Seismic Hazard Maps Research Articles

Numerical Evaluation of Slope Stability measures: A Case Study of Birham Landslide, Murree, Pakistan.

Slope failures endanger the public safety and one of major hazard considered in mountainous terrain. In this paper, slope stability measures have been evaluated using the limit equilibrium method (LEM). A case study of slope failure from Birham land slide, Murree, Pakistan has been modelled using SLOPE/W program. In-situ boring tests are performed to collect laboratory test specimens. Geotechnical properties (i.e. shear strength and stiffness parameters) for the idealised slope sections are based onlaboratory tests performed on the collected in-situ specimens. Slope stability measures are evaluated in terms of factor of safety (FoS) for static and dynamic loading. Pseudo-static method is used for dynamic analysis, considering the Peak ground acceleration (PGA) from seismic hazard map of Pakistan. Results shows that static and dynamic FoS of original slope are inadequate therefore resistance to slip surface of original unstable slope is provided by slope geometry modification with pile reinforcement. Based on these remedial measures, computed FoS of modified slope are found to be sufficient for static and dynamic slope stability.

Ensemble Smoothed Seismicity Models for the New Italian Probabilistic Seismic Hazard Map

Ensemble Smoothed Seismicity Models for the New Italian Probabilistic Seismic Hazard Map

Incorporating the local faults effects in development of seismic ground-motion hazard mapping for the Peninsular Malaysia region

The probabilistic seismic ground-motion hazard maps for the Peninsular Malaysia region have been developed by the present study. Despite the earlier seismic hazard maps for this region, which were proposed only based on far-field Sumatran seismic sources, this study has attempted to present the new maps using the combination of the local faults within the region, Sumatran fault, and Sumatran subduction source zones. The composite earthquake catalogue of the study region has been extended to cover an area limited by 10°S–10°N Latitude and 90°–110°E Longitude with the period from 1900 to 2014. The seismic source zones were categorized into subduction and fault sources. Line, area, and background source models were used to model the seismic sources with variable characteristics along them. In order to consider the epistemic uncertainty, logic-tree framework was used to incorporate basic quantities such as different source modelling, maximum magnitudes, and ground-motion prediction equations (GMPEs). The hazard maps are presented over a 12.5 km grid in terms of peak ground acceleration (PGA) for 10 and 2% probabilities of exceedance in 50 years corresponding to 475 and 2475 years return periods (RP), respectively. The proposed new hazard maps give the expected ground motions based on the extended earthquake catalogue, upgraded seismic source parameters, and more compatible GMPEs than applied in the development of previous hazard maps. The estimated PGAs on rock site condition across the Peninsular Malaysia region for RP475 and 2475 years are in the range of 1.0–10.0%g and 2.0–20.0%g, respectively. The horizontal elastic acceleration response spectra on different soil site conditions have been also presented for the region of interest following the principles of Eurocode 8 through the calculated uniform hazard spectra.

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

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

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

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

Characterizing the Epistemic Uncertainty in the USGS 2014 National Seismic Hazard Mapping Project (NSHMP)

Characterizing the Epistemic Uncertainty in the USGS 2014 National Seismic Hazard Mapping Project (NSHMP)

Evaluasi Struktur Gedung X di Jakarta Berdasarkan SNI 03-1726-2012 Ketahanan Gempa untuk Struktur Gedung

E arthquake risk in Jakarta is one of intermediate category in Indonesia b ased on the 2010 seismic hazard map published by the Ministry of Public Works of Republic Indonesia. The purpose of this research was to know the ultimate performance limit of the existing X building in Jakarta . Evaluation of these building was based on guidelines SNI 03-1726-2012, SNI 03-2847-2013 and PPPURG 1987. The structure m odel of X building was designed and analyzed using ETABS Version 9.7.2. The result showed value of story drift was affected by dynamic response spectrum load, the maximum drift in x – direction is 68.60 mm and y – direction is 101.2 mm. Th e X building was declared unsafe in performance condition of the ultimate limits. It was important to know the condition of the building that would be affected by earthquake load and to prevent collapse of the building structures that c ould cause loss of live people in the building and the collisions between buildings. Keywords : building, earthquake, respon spectrum analysis, story drift.

Performance of an Existing Reinforced Concrete Building Designed in Accordance to Older Indonesian Seismic Code: A Case Study for a Hotel in Kupang, Indonesia

The recent seismic code SNI 1726-2012 is significantly different compared to the older code SNI 1726-2002. The seismic hazard map was significantly changed and the level of maximum considered earthquake was significantly increased. Therefore, buildings designed according to outdated code may not resist the higher demand required by newer code. In this study, seismic performance of Hotel X in Kupang, Indonesia which was designed based on SNI-1726-2002 is investigated. The structure was analyzed using Nonlinear Time History Analysis. The seismic load used was a spectrum consistent ground acceleration generated from El-Centro 18 May 1940 North-South component in accordance to SNI 1726-2012. The results show that Hotel X can resist maximum considered earthquake required by SNI 1726-2012. The maximum drift ratio is 0.81% which is lower than the limit set by FEMA 356-2000 (2%). Plastic hinge damage level is also lower than the allowance in ACMC 2001.

Seismic Hazard Map for Papua Island

Development of seismic hazard maps for Indonesia has been conducted by experts and the results published in many science media, such as seminars and journals. However, published seismic hazard maps of Papua Island, which comprises two territories, Indonesian Papua and Papua New Guinea, are rarely found. In this paper a seismic hazard map of Papua (Papua Indonesia and Papua New Guinea) has been developed. The map was developed using probabilistic seismic hazard analysis. The analysis also used updated earthquake epicenter data up to 2016 and seismic sources studied by seismologists and geologists. The result of the complete seismic hazard analysis was a seismic hazard map of Papua with a hazard level of 10% probability of exceedance over 50 years. From the map, it can be noticed that ground motion across Papua Island is 0.06g-2.01g.

Evolution of seismic hazard maps in Turkey

A review on the historical evolution of seismic hazard maps in Turkey is followed by summarizing the important aspects of the updated national probabilistic seismic hazard maps. Comparisons with the predecessor probabilistic seismic hazard maps as well as the implications on the national design codes conclude the paper.

Seismic hazard map of the Middle East

The collaborative project Earthquake Model of the Middle East (EMME, 2010–2015) brought together scientists and engineers from the leading research institutions in the region and delivered state-of-the-art seismic hazard assessment covering Afghanistan, Armenia, Azerbaijan, Cyprus, Georgia, Iran, Iraq, Jordan, Lebanon, Palestine, Pakistan, Syria and Turkey. Their efforts have been materialized in the first homogenized seismic hazard model comprising earthquake catalogues, mapped active faults, strong motions databank, ground motion models and the estimated ground motion values for various intensity measure types and relevant return periods (e.g. 475–5000 years). The reference seismic hazard map of the Middle East, depicts the mean values of peak ground acceleration with a 10% chance of exceedance in 50 years, corresponding to a mean return period of 475 years. A full resolution poster is provided with this contribution.

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

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

Seismic hazard assessment in the megacity of Blida (Algeria) and its surrounding regions using parametric-historic procedure

The region of Blida is characterized by a relatively high seismic activity, pointed especially during the past two centuries. Indeed, it experienced a significant number of destructive earthquakes such as the earthquakes of March 2, 1825 and January 2, 1867, with intensity of X and IX, respectively. This study aims to investigate potential seismic hazard in Blida city and its surrounding regions. For this purpose, a typical seismic catalog was compiled using historical macroseismic events that occurred over a period of a few hundred years, and the recent instrumental seismicity dating back to 1900. The parametric-historic procedure introduced by Kijko and Graham (1998, 1999) was applied to assess seismic hazard in the study region. It is adapted to deal with incomplete catalogs and does not use any subjective delineation of active seismic zones. Because of the lack of recorded strong motion data, three ground prediction models have been considered, as they seem the most adapted to the seismicity of the study region. Results are presented as peak ground acceleration (PGA) seismic hazard maps, showing expected peak accelerations with 10% probability of exceedance in 50-year period. As the most significant result, hot spot regions with high PGA values are mapped. For example, a PGA of 0.44 g has been found in a small geographical area centered on Blida city.

Foundation News

The 2010 7.0 MW earthquake that struck southern Haiti had a devastating impact on the country. It is estimated that 230,000 people were killed, 300,000 injured, and 2 million displaced ( https://www.gao.gov/assets/660/658445.pdf ). Since that time, the city of Port-au-Prince, with approximately 3 million inhabitants, continues to expand at a fast pace. Accurate characterization of the regional earthquake hazard, particularly along the active Enriquillo Fault, is key to informing urban development and construction practices during the long reconstruction phase through which Haiti continues to progress. Our team recently showed that the seismic hazard map currently in use is significantly incomplete for the Port-au-Prince metropolitan area. This conclusion was reached based on the discovery of an overlooked component of north-south shortening along the Cul-de-Sac Plain to the north of the Massif de la Selle using space geodetic measurements from GPS. Therefore, new regional seismic hazard estimates are needed to better inform development in order to help lessen the devastating impact of future seismic activity.

Updating active fault maps and sliprates along the Sumatran Fault Zone, Indonesia

The accuracy of active fault map, slip rate and its seismic parameters is crucial for seismic hazard analysis. Fault maps, segmentations and slip rates of the Sumatran Fault Zone (SFZ) have been revised in relation with ongoing activities for updating Indonesian seismic hazard map. In the northern part, several secondary fault strands in the eastern side of the main SFZ are added, including the Pidie, Biruen, Lhok-Sumawe, Peusangan, and Oreng faults. The Batee fault is now considered active. In the southern part, from Suoh pull-apart graben, SFZ branches into two major strands: the west and east Semangko fault segments. Toward south, the west and east Semangko faults are connected with series of marine grabens in the Sunda Strait, forming a 70-km-wide pull-apart structure that is bounded by SFZ and the Ujung Kulon fault, which carries SFZ dextral movement further south into southwest of Java island. Previously, slip rates along SFZ are considered increasing northward from about 5 mm/yr in Sunda Strait to 30 mm/yr in Toba Area. Consequently, fore arc region was thought to be stretched. Nowadays, according to the latest geological and GPS studies, slip rates appear to be more constant at ∼15 mm/yr. The total amount of parallel-SFZ extension on the Sunda-strait marine grabens is estimated to be about 18.7 km, almost identical with the largest geomorphic offset along SFZ. In assumption, the SFZ onset since 2 Ma indicates a slip rate of about 9 mm/yr in Sunda Strait. New slip rate measurement near Lake Ranau yields 8-12 mm/yr. Revised slip-rate measurements in both Lake Maninjau and Lake Toba yield about similar rates, ∼14-15 mm/yr. Thus, Sumatran fore-arc acts move northward along SFZ, which is more like a rigid block instead of much stretched.

Update of the Urban Seismic and Liquefaction Hazard Maps for Memphis and Shelby County, Tennessee: Liquefaction Probability Curves and 2015 Hazard Maps

Update of the Urban Seismic and Liquefaction Hazard Maps for Memphis and Shelby County, Tennessee: Liquefaction Probability Curves and 2015 Hazard Maps

Seismic hazard assessment of the Shillong Plateau, India

The Shillong Plateau is an earthquake-prone region in the northeastern India. Based on regional seismotectonic studies, we present here a deterministic seismic hazard assessment (DSHA) and maps of peak horizontal accelerations (PHA) for three largely populated districts – the East Khasi hills, the Ri-Bhoi, and the West Garo hills – within the Shillong Plateau. The hazard analysis methodology is based on the analysis of 72 earthquake sources (active faults) located within 500 km seismotectonic region around the plateau. Using an average sample log-likelihood approach, suitable ground motion prediction equations (GMPEs) are identified. As a variation in hypocentral distances can affect the ranks (or weights) of selected GMPEs, DSHA is performed separately for the three selected districts. Analyses show that the northern part of the East Khasi hills, eastern part of Ri-Bhoi district and the West Garo hills districts exhibit the highest PHA value of 0.46 g at site class A (hard rocks). In addition, response spectra for the Shillong city, Nongpoh, and Tura indicate that the maximum spectral acceleration reaches 0.67 g, 0.77 g, and 0.64 g at 0.1 s, respectively. These assessments indicate that the Barapani, Oldham, and Dauki faults influence significantly the seismic hazard in the studied region.

Intelligent seismic risk mitigation system on structure building

Indonesia located on the Pacific Ring of Fire, is one of the highest-risk seismic zone in the world. The strong ground motion might cause catastrophic collapse of the building which leads to casualties and property damages. Therefore, it is imperative to properly design the structural response of building against seismic hazard. Seismic-resistant building design process requires structural analysis to be performed to obtain the necessary building responses. However, the structural analysis could be very difficult and time consuming. This study aims to predict the structural response includes displacement, velocity, and acceleration of multi-storey building with the fixed floor plan using Artificial Neural Network (ANN) method based on the 2010 Indonesian seismic hazard map. By varying the building height, soil condition, and seismic location in 47 cities in Indonesia, 6345 data sets were obtained and fed into the ANN model for the learning process. The trained ANN can predict the displacement, velocity, and acceleration responses with up to 96% of predicted rate. The trained ANN architecture and weight factors were later used to build a simple tool in Visual Basic program which possesses the features for prediction of structural response as mentioned previously.

Development of two components acceleration time histories for Semarang, Indonesia, due to Semarang fault earthquake scenarios using 30 meters soil deposit model

Development of surface acceleration time histories is important for dynamic analysis of structure design and evaluation. Acceleration time histories usually developed from seismograph records due to specific earthquake event. Following the research conducted by Team for Revision of Seismic Hazard Maps of Indonesia 2010 and 2016, Lasem fault and Semarang fault are two closest and dangerous shallow crustal fault earthquake sources which must be taken into account for seismic mitigation of Semarang. This paper presents the development two components surface acceleration time histories for Semarang caused by Semarang fault earthquake scenarios, with magnitude from 6 Mw to 7 Mw and maximum epicentre distance 15 Km. This research was performed by conducting deterministic hazard analysis, response spectral matching and site response analysis to obtain a pair of modified acceleration time histories. Site response analysis was performed by conducting 30 meters soil deposit model by taking the assumption that the position of bedrock elevation is 30 meters below the surface layer. Modified acceleration time histories were developed from a pair time histories (North-South/NS and East-West/EW direction) collected from worldwide historical earthquakes. Modified time histories were developed due to limited time histories data caused by Semarang fault earthquake source.

Development of seismic risk microzonation map for Semarang due to Semarang fault earthquake scenarios with maximum magnitude 6.9 Mw

Research on seismic microzonation of Semarang is still ongoing. The first seismic microzonation research for this area was performed on 2015. Seismic microzonation map was developed by implementing deterministic 1-D site response analysis at 190 boring locations. Lasem fault was considered to be the main earthquake source which taken into account for seismic microzonation research of Semarang. The second research for developing seismic microzonation map was performed on 2016. Following the research conducted by Team for Updating Seismic Hazard Maps of Indonesia 2016, Rawapening Fault, Ungaran Fault, Weleri Fault, Demak Fault and Semarang Fault are five new shallow crustal fault earthquake sources identified in this research. This paper presents the development of seismic risk microzonation map caused by Semarang fault earthquake scenarios with maximum 6.9 Mw. Deterministic 1-D site response analysis was performed at 288 boring locations for developing seismic risk microzonation map. This research was performed by implementing response spectral matching and site propagation analysis. Due to inadequate data caused by Semarang fault earthquake, response spectral matching was implemented in this research to obtain modified acceleration time histories. All acceleration time histories were developed from five different earthquakes with magnitude 6.05 – 6.9 Mw and maximum epicentre distance 15 Km.