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1,664 records · Page 55Linked to original sources
USGS2024

Agricultural return flow dynamics on a reach of the East River, Colorado, as assessed by mass balance

The U.S. Geological Survey, in cooperation with the Upper Gunnison River Water Conservancy District, studied historical streamflow in a reach of the East River, Colorado, to gain a preliminary understanding of return flow dynamics. Return flow is agricultural irrigation water that is not consumed by evapotranspiration and instead reaches streams by surface and subsurface flow paths. The study reach had a contributing area of 50 square miles and contained 5.23 square miles of pastures irrigated with water diverted from the East River and its tributaries. By comparing upstream inflows to downstream outflows, the net water balance of the study reach from 1994 to 2023 was assessed. Two general hydrologic conditions for the study reach were identified. One hydrologic condition was characterized by a net loss or consumption of water, termed here as general deficit. This general deficit condition extended about 16 years, from 1997 to 2012. During general deficit years, there was usually a notable net loss of streamflow from April through July, and a small net gain, possibly related to return flows, occurred in August about 75 days after the minimums for losses. The second hydrologic condition was characterized by a net gain of water, termed here as general surplus. This second condition extended about 10 years, from 2014 to 2023. During general surplus years, two separate transitions from net loss to net gain commonly occurred during June through August. Losses during general surplus years were smaller than losses during general deficit years, the respective gains were larger, and times between losses and gains were about 18 and 22 days. Differences between the two hydrologic conditions could reflect interactions among irrigation water, available capacity to store additional shallow groundwater, and streamflow. However, deciphering the causes for the shifts between the two general hydrologic conditions was beyond the scope of this report.

Colorado↗
USGS2024

Are the horizontal-to-vertical spectral ratios of earthquakes and microtremors the same?

We consider the similarities and differences between earthquake and microtremor horizontal‐to‐vertical spectral ratios (eHVSR and mHVSR, respectively) using a dataset of 161 sites in southern California. Quantitative comparisons are made in terms of the eHVSR and mHVSR lognormal median curves, as well as the frequencies and amplitudes associated with the fundamental‐ and higher‐mode resonances where present. The results show only 58% of the eHVSR–mHVSR pairs agree in terms of their median curve and only 25% of the eHVSR–mHVSR pairs agree in terms of shared resonances, which increases to 68% if flat HVSRs are considered equivalent. Furthermore, while the shared resonances match very well in terms of frequency (root mean square error, RMSE, <0.11 Hz), the amplitudes of those resonances do not agree (RMSE >1.6). These findings demonstrate that while eHVSR and mHVSR agree at some sites, they are not equivalent at all sites. To investigate if the agreement between eHVSR and mHVSR could be related to features of the microtremor data, earthquake recordings, and/or the site conditions, three machine learning (ML) models at varying levels of interpretability are presented. The ML models—which include multivariate logistic regression, gradient‐boosted trees, and support vector machines—show only partial success at using site‐specific data to predict whether eHVSR and mHVSR will likely agree in terms of their median curve (accuracy of 78%) and number of resonances (accuracy of 84%). Therefore, we conclude that while eHVSR and mHVSR can be quite similar in terms of resonant frequencies at some sites, they are not identical at all sites. Furthermore, preliminary evidence shows that the agreement of eHVSR and mHVSR can be predicted a priori given features of the microtremor measurements, earthquake recordings, and site conditions, although a larger dataset will be necessary for developing a robust predictive model.

California↗
USGS2025

Phase 1 technical implementation plan for the expansion of the ShakeAlert earthquake early warning system to Alaska

Executive Summary The conference report accompanying the fiscal year (FY) 2022 Consolidated Appropriations Act (Public Law 117–103) for the U.S. Department of the Interior and related agencies directed the U.S. Geological Survey (USGS) to “work with the State of Alaska to develop an implementation plan to be completed within two years in order to put ShakeAlert/Earthquake Early Warning in Alaska” (p. 29). Congress included $1 million in the FY 2022 appropriation to conduct this effort. The USGS Earthquake Hazards Program, along with partner organizations, has developed the ShakeAlert earthquake early warning (EEW) system for the West Coast, which currently operates in California, Oregon, and Washington. The purpose of the system and its alert delivery partners is to reduce the impact of earthquakes and save lives and property by delivering ShakeAlert-powered alerts that are transmitted to the public via mass notification technologies, and by providing more detailed data streams to institutional users and commercial service providers to trigger automated, user-specific, protective actions. ShakeAlert was designed in such a way that it could be expanded to other U.S. regions with high earthquake risk, after the build-out of seismic and geodetic networks to support ShakeAlert in a specified region is completed and the necessary funding is secured for long-term operation and maintenance. When an earthquake occurs, seismic waves radiate from the rupturing fault like waves on a pond. It is these waves that people feel as earthquake shaking and that can cause damage to structures. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Early warnings of impending shaking are then sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. There will almost always be a region near the earthquake epicenter where alerts arrive after damaging shaking has begun. The ShakeAlert system updates its ground-motion estimates as an earthquake grows larger. In response to the FY 2022 congressional direction, the USGS worked with the State of Alaska to devise this implementation plan for ShakeAlert expansion to Alaska. The USGS engaged with the Alaska Division of Homeland Security and Emergency Management (DHS&EM) and the Alaska Division of Geological and Geophysical Surveys (DGGS). A cooperative agreement was awarded to the Alaska Earthquake Center (AEC) at the University of Alaska Fairbanks (UAF) for their contributions to the plan and their work coordinating with other networks in Alaska. The USGS engaged with the Alaska Seismic Hazards Safety Commission (ASHSC) throughout the process. The USGS also held a series of Alaska stakeholder engagements. The process of developing the implementation plan was facilitated by contracted staff from Corner Alliance, which is a government consulting firm. This implementation plan describes the details and estimates the costs for a Phase 1 expansion of the ShakeAlert system to Alaska. A geographically limited Phase 1 goal was chosen that covers the highest risk and most populated areas of Alaska. The areas proposed encompass the State’s main population centers and 90 percent of the State’s population. This Phase 1 design is considered very challenging and ambitious from the viewpoint of network operators. The lessons learned if this plan is implemented could be used to consider subsequent phases to expand EEW beyond Phase 1 in Alaska in the future. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System (ANSS). This implementation plan calls for a total of 450 high-quality, real-time EEW-capable ANSS seismic stations in Alaska: 270 new stations, 160 upgraded stations, and 20 existing stations. These seismic station numbers are based on a station spacing of 10 kilometers (km) in urban areas, 20 km in seismic source areas that endanger population centers, and 40 km in other areas. The associated costs also include support for some EEW-capable global navigation satellite system (GNSS) stations, with a focus on improving warnings for large subduction zone earthquakes. For effective EEW, ShakeAlert requires low-latency, high-availability, robust telemetry links to deliver continuous, real-time data from field stations to the data centers. The Alaska data processing hardware infrastructure would follow the general design for fail-safe operation that is used for the ShakeAlert system on the West Coast. The ShakeAlert architecture uses two independent layers: the production layer for earthquake processing and the alert layer to make alerting decisions and serve alerts to users. This implementation plan includes two geographically separated data centers in Alaska, each with two fully independent production and alert layers using the same system design developed for the West Coast. As of March 2024, the ShakeAlert system is at version 3.0.1, with more advanced versions in the development and testing pipeline. ShakeAlert originally used two algorithms to determine the location and magnitude of earthquakes using seismic data. A third algorithm that can calculate very large magnitudes of very large earthquakes with geodetic data was added in March 2024. ShakeAlert publishes several data and alert products to meet the needs of different users. All messages include the location of the earthquake, either as a point or a line, and its magnitude. Ground-shaking estimates are published in two forms, as ground-motion contours and a map grid. Providing adequate warning time for strong shaking (the “target threshold”) requires sending alerts at a threshold lower than that strong shaking level (the “alert threshold”). The thresholds for public alerting in Alaska would be a joint USGS and State decision. To have the greatest benefit, ShakeAlert-powered alerts would be delivered to institutional users and individuals by all practical pathways. The USGS alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission nor the infrastructure and expertise to perform mass notifications to the public or implement automatic actions for end users of the alerts. To meet this need, ShakeAlert recruits private sector “technology enablers” that have the necessary expertise to develop end-user implementations using EEW alerts with the goal of stimulating an EEW industry. Earthquake early warning alerts are useless if people do not know how to respond to them. Although the alert messages include instructions about what to do (drop, cover, and hold on), alerts are more effective if people have been trained in advance. Messages about ShakeAlert’s capabilities, limitations, and benefits could be integrated with existing earthquake education programs, including State-run programs. Therefore, ShakeAlert would coordinate with both public and private partners and stakeholders through various partnerships and agreements to accomplish consistent and ongoing public earthquake hazard education. The estimated capital cost of completing the computing infrastructure and sensor networks for the Phase 1 ShakeAlert expansion to Alaska is approximately $66 million in 2024 dollars. The annual operation and maintenance cost of the completed system is estimated to be $12 million per year in 2024 dollars when fully built out.

Alaska↗
USGS2024

Simulating present and future groundwater/surface-water interactions and stream temperatures in Beaver Creek, Kenai Peninsula, Alaska

In many places, coldwater ecosystems are facing increasing pressure from anthropogenic warming. This study examined stream temperatures and the water balance in the Beaver Creek watershed on the Kenai Peninsula in south-central Alaska—an area that is experiencing rapid warming. Low-gradient streams near the Kenai coast provide important spawning and rearing habitat for salmon but may be especially vulnerable to rising temperatures, because of long residence times, inflows from abundant riparian wetlands, and reliance on groundwater discharge that may also warm, or decrease in volume with rising evapotranspiration. In recent decades, observed maximum 7-day temperatures have consistently exceeded statistical (regression-based) projections. Here we simulate total streamflows and temperatures with a physics-based model that links the Soil Water Balance, MODFLOW 6 and SNTEMP simulation codes on a 7-day timestep. The model is based on existing data and groundwater levels, instream flows, and stream temperatures collected during 2019–23. Future climate scenarios were developed for 2023–50 from downscaled climate projections. Results indicate that groundwater discharge is about 64 percent of the total streamflow during the months of May through September. Total streamflow and groundwater discharge are expected to remain similar to current conditions through 2050. Stream temperatures are expected to rise; by midcentury, near the Beaver Creek mouth the model predicts 34 to 63 additional days per year with average weekly temperatures above 13 degrees Celsius, 14 to 81 additional days with average weekly temperatures above 15 degrees Celsius, and routine exceedances of 20 degrees Celsius during the warmest periods. Projected stream temperatures vary spatially. Areas of high groundwater inflows in the lower main stem and some tributaries may be most resilient to warming air temperatures during dry conditions. During storm events, groundwater-dominated tributaries may have the coolest stream temperatures.

Alaska↗
USGS2025

Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems

Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWS) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWS. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms, through the ability to characterize infiltration during, as well as the drainage and drying processes between major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWS. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.

Alaska↗
USGS2026

Characterizing precariously balanced rocks (PBRs) in the eastern United States for estimating maximum past earthquake ground motions

Fragile geologic features (FGFs) can be used to estimate an upper bound to the strength of earthquake ground shaking in the past thousands to tens of thousands of years. FGFs could be especially useful in the eastern United States, where few active faults are available for paleoseismic studies and where low seismic attenuation means that an earthquake could damage FGFs at large distances. This article describes a pilot study of one form of FGF, precariously balanced rocks (PBRs), in the Blue Ridge of Virginia, ∼160 km from the central Virginia seismic zone (CVSZ) and ∼100 km from Virginia’s Giles County seismic zone (GCSZ). The main goal is to develop and refine methods for studying PBRs in the eastern United States. Photogrammetric 3D models of the rocks were used to locate their centers of mass and delineate their basal contacts, with the latter corroborated by wrapping a wire around the bases to verify the circumferences. Relations between hill geometry and amplification were used to estimate topographic amplification. Seismometers on the PBRs provided the frequencies, amplitudes, and directions of rocking after giving the rocks gentle pushes. The levels of ground shaking likely to topple the rocks were compared with the median hazard curves from the U.S. Geological Survey’s National Seismic Hazard Model and were used to map magnitudes of earthquakes in the nearby region likely to topple the rocks. Results indicate that an M w ≥ 7.5 earthquake is needed in the CVSZ or near the 2020 Sparta, North Carolina, earthquake to topple the two most fragile PBRs and that an earthquake of ~ M w 7–7.5 in the GCSZ is needed. The fragilities and estimated ages of the PBRs (20–40 ka) are thus consistent with the absence of such events in the historical record in the nearby region.

eastern United States↗
USGS2026

Regional models for postfire debris-flow likelihood and rainfall thresholds across the western United States

The U.S. Geological Survey (USGS) uses an empirical model developed with logistic regression (the ‘M1’ model) to rapidly assess debris-flow likelihood and to identify quantitative rainfall thresholds for debris flows after wildfire in the western United States. The M1 model was calibrated to a debris-flow inventory from southern California (United States) and has been applied throughout the western United States. Limited spatial coverage in the calibration dataset has motivated evaluation of M1 model accuracy outside the calibration region (e.g., the Sierra Nevada or the eastern Cascade Range, United States). Previous test cases showed that M1 overpredicts debris-flow likelihood and underpredicts rainfall thresholds for some locations (e.g., Arizona, northern California, Colorado, New Mexico, United States). We sought to improve the regional applicability of a debris-flow likelihood model by expanding the debris-flow inventory used for calibration, testing multiple potential models and generating an updated model framework. The updated inventory includes 3788 observations from 67 burned areas paired with short duration rainfall ratios. The updated model framework consists of a modified model structure and sets of coefficients calibrated separately to the entire updated inventory and to subsets of the inventory that intersect three Environmental Protection Agency (EPA) Level 2 ecoregions (Mediterranean California, Upper Gila Mountains and Western Cordillera). Comparisons of predictions from the updated models with observed rainfall and debris-flow activity show that the updated models outperform the M1 model by ~15%–60% and improve the uniformity of predictive performance across the western United States. The updated models also reduce false positive rates relative to M1 and generate rainfall thresholds that are better aligned with relative differences in regional climatology and debris-flow activity.

Arizona, California, Colorado, Idaho, Montana, Nev↗
USGS2026

The petrogenesis of Þingmúli volcano, East Fjords, Iceland

In this work we revisit Þingmúli volcano (Þ = Th), a classic locality known as an example of a complete tholeiitic differentiation. Þingmúli is a ~ 9.5 Ma extinct central volcano located in the East Fjords of Iceland, in which the whole compositional spectrum from basalt to rhyolites have erupted. These volcanic products have been previously considered as petrogenetically related by an ideal fractionation trend, regardless any temporal relationship or volumetric considerations. Here we report new whole-rock geochemistry, mineral chemistry, isotope analyses, estimation of residence times of the different eruptive deposits, and an update of the original petrogenetic model. Our results highlight that an enriched source, likely spinel lherzolites, generated transitional-alkaline basaltic melts after 15–20% of partial melting at depths of 40–45 km. Many of these basaltic melts erupted at various stages of the volcano's history, while others remained longer in the volcanic plumbing system. These evolved by fractional crystallisation into basaltic andesite magmas with a residence time of ~5 years based on the crystal size distribution of the plagioclase population. Isotopic differences between the basalts/basaltic andesites ( 87 Sr/ 86 Sr ~ 0.7034; 143 Nd/ 144 Nd ~ 0.51315) and the erupted rhyolites ( 87 Sr/ 86 Sr ~ 0.7037; 143 Nd/ 144 Nd ~ 0.51304) indicate that the latter are not petrogenetically related to the former. Therefore, instead of a fractional crystallisation mechanism to generate the rhyolites, we propose the partial melting of ignimbrite layers located beneath the volcano. The broad range of trace element concentrations in andesites and dacites and their different isotopic values compared to the basalts strongly suggest that these magmas have been generated by magma mixing between basaltic and rhyolitic melts, similar to modern day Icelandic volcanoes such as Hekla. These results highlight the need to revisit previously studied Icelandic classic localities and reassess their traditionally proposed petrogenetic models.

Þingmúli volcano, East Fjords↗
USGS2025

A review of abrupt permafrost thaw: Definitions, usage, and a proposed conceptual framework

Purpose of Review We review how ‘abrupt thaw’ has been used in published studies, compare these definitions to abrupt processes in other Earth science disciplines, and provide a definitive framework for how abrupt thaw should be used in the context of permafrost science. Recent Findings We address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire. Summary Permafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic flow, threatening infrastructure and the cultures and livelihoods of northern communities. The term ‘abrupt thaw’ has emerged in scientific discourse over the past two decades to differentiate processes that rapidly impact large depths of permafrost, such as thermokarst, from more gradual, top-down thaw processes that impact centimeters of near-surface permafrost over years to decades. However, there has been no formal definition for abrupt thaw and its use in the scientific literature has varied considerably. Our standardized definition of abrupt thaw offers a path forward to better understand drivers and patterns of abrupt thaw and its consequences for global greenhouse gas budgets, impacts to infrastructure and land-use, and Arctic policy- and decision-making.

Current Climate Change Reports↗
USGS2026

Evaluating groundwater quality influences from oil field operations and other anthropogenic activities in an urban setting, Santa Fe Springs, California

Groundwater quality is often affected by anthropogenic activities in urban settings. This study examines groundwater quality in and around the Santa Fe Springs Oil Field in Los Angeles County, California, where oil and gas production commonly intersects with high density industrial, commercial and residential land uses. Utilizing a combination of new and historical data, we evaluated potential pathways that would allow for oil field formation fluids to migrate into groundwater and whether mixing may have occurred based on the distribution of groundwater and oil field formation fluid tracers in samples. Samples were analyzed for a wide array of constituents including volatile organic compounds, light hydrocarbons, major ions, and various isotopic compositions. Despite evidence of oil field infrastructure providing potential pathways of migration via uncemented annular spaces, casing breaches and historical disposal of oil field formation water in surface ponds, the distribution and occurrence of stable isotopes of water, chloride, boron, and total dissolved solids do not indicate mixing of oil field formation water and groundwater. However, methane isotopic signatures and the presence of heavier alkanes suggest gas from oil-bearing formations have migrated from depth via oil field well infrastructure. Volatile organic compound detections were mainly from manufactured compounds unrelated to oil and gas production, with a relatively limited number of petroleum hydrocarbons also detected. Volatile organic compounds were generally found in wells tapping shallow, modern aged groundwater, indicating anthropogenic activities occurring at or near land surface as the source. Study results suggest that while oil field infrastructure provides migration pathways for oil field formation fluids to be introduced into groundwater, urban land uses not related to oil and gas production are the primary drivers of groundwater quality degradation.

California↗
USGS2024

Framework for mapping liquefaction hazard–Targeted design ground motions

Liquefaction-induced ground failure poses substantial challenges to geotechnical earthquake engineering design. Current approaches for designing against liquefaction hazards, as specified in most seismic provisions, focus on estimating a liquefaction factor of safety ( 𝐹⁢𝑆𝐿 ) and typically characterize earthquake loading using design parameters based on probabilistic or deterministic ground motion levels. Because 𝐹⁢𝑆𝐿 is estimated deterministically, this basis of design neglects considerable uncertainties for estimating liquefaction triggering and its consequences and results in a lack of liquefaction-specific design criteria, particularly as structural design has advanced toward risk-targeted performance objectives. This study presents a framework for developing liquefaction-targeted design criteria based on a minimum acceptable return period of liquefaction, informed by probabilistic liquefaction hazard analysis (PLHA). PLHA quantifies annualized rates of liquefaction by considering contributions from (1) the full ground-motion probability space, and (2) uncertainties in liquefaction triggering using probabilistic models. PLHA is used in this study to characterize the current, effective return periods of 𝐹⁢𝑆𝐿 ( 𝑇𝑅,𝐹⁢𝑆 ) obtained from conventional liquefaction hazard analysis (CLHA) using uniform-hazard ground motions. 𝑇𝑅,𝐹⁢𝑆 is evaluated in a parametric study of nearly 100 sites throughout the conterminous United States. The results indicate large geographic variations in acceptable liquefaction hazard levels, with implied 𝑇𝑅,𝐹⁢𝑆 ranging between approximately 1,000 to 3,000 years. To address these inconsistencies without the computational demands of full PLHA, a framework is proposed for developing a liquefaction-targeted design peak ground acceleration, 𝑃⁢𝐺⁢𝐴𝐿 , for use in liquefaction models that result in consistent liquefaction design levels across all geographic locations. The mapped 𝑃⁢𝐺⁢𝐴𝐿 is shown to be somewhat sensitive to site-specific properties, and adjustment factors are developed and presented. The proposed 𝑃⁢𝐺⁢𝐴𝐿 mapping procedure produces 𝐹⁢𝑆𝐿 estimates that are consistent with those obtained from full PLHA at a target 𝑇𝑅,𝐹⁢𝑆 , providing a promising roadmap to incorporating PLHA concepts into current liquefaction design methods.

Journal of Geotechnical and Geoenvironmental Engin↗
USGS2026

A ground-motion model derived using a generalized mean rupture distance for large slab interface earthquakes

Source–station distance is a central input to ground‐motion models (GMMs) for predicting seismic shaking. GMM development uses distance metrics including the Joyner–Boore distance, which is the shortest distance from an observation point to the surface projection of the earthquake rupture, and R rup the shortest distance to the rupture in three dimensions. Thompson and Baltay (2018) proposed the generalized mean rupture distance R p to address observed near‐fault ground‐motion saturation. R p accounts for the contribution to the shaking of all parts of the rupture and provides a simple method for incorporating spatially variable slip. They used R p to develop a GMM for shallow crustal earthquakes, assuming uniform slip. Here, we investigate the improvement offered by an R p ‐based GMM for large subduction interface earthquakes by recalibrating the path term for a published GMM ( Parker et al. , 2022 ) using R p derived from distributed slip models (DSMs). Inspection of within‐event and total residuals indicates that the recalibrated model fits the data at least as well as an alternative in which the path term was recalibrated using R rup and the same dataset. Incorporating slip information in its entirety or trimming the DSM geometry is preferable to assuming uniform moment release on a prescribed model fault that extends beyond the actual ruptured area. R p tuned to minimize model uncertainty is closer to the maximum distance to rupture for peak ground velocity (PGV) than acceleration, possibly reflecting the contribution to high‐frequency shaking of slip on local asperities. However, when the moment is concentrated far from stations, PGV is fit adequately with R p closer to R rup ⁠ . Our results suggest incorporating slip‐derived moment release through R p could improve GMMs for slab interface events, especially if the implementation of R p ‐based models is refined using a larger dataset of earthquakes with greater geographic diversity to account for regional ground‐motion variations.

Seismological Research Letters↗
USGS2026

The potential impact of three-dimensional distributed slip models derived from real-time GNSS data on the performance of the ShakeAlert earthquake early warning system for slab interface earthquakes

The ShakeAlert® earthquake early warning (EEW) system is designed to warn users of imminent strong ground motion with sufficient time to take protective actions. ShakeAlert currently uses three algorithms to characterize the earthquake source. One estimates the location and magnitude using the first few seconds of the P wave and, while fast, tends to underestimate magnitude for M w 7.0+ earthquakes. A second estimates the location, orientation, length, and corresponding magnitude of a line source using observed peak ground acceleration and contributes primarily to M w 5.5+ earthquakes. The third infers earthquake magnitude from peak ground displacement measured using Global Navigation Satellite System (GNSS) data and offers nonsaturating magnitudes for M w 7.0+ earthquakes. Other EEW algorithms exist that infer temporally evolving spatially variable slip on a 3D fault surface from real‐time GNSS data, information that might enable more accurate and timely alerts in the event of large‐magnitude subduction interface earthquakes. Here, we evaluate the potential contribution of one such algorithm, BEFORES ( Minson et al. , 2014 ), to improve ShakeAlert performance through a simulated real‐time implementation of Bayesian evidence‐based fault orientation and real‐time earthquake slip (BEFORES) and other ShakeAlert algorithms using data for eight M w 7.6+ earthquakes. The test results demonstrate that BEFORES can produce well‐constrained and accurate magnitude estimates as soon as or sooner than other EEW algorithms, in turn enabling it to increase the amount of warning time users receive in many cases. However, with a modified Mercalli intensity (MMI) threshold of 3.5, which is commonly used for issuing alerts, BEFORES would tend to alert large geographic regions that did not feel strong shaking (MMI 6+). This effect can be mitigated using a higher alert threshold of MMI 4.5 without negative impact on the amount of warning time obtainable with BEFORES.

Bulletin of the Seismological Society of America↗
USGS2026

Detecting earthquakes in noisy real-time GNSS data with deep learning for improved PGD magnitude estimation

To disseminate accurate and useful warnings, earthquake early warning (EEW) systems must quickly determine the size and location of an earthquake to estimate expected shaking. Traditional seismic‐based algorithms tend to underestimate the true magnitudes of large earthquakes, a phenomenon known as magnitude saturation. This limitation motivated the recent inclusion of Global Navigation Satellite Systems (GNSS) data into the U.S. Geological Survey’s ShakeAlert EEW system with the Geodetic First Approximation of Size and Time (GFAST) algorithm because GNSS data do not saturate with large ground motions. However, the noise levels of GNSS data are very high compared with traditional seismic data, which obscures P ‐wave arrivals and can result in less accurate magnitude estimations if displacement amplitudes are low, such as for lower magnitude earthquakes or large source–station distances. In this study, we develop a deep‐learning model that detects earthquakes in GNSS data and use the Ridgecrest, California, earthquake sequence as a case study to demonstrate how the model could act as a filter to reduce the amount of low‐quality data that enters an algorithm like GFAST. To preserve our limited real earthquake data for model inference, we generated a training dataset composed of >700,000 synthetic displacement waveforms. We combined the synthetic waveforms with real‐time GNSS noise to produce realistically noisy training waveforms and then tested our model on additional synthetic data and performed inference using the real data that were held back. We discuss the performance of our trained model on both the unseen synthetic data and real inference data. Our model can be used to selectively filter only high‐quality data where an earthquake signal is observed for input into an algorithm like GFAST (outperforming a simple signal‐to‐noise ratio–based filter) to reduce the error in GFAST’s real‐time earthquake magnitude estimations.

California↗
USGS2025

Local, regional, and distal recordings of seismic unrest at Tau Island volcano, American Samoa

A seismic swarm near Taʻū Island, a volcanic island in eastern American Samoa, occurred from July to October 2022. The earliest unrest was noted as felt shaking reports in late July, and instrumentation varied in the beginning of the sequence as the U.S. Geological Survey (USGS) Hawaiian Volcano Observatory responded by installing temporary and then permanent seismometers to monitor the activity. This network variability made it difficult to characterize the earliest seismicity and contextualize the entire sequence to discriminate between an underlying tectonic or volcanic source. Here, we present results analyzing hydroacoustic detections from an International Monitoring System hydrophone array near Wake Island, 4500 km northwest of Taʻū Island volcano. Using least-squares beamforming analysis, we create a catalog of T-wave detections from the direction of Taʻū Island to track the earthquakes, some of which were located by the USGS National EarthquakeInformation Center. Both the rate and hydroacoustic pressures, which we interpret as a proxy for earthquake size, gradually increased from late July to August, peaking on August 19 (rate) and August 24 (size), before decreasing to background in late September. Minutes-long bursts of tremor were also contemporaneously recorded as local network data became avail-able on August 20. Tremor activity continued throughout the rest of August, peaking on August 25, before ending in earlySeptember. These tremor bursts were band-limited to ~ 1–5 Hz and recorded as S waves at a regional station on the island of Upolu in Samoa, 250 km to the west of Taʻū Island. Our results do not constrain the tremor locations, but comparisons of earthquake and tremor reduced displacements recorded locally and regionally suggest a deeper tremor source. We interpret the increase in earthquake size and rate, together with the occurrence, characteristics, and relative depth of the tremor to be the result of magmatic activity beneath Taʻū Island volcano.

American Samoa, Taʻū Island↗
USGS2025

An evaluation of the effects of different deicing salt application rates on three watersheds in Essex County, New York

The U.S. Geological Survey, in cooperation with the New York State Department of Transportation, evaluated the effects of different deicing salt application rates on surface water, groundwater, and highway runoff quality near State highways in northern New York. Three reaches of State highways were tested with different deicing treatments between October 2019 and November 2022: a salt-sand mixture (Treatment A), a salt mixture applied at a lower rate (Treatment B), and a control mixture consistent with typical deicing salt amounts and application rates. Data on pavement conditions and the quality of surface water, highway runoff, and groundwater were collected. Surface electromagnetic data were also collected. Surface-water and groundwater quality downgradient from the State highways were compared with water quality at upgradient locations. The percentage of snow or ice coverage was used to evaluate the effectiveness of the salt applications. This report provides an overview of the transport of deicing salt. The Treatment B watershed had deicing mixture applied more frequently than other highway reaches, which caused it to have the highest annual total chloride application. Despite differences in chloride application, flow-weighted mean chloride concentrations in highway runoff were comparable across treatments. Chloride concentrations were elevated in surface water and groundwater downgradient from highways relative to chloride concentrations upgradient from highways. A chloride mass balance, calculated for one treatment watershed, indicated that groundwater affected by legacy deicing practices may be contributing additional chloride to surface water. Spatial patterns from electromagnetic surveys show a shallow saline plume alongside the highway in that area. Differences in winter severity and pavement-surface conditions drove deicing salt applications in the treatment areas. This study found that several factors affect chloride loads in the watersheds, including variable winter conditions, adaptive snow and ice management, legacy management practices, and area-specific aquifer and groundwater conditions.

New York↗
USGS2026

Water use in Louisiana, 2020

The U.S. Geological Survey (USGS), in cooperation with the Louisiana Department of Transportation and Development, collected water-withdrawal and water-use data from a 2020 inventory of water withdrawals in Louisiana. In 2020, approximately 8,700 million gallons per day (Mgal/d) of water was withdrawn from groundwater and surface-water sources in Louisiana, which represented a 0.22-percent decrease from 2015. Total groundwater withdrawals were about 1,900 Mgal/d, an increase of 7.1 percent from 2015, and total surface-water withdrawals were about 6,800 Mgal/d, a decrease of 2.1 percent from 2015 to 2020. Total water withdrawals, in million gallons per day, in 2020 for the various categories of use were as follows: public supply, 720; industry, 2,100; power generation, 4,100; rural domestic, 39; livestock, 7.0; rice irrigation, 930; general irrigation, 250; and aquaculture, 590. From 2015 to 2020, Louisiana’s total withdrawals for public supply increased by 1.4 percent, industry decreased by 2.3 percent, power generation decreased by 4.9 percent, rural domestic decreased by 1.2 percent, livestock increased by 11 percent, rice irrigation increased by 13 percent, general irrigation increased by 12 percent, and aquaculture increased by 20 percent. About 51 percent (approximately 960 Mgal/d) of all groundwater withdrawn was from the Chicot aquifer system and 24 percent (approximately 450 Mgal/d) was withdrawn from the Mississippi River alluvial aquifer. Since 2015, withdrawals from the Chicot aquifer system increased by 13 percent, and withdrawals from the Mississippi River alluvial aquifer increased by 18 percent. About 72 percent (4,900 Mgal/d) of all surface water withdrawn was from the Mississippi River main stem. This value represents a 1.1-percent decrease in withdrawals from 2015 to 2020. All water-withdrawal and water-use data presented in this report should be considered estimates. Because of rounding, totals and percentages presented in the tables, figures, and text in the report may differ slightly from totals or percentages calculated individually.

Louisiana↗
USGS2024

Produced water geochemistry from hydraulically stimulated Niobrara Formation petroleum wells: Origin of salinity and temporal perspectives on treatment and reuse

Produced water (i.e., a mixture of returned injection fluids and geologic formation brines) represents the largest volumetric waste stream associated with petroleum production in the United States. As such, produced water has been the focus of intense study with emphasis on understanding the geologic origin of the fluids, environmental impacts of unintended or intentional release, disposal concerns, and their commodity (e.g., lithium) potential. However, produced water geochemistry from many active petroleum plays remain poorly constrained leading to knowledge gaps associated with the origin of brine salinity and parameters (e.g., radium levels) that can impact treatment, disposal, and possible reuse. Here we evaluate the major ion geochemistry, radium concentrations, and stable water isotope composition of ~120 produced water samples collected from 17 producing unconventional petroleum wells in Weld County, Colorado from the Late Cretaceous Niobrara Formation. This sample set encompasses eight produced water time series from four new wells across production days 0 to ~365 and from four established wells across production days ~1000 to ~1700. Additionally, produced water from nine other established Niobrara Formation wells were sampled at discrete time points ranging from day 458 to day 2256, as well as hydraulic fracturing input fluids. These results expand the available Niobrara Formation produced water geochemical data, previously limited to few wells sampled within the first year of production, allowing for the heterogeneity of major ions and radium to be evaluated. Furthermore, we explore the geochemical relationships between major ion ratios and stable water isotope composition to understand the origin of salinity in Niobrara Formation brines from the Denver-Julesburg Basin. These findings are discussed with perspective toward potential treatment and reuse of Niobrara produced water prior to disposal.

Colorado, Nebraska, Wyoming↗