new relations provide better estimates of the macroseismic intensity distribution, espe-cially in the region near the rupturing fault plane.
The conventional magnitude scale M suffers saturation when the rupture dimension of the earthquake exceeds the wavelength of the seismic waves used for the magnitude determination (usually 5–50 km). This saturation leads to an inaccurate estimate of energy released in great earthquakes. To circumvent this problem the strain energy drop W (difference in strain energy before and after an earthquake) in great earthquakes is estimated from the seismic moment M_0. If the stress drop Δσ is complete, W = W_0 = (Δσ/2μ)M_0 ∼ M_0/(2×10^4), where μ is the rigidity; if it is partial, W_0 gives the minimum estimate of the strain energy drop. Furthermore, if Orowan's condition, i.e., that frictional stress equal final stress, is met, W_0 represents the seismic wave energy. A new magnitude scale M_w is defined in terms of W_0 through the standard energy-magnitude relation log W_0 = 1.5M_w + 11.8. M_w is as large as 9.5 for the 1960 Chilean earthquake and connects smoothly to M_s (surface wave magnitude) for earthquakes with a rupture dimension of about 100 km or less. The M_w scale does not suffer saturation and is a more adequate magnitude scale for great earthquakes. The seismic energy release curve defined by W_0 is entirely different from that previously estimated from Ms. During the 15-year period from 1950 to 1965 the annual average of W_0 is more than 1 order of magnitude larger than that during the periods from 1920 to 1950 and from 1965 to 1976. The temporal variation of the amplitude of the Chandler wobble correlates very well with the variation of W_0, with a slight indication of the former preceding the latter. In contrast, the number N of moderate to large earthquakes increased very sharply as the Chandler wobble amplitude increased but decreased very sharply during the period from 1945 to 1965, when W_0 was largest. One possible explanation for these correlations is that the increase in the wobble amplitude triggers worldwide seismic activity and accelerates plate motion which eventually leads to great decoupling earthquakes. This decoupling causes the decline of moderate to large earthquake activity. Changes in the rotation rate of the earth may be an important element in this mechanism.
A new approach to the problem of site seismic hazard analysis is proposed, based on intensity data affected by uncertainties. This approach takes into account the ordinal and discrete character of intensities, trying to avoid misleading results due to the assumption that intensity can be treated as a real number (continuous distribution estimators, attenuation relationships, etc.). The proposed formulation is based on the use of a distribution function describing, for each earthquake, the probability that site seismic effects can be described by each possible intensity value. In order to obtain site hazard estimates where local data are lacking, the dependence of this distribution function with the distance from the macroseismic epicenter and with epicentral intensity is examined. A methodology has been developed for the purpose of combining such probabilities and estimating site seismicity rates which takes into account the effect of uncertainties involved in this kind of analysis. An application of this approach is described and discussed.
We discuss the following problem given a random sample X = (X
1, X
2,…, X
n) from an unknown probability distribution F, estimate the sampling distribution of some prespecified random variable R(X, F), on the basis of the observed data x. (Standard jackknife theory gives an approximate mean and variance in the case R(X, F) = \(\theta \left( {\hat F} \right) - \theta \left( F \right)\), θ some parameter of interest.) A general method, called the “bootstrap”, is introduced, and shown to work satisfactorily on a variety of estimation problems. The jackknife is shown to be a linear approximation method for the bootstrap. The exposition proceeds by a series of examples: variance of the sample median, error rates in a linear discriminant analysis, ratio estimation, estimating regression parameters, etc.
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