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Updating the crustal fault model for the 2023 National Seismic Hazard Model for Alaska
We present the crustal fault model for Alaska, based on geologic observations, as a primary input for the 2023 revision of the U.S. Geological Survey National Seismic Hazard Model. We update the 2013 Alaska Quaternary fault and fold database to produce a simplified model of 105 fault sections and four fault zone polygons with basic geologic parameters including slip sense and rate. Significant updates include the following: (1) a slip rate of ∼53 mm/year on the Queen Charlotte Fault indicating it accommodates all of the plate boundary motion; (2) quantified slip rates on megathrust splay faults in the southern Prince William Sound region and near Kodiak Island; (3) improved details of structures in the Chugach-St. Elias orogen; (4) revision of the Castle Mountain Fault from right-lateral slip to a predominantly reverse fault; (5) improved Interior Alaska tectonic models that clarify relationships between the Denali, Totschunda, and thrust faults on both sides of the Alaska Range; (6) identified large earthquake sources in the eastern Brooks Range; and (7) omission of the Chatham Strait section of the Denali Fault. The fault model underscores that the collision of the Yakutat microplate is the dominant driver of active crustal faulting in most of Alaska.
Creep rate models for the 2023 US National Seismic Hazard Model: Physically constrained inversions for the distribution of creep on California faults
Widespread surface creep is observed across a number of active faults included in the United States (US) National Seismic Hazard Model (NSHM). In northern California, creep occurs on the central section of the San Andreas fault, along the Hayward and Calaveras faults through the San Francisco Bay Area, and to the north coast region along the Maacama and Bartlett Springs faults. In southern California, creep is observed across the Coachella segment of the San Andreas fault, through the Brawley Seismic Zone, and along the Imperial and Superstition Hills faults. Seismic hazard assessments for California have accounted for creep using various data and methods, including the most recent Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3) in 2013. The purpose of this study is to expand and update the UCERF3 creep rate data set for the 2023 release of the US NSHM and to invert geodetic data and the surface creep rate data for the spatial distribution of interseismic fault creep on California faults using an elastic model with physical creep constraints. The updated surface creep rate compilation consists of a variety of data types including alignment arrays, offset cultural markers, creepmeters, Interferometric Synthetic Aperture Radar, and Global Positioning System data. We compile a total of 497 surface creep rate measurements, 400 of which are new and 97 of which appear in the UCERF3 compilation. We compute creep rate distributions for each of the five 2023 NSHM geodetic‐based and geologic‐based deformation models. Computed creep rates are used to reduce the total fault moment rate available for earthquake sequences in the NSHM model. We find that, despite relatively large variability in model long‐term slip rates across all five deformation models, the variability in depth‐averaged creep rate across all models is relatively small, typically 5–10 mm/yr along the creeping San Andreas fault section and only 2–4 mm/yr along the Maacama and Rodgers Creek‐Hayward faults.
Comparing subduction ground-motion models to observations for Cascadia
We evaluate Cascadia subduction ground-motion models (GMMs), considered for the 2023 US National Seismic Hazard Model (NSHM) update, by comparing observations to model predictions. The observations comprise regional recordings from intraslab earthquakes, including contributions from 2021 and 2022 events in southern Cascadia and global records from interface earthquakes. Since the 2018 NSHM update, new GMMs for Cascadia have been published by the Next Generation Attenuation (NGA)-Subduction Project that require independent evaluation. In the regional intraslab comparisons, we highlight a characteristic frequency dependence for Cascadia data, with short periods having lower ground motions and longer periods being comparable to other subduction zones. We evaluate differences in northern and southern Cascadia and find that the NGA-Subduction GMMs developed using southern Cascadia data perform better in this region than the model that did not consider these data. We compare ground-motion variability in Cascadia with the NGA-Subduction model predictions and find differences at short periods ( T = 0.1 s) due to the use of global versus regional data in the development of these models. Moreover, the within-event component of aleatory variability from the GMMs overpredicts the standard deviation of Cascadia recordings at very short periods ( T < 0.05 s). Using global interface earthquakes as a proxy to evaluate the Cascadia GMMs, we find long-period overprediction from a simulation-based GMM and some of the empirical GMMs. When comparing recent observations, we find a similar misfit to GMMs and the 2010 and 2022 Ferndale earthquakes. Finally, we observe different basin amplification factors arising in different subsets of the data, which indicate that differences in basin factors between empirical GMMs could arise from the data selection choices by the developers. As part of evaluating the regional basin terms, we apply basin amplification factors from the magnitude 9 Cascadia earthquake simulations to the empirical GMMs for interface earthquakes. The comparisons presented in this study indicate that the NGA-Subduction GMMs for Cascadia perform well relative to observations and older subduction GMMs.
Capturing the uncertainty of seismicity observations in earthquake rate estimates: Implications for probabilistic seismic hazard analysis and the USGS National Seismic Hazard Model
The rate of earthquakes in a region is a fundamental input to Probabilistic Seismic Hazard Analysis. We present a Monte Carlo method for computing that rate from seismicity catalogs while including a range of data and analysis uncertainties. This method is applied to regions for which the b value is assumed to be spatially invariant. Each region is broken down into epochs for which each epoch is estimated to have a uniform magnitude of completeness ( M c ). The distribution of earthquake rates for M ≥ M c is determined for each epoch by considering the Poisson likelihood of rates given the number of observed earthquakes with M ≥ M c . We use a Monte Carlo process to include the uncertainty in b , M c , and individual event magnitudes. The result for each epoch is the joint distribution of the Poisson rate of earthquakes with magnitudes larger than the minimum value used to calculate hazard ( M 1 ) and the Gutenberg–Richter b values, which control the extrapolation to other magnitudes. The rate for each region is either the duration‐weighted average over the epochs or, to better capture temporal variations, we also consider mixture models. The mixture models also provide an avenue to allow temporal variations in b values. To implement this joint distribution in a logic tree, we use the mean and 95% confidence branches, each of which is parameterized with an M ≥ M 1 rate and b value. We explore different ways of defining those branches, as well as non‐Gutenberg–Richter branches, and their impact on hazard estimates. The mean hazard, but not the fractiles, is robust with respect to these choices. To illustrate these new methods, we use synthetic data and catalogs from recent U.S. Geological Survey National Seismic Hazard Models for the Central and Eastern United States and for Puerto Rico and the U.S. Virgin Islands.
Evaluation of ground motion models for USGS seismic hazard forecasts: Induced and tectonic earthquakes in the Central and Eastern U.S.
Ground motion model (GMM) selection and weighting introduces a significant source of uncertainty in United States Geological Survey (USGS) seismic hazard models. The increase in moderate moment magnitude induced earthquakes (Mw 4 to 5.8) in Oklahoma and Kansas since 2009, due to increased wastewater injection related to oil and gas production (Keranen et al., 2013; 2014; Weingarten et al., 2015; McNamara et al., 2015a), provides useful near-source (< 40 km) instrumental ground-motion observations for comparisons between central and eastern US (CEUS) induced (Rennolet et al., 2017) and tectonic (Goulet et al., 2014) earthquakes. In this study, we evaluate over 50 GMMs using two well-established probabilistic scoring methods: log likelihood (LLH) (Scherbaum et al., 2004; 2009) and multivariate LLH (MLLH) (Mak et al., 2017). The LLH approach compares the mean and standard deviation (σ) of the observed and modeled ground motions. The MLLH approach advances the LLH method by considering the variability (φ,τ) of multiple correlated variables namely intra- (within) and inter- (between) event residuals. For the probabilistic scoring GMM evaluation methods (LLH, MLLH), we compute horizontal component peak ground acceleration (PGA) and 1s period pseudo spectral acceleration (PSA1.0) total residuals using GMM software (nshmp-haz) recently implemented by the USGS National Seismic Hazard Model Project (NSHMP). We observe from LLH and MLLH scores that: 1) newer GMMs with lower standard deviations (σ,φ,τ) score better than older GMMs with higher published uncertainty; 2) 2014 CEUS GMMs score better for CEUS tectonic earthquakes than induced earthquakes; 3) NGA-West2, G17 and A15 GMMs score well for CEUS induced earthquake ground motions; and 4) NGA-East GMMs score well for CEUS tectonic earthquake ground motions. We also use the LLH and MLLH scores to evaluate GMM weights applied in past USGS seismic hazard forecasts and to inform weighting of GMMs in future seismic hazard forecasts.
U.S. Geological Survey natural hazards science strategy— Promoting the safety, security, and economic well-being of the Nation
Executive Summary The mission of the U.S. Geological Survey (USGS) in natural hazards is to develop and apply hazard science to help protect the safety, security, and economic well-being of the Nation. The costs and consequences of natural hazards can be enormous, and each year more people and infrastructure are at risk. USGS scientific research—founded on detailed observations and improved understanding of the responsible physical processes—can help to understand and reduce natural hazard risks and to make and effectively communicate reliable statements about hazard characteristics, such as frequency, magnitude, extent, onset, consequences, and where possible, the time of future events. To accomplish its broad hazard mission, the USGS maintains an expert workforce of scientists and technicians in the earth sciences, hydrology, biology, geography, social and behavioral sciences, and other fields, and engages cooperatively with numerous agencies, research institutions, and organizations in the public and private sectors, across the Nation and around the world. The scientific expertise required to accomplish the USGS mission in natural hazards includes a wide range of disciplines that this report refers to, in aggregate, as hazard science. In October 2010, the Natural Hazards Science Strategy Planning Team (H–SSPT) was charged with developing a long-term (10-year) Science Strategy for the USGS mission in natural hazards. This report fulfills that charge, with a document hereinafter referred to as the Strategy, to provide scientific observations, analyses, and research that are critical for the Nation to become more resilient to natural hazards. Science provides the information that decisionmakers need to determine whether risk management activities are worthwhile. Moreover, as the agency with the perspective of geologic time, the USGS is uniquely positioned to extend the collective experience of society to prepare for events outside current memory. The USGS has critical statutory and nonstatutory roles regarding floods, earthquakes, tsunamis, landslides, coastal erosion, volcanic eruptions, wildfires, and magnetic storms—the hazards considered in this plan. There are numerous other hazards of societal importance that are considered either only peripherally or not at all in this Strategy because they are either in another of the USGS strategic science plans (such as drought) or not in the overall mission of the USGS (such as tornados).
Natural hazards science strategy
The mission of the U.S. Geological Survey (USGS) in natural hazards is to develop and apply hazard science to help protect the safety, security, and economic well-being of the Nation. The costs and consequences of natural hazards can be enormous, and each year more people and infrastructure are at risk. USGS scientific research—founded on detailed observations and improved understanding of the responsible physical processes—can help to understand and reduce natural hazard risks and to make and effectively communicate reliable statements about hazard characteristics, such as frequency, magnitude, extent, onset, consequences, and where possible, the time of future events. To accomplish its broad hazard mission, the USGS maintains an expert workforce of scientists and technicians in the earth sciences, hydrology, biology, geography, social and behavioral sciences, and other fields, and engages cooperatively with numerous agencies, research institutions, and organizations in the public and private sectors, across the Nation and around the world. The scientific expertise required to accomplish the USGS mission in natural hazards includes a wide range of disciplines that this report refers to, in aggregate, as hazard science. In October 2010, the Natural Hazards Science Strategy Planning Team (H–SSPT) was charged with developing a long-term (10-year) Science Strategy for the USGS mission in natural hazards. This report fulfills that charge, with a document hereinafter referred to as the Strategy, to provide scientific observations, analyses, and research that are critical for the Nation to become more resilient to natural hazards. Science provides the information that decisionmakers need to determine whether risk management activities are worthwhile. Moreover, as the agency with the perspective of geologic time, the USGS is uniquely positioned to extend the collective experience of society to prepare for events outside current memory. The USGS has critical statutory and nonstatutory roles regarding floods, earthquakes, tsunamis, landslides, coastal erosion, volcanic eruptions, wildfires, and magnetic storms—the hazards considered in this plan. There are numerous other hazards of societal importance that are considered either only peripherally or not at all in this Strategy because they are either in another of the USGS strategic science plans (such as drought) or not in the overall mission of the USGS (such as tornados).
Deterministic physics-based earthquake sequence simulators match empirical ground-motion models and enable extrapolation to data poor regimes: Application to multifault multimechanism ruptures
We use the deterministic earthquake simulator RSQSim to generate complex sequences of ruptures on fault systems used for hazard assessment. We show that the source motions combined with a wave propagation code create surface ground motions that fall within the range of epistemic uncertainties for the Next Generation Attenuation‐West2 set of empirical models. We show the model is well calibrated where there are good data constraints, and has good correspondence in regions with fewer data constraints. We show magnitude, distance, and mechanism dependence all arising naturally from the same underlying friction. The deterministic physics‐based approach provides an opportunity for better understanding the physical origins of ground motions. For example, we find that reduced stress drops in shallow layers relative to constant stress drop with depth lead to peak ground velocities in the near field that better match empirical models. The simulators may also provide better extrapolations into regimes that are poorly empirically constrained by data because physics, rather than surface shaking data parameterizations, is underlying the extrapolations. Having shown the model is credible, we apply it to a problem where observations are lacking. We examine the case of crustal faults above a shallow subduction interface seen to break coseismically in simulations of the New Zealand fault system. These types of events were left out of consideration in the most recent New Zealand national seismic hazard model due to the modeling complexity and lack of observational data to constrain ground‐motion models (GMMs). Here, we show that in the model, by breaking up the coseismic crustal and interface rupturing fault motions into two separate subevents, and then recombining the resulting ground‐motion measures in a square‐root‐of‐sum‐of‐squares incoherent manner, we reproduce well the ground‐motion measures from the full event rupture. This provides a new method for extrapolating GMMs to more complex multifault ruptures.
Summary of November 2010 meeting to evaluate turbidite data for constraining the recurrence parameters of great Cascadia earthquakes for the update of national seismic hazard maps
This report summarizes a meeting of geologists, marine sedimentologists, geophysicists, and seismologists that was held on November 18–19, 2010 at Oregon State University in Corvallis, Oregon. The overall goal of the meeting was to evaluate observations of turbidite deposits to provide constraints on the recurrence time and rupture extent of great Cascadia subduction zone (CSZ) earthquakes for the next update of the U.S. national seismic hazard maps (NSHM). The meeting was convened at Oregon State University because this is the major center for collecting and evaluating turbidite evidence of great Cascadia earthquakes by Chris Goldfinger and his colleagues. We especially wanted the participants to see some of the numerous deep sea cores this group has collected that contain the turbidite deposits. Great earthquakes on the CSZ pose a major tsunami, ground-shaking, and ground-failure hazard to the Pacific Northwest. Figure 1 shows a map of the Pacific Northwest with a model for the rupture zone of a moment magnitude M w 9.0 earthquake on the CSZ and the ground shaking intensity (in ShakeMap format) expected from such an earthquake, based on empirical ground-motion prediction equations. The damaging effects of such an earthquake would occur over a wide swath of the Pacific Northwest and an accompanying tsunami would likely cause devastation along the Pacifc Northwest coast and possibly cause damage and loss of life in other areas of the Pacific. A magnitude 8 earthquake on the CSZ would cause damaging ground shaking and ground failure over a substantial area and could also generate a destructive tsunami. The recent tragic occurrence of the 2011 M w 9.0 Tohoku-Oki, Japan, earthquake highlights the importance of having accurate estimates of the recurrence times and magnitudes of great earthquakes on subduction zones. For the U.S. national seismic hazard maps, estimating the hazard from the Cascadia subduction zone has been based on coastal paleoseismic evidence of great earthquakes over the past 5,000 years. The instrumental catalog of earthquakes is of little use for constraining the hazard of the CSZ, because there are virtually no recorded earthquakes on most of the plate interface of the CSZ. There are no historical accounts in the past 150 years of large earthquakes on most of the CSZ. Until about 20 years ago, some interpreted this lack of recent and historical earthquakes as an indicator that the subduction zone was slipping aseismically and could not produce a great earthquake. The work of Brian Atwater and others, in the late 1980s and the 1990s (Atwater, 1987, 1992; Atwater and others, 1995; Nelson and others, 1996; Clague, 1997; Atwater and Hemphill-Haley, 1997; Atwater and others, 2004) demonstrated that submerged forests, buried soils, tsunami deposits, and liquefaction along and near the coast were compelling evidence of repeated great Cascadia earthquakes over at least the past 5,000 years. Atwater and Hemphill-Haley (1997) concluded from paleoseismic evidence at Willapa Bay, Washington, that great earthquakes ruptured the CSZ with an average recurrence time of about 500 years. The date of the last great CSZ earthquake, January 26, 1700, was established from historical records of the so-called orphan tsunami in Japan that is inferred to have been produced by this earthquake (Satake and others, 1996, 2003; Atwater and others, 2005) and is consistent with tree-ring data from drowned forests in Washington and Oregon. From modeling the observations of the tsunami, Satake and others (2003) estimated a moment magnitude of about 9.0 for this earthquake. Many other paleoseismic sites have been investigated along the Pacific Northwest coast from Vancouver Island to northern California and show evidence of great CSZ earthquakes. Nelson and others (2006) summarized the dates found from these studies and proposed correlations between sites indicating the extent of rupture for individual events. Dating of inferred tsunami deposits in Bradley Lake, Oregon by Kelsey and others (2005), as well as tsunami and subsidence evidence from Six Rivers, Oregon (Kelsey and others, 2002) and Coquille River (Witter and others, 2003), indicates that there were probably M w 8 ruptures in the southern portion of the CSZ in addition to the M w 9 events that rupture the whole length of the CSZ (Nelson and others, 2006). A parallel development over the past 20 years or more is the use of deep-sea turbidite deposits for identifying and dating great Cascadia earthquakes over the past 10,000 years (Adams, 1990; Goldfinger and others, 2003, 2008, in press; Goldfinger, 2011). Turbidites are sediment deposits in the deep ocean from turbidity currents, which are energetic flows of sediment and water along the continental shelf and slope. Adams (1990), using the counts of turbidites in deep-sea cores off the coast of Oregon and Washington collected and analyzed by Griggs (1969) and Griggs and others (1969), proposed that these turbidites were caused by the shaking of great Cascadia earthquakes. Part of his reasoning was that the number (13) of turbidite deposits that occurred since deposition of the Mazama Ash 7,000 years ago gave a recurrence time of about 500 years, consistent with that derived from the coastal submergence data. Adams (1990) also proposed the “confluence test” which evaluates the number of turbidites for submarine channels that form a confluence. He reported that the number of turbidites in the single downstream channel equaled the number in each of the tributary channels. He reasoned that this indicated that the turbidites in each tributary were simultaneously triggered and were, therefore, caused by a common forcing agent. He concluded that shaking from extended ruptures of great Cascadia earthquakes was the most likely cause of these turbidites. Based on the paleoseismic evidence of past great earthquakes, the hazard from the Cascadia subduction zone was included in the 1996 U.S. NSHM (Frankel and others, 1996), which were the basis for seismic provisions in the 2000 International Building Code. These hazard maps used the paleoseismic studies to constrain the recurrence rate of great CSZ earthquakes. Goldfinger and his colleagues have since collected many more deep ocean cores and done extensive analysis on the turbidite deposits that they identified in the cores (Goldfinger and others, 2003, 2008, in press; Goldfinger, 2011). Using their dating of the sediments and correlation of features in the logs of density and magnetic susceptibility between cores, they developed a detailed chronology of great earthquakes along the CSZ for the past 10,000 years (Goldfinger and others, in press). These correlations consist of attempting to match the peaks and valleys in logs of density and magnetic susceptibility between cores separated, in some cases, by hundreds of kilometers. Based on this work, Goldfinger and others (2003, 2008, in press) proposed that the turbidite evidence indicated the occurrence of great earthquakes (M w 8) that only ruptured the southern portion of the CSZ, as well as earthquakes with about M w 9 that ruptured the entire length of the CSZ. For the southernmost portion of the CSZ, Goldfinger and others (in press) proposed a recurrence time of M w 8 or larger earthquakes of about 230 years. This proposed recurrence time was shorter than the 500 year time that was incorporated in one scenario in the NSHM’s. It is important to note that the hazard maps of 1996 and later also included a scenario or set of scenarios with a shorter recurrence time for M w 8 earthquakes, using rupture zones that are distributed along the length of the CSZ (Frankel and others, 1996; Petersen and others, 2008). Originally, this scenario was meant to correspond to the idea that some of the 500-year averaged ruptures seen in the paleoseismic evidence could have been a series of M w 8 earthquakes that occurred over a short period of time (a few decades), rather than M w 9 earthquakes. Figure 2 shows the logic tree for the CSZ used in the 2008 NSHM’s (Petersen and others, 2008). This logic tree includes whole CSZ rupture earthquakes (M w 8.8–9.2) and partial CSZ rupture earthquakes (M w 8.0–8.7). In this latest version of the NSHM’s, the effective recurrence time of earthquakes on the CSZ with moment magnitudes greater than or equal to 8.0 over the various models is about 270 years (Petersen and others, 2008). This recurrence time applies to the entire CSZ, so that the hazard from great earthquakes was approximately equal along the whole zone, although the hazard estimates taper on the northern and southern ends of the CSZ, because of the way rupture zones of M w 8 earthquakes were distributed along the strike of the CSZ. The NSHM will be updated in 2013, as part of the standard update cycle that corresponds to the update cycle of the national model building codes that are based on the seismic hazard maps. A meeting was necessary to assemble a wide group of experts to hear Dr. Goldfinger explain his methodology for dating and correlating the turbidites and for developing the earthquake chronology. The overall goal of the workshop was to evaluate observations of turbidite deposits to provide constraints on the recurrence times and rupture extents of great Cascadia subduction zone earthquakes for the next update of the NSHM. Before the meeting, participants were supplied with the U.S. Geological Survey (USGS) Professional Paper of Goldfinger and others (in press), as well as material from Brian Atwater and Alan Nelson. The agenda of the meeting was developed by Art Frankel, with assistance from Chris Goldfinger, Brian Atwater, Alan Nelson, Mark Petersen, and Craig Weaver. The meeting was hosted by Chris Goldfinger of Oregon State University. We stress that it is difficult to evaluate in a two-day meeting the large amount of work that Goldfinger and his colleagues have done over the past 15 years or more. This meeting is the first step in a process that develops the inputs to the update of the national maps. The conclusions of this workshop will be discussed and possibly modified at the regional Pacific Northwest workshop for the hazard maps to be held in early 2012. Vetting new research results using informed expert opinion is an integral part of updating the national maps and does not reflect on the veracity of these results.
Staircase Falls Rockfall on December 26, 2003, and Geologic Hazards at Curry Village, Yosemite National Park, California
Since 1857, several hundred rockfalls, rockslides, and debris flows have been observed in Yosemite National Park. At 12:45 a.m. on December 26, 2003, a severe winter storm triggered a rockfall west of Glacier Point in Yosemite Valley. Rock debris moved quickly eastward down Staircase Falls toward Curry Village. As the rapidly moving rock mass reached talus at the bottom of Staircase Falls, smaller pieces of flying rock penetrated occupied cabins. Physical characterization of the rockfall site included rockfall volume, joint patterns affecting initial release of rock and the travel path of rockfall, factors affecting weathering and weakening of bedrock, and hydrology affecting slope stability within joints. Although time return intervals are not predictable, a three-dimensional rockfall model was used to assess future rockfall potential and risk. Predictive rockfall and debris-flow methods suggest that landslide hazards beneath these steep cliffs extend farther than impact ranges defined from surface talus in Yosemite Valley, leaving some park facilities vulnerable.
Testing characteristic magnitude distributions in modern PSHA models
The characteristic magnitude distribution hypothesis predicts a higher rate of large earthquakes than a Gutenberg–Richter extrapolation of the small‐earthquake rate would imply. Characteristic magnitude distributions have been commonly applied to faults in probabilistic seismic hazard analysis (PSHA), and in modern models they can emerge from the way short‐term seismicity constraints are combined with long‐term geologic and geodetic constraints. We test the characteristic magnitude distribution hypothesis by comparing the fault‐based magnitude distributions from the 2023 update to the National Seismic Hazard Model (NSHM23) in the Western United States with observed seismicity over the past 93 yr. We find that observed magnitude distributions fall outside the model‐predicted confidence bounds in regions where NSHM23 produces characteristic magnitude distributions: in these regions, the model predicts higher rates of large earthquakes than are observed. An analysis of the earlier California model (Uniform California Earthquake Rupture Forecast, version 3) also reveals discrepancies between the modeled and observed magnitude distributions. In addition, we find that observed magnitude distributions near modeled faults are not significantly different from those in background regions. These results challenge the prevalence of characteristic magnitude distributions in fault‐based seismic hazard models and call for a reassessment of how disparate data sets are integrated in PSHA.
Precariously balanced rocks in northern New York and Vermont, U.S.A.: Ground-motion constraints and implications for fault sources
Precariously balanced rocks (PBRs) and other fragile geologic features have the potential to constrain the maximum intensity of earthquake ground shaking over millennia. Such constraints may be particularly useful in the eastern United States (U.S.), where few earthquake‐source faults are reliably identified, and moderate earthquakes can be felt at great distances due to low seismic attenuation. We describe five PBRs in northern New York and Vermont—a region of elevated seismic hazard associated with historical seismicity. These boulders appear to be among the most fragile PBRs in the region, based on reports from hobbyists. The PBRs are glacial erratics, best evidenced by glacial striations on bedrock pedestals. The pedestals themselves are locally high knobs, often situated on regionally high topography; this setting limits soil development and indicates that any outwash deposits were likely ephemeral. As a result, PBR ages can be reliably established by the retreat of the last continental ice sheet, ∼15–13 ka. To quantify the fragility of the PBRs, we surveyed them with ground‐based light detection and ranging and calculated geometric parameters from the point clouds, field observations, and seismic responses. Preliminary validation of the 2023 time‐independent U.S. National Seismic Hazard Model (NSHM) shows that the existence of PBRs is generally consistent with the median site‐specific hazard curves. Only the Blue Ridge Road site suggests a modest reduction in hazard. To visualize the ensemble of data, we mapped the minimum permissible distance to potential source faults around each PBR site as a function of source magnitude by using the ground‐motion models from the 2023 NSHM. Viewed in this manner, our data are consistent with potential M ∼6.5 earthquake‐source faults in many parts of the Lake Champlain Valley and northern Adirondack Mountains. Our work illustrates a potential pathway for better constraining earthquake‐source faults in regions of cryptic faults.
Empirical ground-motion basin response in the California Great Valley, Reno, Nevada, and Portland, Oregon
We assess how well the Next-Generation Attenuation-West 2 (NGA-West2) ground-motion models (GMMs), which are used in the US Geological Survey’s (USGS) National Seismic Hazard Model (NSHM) for crustal faults in the western United States, predict the observed basin response in the Great Valley of California, the Reno basin in Nevada, and Portland and Tualatin basins in Oregon. These GMMs rely on site parameters such as the time-averaged shear-wave velocity ( V S ) in the upper 30 m of Earth’s crust ( V S30 ) and depths to 1.0 and 2.5 km/s shear-wave isosurfaces ( Z 1.0 and Z 2.5 ) to capture basin effects and were developed using observations and simulations primarily from the Los Angeles region in southern California. Using ground-motion records from mostly small-to-moderate earthquakes and mixed-effects regression analysis, we find that the GMMs perform well with our local basin-depth models for the California Great Valley. With our local basin-depth models for Reno, the GMMs do not perform as well for this relatively shallow basin and exhibit little sensitivity to the basin parameters used in the NGA-West2 GMMs. We also find good performance for the local Z 1.0 model across the Portland region, whereas the local Z 2.5 model provides little predictive power except at sites in the deepest part of the Tualatin basin. Additional work could improve the performance of the site and basin terms in the NGA-West2 GMMs for regions with geologic structure different than the deep basins in southern California and the Great Valley. In addition, we find significant discrepancies among the GMMs in how the uncertainty in the ground motion varies with basin depth and pseudospectral period. Our results can help guide seismic hazard analyses on whether to include these local basin-depth models.
Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey
Executive Summary Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021). Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts. The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information. The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are: (1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time. Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise. (2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced. Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate. (3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts. Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity. The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.
A Unified Flash Flood Database across the United States
Despite flash flooding being one of the most deadly and costly weather-related natural hazards worldwide, individual datasets to characterize them in the United States are hampered by limited documentation and can be difficult to access. This study is the first of its kind to assemble, reprocess, describe, and disseminate a georeferenced U.S. database providing a long-term, detailed characterization of flash flooding in terms of spatiotemporal behavior and specificity of impacts. The database is composed of three primary sources: 1) the entire archive of automated discharge observations from the U.S. Geological Survey that has been reprocessed to describe individual flooding events, 2) flash-flooding reports collected by the National Weather Service from 2006 to the present, and 3) witness reports obtained directly from the public in the Severe Hazards Analysis and Verification Experiment during the summers 2008–10. Each observational data source has limitations; a major asset of the unified flash flood database is its collation of relevant information from a variety of sources that is now readily available to the community in common formats. It is anticipated that this database will be used for many diverse purposes, such as evaluating tools to predict flash flooding, characterizing seasonal and regional trends, and improving understanding of dominant flood-producing processes. We envision the initiation of this community database effort will attract and encompass future datasets.
Duration of fuels reduction following prescribed fire in coniferous forests of U.S. national parks in California and the Colorado Plateau
Prescribed fire is a widely used forest management tool, yet the long-term effectiveness of prescribed fire in reducing fuels and fire hazards in many vegetation types is not well documented. We assessed the magnitude and duration of reductions in surface fuels and modeled fire hazards in coniferous forests across nine U.S. national parks in California and the Colorado Plateau. We used observations from a prescribed fire effects monitoring program that feature standard forest and surface fuels inventories conducted pre-fire, immediately following an initial (first-entry) prescribed fire and at varying intervals up to >20 years post-fire. A subset of these plots was subjected to prescribed fire again (second-entry) with continued monitoring. Prescribed fire effects were highly variable among plots, but we found on average first-entry fires resulted in a significant post-fire reduction in surface fuels, with litter and duff fuels not returning to pre-fire levels over the length of our observations. Fine and coarse woody fuels often took a decade or longer to return to pre-fire levels. For second-entry fires we found continued fuels reductions, without strong evidence of fuel loads returning to levels observed immediately prior to second-entry fire. Following both first- and second-entry fire there were increases in estimated canopy base heights, along with reductions in estimated canopy bulk density and modeled flame lengths. We did not find evidence of return to pre-fire conditions during our observation intervals for these measures of fire hazard. Our results show that prescribed fire can be a valuable tool to reduce fire hazards and, depending on forest conditions and the measurement used, reductions in fire hazard can last for decades. Second-entry prescribed fire appeared to reinforce the reduction in fuels and fire hazard from first-entry fires.
Natural hazards activities of the National Geophysical Data Center
The National Geophysical Data Center (NGDC), a part of the National Oceanic and Atmospheric Administration, has been given the task of collecting, managing, and disseminating the great mass of inofmation produced by scientific observations of the geophysical environment. This article describes NGDC data bases that speifically relate to natural hazards.