19-22. Testing the 2018 National Seismic Hazard Model
Closing Date: January 4, 2021
This Research Opportunity will be filled depending on the availability of funds. All application materials must be submitted through USAJobs by 11:59 pm, US Eastern Standard Time, on the closing date.
How to Apply
Apply Here
The National Seismic Hazard Model (NSHM) forecasts where, when, and how often earthquakes occur and how strong the resulting ground shaking will be. It is applied in building codes, homeowner and commercial insurance rate setting, public policy decision making, governmental risk assessments, and planning decisions. The probabilistic seismic hazard analyses in the NSHM incorporate two components (1) earthquake source models and (2) ground motion models (GMMs). Each component has large uncertainties that affect the hazard model's capacity to forecast future shaking.
The Research Opportunity seeks to leverage recently developed data and methods for testing the NSHM with simulations and empirical intensity and ground shaking data to develop new frameworks for the seismic hazard calculations. We seek a candidate to conduct research on testing of the NSHM and its components, including comparison of model predictions with observed shaking and intensity data over the past two centuries. It is critical for the NSHM Project to assess the usefulness of the modeling components and the overall hazard model that incorporates these components. The insights from this model testing will allow us to improve the NSHMs and increase the acceptance of the model in the seismological and earthquake engineering communities. Similar to the CSEP methodology, we need to compare the intensity database to a suite of long-term shaking simulations. Comparison of these simulations to our observed dataset will allow us to further explore the range of variability in acceptable models and assess their uncertainties.
Example research directions that may be addressed by the Fellow are provided below, but other research efforts to improve earthquake recurrence and/or ground motion characterizations in seismic hazard products are also encouraged.
(1) While comparisons by Stirling and Petersen (2006) showed that ground shaking across the U.S. was roughly compatible with the observed intensity data, new assessments by Salditch et al. (2020) indicate that observed intensity data show shaking lower than expected from seismic hazard models for California. Why? Possible reasons for this discrepancy include limitations of the dataset, a bias in the hazard models, or that seismicity throughout the historical period has been lower than the long-term average, perhaps purely by chance due to the variability of earthquake recurrence such that California and other active areas have experienced a lull in seismic moment release. Changes in the mean rate of earthquakes could explain a bias in the hazard models for California.
(2) Does the discrepancy reflect limitations of the dataset? The Salditch et al. (2020) dataset assumes that large events (Mw ≥ 6.0) control maximum observed intensities. However, smaller earthquakes can generate locally high intensities. It is possible to assess the extent to which smaller earthquakes contribute to hazard derived from the NSHM by recalculating it using only Mw ≥ 6.0 sources.
(3) Are available intensity data, including California Historical Intensity Mapping Project (CHIMP) data, other historical intensity data, and recent data from the Did You Feel It? (DYFI) system, consistent with published ground motion models applied in the products of the NSHMs? How do the aleatory variabilities and epistemic uncertainties applied in the NSHMs compare with the intensity data? To assess a possible bias in the ground motion models we need to explore regional variability in ground shaking. Regional differences in these uncertainty parameters could help explain why ground shaking levels are lower or higher than expected in active portions of California. Several investigators have explored non-ergodic ground motions which define alternative ways to assess epistemic uncertainty and aleatory variability. Understanding these regional differences may help us understand these biases. Moreover, damage is often more correlated with PGV or longer period spectral accelerations than with PGA.
(4) Are the differences between the historical intensity data and NSHM prediction likely due to the variability of earthquake recurrence? This can be explored via numerical simulations using an ensemble of earthquake histories consistent with the NSHM to generate long shaking histories. Comparing the ensemble to the NSHM predictions will indicate which (if any) inputs to the NSHM should be reevaluated and improved to make the models more compatible with the intensity data recorded over the past two centuries.
The goal of this work is to improve the NSHMs through testing input components and the final model. This will improve the reliability and acceptability of the model in building codes, risk assessments, and other public policy applications. Interested applicants are strongly encouraged to contact the Research Advisor(s) early in the application process to discuss project ideas.
References:
Salditch, L., Gallahue, Molly M., Lucas, et al. (2020) California historical intensity mapping project (CHIMP): A consistently reinterpreted dataset of seismic intensities for the past 162 yr and implications for seismic hazard maps, Seismological Research Letters, doi: 10.1785/0220200065.
Stirling, M. and Petersen, M. (2006) Comparison of the historical record of earthquake hazard with seismic-hazard models for New Zealand and the continental United States, Bulletin of the Seismological Society of America, 96(6): 1978-1994.
Proposed Duty Station: Golden, CO
Areas of PhD: Geology, seismology, civil engineering, or related fields (candidates holding a Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).
Qualifications: Applicants must meet one of the following qualifications: Research Geologist, Research Geophysicist, Research Engineer.
(This type of research is performed by those who have backgrounds for the occupations stated above. However, other titles may be applicable depending on the applicant's background, education, and research proposal. The final classification of the position will be made by the Human Resources specialist.)
Human Resources Office Contact: Joseline Martinez Lopez, 303-236-9559, jmartinezlopez@usgs.gov