Seismic Hazard Maps Research Articles

Seismic hazard analysis on Solok Regency, West Sumatra to support local government development program

Solok Regency is an administrative area located in West Sumatra that is currently carrying out disaster mitigation programs. Mostly, major infrastructure such as the Solok Local Government Buildings Complex, school facilities, hospital buildings, and many dense residential buildings are scattered over this area. One notable event happened on September 30, 2009, which forced the local government to take serious prevention steps to reduce casualties and damages in the future. Furthermore, there is a need to develop a comprehensive study to analyze the seismic hazards by determining the value of Peak Ground Acceleration (PGA) at the bedrock. The analysis was carried out using the Probability Seismic Hazard Analysis (PSHA) by calculating several seismic sources towards Solok regency by a radius of 500 kilometers from the Arosuka area for a 2475-year return period. The result showed a PGA value of 1.052g on Arosuka, Solok regency, while the Openquake platform shows the range of PGA values varies from 0.576g – 1.368g. The PGA values were then visualized into a seismic hazard map using a geographic information system (GIS). In addition, these scientific results are used as basic information to estimate the seismic vulnerability to support the disaster risk reduction program in West Sumatra.

Seismic Hazard Maps of Bengkulu City, Indonesia, Considering Probabilistic Spectral Response for Medium and Stiff Soils

Background: This paper presents the extended work of a seismic hazard map for Bengkulu City, Indonesia. In this current study, seismic hazard maps are generated by considering site variations in Bengkulu City, Indonesia. Methods: First, site investigation data is collected. Furthermore, the probabilistic spectral response for Bengkulu City is analysed. The spectral matching method is implemented to obtain appropriate ground motion considering the most dominant earthquake scenario that occurred. A seismic ground response analysis is conducted to obtain several ground motion parameters, such as peak ground acceleration, spectral acceleration values at 0.2 s and 1 s, and ground motion amplification. Results: The results show that peak ground acceleration in the study area is generally within the range of 0.5 to 0.6g. It indicates that most sites in Bengkulu city could undergo strong motion. Spectral accelerations at 0.2 s and 1 s are also dominantly found in the range of 0.9 to 1.2g and the range of 0.5 to 0.7g. Generally, ground motion in the study area could amplify up to 1.1 to 1.5. Conclusion: Spectral acceleration curve for site classes in Bengkulu City shows a similar trend to other spectral accelerations. It indicates that the spectral acceleration proposed in this study could be implemented in the study area.

Seismic hazard maps and spectra deduced for sustainable urban developments in Kuwait

Seismic hazard maps and spectra deduced for sustainable urban developments in Kuwait

Deterministic and probabilistic Seismic Hazard Assessments for Merangin Kerinci Sumatera

This paper presents calculated ground motions for Merangin Kerinci in the Provinsi of Jambi Sumatera. The ground motions were calculated using a probabilistic seismic hazard analysis. The earthquake catalogue used in the analysis included all recorded earthquakes up to the end of July 2019, trimmed for magnitude completeness. Uncertainty in input parameters was considered using a logic tree, with branches including shallow crustal faults of the Great Sumatran Faults and Sumatera Megathrust Subduction. Ground motions are presented for the local site conditions, measured at those sites which can be classified as Site Class D/C (stiff soil to Soft Rock/Very Dense Soil). Ground motions, including Peak Ground Acceleration (PGA), and spectral accelerations at periods ranging from 0.1 s to 10.0s were calculated the site. Data are presented for return periods of 175 years, 475 years, 2,500 years, 5,000 years, and 10,000 years for PSHA, and at mean, 50th, and 84th percentile confidence levels for DSHA. Compared to the Indonesian Seismic Hazard Map (ISHM) 2017 (at DSHA at 5% damping and 84th Percentile), the deterministic PGA values calculated in this study are relatively closed, which is accounted for 0.58g found in this study compared to the range of 0.6g – 0.7 in the ISHM 2017. On the other hand, the probabilistic PGA values for a particular of 5,000 years return period (SEE), the PGA values found in this assessment is 0.73g which is lower than the range of 0.8g – 0.9g in the ISHM 2017.

A data-driven artificial neural network model for the prediction of ground motion from induced seismicity: The case of The Geysers geothermal field

Ground-motion models have gained foremost attention during recent years for being capable of predicting ground-motion intensity levels for future seismic scenarios. They are a key element for estimating seismic hazard and always demand timely refinement in order to improve the reliability of seismic hazard maps. In the present study, we propose a ground motion prediction model for induced earthquakes recorded in The Geysers geothermal area. We use a fully connected data-driven artificial neural network (ANN) model to fit ground motion parameters. Especially, we used data from 212 earthquakes recorded at 29 stations of the Berkeley–Geysers network between September 2009 and November 2010. The magnitude range is 1.3 and 3.3 moment magnitude (Mw), whereas the hypocentral distance range is between 0.5 and 20 km. The ground motions are predicted in terms of peak ground acceleration (PGA), peak ground velocity (PGV), and 5% damped spectral acceleration (SA) at T=0.2, 0.5, and 1 s. The predicted values from our deep learning model are compared with observed data and the predictions made by empirical ground motion prediction equations developed bySharma et al. (2013)for the same data set by using the nonlinear mixed-effect (NLME) regression technique. For validation of the approach, we compared the models on a separate data made of 25 earthquakes in the same region, with magnitudes ranging between 1.0 and 3.1 and hypocentral distances ranging between 1.2 and 15.5 km, with the ANN model providing a 3% improvement compared to the baseline GMM model. The results obtained in the present study show a moderate improvement in ground motion predictions and unravel modeling features that were not taken into account by the empirical model. The comparison is measured in terms of both theR2statistic and the total standard deviation, together with inter-event and intra-event components.

Validation of seismic hazard curves using a calibrated 14 ka lacustrine record in the Eastern Alps, Austria

Seismic hazard maps are crucial for earthquake mitigation and mostly rely on probabilistic seismic hazard analysis (PSHA). However, the practise and value of PSHA are under debate because objective testing procedures for seismic hazard maps are scarce. We present a lacustrine turbidite record revealing 44 earthquakes over the last ~ 14 ka and use it to test seismic hazard curves in southern Austria. We derive local seismic intensities for paleo-earthquakes by applying scaling relationships between the sedimentary imprint and seismic intensity of well-documented historical earthquakes. The last ~ 2.8 ka of the record agree with a Poissonian recurrence behaviour and therefore a constant hazard rate, which is the modelling choice for standard PSHA. The lacustrine data are consistent with the intensity-frequency relationship of the local seismic hazard curve, confirming the current PSHA approach for this part of Austria. On longer timescales, distinct phases of enhanced regional seismicity occurred, indicating a potential increase of seismic hazard after large earthquakes—a factor hitherto disregarded in the PSHA of the Eastern Alps. Our new method forms an independent procedure to test hazard maps in any setting where suitable lake systems are available.

Study of Local Site Conditions for Seismic Hazard Assessment at the BHU Campus, Varanasi, North India, using Ambient Noise Measurements

Abstract The ambient noise measurement approach has been applied for detailed seismic hazard mapping in the Banaras Hindu University (BHU), campus, Varanasi. Thirty three single stations, two standard penetration tests (SPT), and two array micro tremor measurements were carried out to determine the local site characteristics. In this study, H/V spectral ratio confirms that the sites have an average predominant frequency of around 0.53Hz and an average amplitude of 7.94. These resonant frequencies are related to the thickness of the sediments in the region. Based on the available lithological data and estimated sub-surface structures, shallow and deeper cross-sections through two profiles within the BHU campus are presented. The estimated shallow sub-surface structures are correlated with 150 m boreholes data for a better understanding of sub-soil stratification. These studies show the presence of clay up to a depth of ~40 m, mixed with sand and pebbles at some locations, followed by layers of sand, and clay with pebbles ~200 m. Findings of the present study are also well correlated with inverted shear wave velocity profiles. The Vs observed from the array measurements and N-value from standard penetration test (SPT) are positively correlated to each other and give a better understating of Vs. Thus, the inverted 1-D shear velocity models clearly show low shear wave velocity having sediment thickness of 30 to 40 meters. Finally, fundamental frequency, amplification, vulnerability index, and shear wave velocity maps are presented. Additionally, the borehole data are used to calibrate the results of the present study of the shallow sub-surface structure. Subsequently, computed maps are a very useful tool for engineers to quantify the intensity of earthquake ground motion, which will be helpful to determine the capacity of buildings to resist earthquakes.

The earthquake environmental effects (EEEs) of the 6th February 2018, Hualien earthquake (Mw=6.4): A contribution to the seismic hazard estimation in the epicentral area

The macroseismic intensity of the February 6, 2018, Mw 6.4, Hualien earthquake, which caused extensive damage around the Hualien area of eastern Taiwan is reassessed using the Environmental Seismic Intensity (ESI-07) scale. We compiled data on earthquake environmental effects (EEEs) caused by the 2018 Hualien earthquake, which includes surface ruptures, ground cracks, liquefaction, and occasional landslides, and estimated the epicentral intensity (I0) as well as site-specific intensities. We found that the ESI-07 epicentral intensity of the Hualien quake in 2018 is IX. We note that the epicentral area of the 2018 Hualien earthquake was the mesoseismal area of the October 22, 1951, (Mw 6.6) Hualien earthquake, as reported in primary contemporary sources and historical earthquake catalogs. The 1951 Hualien earthquakes also caused prominent surface ruptures, liquefaction, and ground cracks. Consequently, we reassess the macroseismic intensities of this historical seismic event and compare it to the Hualien earthquake in 2018. The comparison suggests similar epicentral intensities for the two earthquakes (IX and X ESI-07). Moreover, we conducted a systematic comparison between intensity obtained using different scales which revealed the differences of two to three degrees between the ESI-07 and traditional intensity scales. This result reconfirms the significance of documentation and recording of earthquake environmental effects to make intensity assessments for modern seismic events consistent with the historical earthquake records. Moreover, a re-evaluation of historical earthquake intensity in eastern Taiwan could be performed in order to update the seismic hazard map. Application of the ESI-07 intensity scale of recent and historical earthquakes will be helpful in post-earthquake recovery efforts for a future earthquake. The prepared ShakeMaps from the ESI-07 values suggests completely different shapes to the previously generated ShakeMaps considering the peak ground acceleration or peak ground velocity. It suggests that the ShakeMaps prepared from the earthquake environmental effects can be complemented with the instrumental based intensity map to have a better seismic hazard prediction and future land use planning for the region.

A study on the effect of site response on California seismic hazard map assessment

Prior studies have repeatedly shown that probabilistic seismic hazard maps from several different countries predict higher shaking than that observed. Previous map assessments have not, however, considered the influence of site response on hazard. Seismologists have long acknowledged the influence of near-surface geology, in particular low-impedance sediment layers, on earthquake ground-motion at frequencies of engineering concern. Although the overall effects of site response are complex, modern ground-motion models (GMMs) account for site effects using terms based on VS30, the time-averaged shear-wave velocity in the upper 30 m of the Earth’s surface. In this study, we consider general implications of incorporating site terms from modern GMMs using site-specific VS30 as a proxy in probabilistic seismic hazard maps for California. At the long periods (1–5 s) that affect tall buildings, site terms amplify the mapped hazard by factors of 1–3 at many sites relative to maps calculated for the standard reference soft-rock site condition, VS30 = 760 m/s. However, at the short periods of ground-motion that are the main contributors to peak ground acceleration (PGA) and thus affect smaller structures, only negligible effects occur due to nonlinear deamplification of strong ground-motion at high frequencies. Nonlinear deamplification increases as the shaking level increases. For very strong shaking, deamplification can overcome the linear amplification, yielding net deamplification. We explore the implications of these results for the evaluation of hazard maps. Because site effects do not change the maps appreciably at short periods, we can exclude site response as an explanation for why the maps overpredict historically observed shaking as captured by the California Historical Intensity Mapping Project (CHIMP) dataset. The results are expected to be generalizable to regions that are comparable to California in terms of structure and seismicity rates. In low-to-moderate-seismicity regions where the hazard reflects weaker shaking, nonlinear site response is expected to be less important for the hazard.

Seismic hazard map of India and neighbouring regions

This article presents probabilistic seismic hazard analysis (PSHA) of India and adjoined region, carried out to develop a new national seismic hazard map for India. The hazard map is developed using fault oriented spatially smoothed seismicity approach. A catalog of earthquakes has been compiled for the region (Latitude 50N − 400 N and Longitude 650E − 1000E) from 2600BCE to 2019CE to estimate the seismicity parameters. Eighteen suitable ground motion prediction equations in the logic tree framework are used for the four major geological regions of the country. The hazard is estimated at rock sites (B-C boundary type) conditions in terms of peak ground acceleration (PGA), short-period (0.2 s), and long-period (1s) spectral acceleration maps and uniform hazard spectra, with 2% and 10% probabilities of exceedance in 50 years. Higher hazard values are observed in the Hindukush-Pamir regions and Northeast India, whereas central India and the southern peninsular regions are less prone to seismic threat. The proposed maps find their application in the seismic design of structures, risk assessment, and as an input for updating the existing code provisions.

Identifying Exposure of Urban Area to Certain Seismic Hazard Using Machine Learning and GIS: A Case Study of Greater Cairo

The 1992 Cairo earthquake, with a moment magnitude of 5.8, is the most catastrophic earthquake to shock the Greater Cairo (GC) in recent decades. According to the very limited number of seismological stations at that time, the peak ground acceleration (PGA) caused by this event was not recorded. PGA calculation requires identification of nature of the earthquake source, the geologic setting of the path between the source and site under investigation and soil dynamic properties of the site. Soil dynamic properties are acquired by geotechnical investigations and/or geophysical survey. These two methods are costly and are not applicable in regional studies. This study presents an adaptive and reliable PGA prediction model using machine learning (ML) along with six standard geographic information system (GIS) interpolation methods (IDW, Kriging, Natural, Spline, TopoToR, and Trend) to predict the spatial distribution of PGA caused by this event over the GC. The model is employed to estimate the exposure of the urban area and population in the GC based on the available geotechnical and geophysical investigations. The exposure (population) data is from free and easy-access sources, e.g., Landsat images and the Global Human Settlement Population Grid (GHS-POP). The results show that Natural, Spline, and Trend are not suitable GIS interpolation techniques for generating seismic hazard maps (SHMs), while the Kriging Method shows sufficient prediction. Interestingly, with an accuracy of 96%, the ML model outperforms the classical GIS methodologies.

“Ghost Transient” Corrections to the Southern California GPS Velocity Field from San Andreas Fault Seismic Cycle Models

Abstract Seismic cycle models of the northern and southern San Andreas fault (SAF) were developed to estimate corrections for viscoelastic transients embedded in the present-day Global Positioning System (GPS) velocity field. These models incorporate a viscous shear zone embedded in either a layered or a 3D viscoelastic structure. In the southern SAF model, the 3D effective viscosity structure is based on the Southern California Earthquake Center (SCEC) community rheology model (CRM) and the SCEC community thermal model. Viscoelastic materials are represented with Burgers or Maxwell viscoelastic rheologies, and ranges of rheological parameters and earthquake chronologies are explored. For the northern and southern SAF models, surface velocity perturbations or “ghost transients” (GTs) of up to 3.5–6 mm/yr are obtained for a wide range of conditions. In all cases, the GT velocities are consistent with left-lateral rather than right-lateral motion across the SAF, and subtracting them from the present-day GPS velocity field increases the apparent SAF offset rate. For the southern SAF model, GT velocities are fairly insensitive to the timing of large SAF earthquakes prior to 1857, but they are sensitive to rheology (i.e., temperatures and strain rates assumed for computing CRM effective viscosities). For the northern SAF model, GT velocities are sensitive to both rheology (mantle, lower crust and shear zone effective viscosities, and Burgers Body parameters Δb and RB) and mean earthquake recurrence interval. For the reference northern and southern SAF models provided to U.S. Geological Survey National Seismic Hazard Mapping Project deformation modelers, the maximum GT velocities are 3.73 and 4.84 mm/yr, respectively.

Near-Real-Time Strong Motion Acquisition at National Scale and Automatic Analysis.

A strong motion monitoring network records data that provide an excellent way to study how source, path, and site effects influence the ground motion, specifically in the near-source area. Such data are essential for updating seismic hazard maps and consequently building codes and earthquake-resistant design. This paper aims to present the Italian Strong Motion Network (RAN), describing its current status, employment, and further developments. It has 648 stations and is the result of a fruitful co-operation between the Italian government, regions, and local authorities. In fact, the network can be divided into three sub-networks: the Friuli Venezia Giulia Accelerometric Network, the Irpinia Seismic Network, and all the other stations. The Antelope software automatically collects, processes, and archives data in the data acquisition centre in Rome (Italy). The efficiency of the network on a daily basis is today more than 97%. The automatic and fast procedures that run in Antelope for the real-time strong motion data analysis are continuously improved at the University of Trieste: a large set of strong motion parameters and correspondent Ground Motion Prediction Equations allow ground shaking intensity maps to be provided for moderate to strong earthquakes occurring within the Italian territory. These maps and strong motion parameters are included in automatic reports generated for civil protection purposes.

Macroseismic intensity-based catalogue of earthquakes in Ecuador

Earthquake magnitude catalogues and peak ground acceleration (PGA) maps for Ecuador may be found in several studies, however, there are rare works on the characterisation of the epicentral macroseismic intensities associated with earthquakes. In view of the concept that macroseismic intensity enables us to categorise the extent and severity of damage to buildings and structures caused by an earthquake, this study aims to compile a macro-seismic intensity-based catalogue of earthquakes in Ecuador, characterise the epicentral macroseismic intensities associated to seismogenic sources and perform a comparison with the National Seismic Hazard Map. This paper is the first that presents a catalogue of earthquakes with macroseismic intensities ≥VII and a series of maps of earthquake epicentres according to intensity, focal depth, data and magnitude of seismic events in Ecuador, based on the study of historical and instrumental records from 1900 to 2021. The obtained data shows that 95% of the territory of Ecuador has a PGA 0.1 g, which corresponds to seismic intensities greater than VII, while regions with seismicityVIII (ag = 0.2 g) constitute 86%, and 3.8% of the territory of Ecuador has very high seismicity (IX), where the PGA exceeds 0.5 g. This information suggests that the normative National Seismic Hazard Map of Ecuador underestimate the hazard mainly in the south-east and in the Central Andes of Ecuador, and require an actualization.

Analysis of Soil Acceleration in The Mentawai Region with The Method Probabilistic Seismic Hazard Analysis (PSHA)

The Mentawai Islands are one of the areas that are active in seismicity. An earthquake measuring 7.2 on the Richter scale on October 25, 2010 resulted in many casualties and material losses. Many buildings collapsed and facilities were damaged so that space managers needed a seismic hazard map to be able to organize the space by considering the disaster aspect. This prompted researchers to conduct research aimed at making seismic hazard maps and knowing the level of earthquake hazard in the Mentawai region. Seismic hazard maps are useful in planning earthquake-resistant buildings and can describe the effects of earthquakes at a location which will help in anticipating community preparedness and earthquake disaster mitigation efforts. Seismic hazard data processing uses the Probabilistic Seismic Hazard Analysis (PSHA) method. PSHA is based on earthquake parameters that produce the largest ground motion. The magnitude of the intensity at a location due to an earthquakein the earthquake source area with a magnitude of M and a distance of R, the attenuation function can be used. The attenuation functions in this study are Joyner-Boore (1997) and Young et al (1997). This type of research is descriptive, namely by collecting NEIC/USGS earthquake catalog data for the period 1950 - 2021 with M 5 SR.The results of this study indicate that the area of ywhich has a high level of seismic hazard is found in the Siberut area with a maximum PGA range of 1.17 g - 3.70 g. The area with a low seismic hazard level is the Pagai area with a PGA range of 0.80 g - 2.86 g. This result represents a 10% chance of being exceeded in 50 years.

Development of seismic map for offshore platform design in Indonesia, case study of the North Coast of Java

Indonesia’s design of earthquake-resistant offshore platforms does not yet have specific regulations. The commonly used standard in Indonesia, API RP 2A WSD, does not explicitly state the earthquake return period for offshore structures. A more detailed procedure is described in ISO 19901-2:2004. Two methods are introduced in the standard. First, the simplified method allows the use of earthquake maps with a return period of 1000 years. Second, the detailed method requires a site-specific seismic hazard study to determine the return period of earthquakes. This paper presents the development of seismic hazard maps using a simplified method following ISO 19901-2:2004. The maps are prepared using the probabilistic method with a case study on the North Coast of Java. The results show that the study area falls into seismic zones 1 and 2. The seismic hazard maps can be used for earthquake resistance design for structures with exposure level L2 and L3 based on the seismic risk category following the ISO.

Local seismic hazard map based on the response spectra of stiff and very dense soils in Bengkulu city, Indonesia

It is well known that seismic hazard assessment should be implemented to design infrastructures in an earthquake-prone area such as Bengkulu. This paper presents local seismic hazard maps based on the response spectra of stiff and very dense soils in Bengkulu city, Indonesia. We collect the soil data and conduct the seismic wave propagation. The input motion for wave propagation analysis is generated from the spectral acceleration curves of stiff and dense soils. Various ground motion parameters such as peak ground acceleration, short-period and long-period spectral accelerations, and amplification factors are presented in microzonation maps. The results show that the peak ground acceleration in the study area ranges from 0.2 to 0.8 g, while the spectral acceleration varies between 0.5–1.5 g and 0.4–0.8 g for periods of 0.2 and 1 s, respectively. The amplification factor of the site is observed to vary from 0.5 to 1.6. Considering other spectral accelerations in Bengkulu, the spectral acceleration design shows a good performance. The results indicate the site characteristics of Bengkulu city, which can provide engineers with site class for structural building design.

Machine learning techniques for estimating seismic site amplification in the Santiago basin, Chile

Seismic site amplification and seismic hazard maps are crucial inputs for decision making and risk evaluation in places where seismicity imposes a significant risk to human life and infrastructure. In this work, we propose a novel machine learning (ML) based methodology to integrate qualitative and quantitative data to map the degree of seismic amplification in an area of Chile, one of the most seismically active countries on Earth. Our method uses measurements of surface shear wave velocities (Vs30) and predominant frequencies (f0) combined with gravity anomaly maps to update the geographic extension of seismic amplification classes. Additionally, we trained the predictive models to interpolate and extrapolate Vs30 and f0 to the unsampled sites. Applying this method to the Santiago basin resulted in (i) a refined seismic amplification map, and (ii) maps of Vs30 and f0 estimated with improved accuracy. The best predictions, obtained by ML techniques and validated through cross-validation, are possibly due to the inclusion of spatial covariates for algorithm training, enhancing the ability of the model to capture the spatial correlations of geological, geophysical and geotechnical data. The estimation of predominant frequencies (f0) is improved considerably by including gravity as a covariant. The accuracy of the f0 predictions apparently depends more on the choice of covariates than on the algorithm used, while the Vs30 predictions are more sensitive to the chosen algorithm. These results illustrate the great potential of machine learning predictive algorithms in digital soil mapping, which surpass traditional geostatistical techniques. The major contribution of this work is to introduce a novel methodology, based on artificial intelligence models, to extend local measurements of site-specific dynamic properties. This information can be used to quantitatively estimate seismic hazard over a regional scale.

Global polygons for terrain classification divided into uniform slopes and basins

Global terrain classification data have been used for various issues related to topography such as the estimation of soil types and of ground vulnerability to earthquakes and the creation of seismic hazard maps. However, due to the resolution of digital elevation models (DEMs), the terrain classification data from previous studies could not discriminate small landforms such as plains at the bottom of narrow valleys and small rises in plains. Owing to the greater regional variation of small landforms, there is trade-off between DEMs of higher resolution and the creation of global geomorphological legends. To address this problem, we first merged regions with similar topographic characteristics using slope gradients and HAND (height above the nearest drainage) calculated by the 90-m-spatial-resolution DEMs interpolated from the multi-error-removed improved-terrain DEM (MERIT DEM), and united the polygons with the unit catchments of the MERIT-Basins dataset, so that the polygons contain calculated terrain measurements (slope gradient, HAND, surface texture, local convexity, sinks) and noise types as attributes, as well as the ID number of the unit catchment. In addition, we performed k-means clustering on the dataset using slope gradient, HAND, and surface texture, which can be combined with the dataset as a simple terrain classification. The clustering results were prepared in 15 and 40 global uniform clusters and 15 and 40 clusters for each basin to understand the global appearance of the terrain and provide zoning data for regional problem-solving. The 15 clusters were prepared to observe the outline of the terrain without any processing, whereas the 40 clusters were prepared to group and reclassify the polygons to create zoning data for each region. This dataset showed improvements in terms of capturing the small rises in plains compared to the authors' previous global terrain classification data. This dataset can be used as a proxy and is expected to contribute to modeling and estimation in various applications that are known to be related to topography. The datasets of this article are available at [https://gisstar.gsi.go.jp/terrain2021/].

Earthquake probability in the National Seismic Hazard Maps for Japan and people’s risk perceptions: the search for more effective expression

This study summarizes the findings of an attitude survey focused on people’s perceptions of seismic hazard maps, which illustrate the risk of an earthquake in each location throughout Japan. These seismic hazard maps depict the likelihood of an earthquake with a seismic intensity of “6 Lower” or more within 30 years, with 3.0% being considered a high possibility. The 3.0% occurrence probability within 30 years can be reworded to 2.0% occurrence probability within 20 years, 0.1% occurrence probability within a year, 4.9% occurrence probability within 50 years, or 39.4% occurrence probability within 500 years when being converted according to a Poisson distribution. In this study, we convert the occurrence probability within 30 years in the seismic hazard maps to obtain that within a year up to that within 1000 years, present the involved risk and demonstrate the yearly probability of the people who see the maps becoming most convinced of the need for countermeasures. Although those are shorter than the occurrence probability within 30 years anyway, it is a characteristic that the peaks existed at the occurrence probability within 10–20 years, not at the occurrence probability within one year or five years. However, the results changed according to the age of the people viewing the maps, and it was when the risk was presented as the occurrence probabilities within 20 and 30 years for the people in their 20–40 s, while it was when the risk was presented the occurrence probabilities within 10 years for the people in their 50–60 s, the perception toward the need of countermeasures increased the most. In addition, regardless of gender and place of residence (coast of the Sea of Japan or the Pacific coast), the perception toward the need of countermeasures peaked at the occurrence probabilities within 10 and 20 years.Graphical