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USGS2026

Modeled groundwater and surface-water interactions surrounding Mobile Bay, Alabama, 2008–15

The U.S. Geological Survey, in cooperation with the Gulf Coast Ecosystem Restoration Council, has used MODFLOW 6 to develop a groundwater-flow model to simulate groundwater and surface-water interactions in the Mobile Bay, Alabama, area. The model results indicated that, on average, groundwater discharge near the coastline is equal to 2.5 percent of the surface water that flows into the bay. The model was also used to determine how changes in recharge, sea level, and groundwater pumping affect groundwater levels and discharge rates. The results indicate that more groundwater discharge occurred in the winter and spring when recharge was higher, sea level was lower, and groundwater pumping was lower than during the summer and fall. Additionally, the amount of emergent groundwater was closely related to sea level; when sea level was higher, there was more area with emergent groundwater. Furthermore, the depth of nonemergent groundwater was related to trends in recharge and pumping. During periods of increased recharge and reduced pumping, a significant portion of the model area exhibited a depth to the water table of less than 1 meter below the land surface. Conversely, during periods of decreased recharge and heightened pumping, much of the model area showed a depth to the water table ranging from 1 to 5 meters.

Alabama, Mississippi↗
USGS2026

Beaver dam analogs as nature-based solutions to mitigate snowpack loss in northern New Mexico

Reductions in snow have left many streams in northern New Mexico dry or with very low flows during the summer. Base flow, defined as the contribution of groundwater to streamflow, can sustain streamflow during the summer and during drought conditions. Beaver dam analogs can be used to “slow the flow,” or increase the infiltration of rain-based runoff to replenish shallow groundwater reservoirs and increase base flow and potentially increase summertime streamflow.

New Mexico↗
USGS2025

Ubiquity and causes of soil water preferential flow across 17 ecoregions

Preferential flow (PF) in soil causes the rapid transport of water, nutrients, and contaminants into the subsurface, influencing groundwater recharge and streamflow. Data scarcity has hindered the quantification of PF occurrence and the identification of its drivers across diverse ecoregions. We address this gap by analyzing high-frequency, multi-depth soil moisture data across 17 ecoregions in the USA, using ∼1,500 sensors at 40 sites. We discovered that PF is widespread, with sites experiencing PF in up to 60% of rainfall events ≥2 mm. Multiple approaches consistently show that PF is more likely to occur with increased peak rainfall intensity, finer textured material, low soil moisture variability, humid climate, and higher net primary productivity. This suggests that PF patterns could shift with projected climate changes, increasing uncertainty in predictions of groundwater recharge, water quality, and streamflow generation.

conterminous United States and Puerto Rico↗
USGS2025

Detecting hidden sedimentary geothermal systems in the Upper Colorado River Basin

Geothermal resources exist in sedimentary rock where circulation of water for efficient extraction or storage of heat is possible. Except in rare instances where hot water is expressed at the land surface, sedimentary geothermal resources are hidden, so the identification of these systems is optimally accomplished using predictive subsurface modeling. An integrated approach using detailed paleogeographic interpretations, subsurface geologic mapping, and numerical modeling has produced regional geologic and temperature models for the Upper Colorado River Basin, a large watershed in central North America that contains many sedimentary basins. These models identify areas of hidden sedimentary geothermal resource potential in low temperature (<90°C), moderate temperature (90–150°C), and high temperature (>150°C) fairways across the study area. These models incorporate maps of key horizons in outcrop and the subsurface to create a robust structural framework that can be used to target favorable geology for natural or engineered permeability. This framework is populated with lithologies derived from detailed palaeogeographical maps and over 40,000 bottom hole temperature (BHT) values were used to create a calibrated three-dimensional (3D) temperature model across the region. The resulting maps serve as a regional sedimentary geothermal play fairway screening tool for evaluating different grades of sedimentary geothermal resources and for identifying areas of interest where more detailed, prospect-scale studies can be undertaken.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2024

Effects of stochastically-simulated near-fault ground motions on soil liquefaction

The scarcity of historically recorded near-fault ground motions poses a challenge to systematically understanding the influence of near-fault effects on various types of seismic demands for engineering purposes. In particular, the current state of knowledge of the influence of ground-shaking intensity on soil liquefaction and its consequences does not specifically account for the effects of near-fault ground motion characteristics. In this study, the influence of near-fault ground motions on liquefaction triggering and lateral spreading are investigated using non-linear modeling of a hypothetical liquefiable soil column in the finite-element computational platform OpenSees subjected to simulated ground motion time series that represent strong earthquake shaking in the near field. The simulated ground motion time series and resulting datasets are based on a parametric stochastic model and are developed for a range of source and path parameters to represent a realistic variability of ground motion characteristics. Dependencies between ground motion intensity measures (IMs) and liquefaction demand parameters are investigated for near-fault pulse and nonpulse-like ground motion sets. Evolutionary IMs, such as cumulative absolute velocity (CAV) and the time-varying magnitude-adjusted peak ground acceleration (PGAM), are considered in developing liquefaction triggering probability density functions. Post-liquefaction triggering responses such as lateral spreading displacements are examined in relation to PGA M and CAV. The ground motion simulations are validated by comparing their liquefaction-capacity PGA M fragilities and post-triggering CAV vulnerability relationships to historical records from the 1994 Northridge earthquake in California, USA. Finally, a path forward for future studies that includes finding systematic differences in the IM-liquefaction demand relationships between near-fault and far-field stochastic ground motion sets is outlined.

Conference Paper↗
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

Formation of the Mount Weld rare earth element deposit, Western Australia: A carbonatite-derived laterite

Carbonatite-hosted rare earth element (REE) deposits are the primary source of the world’s light REEs. The Mount Weld REE deposit in Western Australia is hosted in a lateritic sequence that reflects supergene enrichment of the underlying carbonatite. Water-rock interaction is a key to the formation of this world-class deposit. REE enrichment in the laterite is controlled by the breakdown of primary minerals, the release and transport of REEs, and the formation of secondary minerals. Secondary REE-bearing phosphate minerals are the primary REE-host phases in the laterite ore with monazite as the dominant phase; other REE-bearing phases include rhabdophane, cerianite, churchite, florencite, and crandallite subgroup minerals. Profiles through the laterite show that in the REE-rich zone, apatite and primary calcite and dolomite have broken down such that the loss of Ca and Mg, as well as Si and K, leads to a relative increase in the REEs. Sequestering of REEs in secondary mineral phases formed by groundwater further enhances the REE concentration.

Mount Weld Mine↗
USGS2026

Deep critical zone controls on shallow landslides

The deep critical zone (CZ) has long been recognized for its importance in influencing shallow landslides but was not considered feasible to include in slope stability models at the watershed scale. In this study, we demonstrate that simple approximations of the CZ in a fully coupled hydrologic and soil slope stability model can effectively capture the location, timing, and likely size of shallow landslides. To achieve this, we use coupled, process-based models that incorporate the effects of 1) deep CZ structures, 2) three-dimensional transient hydrology, and 3) multidimensional slope stability, calibrated with data from an intensively monitored field site. Our results show that the hydrologically active deep CZ guides groundwater flow, influencing where it drains from or exfiltrates to the soil mantle, producing distinct patterns of soil saturation and seepage forces at the soil-bedrock boundary. Deep conductive weathered critical zone drains the soil mantle, reducing the likelihood of destabilizing pore pressures, while the downslope thinning of the CZ forces groundwater to the surface. This creates localized instability and a tendency for similar-sized landslides across the landscape. In contrast, the absence of conductive weathered bedrock results in more widespread destabilizing pore pressures, leading to larger landslides and the likelihood of landslides earlier in a storm than in landscapes underlain by a deep CZ. Our findings suggest that first-order variations of deep CZ can provide physical explanations for variations observed in the susceptibility, magnitude, and timing of shallow landslides, and that CZ structure may be inferred from patterns and timing of landsliding.

Proceedings of the National Academy of Sciences↗
USGS2026

Discrete element investigation of the influence of shallow soil density on the manifestations of strike-slip surface fault rupture

This study investigates the influence of soil relative density on strike-slip surface fault rupture manifestations using three-dimensional numerical simulations performed with the discrete element method (DEM). The simulations capture the formation of distinctive fault strands within complex flower structures using tens of millions of grains. The tendency for dense soils to localize shear manifests as multiple localized shear bands within wide zones of deformation in strike-slip fault rupture, whereas diffuse shear deformation develops within narrow zones in loose soils. The spatial extents of soil deformation are consistent between simulations having similar relative densities but with different quantities of grains. However, individual shears are more distinguishable in assemblages of finer grains than in assemblages of coarser grains. The simulations show the progressive development of new shears within the bounds of previously developed shears. Shear activity transitions inward as fault activity diminishes along the outermost shears and continues along newly developed shears until a vertically dipping throughgoing shear structure develops that accommodates most of the fault displacement thereon. The throughgoing fault develops at smaller fault displacements in looser soils because the first shear rupture propagates closer to the vertical direction and does not undergo as much inward translation of shear activity, as is observed in denser soils. In all simulations, ground surface uplift develops between nonintersecting active shears, and ground surface subsidence tends to develop where new shears intersect previous shears. The surface traces in these simulations are shown to be consistent with analog models and case histories of surface fault rupture occurring in different shallow subsurface materials. Although computationally costly, these modeling results are valuable for providing a strong numerical supplement to traditional analog models used to represent the mechanics of strike-slip zones in soil, and they provide quantifiable stresses and large-strain deformations throughout the model domain.

Journal of Geotechnical and Geoenvironmental Engin↗
USGS2025

Depth of magma crystallization and fluid exsolution beneath the porphyry-skarn Cu deposits at Santa Rita and Hanover-Fierro, New Mexico, USA

The depth level at which porphyry Cu–forming magmas fractionated and exsolved mineralizing fluids is actively debated. In the classic model, extensive magma fractionation occurs in large, upper crustal magma chambers, and concomitant fluid exsolution leads to forceful expulsion of residual magmas in the form of porphyry dikes, stocks, and breccia pipes, which subsequently serve as pathways for the mineralizing fluids. In contrast, some recent studies highlighting the role of deep crustal magma fractionation in the production of fertile magmas essentially deny the existence of upper crustal magma chambers at the time of mineralization. To address this, we conducted a detailed thermobarometric investigation of 13 intermediate to felsic, porphyritic intrusive rocks related to porphyry-skarn Cu mineralization at Santa Rita and Hanover-Fierro, New Mexico, United States, representing two premineralization magmas (61–60 Ma), seven synmineralization magmas (60–58 Ma), and four late- to postmineralization magmas (58–57 Ma). For each sample, the pressure of last magma crystallization before final magma ascent to the current exposure level was reconstructed based on Al-in-hornblende barometry of small hornblende inclusions trapped within quartz phenocrysts and through titanium-in-quartz (TitaniQ) thermobarometry of the host quartz phenocrysts themselves. Since quartz is one of the last crystallizing magmatic minerals, and no significant phenocryst growth could have occurred in small dikes and stocks after final magma emplacement, quartz phenocrysts and their contained hornblende inclusions record the depth of last magma crystallization before final magma ascent. When present, hornblende phenocrysts and hornblende inclusions within other major phenocrysts were also analyzed. Both quartz and hornblende barometers return consistent average pressures of 3.2 ± 0.4 kbar for the entire suite of pre- to postmineralization magmas, corresponding to depths of 11 to 14 km. The synmineralization magmas return even more consistent average pressures of 3.1 ± 0.2 kbar, corresponding to a depth of 12 ± 1 km. The volume of the mineralizing porphyry dikes and stocks at the emplacement level is far too small to have provided all the fluids and metals required to form the observed ore deposits. Therefore, the majority of the ore-forming fluids must have originated from the magmas that crystallized at 12 ± 1 km depth. The ore deposits, conversely, formed at ~5-km paleodepth. This implies that most of the mineralizing fluids traveled an average vertical distance of ~7 km from their magmatic source to the eventual site of ore precipitation. The relatively unaltered nature and low veining degree of deeper parts of mineralized porphyry dikes and stocks suggest that the fluid transport through these intrusive bodies occurred mostly at near-solidus conditions by means of fluid percolation along grain boundaries. In summary, our results suggest that (1) a large, upper crustal pluton exists ~7 km beneath the Santa Rita and Hanover-Fierro deposits; (2) abundant phenocryst crystallization occurred at this depth level; and (3) this pluton was the main source for the exsolution of ore-forming fluids. However, the investigated rocks have elevated whole-rock Sr/Y ratios, indicating magma fractionation at deep crustal levels. As a result, our preferred model is a combination of the two end-member models introduced above, with most magma fractionation having occurred in the deep crust and with residual, intermediate to felsic melts having ascended and accumulated at 11 to 14 km paleodepth, where they continued to crystallize with comparatively little crystal-liquid separation, before some of these magmas ascended further to shallow levels and quenched to porphyries.

New Mexico↗
USGS2025

Groundwater surveillance of swine pathogens from private wells supplying swine farms in Iowa

Biosecurity practices are essential for maintaining pig health and productivity. Despite these measures, pathogen spread still occurs. Water is one of the largest daily inputs on swine farms by volume and is not routinely tested or disinfected before it is consumed by the animals [1-3], making it a poorly understood biosecurity risk. Groundwater from privately-owned wells is a common water source for swine farms. Pathogens in the landscape, such as bacteria, viruses, and protozoa, can reach groundwater more rapidly through soil macropores, maintaining viability and facilitating transmission of pathogens into aquifers [3-13].

Iowa↗
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↗
USGS2025

Review and synthesis of the applications of machine learning to coalbed methane recovery

Over the last 30 years, a substantial literature has evolved on the use of machine learning (ML) to assess, predict, and improve the efficiency of coalbed methane (CBM) recovery. In the United States, the production of CBM declined as shale gas production matured, but CBM continues to be an important energy resource in other parts of the world. ML applications that have the potential to improve CBM reservoir management and production forecasts, and to increase exploration and operational efficiency, are still of significant interest. The integration of geostatistical techniques into the CBM ML applications has been largely absent but represents an opportunity for improvement. The literature demonstrates the widespread interest in, and applicability of, ML algorithms applied to CBM problems, and that they continue to result in improvements in predictive performance. However, (1) much of the research is more academic than operational, (2) many results are based on simulations, or small or proprietary datasets, (3) ML performance information can be inconsistent and sometimes entirely omitted, (4) most methodologies are unique to the specific CBM situation and likely not generalizable, (5) no standard data repositories are available to directly compare the performance of competing algorithms, and (6) the spatial component is often omitted. Finally, relatively new ML protocols involving causality analysis and reinforced learning, as well as hybrid workflows combining both supervised and unsupervised learning, are anticipated to dominate the future investigations. Integration of geostatistical and geospatial analysis with ML should enhance performance.

Book chapter↗
USGS2024

Onset of aftershocks: Constraints on the Rate-and-State model

Aftershock rates typically decay with time t after the mainshock according to the Omori–Utsu law, R (t)=K(c+t) −p ⁠ , with parameters K , c , and p . The rate‐and‐state (RS) model, which is currently the most popular physics‐based seismicity model, also predicts an Omori–Utsu decay with p = 1 and a c ‐value that depends on the size of the coseismic stress change. Because the mainshock‐induced stresses strongly vary in space, the c ‐value should vary accordingly. Short‐time aftershock incompleteness (STAI) in earthquake catalogs has prevented a detailed test of this prediction so far, but the newly developed a ‐positive method for reconstructing the true earthquake rate now allows its testing. Using previously published slip models, we calculate the coseismic stress changes for the six largest mainshocks in Southern California in recent decades and estimate the maximum shear as a scalar proxy of the coseismic stress tensor. Aftershock rates reconstructed for events in different stress ranges show that the rates follow a power law with p = 1 independent of stress with no clear sign of a c ‐value. The onset of the power‐law decay is abrupt and more delayed in areas with smaller stress changes. The observations do not necessarily contradict the RS model, as STAI limits the resolution for early aftershocks, and the RS model can reproduce the observations for specific Aσ values. However, the observations lead to strong constraints, namely Aσ <10 kPa and a power‐law decay of the background rate with distance to the fault, with exponent 2.7.

Seismological Research Letters↗
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↗
USGS2022

New Hampshire and Landsat

At its widest point, a mere 80 miles separate the eastern and western borders of New Hampshire. Its northern and southern borders are just 175 miles apart. Even so, few States can boast as much rugged natural beauty per mile as the Nation’s fifth smallest. Nestled within New Hampshire are 93 State parks teeming with moose, Ursus americanus (Pallas, 1780; black bears), coyotes, beavers, river otters, and foxes. The largest section of White Mountain National Forest cuts across north-central New Hampshire, drawing visitors to its lakes, streams, mountain peaks, and hardwood forests. New Hampshire also is home to Lake Winnipesaukee, the State’s largest lake, notable for its floating post offices, the annual “ice-out” contest that sees residents vying to guess the date its surface ice dissipates, and its supporting role in films such as “On Golden Pond” and “What About Bob?” However, the scenic forests of New Hampshire face challenges in the form of invasive species such as Lymantria dispar (Linnaeus, 1758; spongy moth), Adelges piceae (balsam woolly adelgid), and Agrilus planipennis (emerald ash borer). In recent years, New Hampshire’s lakes and streams have seen more cyanobacterial blooms as well. The U.S. Geological Survey Landsat Program offers a consistent, reliable, and historically unmatched source of Earth observations that can aid in the mapping, monitoring, and management of New Hampshire’s land and water resources. Here are a few ways Landsat data have been used in the Granite State.

New Hampshire↗
USGS2025

Refining the earthquake history of south-central Alaska through lake records

The Alaska–Aleutian subduction zone (AASZ) is one of the world's most seismically active plate boundaries and the source of the 1964 M w 9.2 Great Alaska earthquake–the second largest instrumentally recorded earthquake in the world. Understanding the nature and frequency of such earthquakes is necessary for seismic and tsunami hazard assessment, but instrumental and historical records that span less than 150 years are too short to allow a statistically reliable analysis of earthquake recurrence times. This calls for studies of evidence of past earthquakes, extending the earthquake catalog further back in time. Subduction-zone paleoseismology in south-central Alaska is predominantly based on coastal evidence of land-level changes and tsunamis generated by megathrust earthquakes and preserved in the geological record. A complementary approach is lacustrine paleoseismology, which is still a relatively young discipline in Alaska. However, globally, lake basins are well-established high-resolution and continuous recorders of paleoseismic activity along subduction zones, relying on the identification of underwater landslide deposits and turbidites generated by seismic shaking. As a result, lake basins not only register ground shaking from megathrust earthquakes, but also from intraslab and crustal earthquakes, which are typically not accompanied by significant land-level changes. In this review paper, we combine coastal and lacustrine paleoseismology approaches to refine the south-central Alaskan earthquake history by comparing the paleoseismic records from two lakes (i.e., Eklutna Lake, located in the Chugach Mountain Range, and Skilak Lake, situated on the Kenai Peninsula) with the coastal and crustal earthquake catalog in Alaska. The resulting age ranges of all known megathrust earthquakes involving the Alaskan megathrust between the Kodiak and Prince William Sound (PWS) sections are more precise and accurate for the last 1.3 kyrs BP than the previously published age ranges from coastal records. As a result, this study supports the following key conclusions: (1) The 1964 CE earthquake was an exceptionally strong and unique event in the last 2000 years, rupturing the PWS, Kenai, Barren Islands, and Kodiak sections simultaneously. (2) The high-resolution and seasonal markings of the varved lake records now disentangle for the first time closely timed earthquakes, which was not possible based on the coastal evidence alone. (3) No persistent megathrust rupture boundaries exist. So, the possibility of a full rupture of the entire eastern AASZ, from PWS to Semidi cannot be excluded. (4) The rupture pattern in the eastern AASZ reveals superimposed cycles of multi-asperity ruptures (1964 earthquake) and clustered complementary partial ruptures, or rupture cascades. (5) The PWS section hosts the largest asperity in the eastern AASZ. (6) The shaking record of megathrust earthquakes indicates a time-dependent (quasiperiodic) behavior for the study area, but the observation of complementary clusters means that the hazards will not drop to zero but instead may even increase for a neighboring section. (7) The time-independent behavior of intraplate earthquakes implies that the intraslab hazard did not decrease following the 2016 and 2018 earthquakes. This study utilizes an integrated approach for subduction zone paleoseismology as a solution for unraveling recurrence and rupture patterns in Alaska, which can be applied worldwide.

Alaska↗
USGS2026

Cotton farming pesticides affect ileal microbiota activity expressions of virulome but not resistome or metabolic pathways in a sedentary wild passerine

The increased use of agrochemicals to enhance crop production has had detrimental environmental effects including implication in the sharp decline of North American farmland-breeding birds. Here, using a combination of deep shotgun metatranscriptomics and pesticide exposure data, we sought to assess whether exposure to cotton ( Gossypium spp.) production had a differential effect on ileum multi-kingdom microbial activity, metabolism, anti-microbial resistance, and virulence factors of sedentary northern mockingbirds ( Mimus polyglottos ) sampled from two cotton-producing areas (16 birds in total) and one uncultivated area (7 birds) in Texas, USA. Both Shannon Index values (Adj. r 2 = 0.174, F (1,21) = 5.633, p = 0.027) and a Mantel test (Spearman ρ = 0.184, p = 0.013) supported a relationship between metabolically active microbiota Bray–Curtis dissimilarities and differences in pesticide mixtures among study areas. Virulence factor richness (Adj. r 2 = 0.182, F (1,21) = 5.890, p = 0.024), Shannon Index (Adj. r 2 = 0.231, F (1,21) = 7.612, p = 0.012), and load (sum of virulence factor abundances; Adj. r 2 = 0.160, F (1,21) = 5.194, p = 0.033) were related to total pesticide load (total quantity of pesticides). We found no pesticide effects on expression of either antimicrobial resistance genes or metabolic pathways.

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