USGS Science⌕ Search

USGS · 70197878

Fault displacement hazard for strike-slip faults

Abstract

In this paper we summarize data, methods, and models developed for a probabilistic assessment of fault displacement hazards across the U.S. We compare earthquake displacement data and empirical fault displacement models that have been developed for normal faults, strike-slip faults, and reverse faults. In general, the data and models are similar near the center of the fault for the three faulting types, but differ near the ends with the strike-slip data being lower than the reverse and normal faulting data. We also compare these U.S. models with data and equations developed using Japanese fault displacement data. The Japan model is also similar to the U.S. models near the center of the fault but decays less rapidly near the ends of the fault. In addition, we discuss impacts of models developed to analyze off-fault strain on secondary faults, multi-strand displacement hazard, and various mapping quality factors. For our study, we show example fault displacements for a M 7 fault with recurrence of 800 and 1600 years. We conclude that a deterministic assessment of fault displacements is often higher than the probabilistic displacements for less active faults with earthquake rupture recurrence that is longer than the hazard return period of interest. Fault displacement hazard is applied in engineering applications for buildings, bridges, pipelines, and nuclear facilities. We present three applications for fault displacement hazard at nuclear facilities and important structures.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mark D. Petersen, Rui Chen. 2018. Fault displacement hazard for strike-slip faults. https://pubs.usgs.gov/publication/70197878

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Authoritative knowledge infrastructure for GeoAI: Implications for scientific spatial data providers

Geospatial Artificial Intelligence (GeoAI) increasingly relies on automated analysis of authoritative geospatial data, exposing limitations in data infrastructures originally designed for simple dissemination rather than for knowledge-driven use. From the perspective of scientific spatial data providers, the challenge is enabling GeoAI responsibly while retaining semantic clarity, provenance, reproducibility, and governance. This short paper (i) examines how GeoAI exposed limitations within existing geospatial data infrastructures, and (ii) identifies provider-side requirements for an authoritative knowledge infrastructure. Drawing on GIScience, scientific workflow, and operational AI literature, the paper outlines implications for national mapping organizations that seek to support advanced analytics without jeopardizing scientific rigor or stewardship responsibilities.

Conference Paper↗

Springs of the Catskill Mountains: A conduit flow system in predominantly siliciclastic strata

The Catskill Mountains of New York state are composed of thick sequences of interbedded mudstone, sandstone, and siltstone that are intercalated with thin beds of paludal limestone and calcareous mudstone. Sandstones often contain rip-up clasts of calcareous material at their bases and contain minor amounts of carbonate cement throughout their mass. This minor amount of calcareous material weathers out to produce thin zones of solutional porosity and permeability integrated within perched aquifers that feed perennial hillslope springs. Solutional features are evident within thin carbonate lenses and along fractures in sandstones, occasionally resulting in explorable cave-sized conduits. This study focuses on the behavior of bedrock springs and seeps in the headwaters of the Neversink River basin above the Neversink Reservoir. Bedrock springs are numerous throughout the Catskill Mountains and serve to provide baseflow to the headwater streams that tends to be more persistent during dry times than other baseflow sources. We observed dissolution-influenced conduits within the bedrock, and suffosional conduits within unconsolidated materials. Continuous water temperature at six springs was monitored at hourly intervals from May to October 2022 to investigate the thermal response of groundwater to daily and seasonal changes in air temperature along with event-based meteorological events. Temperature monitoring was augmented at some springs with time-lapse photography to evaluate persistence of flow. The thermal responses of springs to precipitation events were highly variable across sites, with some springs exhibiting flashy responses indicating a strong connection to the surface, while other springs showed muted or no thermal response to events. The seasonal thermal response also varied across sites having lag times of 23-48 days between peak air temperature and peak spring water temperature. The water temperatures and geochemical compositions of these bedrock springs support a conceptual model of multiple residence times, showing both event and seasonal groundwater storage within the conduit flow system that feeds the springs of the Catskill Mountains.

New York↗

Rapid deglaciation of the Tuolumne Meadows region linked to glacier hypsometry

During the LGM deglaciation (19–11 ka), episodes of glacier retreat and stabilization in the western United States are often attributed to abrupt climate change events via changes in Atlantic Meridional Overturning Circulation (e.g., Becker et al. 2025; McGee et al. 2018; Phillips 2016). However, there is considerable variability in the magnitude and timing of glacier retreat across the western US that is difficult to reconcile with a uniform climate forcing (Marcott et al. 2019), indicating either heterogeneous climate change or the influence of local non-climatic variables, such as glacier hypsometry (Young et al. 2011). Prior work from basal lake radiocarbon ages (Gillespie and Clark 2011) and cosmogenic nuclide dating (Phillips 2016; Phillips et al. 2009; Rood et al. 2011) established that Sierra Nevada glaciers receded from LGM moraines to north-facing cirques between 18 and 15 ka, with most deglaciation occurring at 15.8 ± 0.5 ka. As discussed above, geomorphic evidence supports abrupt glacier stagnation and in situ melting in the Tuolumne Meadows region.

Calfiornia↗