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Results for “Arizona Geological Survey Contributed Report”

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USGS1999

Episodic sediment-discharge events in Cascade Springs, southern Black Hills, South Dakota

Cascade Springs is a group of artesian springs in the southern Black Hills, South Dakota, with collective flow of about 19.6 cubic feet per second. Beginning on February 28, 1992, a large discharge of red suspended sediment was observed from two of the six known discharge points. Similar events during 1906-07 and 1969 were documented by local residents and newspaper accounts. Mineralogic and grain-size analyses were performed to identify probable subsurface sources of the sediment. Geochemical modeling was performed to evaluate the geochemical evolution of water discharged from Cascade Springs. Interpretations of results provide a perspective on the role of artesian springs in the regional geohydrologic framework. X-ray diffraction mineralogic analyses of the clay fraction of the suspended sediment were compared to analyses of clay-fraction samples taken from nine geologic units at and stratigraphically below the spring-discharge points. Ongoing development of a subsurface breccia pipe(s) in the upper Minnelusa Formation and/or Opeche Shale was identified as a likely source of the suspended sediment; thus, exposed breccia pipes in lower Hell Canyon were examined. Upper Minnelusa Formation breccia pipes in lower Hell Canyon occur in clusters similar to the discrete discharge points of Cascade Springs. Grain-size analyses showed that breccia masses lack clay fractions and have coarser distributions than the wall rocks, which indicates that the red, fine-grained fractions have been carried out as suspended sediment. These findings support the hypothesis that many breccia pipes were formed as throats of abandoned artesian springs. Geochemical modeling was used to test whether geochemical evolution of ground water is consistent with this hypothesis. The evolution of water at Cascade Springs could not be suitably simulated using only upgradient water from the Minnelusa aquifer. A suitable model involved dissolution of anhydrite accompanied by dedolomitization in the upper Minnelusa Formation, which is caused by upward leakage of relatively fresh water from the Madison aquifer. The anhydrite dissolution and dedolomitization account for the net removal of minerals that would lead to breccia pipe formation by gravitational collapse. Breccia pipes in the lower Minnelusa Formation are uncommon; however, networks of interconnected breccia layers and breccia dikes are common. These networks, along with vertical fractures and faults, are likely pathways for transmitting upward leakage from the Madison aquifer. It is concluded that suspended sediment discharged at Cascade Springs probably results from episodic collapse brecciation that is caused by subsurface dissolution of anhydrite beds and cements of the upper Minnelusa Formation, accompanied by replacement of dolomite by calcite. It is further concluded that many breccia pipes probably are the throats of artesian springs that have been abandoned and exposed by erosion. The locations of artesian spring-discharge points probably have been shifting outwards from the center of the Black Hills uplift, essentially keeping pace with regional erosion over geologic time. Thus, artesian springflow probably is a factor in controlling water levels in the Madison and Minnelusa aquifers, with hydraulic head declining over geologic time, in response to development of new discharge points. Development of breccia pipes as throats of artesian springs would greatly enhance vertical hydraulic conductivity in the immediate vicinity of spring-discharge points. Horizontal hydraulic conductivity in the Minnelusa Formation also may be enhanced by dissolution processes related to upward leakage from the Madison aquifer. Potential processes could include dissolution resulting from leakage in the vicinity of breccia pipes that are abandoned spring throats, active spring discharge, development of subsurface breccias with no visible surface expression or spring discharge, as well as general areal leakage from the Madison aquifer into the Minnelusa Formation.

South Dakota↗
USGS2026

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen↗
USGS2025

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California↗
USGS2025

Estimated average annualized tsunami losses for the United States

Tsunami hazards are substantial threats to coastal communities across the United States (U.S.) and its territories. U.S. states and territories collaborate through the National Tsunami Hazard Mitigation Program (NTHMP) to develop their own tsunami-hazard information for outreach and evacuation planning. An effort to curate this tsunami-hazard information to support comprehensive risk analysis at the national level has not yet been completed. In support of this effort, the Federal Emergency Management Agency (FEMA) collaborated with the NTHMP, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS) starting in 2023. This collaboration included the collection and analysis of existing tsunami hazard data and methods in the U.S. Tsunami subject matter experts identified and selected scientifically defensible methods for estimating the risks to buildings and populations in coastal communities. These efforts may support decision making regarding resilience policies, priorities, strategies and funding levels. Tsunamis can be triggered by earthquakes, subaerial or submarine landslides, volcanic eruptions, glacial calving, near-earth objects, weather or other events. These events can cause severe destruction, injuries, and loss of life due to powerful currents and flooding. Tsunamis pose a substantial threat to the western United States and all U.S. territories, as described below. ■ Hawaii is threatened by distant tsunamis due to its central location in the Pacific Ocean basin and has a history of local events. ■ Alaska, particularly the Aleutian Islands, faces local tsunami threats due to proximity to the Alaska-Aleutian Subduction Zone, as well as distant tsunamis from around the Pacific Ocean basin. ■ The western coast of the U.S. is threatened by distant tsunamis from around the Pacific Ocean basin and local source tsunamis from earthquakes generated within the Cascadia Subduction Zone in the Pacific Northwest. ■ American Samoa faces local tsunami threats from earthquakes generated in the nearby Tonga Trench, as well as distant tsunami threats. ■ Guam and the Commonwealth of the Northern Mariana Islands are threatened by local tsunamis from the nearby Mariana Subduction Zone, as well as distant sources from around the Pacific Ocean Basin. ■ Puerto Rico and the United States Virgin Islands are threatened by multiple local and distant tsunami sources, such as the Puerto Rico Trench (PRT), given their location in the complex seismic region of the Caribbean Sea. Several historical events stand out because of their catastrophic impacts. ■ In the Pacific Northwest, the 1700 Cascadia earthquake caused a tsunami that affected coastal Native American communities, though the extent of the damage is not fully documented (Ludwin, et al., 2005). ■ In Puerto Rico, the 1918 earthquake triggered a tsunami that caused $77 million in damage in 2022 dollars and 116 fatalities, primarily along the western coast (Coffman et al., 1982). ■ The 1946 Aleutian Islands earthquake triggered a massive tsunami that devastated Hilo, Hawaii, killing 158 people and resulting in approximately $375 million in damage (adjusted to 2022 dollars) (Fisher et al., 2023). ■ The 1964 Alaska earthquake (M 9.2) generated tsunamis that caused severe destruction in some communities across Alaska, Oregon, and California. This disaster led to a total of 124 fatalities and approximately $2.9 billion in property damage (adjusted to 2022 dollars) (Brocher et al., 2014) (Alaska Science Center, 2024). ■ In American Samoa, a tsunami generated by the 2009 Samoa earthquake (Mw 8.1) caused widespread devastation, resulting in 34 confirmed fatalities (Apatu et al., 2013) and economic losses exceeding $160 million (adjusted to 2022 dollars) (DHS, 2011). More recent events, including the 2010 Chile earthquake, the 2011 Japan earthquake, and the 2022 Tonga volcanic eruption, resulted in millions of dollars in damage to numerous ports and harbors in the U.S. South Pacific territories, Hawaii, and along the west coast of the U.S. (Lynett, et al., 2022) (Wilson, et al., 2013). Since these events, the expansion of the built environment in lowlying areas along the coast has increased the exposure of buildings and people, thereby further escalating community risk from tsunamis. This report provides a comprehensive national assessment of earthquake-generated tsunami risk. It does not include impacts from tsunamis generated by landslides, volcanic eruptions, glacial calving, near-earth objects, weather, or other events. This study is based on the best available hazard data from the U.S. Pacific Coast (California, Oregon and Washington), Alaska, Hawaii, U.S. Pacific Territories (American Samoa, Guam and Commonwealth of the Northern Mariana Islands) and Caribbean Territories (Puerto Rico and United States Virgin Islands). Tsunami risks associated with states along the East Coast, Gulf Coast, and Great Lakes are not included in this study because Hazus 6.1 software (FEMA 2024a) does not currently include the ability to analyze tsunami risk in those states. Once modeling capabilities and tsunami hazard data become available for additional states, FEMA may incorporate these data into future editions of this study.

Alaska, California, Hawaii Oregon, Washington↗
USGS2024

Earthquake-triggered ground-failure inventory associated with the M7.1 2018 Southcentral Alaska earthquake

The 30 November 2018, magnitude (Mw) 7.1 earthquake in Southcentral Alaska triggered substantial landslides, liquefaction, and ground cracking throughout the region, resulting in widespread geotechnical damage to buildings and infrastructure. Despite a challenging reconnaissance and remote-sensing environment, we constructed a detailed digital inventory of ground failure associated with the event from several sources. Sources included information derived from remotely sensed data, and data compiled from literature, social media postings, and earthquake damage information compiled by local, state, and federal agencies. Each instance of ground failure within the inventory contains information on the location and type of observed ground failure, and the methods and data used to document the occurrence. Where high-quality data, such as LIDAR or satellite imagery, were available and showed the ground-failure instance clearly, the extent is mapped as a polygon or polyline. All other locations are mapped as points. There are a total of 886 ground-failure instances documented within the inventory (400 landslides, 286 liquefaction features, and 200 features unattributed to specific processes). A semi-quantitative confidence scheme is used to describe mapping certainty associated with each ground-failure feature. This inventory represents a relatively moderate ground-failure-triggering event that occurred in a subarctic environment. This data paper describes the content within the inventory, the inventory data collection procedures, and limitations of the data. Events of this type are not often documented in detail; thus, adding the inventory data to the US Geological Survey Open Repository of Earthquake-Triggered Ground-Failure Inventories further diversifies the datasets available to the scientific community to be used to better understand and model earthquake-triggered ground failure.

Alaska↗
USGS2026

Wavelet Inversion for SliP (WISP): Open-source earthquake slip modeling software

Models of the spatiotemporal evolution of earthquake slip, termed finite-fault models, are a critical component of rapid earthquake and tsunami response, earthquake forecasting, seismic ground-motion estimates, and studies of earthquake kinematics. Here, we detail a newly released finite-fault modeling software, Wavelet Inversion for SliP (WISP), in use at the U.S. Geological Survey’s National Earthquake Information Center (NEIC) and available to the public. WISP version 1.1.0 allows inversion of teleseismic body and surface waves, as well as local strong-motion, static and dynamic Global Navigation Satellite System, and satellite imagery (e.g., Interferometric Synthetic Aperture Radar) observations on single or multiple planar fault segments. The software is used in NEIC rapid response of earthquakes M w ≥ 7, generally resulting in a published model within the first few hours after the event origin time. The rupture location and dimensions are then used as inputs to downstream products to estimate earthquake shaking, predict loss, and model the likelihood of secondary hazards, namely landslides and liquefaction. WISP is also used in research studies to evaluate the characteristics of complex ruptures including multifault ruptures and earthquake doublets, among others. The WISP version 1.1.0 software release is composed of Python-wrapped FORTRAN code to accomplish the inversion procedure. A simple command line interface facilitates ease of use even for those with only a cursory knowledge of Python scripting. WISP version 1.1.0 includes a Jupyter Notebook tutorial demonstrating use of the software for modeling the 2015 M w 8.3 Illapel, Chile, earthquake. In parallel with the tutorial, we demonstrate the typical usage of the WISP software using the M w 8.3 Illapel earthquake example here.

Seismological Research Letters↗
USGS2024

Evidence of nitrate attenuation in intertidal and subtidal groundwater in a subterranean estuary at a Cape Cod embayment, East Falmouth, Massachusetts, 2015–16

Nitrogen dynamics in intertidal and nearshore subtidal groundwater (subterranean estuary) adjacent to the Seacoast Shores peninsula, Falmouth, Massachusetts, were investigated during 2015–16 by the U.S. Geological Survey. The peninsula is a densely populated residential area with septic systems and cesspools that are substantial sources of nitrogen to groundwater. The study area is in the Eel River, an estuarine saltwater embayment connected to the ocean adjacent to the western shore of the peninsula, that was the subject of an earlier study by Colman and others (2018, https://doi.org/10.3133/sir20185095 ) on nitrogen transport and transformations in groundwater between onshore and offshore locations. The previous study documented the distribution of nitrate concentrations and nitrate attenuation reactions in fresh groundwater beneath the peninsula and the estuary. The current study extended those observations with more detailed sampling and analysis of shallow groundwater from wells near discharge sites beneath the estuary. The current field investigation included sampling of existing wells and installation and sampling of clusters of wells and temporary sampling points in the subterranean estuary, including (1) shallow transects 0.3 to 1.2 meters (m) deep extending from 1 to 13.5 m offshore and (2) deeper wells (from 1.83 to 4.88 m deep) extending from 4.3 to 14.3 m offshore. Measurements of hydraulic-head gradients 2–5 m below the sediment/water interface in the intertidal and nearshore subtidal zones indicated that groundwater flow generally was upwards (towards the estuary) under all tide conditions in October 2016. The magnitude of the gradient was greatest during low tide conditions, indicating that groundwater discharge likely decreased during high tides. Measurements of specific conductance in shallow groundwater in the subterranean estuary in three transects perpendicular to shore were consistent with the existence of saltwater flow cells (infiltration of overlying saline water, mixing with fresh groundwater, and discharge to the overlying saline water) in the intertidal and nearshore subtidal regions. The size of these flow cells was variable in space and time and dependent on the elevation of the tide (spring or neap). At this location in the Eel River subterranean estuary, and offshore to at least 13.5 m, offshore flow of fresh groundwater apparently prevented a deeper saltwater wedge from discharging to the surface. Nitrate concentrations in shallow groundwater (30 to 122 centimeters [cm] depth) were variable in space and time, ranging from not detectable to 600 micromoles per liter (μmol/L) (8.4 milligrams per liter as N), and were highest in June 2016 at depths from 61 to 122 cm below the sediment/water interface and from 4 to 9 m offshore. Nitrate generally was not detectable in saline shallow groundwater at 30-cm depth or at any depth from 30 to 122 cm from 10 to 13.5 m offshore. Dissolved oxygen concentrations were suboxic (less than 16 μmol/L) in 60 percent of the sampled subterranean groundwater beneath the intertidal and subtidal zones. In the remaining sites, the range of dissolved oxygen concentrations was from 18 to 272 μmol/L and the median concentration was 43 μmol/L. Evidence for microbial nitrate reduction (denitrification and possibly anammox) was provided by the distribution of the reaction product nitrogen gas (excess N 2 , or N 2MIC ), as determined from analysis of the dissolved nitrogen gas and argon gas (Ar) concentrations in groundwater samples. Excess nitrogen gas provided evidence for nitrate reduction in shallow groundwater below the subtidal and, to a lesser extent, intertidal zones adjacent to the Seacoast Shores peninsula. These zones, where evidence for nitrate reduction was detected, were in fresh and brackish groundwater near subtidal or intertidal saltwater cells where discharging fresh groundwater mixed with infiltrating saline water. Infiltrating seawater may have supplied organic carbon, one of several potential electron donors that are required for denitrification. Other potential electron donors, such as organic carbon, iron, manganese, hydrogen, methane, ammonium, elemental sulfur, or sulfide phases, may have been supplied by the estuarine sediments. Drainage from surface runoff near the shore also may have supplied organic carbon to fresh groundwater near the intertidal saltwater cell. The highest amounts of nitrate converted to excess nitrogen gas were estimated to be in the range of 230 to 430 μmol/L in nearly fresh groundwater near the subtidal saltwater cell at depths of 61 to 122 cm below the sediment/water interface and from 10 to 13.5 m offshore. Evidence of denitrification within 10 m of the shore was sparse (generally limited to less than 50 μmol/L of N 2 -N) despite the presence of high nitrate concentrations. The spatial distribution of estimated nitrate reduction in the intertidal and nearshore subtidal fresh and brackish groundwater may be related to local variability in the distribution of reactive electron donors in those zones. Variations in the amount of nitrate reduction to nitrogen gas were not clearly related to potential aqueous electron donors such as dissolved organic carbon, nor to potential reaction products such as alkalinity, but may have been controlled by combinations of aqueous and solid-phase reactants. The distribution of relatively shallow fresh groundwater containing nitrate could indicate potential nitrate discharge areas in the lower intertidal zone and uncertain locations farther offshore; however, the data did not extend all the way to the sediment/water interface or to the offshore freshwater limit. This study confirmed substantial loss of nitrate from some of the fresh and brackish groundwater in shallow subestuarine sediments prior to discharge but did not quantify how much nitrate eventually discharged to the estuary.

Massachusetts↗
USGS2026

Cascadia Subduction Zone science: Call for the next generation community seismic velocity model

The Cascadia subduction zone (CSZ) hosts major seismic and tsunami hazards, yet key questions persist about the relationship between margin structure, fluid distribution, episodic tremor and slip, shallow megathrust behavior, shaking and tsunamigenesis, and the resulting hazard estimates. Addressing these problems requires an empirically grounded, three‐dimensional seismic velocity model to illuminate subsurface structure and properties and to provide a basis for geophysical studies such as earthquake simulations and ground‐motion estimation. In May 2024, the National Science Foundation‐funded Cascadia Region Earthquake Science Center (CRESCENT) community velocity model (CVM) working group, with U.S. Geological Survey and regional partners, convened a workshop to identify priorities for such a model. Participants emphasized the features necessary for addressing key science questions, including implementing findability, accessibility, interoperability, and reusability (FAIR) access, capturing along‐strike and along‐dip structural heterogeneity, resolving shallow offshore–onshore structure, constraining elastic properties and quantifying their uncertainties for numerical wave propagation simulations, their validation benchmarks, and supporting associated accurate earthquake ground‐motion simulations and hazard assessments. This article describes the priorities defined in the workshop, and a description of how, guided by these needs, CRESCENT plans to develop multiple generations of a CVM to advance CSZ science and improve seismic and tsunami hazard modeling across the Pacific Northwest. The CVM will span the CSZ from the surface to ∼100 km depth, offshore and east of the Cascades into Idaho (∼132°–110° W) and the southern and northern tectonic regime transitions (∼36°–52° N) to capture the entire tectonic system as well as its surroundings.

Cascadia Subduction Zone↗
USGS2025

Structural setting and geothermal potential of northeastern Reese River Valley, north-central Nevada: Highly prospective detailed study site for the INGENIOUS project

The northeastern part of the Reese River basin situated ~15 km southeast of Battle Mountain, Nevada, scored highly in the Nevada geothermal play fairway analysis (PFA) for hosting potential hidden geothermal systems. This site (also referred to as Argenta Rise) was therefore chosen for detailed study in the INGENIOUS project (INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems). The high PFA scores resulted primarily from favorable structural settings (e.g., fault intersections and pull aparts) with relatively high slip rates on Quaternary faults. The INGENIOUS project is utilizing additional parameters and more rigorous analytical techniques to further advance exploration at this site. This includes integration of geological (e.g., Quaternary fault mapping) and new geophysical datasets (e.g., gravity, magnetics, MT data, and five reprocessed seismic reflection profiles) to build a structural model and to identify specific favorable sites for potential geothermal upwellings. Two-meter temperature surveys were also conducted in the area (139 measurements). This part of north-central Nevada is characterized by systems of intersecting northerly and ENE-striking faults within the broader Humboldt structural zone, a poorly understood belt of ENE-striking faults and relatively high heat flow extending across northern Nevada. Kinematic analysis of exposed fault surfaces shows that ENE-striking faults have accommodated sinistral-normal slip, and normal slip characterizes N- to NNE-striking faults. Northeastern Reese River Valley lies within a broad left step between major ENE-striking fault zones on the northern flanks of the Argenta Rim and Shoshone Range and thus corresponds to a broad pull-apart in the ENE-striking sinistral-normal fault system. Notably, the nearby Beowawe geothermal system in Whirlwind Valley (with abundant sinter, hot springs, and a geothermal power plant) occupies a fault intersection in a relatively small left step in a major ENE-striking sinistral-normal fault and may serve as an analogue for a potential hidden system in northeastern Reese River Valley. Existing geological maps, high-resolution lidar, and seismic reflection data demonstrate that northeastern Reese River Valley is structurally complex with multiple intersections between the ENE- and N- to NNE-striking fault systems. Some of these fault intersections correspond to low resistivity anomalies, magnetic lows, and/or very subtle 2-m temperature anomalies, which may indicate hidden geothermal upwellings. Three-dimensional modeling and temperature-gradient drilling are planned to further evaluate these sites for geothermal activity.

Nevada↗
USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗
USGS2024

The new self-anchored suspension (SAS) San Francisco Bay Bridge- Its response to a small earthquake

This paper presents a summary of previously published work (Celebi 2023) related to the new Self-Anchored Suspension (SAS) bridge that went into service within the last decade as a replacement for the older truss bridge spanning between Yerba Buena Island and Oakland, California, within the San Francisco Bay Area. During the October 19, 1989 M6.9 Loma Prieta earthquake, which occurred ~100 km south of the Bay Bridge, a section of the upper deck of the truss bridge fell onto the lower deck – thus closing this important lifeline between San Francisco and Oakland. The SAS is unique, self-anchored, and suspended by a single tower that is pivotal in trafficking the cable and hanger system to support the decks. The SAS bridge is extensively instrumented by the California Geological Survey’s Strong Motion Instrumentation Program (CSMIP). There are approximately 85 channels of accelerometers in the seismic monitoring system that recorded the October 14, 2019 Mw4.6 Pleasant Hill earthquake. The data allow a complex but identifiable coupled response of the deck, tower, and cable system. Both acceleration and displacement time-history data are used to extract significant frequencies using system identification methods, including spectral analyses. Results are compared to those from finite-element-model (FEM) analyses carried out during the design and analysis process of the bridge in 2002 (Nader et al. 2002). There are differences between FEM analyses results and those from the low amplitude shaking caused by a seismic event. An apparent frequency (period) of the SAS bridge is assessed (approximately 5.2 seconds). In a plot of deck length versus period, there is an almost linear relationship with periods of other regular suspension bridges, such as the Golden Gate Bridge and the Carquinez Bridge, both in the San Francisco Bay.

California↗
USGS2024

A journey to the center of the USGS National Strong-motion Project processing and beyond

The United States Geological Survey (USGS) National Strong Motion Project (NSMP) has the primary U.S. government responsibility to acquire, process, and disseminate significant strong-motion earthquake ground motion records measured at surficial free-field stations, structures (buildings, dams, and bridges, and geotechnical arrays to the earthquake engineering community. As a result of the deployment of modern seismic instrumentation and growth of tools such as web-services, earthquake data from U.S. and international seismic networks are more accessible than ever. Our mission is to provide raw and processed strong-motion waveforms with PGA values greater than 0.1%g for M3.0 earthquakes and larger in California and M4.0 and larger within the conterminous US, Hawaii, Puerto Rico, and Alaska. Datasets of interest to the engineering and geophysics communities, such as event sequences in areas of induced seismicity and significant global events, are also processed and posted at the Center for Engineering Strong Motion Data (CESMD) at strongmotioncenter.org when available through collaboration with the international strong-motion data community. Here we outline (1) the NSMP’s current workflow to acquire, process, and distribute data at CESMD; (2) our new endeavours and collaborations focusing on comparison and integration of waveform processing software, development of techniques for metadata quality checks before and after earthquakes, and construction of a dynamic site characterization repository; and (3) our topics for possible collaboration topics across the global strong-motion community.

Conference Paper↗
USGS2025

Site-specific, extended ShakeMaps for earthquake engineering applications

The U.S. Geological Survey (USGS) routinely produces ShakeMaps of shaking intensity across the globe. Due to practical constraints, the number of response spectral periods was limited to three standard periods (0.3, 1.0, and 3.0 sec). We have recently developed the tools that are necessary to expand this functionality to include 22 periods (matching the current U.S. National Seismic Hazard Model periods) as well as the orientation-independent components (e.g., “RotD50”). We refer to ShakeMap products that include these extensions as “extended ShakeMaps.” The added level of complexity motivated us to also develop a user-friendly tool called the “ShakeMap Sampling Tool” (SST) that gives all the estimated shaking metrics for a specific location (or list of locations). Additionally, we develop a web application where users can input locations of interest and view/download the SST results. We further familiarize users with the concept of “Composite ShakeMaps.” For earthquakes sequences such as a mainshock and larger foreshocks and aftershocks, this provides a map of the maximum value of each shaking metric, which is useful for overall loss estimates, the full extent of ground failure triggering potential, and a better portrayal of the repeated shaking levels at a given point for a series of earthquakes. Such a site-specific shaking history facilitates earthquake forensics at building or infrastructure sites for which damage may be of concern, as described in the Disproportionate Damage Earthquake trigger specified in the IEBC (2018, Section 405.2.2) and in developing ATC-145 guidelines (Guidelines for Post-Earthquake Assessment, Repair, and Retrofit of Buildings). The composite ShakeMap can be combined with the SST for a variety of earthquake-hazard applications, such as systematically inferring triggering shaking estimates at specific sites of geotechnical interest for landsliding, liquefaction, and lateral-spreading hazards.

Kahramanmaraş↗
USGS2026

A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping

Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD. LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics. Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved 72.1 ± 1.60% overall agreement, compared to 71.1 ± 1.7% agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved 83.4 ± 1.22% agreement, compared to 84.6 ± 1.11% agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.

Remote Sensing of Environment↗
USGS2025

A scientific vision and roadmap for earthquake rupture forecast developments, a USGS perspective

We articulate a scientific vision and roadmap for the development of improved Earthquake Rupture Forecast models, which are one of the two main modeling components used in modern seismic hazard and risk analysis. One primary future objective is to provide fully time-dependent models that include both elastic rebound and spatiotemporal clustering nationwide, which is particularly important for shorter-term hazard and risk considerations (e.g., earthquake insurance products). We also discuss the importance and perennial challenges associated with quantifying epistemic uncertainties, including those associated with deformation-model slip rates, un-quantified sampling errors with respect to off-fault seismicity, and any spatial covariances. The need for more physics-based approaches is also emphasized, as is the benefit of adding model valuation (quantifying usefulness) to our verification and validation protocols. Given the multidisciplinary and system-level nature of this activity, modular design is critical. Future updates will also draw from best-available science by both the United States Geological Survey and the external community. The primary goal of this paper is to highlight plans that guide research and facilitate community engagement with model development, especially with respect to lowering the entry barrier for early career scientists and engineers. The paper is written so readers can focus on the sections that interest them most (see table of contents), with the Introduction and Discussion providing a stand-alone overview and summary.

Bulletin of the Seismological Society of America↗
USGS1976

Uranium and trace elements in stream sediments as an exploration tool

More than 45 trace elements have been reported in anomalous amounts in the uranium ores. The specific suite of elements associated with any one uranium deposit varies according to deposit type and geologic province. The primary geochemical halo of uranium and associated trace elements in the host rock, together with secondary dispersion halo in soils and alluvium, offers a potential geochemical exploration target. Sediment from streams near low-grade uranium occurrences in arkosic sandstone of the Denver basin, Colorado, and sediment from streams in the igneous and metamorphic terrace near the Midnite mine of eastern Washington have been analyzed for acid-extractable U, Cu,Pb, Zn, Ni, Co, Fe, Mn, Mo, Cd, Cr, Ag, V, and Se, and for total Fe, Mn, Hg, As, and organic C. The -80 mesh fraction of the alluvium downstream from a small uraniferous limonite occurrence in the Denver basin shows anomalous concentrations of U, Pb, As, Ni, Mo, V, Zn, and Se. Anomalous concentrations of U persist farther downstream (as much as 1,000 m) than any of the trace elements. In another stream system southeast of Denver, above-background levels of U, Pb, As, Zn, V, Fe, and Mn occur near a uranium anomaly (defined by other methods) which has no surface mineralization. In the Midnite mine area, sediments of streams draining prospect areas showed anomalous concentrations of uranium (as much as 10 times background), but no accompanying anomalous trace-element concentrations, although analyses of Midnite mine ores show that a broad suite of trace elements are associated with uranium.

Open-File Report↗
USGS2025

Seismic moment and local magnitude scales in Ridgecrest, CA from the SCEC/USGS Community Stress Drop Validation Study

We illustrate the systematic difference between moment magnitude and local magnitude caused by underlying earthquake source physics, using seismic moments submitted to the Statewide California Earthquake Center/United States Geological Survey Community Stress Drop Validation Study 2019 Ridgecrest data set. While the relationship between seismic moment and moment magnitude ( M or M w ) of log 10 ( M 0 ) ~ 1.5* M is uniformly valid for all earthquake sizes by definition (Hanks and Kanamori, 1979), the relationship between local magnitude M L and moment is itself magnitude dependent. For moderate events, ~3< M < ~6, M and M L are coincident; for earthquakes smaller than ~3, M L ~ 1.0 log 10 M 0 (Hanks and Boore, 1984). This is a physical consequence of the corner frequency fc becoming larger than the upper frequency of observation and implies that M L and M differ systematically by a factor of 1.5 for these small events. While this idea is not new, we propose a new, continuous relationship between local magnitude and moment, for magnitudes 2 to 6 which extrapolates to smaller and larger magnitudes, applicable to southern California specific to the Ridgecrest region. We make use of the plethora of seismic moments as submitted by many participants of the Community Stress Drop study, compared to the Southern California Seismic Network (SCSN) catalog magnitudes. Overall, the seismic moments in the Community Study recover moment magnitude well, so we use our new M L - M 0 to convert M L to M , refining the SCSN operational M Lr scale. This systematic difference of 50% in slope between local and moment magnitude at small magnitudes has implications for spectral stress drop estimates, earthquake ground motion modeling, as well as other magnitude scales and earthquake occurrence statistics.

California↗
USGS2025

Estimating earthquake source depth using teleseismic broadband waveform modeling at the USGS National Earthquake Information Center

The U.S. Geologic Survey National Earthquake Information Center (NEIC) monitors global seismicity, producing a catalog of earthquake source parameters in near-real-time to provide information that can help mitigate the societal impact of earthquakes. The NEIC commonly relies on teleseismic observations to constrain earthquake source parameters (e.g., location, depth, magnitude, and mechanism) due to a lack of local and regional observations. For these ‘teleseismic’ events, depth phase (i.e., pP , sP ) arrival time observations provide the best estimate on source depth. However, depth phases are often difficult to accurately identify and/or pick. Therefore, NEIC relies on waveform modeling, such as those determined from W-phase ( M ww ), body wave ( M wb ), and regional ( M wr ) moment tensor estimations, to provide constraints on source depth. While depth estimates from these approaches are informative, higher frequency observations provide more precise estimates because depth phases are more prominently observed at higher frequencies. Here, we present NEIC’s relatively high-frequency (~0.04 to 1 Hz) teleseismic waveform modeling approach, termed Synthetic Depth Phase Modeling (SynDepth), for determining source depth. SynDepth was developed to provide NEIC with a tool that enables rapid, accurate, and quantifiable estimates of earthquake source depth in cases where locator depths are not reliable. This relatively simple and fast procedure searches over 1 km-incremented source depths and an expanding triangular source-time function to find the best-fitting solution. We compare automatic SynDepth solutions for a dataset of 1,216 earthquakes (M5.5-M7.6) between 2017 and 2021 to NEIC-derived depth estimates from other methods. Our approach provides a robust depth estimate for earthquakes lacking local arrival time data, and it minimizes the need for analyst review of depth-phase picks ( pP , sP ) or using predefined ‘fixed’ depths.

Seismological Research Letters↗