California Historical Intensity Mapping Project (CHIMP): A Consistently Reinterpreted Dataset of Seismic Intensities for the Past 162 Yr and Implications for Seismic Hazard Maps

Abstract Historical seismic intensity data are useful for myriad reasons, including assessment of the performance of probabilistic seismic hazard assessment (PSHA) models and corresponding hazard maps by comparing their predictions to a dataset of historically observed intensities in the region. To assess PSHA models for California, a long and consistently interpreted intensity record is needed. For this purpose, the California Historical Intensity Mapping Project (CHIMP) has compiled a dataset that combines and reinterprets intensity information that has been stored in disparate and sometimes hard-to-access locations. The CHIMP dataset also includes new observations of intensity from archival research and oral history collection. Version 1 of the dataset includes 46,502 intensity observations for 62 earthquakes with estimated magnitudes ranging from 4.7 to 7.9. The 162 yr of shaking data show observed shaking lower than expected from seismic hazard models. This discrepancy is reduced, but persists, if historical intensity data for the largest earthquakes are smoothed to reduce the effects of spatial undersampling. Possible reasons for this discrepancy include other limitations of the CHIMP dataset, the hazard models, and the possibility that California seismicity throughout the historical period has been lower than the long-term average. Some of these issues may also explain similar discrepancies observed for Italy and Japan.

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Probabilistic seismic hazard maps for California do not perform better relative to historical shaking data when site-specific VS30 is considered

10.5194/egusphere-egu21-6633 ◽

2021 ◽

Author(s):

Molly Gallahue ◽

Leah Salditch ◽

Madeleine Lucas ◽

James Neely ◽

Susan Hough ◽

...

Keyword(s):

Seismic Hazard ◽

Ground Motion ◽

Tall Buildings ◽

Historical Period ◽

Probabilistic Seismic Hazard ◽

Hazard Maps ◽

Site Specific ◽

Seismic Hazard Maps ◽

Intensity Mapping ◽

Aleatory Variability

<div> <p>Probabilistic seismic hazard assessments forecast levels of earthquake shaking that should be exceeded with only a certain probability over a given period of time are important for earthquake hazard mitigation. These rely on assumptions about when and where earthquakes will occur, their size, and the resulting shaking as a function of distance as described by ground-motion models (GMMs) that cover broad geologic regions. Seismic hazard maps are used to develop building codes.</p> </div><div> <p>To explore the robustness of maps&#8217; shaking forecasts, we consider how maps hindcast past shaking. We have compiled the California Historical Intensity Mapping Project (CHIMP) dataset of the maximum observed seismic intensity of shaking from the largest Californian earthquakes over the past 162 years. Previous comparisons between the maps for a constant V<sub>S30</sub> (shear-wave velcoity in the top 30 m of soil) of 760 m/s and CHIMP based on several metrics suggested that current maps overpredict shaking.</p> <p>The differences between the V<sub>S30</sub> at the CHIMP sites and the reference value of 760 m/s could amplify or deamplify the ground motions relative to the mapped values. We evaluate whether the V<sub>S30 </sub>at the CHIMP sites could cause a possible bias in the models.&#160;By comparison with the intensity data in CHIMP, we find that using site-specific V<sub>S30</sub> does not improve map performance, because the site corrections cause only minor differences from the original 2018 USGS hazard maps at the short periods (high frequencies) relevant to peak ground acceleration and hence MMI. The minimal differences reflect the fact that the nonlinear deamplification due to increased soil damping largely offsets the linear amplification due to low V<sub>S30</sub>. The net effects will be larger for longer periods relevant to tall buildings, where net amplification occurs.&#160;</p> <div> <p>Possible reasons for this discrepancy include&#160;limitations of the dataset, a bias in the hazard models, an over-estimation of the aleatory variability of the ground motion or that seismicity throughout the historical period has been lower than the long-term average, perhaps by chance due to the variability of earthquake recurrence. Resolving this discrepancy, which is also observed in Italy and Japan, could improve the performance of seismic hazard maps and thus earthquake safety for California and, by extension, worldwide. We also explore whether new nonergodic GMMs, with reduced aleatory variability, perform better than presently used ergodic GMMs compared to historical data.</p> </div> </div>

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Real-time probabilistic seismic hazard assessment based on seismicity anomaly

Natural Hazards and Earth System Science ◽

10.5194/nhess-20-743-2020 ◽

2020 ◽

Vol 20 (3) ◽

pp. 743-753

Author(s):

Yu-Sheng Sun ◽

Hsien-Chi Li ◽

Ling-Yun Chang ◽

Zheng-Kai Ye ◽

Chien-Chih Chen

Keyword(s):

Seismic Hazard ◽

Real Time ◽

Hazard Assessment ◽

Seismic Hazard Assessment ◽

Seismic Source ◽

Seismic Intensity ◽

Time Dependent ◽

Occurrence Rate ◽

Probabilistic Seismic Hazard Assessment ◽

Probabilistic Seismic Hazard

Abstract. Real-time probabilistic seismic hazard assessment (PSHA) was developed in this study in consideration of its practicability for daily life and the rate of seismic activity with time. Real-time PSHA follows the traditional PSHA framework, but the statistic occurrence rate is substituted by time-dependent seismic source probability. Over the last decade, the pattern informatics (PI) method has been developed as a time-dependent probability model of seismic source. We employed this method as a function of time-dependent seismic source probability, and we selected two major earthquakes in Taiwan as examples to explore real-time PSHA. These are the Meinong earthquake (ML 6.6) of 5 February 2016 and the Hualien earthquake (ML 6.2) of 6 February 2018. The seismic intensity maps produced by the real-time PSHA method facilitated the forecast of the maximum expected seismic intensity for the following 90 d. Compared with real ground motion data from the P-alert network, our seismic intensity forecasting maps showed considerable effectiveness. This result indicated that real-time PSHA is practicable and provides useful information that could be employed in the prevention of earthquake disasters.

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Probabilistic seismic hazard assessment in Greece – Part 3: Deaggregation

Natural Hazards and Earth System Science ◽

10.5194/nhess-10-51-2010 ◽

2010 ◽

Vol 10 (1) ◽

pp. 51-59 ◽

Cited By ~ 3

Author(s):

G-A. Tselentis ◽

L. Danciu

Keyword(s):

Seismic Hazard ◽

Peak Ground Acceleration ◽

Seismic Hazard Assessment ◽

Earthquake Hazard ◽

Earthquake Magnitude ◽

Probabilistic Seismic Hazard Assessment ◽

Hazard Maps ◽

Ground Acceleration ◽

Dense Grid ◽

Motion Parameters

Abstract. The present third part of the study, concerning the evaluation of earthquake hazard in Greece in terms of various ground motion parameters, deals with the deaggregation of the obtained results The seismic hazard maps presented for peak ground acceleration and spectral acceleration at 0.2 s and 1.0 s, with 10% probability of exceedance in 50 years, were deaggregated in order to quantify the dominant scenario. There are three basic components of each dominant scenario: earthquake magnitude (M), source-to-site distance (R) and epsilon (ε). We present deaggregation maps of mean and mode values of M-R-ε triplet showing the contribution to hazard over a dense grid.

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Comparing Probabilistic Seismic Hazard Maps with ShakeMap Footprints for Indonesia

Seismological Research Letters ◽

10.1785/0220190171 ◽

2020 ◽

Vol 91 (2A) ◽

pp. 847-858

Author(s):

Adrien Pothon ◽

Philippe Gueguen ◽

Sylvain Buisine ◽

Pierre-Yves Bard

Keyword(s):

Seismic Hazard ◽

Hazard Assessment ◽

Selection Process ◽

Seismic Hazard Assessment ◽

Probabilistic Seismic Hazard Assessment ◽

Probabilistic Seismic Hazard ◽

Hazard Maps ◽

Data Set ◽

Seismic Hazard Maps ◽

The Past

Abstract A number of probabilistic seismic hazard assessment (PSHA) maps have been released for Indonesia over the past few decades. This study proposes a method for testing PSHA maps using U.S. Geological Survey ShakeMap catalog considered as historical seismicity for Indonesia. It consists in counting the number of sites on rock soil for which the independent maximum peak ground acceleration (PGA) of the ShakeMap footprints between May 1968 and May 2018 exceeds the thresholds from the PSHA map studied and in comparing this number with the probability of exceedance given in the PSHA map. Although ShakeMap footprints are not as accurate and complete as continuous recorded ground motion, the spatially distributed ShakeMap covers 7,642,261 grid points, with a resolution of 1 km2, compensating the lack of instrumental data over this period. This data set is large enough for the statistical analysis of independent PGA values on rock sites only. To obtain the subdata set, we develop a new selection process and a new comparison method, considering the uncertainty of ShakeMap estimates. The method is applied to three PSHA maps (Global Seismic Hazard Assessment Program [GSHAP], Global Assessment Report [GAR], and Standar Nasional Indonesia [SNI2017]) for a selection of sites first located in Indonesia and next only in the western part of the country. The results show that SNI2017 provides the best fit with seismicity over the past 50 yr for both sets of rock sites (whole country and western part only). At the opposite, the GAR and GSHAP seismic hazard maps only fit the seismicity observed for the set of rock sites in western Indonesia. This result indicates that this method can only conclude on the spatial scale of the analysis and cannot be extrapolated to any other spatial resolution.

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Real-time probabilistic seismic hazard assessment based on seismicity anomaly

10.5194/nhess-2019-167 ◽

2019 ◽

Author(s):

Yu-Sheng Sun ◽

Hsien-Chi Li ◽

Ling-Yun Chang ◽

Zheng-Kai Ye ◽

Chien-Chih Chen

Keyword(s):

Seismic Hazard ◽

Real Time ◽

Hazard Assessment ◽

Seismic Hazard Assessment ◽

Seismic Source ◽

Seismic Intensity ◽

Time Dependent ◽

Probabilistic Seismic Hazard Assessment ◽

Probabilistic Seismic Hazard ◽

The Real

Abstract. The real-time Probabilistic Seismic Hazard Assessment (PSHA) is developed for considering the practicability for daily life and the rate of seismic activity with time. The real-time PSHA follows the traditional PSHA framework, but the statistic occurrence rate is substituted by time-dependent seismic source probability. Pattern Informatics method (PI) is a proper time-dependent probability model of seismic source, which have been developed over a decade. Therefore, in this research, we chose the PI method as the function of time-dependent seismic source probability and selected two big earthquakes in Taiwan, the 2016/02/05, Meinong earthquake (ML 6.6) and the 2018/02/06, Hualien earthquake (ML 6.2), as examples for the real-time PSHA. The forecasting seismic intensity maps produced by the real-time PSHA present the maximum seismic intensity for the next 90 days. Compared to real ground motion data from the P-alert network, these forecasting seismic intensity maps have considerable effectiveness in forecasting. It indicates that the real-time PSHA is practicable and can provide a useful information for the prevention of earthquake disasters.

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Do PSHA maps overpredict or are there shaking deficits in the historic record?

10.5194/egusphere-egu21-12450 ◽

2021 ◽

Author(s):

Leah Salditch ◽

Seth Stein

Keyword(s):

Seismic Hazard ◽

Ground Motion ◽

Performance Metrics ◽

Seismic Hazard Assessment ◽

Probabilistic Seismic Hazard Assessment ◽

Ground Shaking ◽

Intensity Mapping ◽

Time Period ◽

Probabilistic Forecasts ◽

The Difference

<p>Probabilistic Seismic Hazard Assessment (PSHA) attempts to forecast the fraction of sites on a hazard map where ground shaking will exceed the mapped value within some time period. Because the maps are probabilistic forecasts, they explicitly assume that shaking will exceed the mapped value some of the time. At a point on a PSHA map, the probability p that during t years of observations shaking will exceed the value on a map with a T-year return period is assumed to be described by the exponential cumulative density function: p = 1 &#8211; exp(-t/T). The fraction of sites, f, where observed shaking exceeds the mapped value should behave the same way. To assess the 2018 USGS National Seismic Hazard Model maps for California, we created the California Historical Intensity Mapping Project (CHIMP), a 162-yr long dataset that combines and consistently reinterprets seismic intensity information that has been stored in disparate and sometimes hard-to-access locations (Salditch et al., 2020). We use two performance metrics; M0 based on the fraction of sites where modeled ground motion is exceeded, and M1 based on of the difference between the mapped and observed ground motion at all sites. M0 is implicit in PSHA because it measures the difference between the predicted and observed fraction of site exceedances and is therefore a key indicator of map performance.</p><p>We explore these metrics for CHIMP. Assuming the dataset to be correct, it appears that the hazard maps overpredicted shaking even correcting for the time period involved. Assuming the model is also correct, a shaking deficit exists between the model and observations. Possible reasons for this apparent overprediction/shaking deficit include: 1) the observations in CHIMP are biased low; 2) the observation period has been less seismically active than typical &#8211; either by chance or temporal variability due to stress shadow effects; 3) the model overpredicts due to either the earthquake rupture forecast or the ground motion models. Similar overpredictions appear for past shaking data in Italy, Japan, and Nepal, implying that seismic hazards are often overestimated. Whether this reflects too-high models and/or biased data remains an important question.</p>

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Probabilistic seismic hazard assessment for Hanoi city

Vietnam Journal of Earth Sciences ◽

10.15625/0866-7187/41/4/14235 ◽

2019 ◽

Vol 41 (4) ◽

pp. 321-338

Author(s):

Pham The Truyen ◽

Nguyen Hong Phuong

Keyword(s):

Seismic Hazard ◽

Hazard Assessment ◽

Seismic Hazard Assessment ◽

Probabilistic Seismic Hazard Assessment ◽

Probabilistic Seismic Hazard ◽

Earthquake Catalog ◽

Return Periods ◽

Hazard Maps ◽

Seismic Hazard Maps ◽

S Period

In this study, the methodology of probabilistic seismic hazard assessment proposed by Cornell and Esteva in 1968 was applied for Hanoi city, using an earthquake catalog updated until 2018 and a comprehensive seismotectonic model of the territory of Vietnam and adjacent sea areas. Statistical methods were applied for declustering the earthquake catalog, then the maximum likelihood method was used to estimate the parameters of the Gutenberg–Richter Law and the maximum magnitude for each seismic source zone. Two GMPEs proposed by Campbell & Bozorgnia (2008) and Akkar et al., (2014) were selected for use in hazard analysis. Results of PSHA for Hanoi city are presented in the form of probabilistic seismic hazard maps, depicting peak horizontal ground acceleration (PGA) as well as 5-hertz (0.2 sec period) and 1-hertz (1.0 sec. period) spectral accelerations (SA) with 5-percent damping on a uniform firm rock site condition, with 10%, 5%, 2% and 0,5% probability of exceedance in 50 years, corresponding to return times of 475; 975; 2,475 and 9,975 years, respectively. The results of PSHA show that, for the whole territory of Hanoi city, for all four return periods, the predicted PGA values correspond to the intensity of VII to IX degrees according to the MSK-64 scale. As for the SA maps, for all four return periods, the predicted SA values at 1.0 s period correspond to the intensity of VI to VII, while the predicted SA values at 0.2 s period correspond to the intensity of VIII to X according to the MSK-64 scale. This is the last updated version of the probabilistic seismic hazard maps of Hanoi city. The 2019 probabilistic seismic hazard maps of Hanoi city display earthquake ground motions for various probability levels and can be applied in seismic provisions of building codes, insurance rate structures, risk assessments, and other public policy.

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