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USGS2026

Evaluating the U.S. Geological Survey’s earthquake shaking hazard forecasts and their implications on seismic risk

We analyze the last six update cycles of the long-term probabilistic earthquake shaking hazard forecast from the U.S. Geological Survey (USGS) and discuss the changes in hazard estimates from the 1996 to the latest 2023 update of the National Seismic Hazard Model (NSHM) for the conterminous U.S. We summarize how our understanding of earthquake hazards has evolved over the last two decades and quantify the implications of changing hazards on people, buildings, and lifeline infrastructure. The net effect of changes in hazard estimates, with reference to the mean hazard from the 2023 NSHM update that has 2% probability of exceedance in 50 years, suggests an overall increase in total geographic areas facing very strong shaking levels (modified Mercalli Intensity (MMI) of VII or more) when compared with any of the previous cycles. This increase puts ~159.2 million people (an increase from 111.8 million when using the 2018 NSHM), ~47.3 million residential buildings (an increase from 32.5 million with the 2018 NSHM), and ~$25.6 trillion of economic exposure of all buildings (an increase from $17.4 trillion when using the 2018 NSHM) at risk from earthquakes. We demonstrate that small changes in hazard estimates do not necessarily imply small changes in risk estimates. Therefore, changes in risk estimates can be used to highlight key USGS NSHM updates for improving risk mitigation efforts.

Earthquake Spectra Journal↗
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↗
USGS2026

Earthquake rupture arrest from depth‐dependent frictional stability on the Pütürge segment of the East Anatolian Fault Zone, Türkiye (Turkey)

Determining why earthquake ruptures stop is a central challenge in earthquake science and seismic hazard assessment. The Pütürge segment of the East Anatolian Fault Zone, Türkiye, exhibits shallow creep (<∼3 km depth) yet hosts M > 6.5 earthquake ruptures at greater depth. Here, we evaluate whether variations in frictional stability along this segment aided arrest of the 2020 M 6.7 Elaziğ and 2023 M 7.8 Pazarcık earthquake ruptures. Analysis of Sentinel‐1 Synthetic Aperture Radar imagery indicates the 2023 M 7.8 rupture propagated laterally into a metamorphic massif within the Pütürge segment, where slip rapidly decayed below detection limits. Creepmeters along this segment recorded no significant surface afterslip (<3 mm) in the following year. To investigate this fault‐slip behavior, we conducted triaxial friction experiments on Pütürge fault gouge sampled from an outcrop exposure. The gouge, composed primarily of muscovite, quartz, and calcite, is velocity strengthening at conditions approximating 0–2.5 km depth and velocity weakening at 4–5 km depth. This transition to velocity‐weakening friction is associated with enhanced comminution and shear localization observed microstructurally. Our results suggest that depth‐dependent frictional stability of the Pütürge fault segment facilitates rupture nucleation and propagation at depth while maintaining rupture‐arresting behavior near Earth’s surface.

Pütürge segment of the East Anatolian Fault Zone↗
USGS2025

Mapping potential sensitivity to hydrogeomorphic change in the UMRS riverscape

In 2020 the U.S. Geological Survey (USGS), as part of the Upper Mississippi River Restoration (UMRR) Program, began a new project to characterize potential hydrogeomorphic change associated with hydrogeomorphic units (HGUs) and their catenae (units linked by their association with sediment sources and flow origins). The goal of the project was to develop a geographic information system (GIS) database of HGUs for the Upper Mississippi River System (UMRS) available to both scientists and river managers working on UMRR studies and HREP planning and design studies. The characterization was based on a hydrogeomorphic change hierarchical classification developed previously for the UMRS. The products were generated with automated techniques in a GIS using systemic datasets. Landforms were mapped from the 2015 UMRS topobathymetric dataset with geomorphon (shape-based) tools tailored for the large riverscape, valley bottom environments in the UMRS. A clustering analysis was applied to the resulting landforms to identify HGUs associated with zones of perennial low flows, bankfull flows, and overbank floodplains. Catenae were assembled based on the proximity of the units to the main channel, tributary mouths, and side channels from previously published aquatic areas (USACE, 2018) coupled with least-cost flowpath linkages between potential sediment origins and planform change units developed by Rogala, Fitzpatrick, and Henderson (2020). These GIS-based analyses were successful at identifying a range of HGUs using an automated technique with available data across the entire riverscape, with emphasis on those that have the potential for hydrogeomorphic change. Most of the resulting features are depositional, as expected in a large river system. However, this is the first attempt of linking tributary inputs, side channel erosion and levee breaches with their depositional counterparts. The approach was successfully piloted in Pools 8 and 10 in the Upper Impounded Reach and Pool 14 in the Lower Impounded Reach, with next steps for application in reaches of the unimpounded section and Illinois River. This report emphasizes results from Pool 10, which was the focus of most of our attention during the pilot phase.

Illinois, Indiana, Iowa, Minnesota, Missouri, Sout↗
USGS2025

Per- and polyfluoroalkyl substances (PFAS) mass flux and mass balance at an aqueous film-forming foam release site in semiarid eastern New Mexico, USA

Passive flux meters (PFMs) directly measure groundwater chemistry mass flux and Darcy flux, providing insight into contaminant source-zone architecture and transport properties. This study uses PFMs to characterize PFAS flux in groundwater at a semiarid site with a thick (greater than 90-m) unsaturated zone where groundwater has been contaminated with per - and polyfluoroalkyl substances (PFAS) related to the use of aqueous film-forming foam (AFFF) for fire training and fire suppression. PFAS mass discharge (PFAS mass flux integrated over a control plane) in groundwater downgradient from several PFAS release areas is calculated using PFM results. In groundwater downgradient from fire-training areas, total PFAS mass discharge (summed across 14 compounds) was estimated to be between 6.0 and 31 g per day in 2020 and between 5.9 and 23 g per day in 2021. Site-specific documentation, generic information on AFFF properties, and literature values of PFAS concentration in AFFF are used to estimate site-specific PFAS-application rates at fire-training areas. These PFAS-application rates are compared to groundwater PFAS-discharge rates. Results suggest that transformation processes (exact pathways unknown) have led to increased discharge of measured PFAS in groundwater relative to initial AFFF formulations. The mass balance approach has broad applicability as a high-level approach that can provide insight into PFAS transport at AFFF sites.

New Mexico↗
USGS2025

Linking stream-reach nitrogen loads and groundwater “reachsheds” to inform wastewater-nitrogen management actions, Cape Cod, Massachusetts

Study Region Cape Cod, Massachusetts, U.S.A. Study Focus Anthropogenic nitrogen (N) is a key factor in degrading groundwater and surface-water quality, particularly in coastal New England where onsite wastewater systems are prevalent. This study evaluated whether direct N-load measurements in streams on Cape Cod, Massachusetts, coupled with flow-path information from groundwater-flow models, can effectively identify potential land areas where nitrogen mitigation could substantially reduce loads to receiving waters. Nitrogen fluxes were measured along 63 stream reaches during winter and summer and paired with simulated groundwater recharge areas to identify and rank potential areas for reduction of nonpoint-source N inputs. New Hydrologic Insights for the Region Reach-scale nitrate-N loads ranged from −39.1–1182 kg-N/yr per 100 m of stream, indicating spatially variable groundwater inputs across seasons. “Reachsheds” — areas contributing groundwater recharge to specific stream reaches — were delineated using a regional groundwater-flow model. Strong correlations were found between observed N loads and land-use characteristics, especially the number of septic systems and total N inputs from the sum of considered sources. Observed N loads were moderately correlated with recharge area size and wastewater flow estimates. Correlating reach-specific groundwater N loads with land use and parcel-scale nitrogen-yield data identified reachsheds with the highest potential for N load reduction. This approach enables targeted implementation of restoration efforts to optimize nutrient management and support regional load reduction.

Massachusetts↗
USGS2025

A probabilistic assessment methodology for the evaluation of geologic energy storage capacity—Natural gas storage in depleted hydrocarbon reservoirs

The need for energy storage, particularly underground, where capacity and duration may far exceed battery storage technologies, is especially relevant given the increasing demands for reliable power alongside the development of intermittent renewable electricity sources. Geologic energy storage facilities already exist, and expanded use would enable storing gases such as methane and hydrogen. In 2018, a National Academies of Sciences, Engineering, and Medicine report, “Future Directions for the U.S. Geological Survey's Energy Resources Program,” recommended that the U.S. Geological Survey (USGS) prioritize assessing underground energy storage in geologic formations in the United States. The U.S. Geological Survey has since developed a methodology for assessing natural gas storage capacities in depleted hydrocarbon reservoirs on a national scale. The methodology introduced in this report prescribes three approaches for calculating gas storage capacity. This methodology relies on the availability of input data, including cumulative hydrocarbon production records, reservoir petrophysical properties, and reservoir pressure data. Assessment inputs can be obtained from public, State-level databases and propriety national-scale databases, although the use of analogs could be warranted for estimating input parameters. Probabilistic assessment results are aggregated to play, petroleum province, regional, and national scales. The steps defined in this report are demonstrated on the Michigan Basin Province, which includes the Mississippian Sandstone Gas Play and the Clinton Structural Play. This methodology could be used to systematically and consistently assess hydrocarbon plays and provinces for natural gas storage capacity across the United States.

Michigan↗
USGS2024

Geospatial PDF map of the compilation of GIS data for the mineral industries and related infrastructure of Africa

Introduction In 2021, the U.S. Geological Survey's (USGS) National Minerals Information Center (NMIC) completed the project titled "Compilation of geospatial data for the mineral industries and related infrastructure of Africa." This project aimed to leverage the expertise and capabilities of the NMIC to collect, synthesize, and interpret geospatial data to inform on the extractive resources of the African region and expand the NMIC's understanding on the impact of mineral industry of African nations in the global economy. The African region, which comprises the independent nations that make up the African continent and its associated islands and dependencies, consists of a total of 58 mineral producing countries. The primary objective of this effort was to create a fully attributed Geographic Information System (GIS) portraying existing mining infrastructure, resources, and development capacity across Africa along with the related infrastructure capable of supporting current (for the reference year 2018) and future extractive industry operations in the region. The compiled GIS geodatabase with supporting documentation including comprehensive metadata was published as a USGS data release titled "Compilation of Geospatial Data (GIS) for the Mineral Industries and Related Infrastructure of Africa." This georeferenced portable document format (GeoPDF) map sheet presents a new geographic information product containing a partial representation of the GIS data. This GeoPDF map provides a visual comparison of the distribution of mineral industry and related infrastructure GIS data, which contributes to a deeper understanding of the intersections and complexities of the extractive industries within Africa.

Open-File Report↗
USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗
USGS2025

Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California

The Mountain Pass carbonatite stock is the largest rare earth element (REE) deposit and only active REE mine in the United States. The carbonatite intrusion and spatially associated alkaline silicate intrusions constitute the Mountain Pass Intrusive Suite, which is located within the Mojave Province in California. Both the carbonatite and the alkaline silicate rocks are enriched in large ion lithophile elements and light REEs, and less enriched to depleted in high field strength elements, indicating the mantle source region was metasomatically enriched in incompatible trace elements. The cause of this metasomatic mantle enrichment and the genetic relationship between the carbonatite and the alkaline silicate stocks are poorly understood. In this study, major and trace element geochemical data and isotopic (Rb-Sr, Sm-Nd, and Lu-Hf) data are presented to constrain genesis of the Mountain Pass Intrusive Suite, from mantle source region to the intrusion of the stocks. Our geochemical data are consistent with derivation of the alkaline silicate and carbonatite melts through partial melting from a shared mantle source region rather than through liquid immiscibility or fractional crystallization and separation of a carbothermal fluid. Although the Rb-Sr isotopic system in the Mountain Pass Intrusive Suite is disturbed at the whole-rock scale, the isotopic systems for whole-rock Sm-Nd (εNd i = ‐2.2 ± 0.8) and zircon Lu-Hf (εHf i = 0.1 ± 1.1) are robust and support mantle derivation of the magmas. Geochemical modeling using experimentally derived partition coefficients was used to identify possible causes of enrichment in incompatible elements through metasomatism in the mantle source region. Modeling of metasomatism by melts derived by partial melting of deeply subducted carbonated sediments approximates observed Mountain Pass Intrusive Suite trace element chemistry. Scattered εHf i in inherited zircon (2.8 ± 2.6) is consistent with derivation from an arc-related environment with substantial crustal contamination. Paleotectonic studies in the Mojave Province indicate that regional subduction preceded emplacement of the Mountain Pass Intrusive Suite by ∼300 Ma. Melting of the Mountain Pass source region may have been caused by post-collisional thermal relaxation and extension.

California↗
USGS2025

Determination of per- and polyfluoroalkyl substances in water by direct injection of matrix-modified centrifuge supernatant and liquid chromatography/tandem mass spectrometry with isotope dilution

A direct-injection liquid chromatography/tandem mass spectrometry method was developed to determine 34 per- and polyfluoroalkyl substances (PFAS), including selected branched isomers, in centrifuge supernatant of matrix-modified (amended with approximately 50 percent methanol) water samples. The method has been validated in reagent water, surface water, groundwater, and wastewater effluent. Other water types (for example, drinking water, untreated wastewater, and landfill leachate) have been analyzed by the method but not systematically validated. Recovery of isotope-dilution standards, added to each sample, may be used to assess method performance in nonvalidated matrices on a sample-by-sample basis. Using this method, PFAS concentrations were determined in the range of 2–2,000 nanograms per liter in water samples. This range can be extended by diluting concentrated samples. At circumneutral pH, most compounds are present in the environment in their ionized form, and data are reported as such (for example, perfluorooctanoic acid is referred to as “perfluorooctanoate” [PFOA], perfluorooctane sulfonic acid is referred to as “perfluorooctane sulfonate” [PFOS]). Sample preparation procedures were designed without the use of filtration and with minimum sample handling steps to mitigate procedural losses of target compounds due to sorption to surfaces. Further, isotope-dilution quantification allowed for the correction of bias that may result from procedural losses, matrix-induced signal suppression or enhancement, and other factors. Validation experiments to characterize bias and variability, method detection level, and holding time were done in four distinct water matrices—reagent water, surface water, treated wastewater effluent, and groundwater—at multiple concentration levels. Mean PFAS recoveries met data quality objectives of bias and variability studies in all four validation matrices except for two compounds with low and variable recovery in the reagent water matrix only. Isotope-dilution standards, treated as surrogate compounds, were analyzed in more than 1,500 customer-submitted environmental samples with aggregate recovery of 102.5±6.5 percent (mean±standard deviation). Maximum holding times for all target compounds in the four validation matrices were 28 days for refrigerated samples and 90 days for frozen samples.

Techniques and Methods↗
USGS2026

Ground motions from finite faults with unknown geometry

Earthquake emergency response and loss modeling require accurate models of ground‐motion intensity metrics (IMs), such as those produced by ShakeMap. In the critical minutes and hours after an earthquake, however, knowledge of the earthquake source geometry limits the accuracy of these models, especially in areas where seismic instrumentation is insufficient to constrain the shaking intensity pattern. Previous attempts to overcome this limitation have centered on computing the mean distance metrics from a suite of assumed source geometries. That approach is inadequate with modern ground‐motion models (GMMs) because they typically include terms for the hanging wall effect, depth to top of rupture, and other nonlinear terms. Such approaches also propagate the distance uncertainty through the GMMs and may not properly allocate the additional uncertainty into the between‐ and within‐event components. Here we present Finite‐Fault SIMulation with Mixed Effects Regression (FFSIMMER), a method to address these limitations by computing IM distributions from a suite of rupture realizations that fully accounts for all geometry‐related GMM terms and allows for the separation of the between‐ and within‐event components of the total uncertainty. The accuracy of this method is limited by the available constraints on the source parameters. To address this, FFSIMMER can incorporate constraints based on knowledge of the source, such as the approximate strike and dip based on knowledge of the plate tectonics and focal mechanism of the earthquake. We demonstrate the improvement in accuracy that can be achieved with the 2025 M 7.7 Mandalay, Burma (Myanmar), earthquake by incorporating constraints on the range of plausible source parameters.

Bulletin of the Seismological Society of America↗
USGS2026

Revisiting the utility of regional-scale, high-quality geophysical data in mineral exploration - A case study featuring the Mammoth Magnetic Anomaly, Pinal County, Arizona

Regional aeromagnetic surveys passively measure the total magnetic intensity (TMI) and are a foundational tool used in mineral exploration (Airo, 2015). With the increased global demand and the number of critical mineral resources required for manufacturing high-tech devices, developing high-quality, regional-scale geophysical surveys could aid critical mineral exploration efforts and geologic mapping. In 2019, the U. S. Geological Survey launched the Earth Mapping Resources Initiative (Earth MRI) to modernize the geologic and geophysical mapping of regions that have the potential to contain critical mineral resources within the United States. In support of planning Earth MRI geophysical surveys, Drenth and Grauch (2019) defined five aeromagnetic data quality rankings (rank 1 through rank 5) applying them to the airborne geophysical survey inventory of the United States (Johnson et al., 2021). Rank 1 aeromagnetic surveys are of the highest quality, meeting modern standards and allowing best practices for qualitative and quantitative interpretation; whereas rank 5 aeromagnetic surveys are of the lowest quality, being useful only for qualitative interpretation of broad features. Through the Earth MRI effort, 48 high-quality, regional-scale rank 1 and 2 airborne magnetic and radiometric geophysical surveys have been planned, collected, or publicly release through May 2025 (U. S. Geological Survey, 2025). Here, a portion of a rank 1 Earth MRI aeromagnetic survey in southeast Arizona is presented and compared to a legacy rank 5 aeromagnetic survey over the Mammoth Magnetic Anomaly (MMA), demonstrating how modern, high-quality aeromagnetic data improves our view of crustal geology, aiding mineral exploration.

Arizona↗
USGS2024

Assessment and characterization of ephemeral stream channel stability and mechanisms affecting erosion in Grand Valley, western Colorado, 2018–21

The Grand Valley in western Colorado is in the semiarid Southwest United States. The north side of the Grand Valley has many ungaged ephemeral streams, which are of particular interest because (1) the underlying bedrock geology, Late Cretaceous Mancos Shale, is a sedimentary rock deposit identified as a major salinity contributor to the Colorado River and (2) despite infrequent streamflows of short duration, monsoon-derived floods in these ephemeral streams can carry substantial amounts of sediment downstream, affecting upstream and downstream banks and channel cross sections. The study area is of interest, because salinity, or the total dissolved solids concentration, in the Colorado River causes an estimated $300 million to $400 million per year in economic damages in the United States, and it is estimated 62 percent of the Upper Colorado River Basin’s total dissolved solid loads originate from geologic sources. In an effort to minimize salt contributions to the Colorado River from public lands administered by the Bureau of Land Management, a comprehensive salinity control approach is typically used to reduce nonpoint sources of salinity through land management techniques and practices. In 2018, the U.S. Geological Survey, in cooperation with the Bureau of Land Management, began an assessment of ephemeral streams located on the north side of the Grand Valley, western Colorado, to characterize stream channel stability and identify mechanisms affecting erosion. The U.S. Geological Survey developed a method for automatically extracting channel cross-section geometry from existing remotely sensed terrain models. Based on estimated flood stage and surrogate streamflows, hydraulic characteristics were calculated. Furthermore, the channel geometries and hydraulic characteristics were used to estimate channel stability using a statistical model. Cross-section stabilities were determined from a stream channel stability assessment for a subset of 1,406 visited (field observed) locations out of 13,415 cross sections, which were delineated from remotely sensed terrain models. The application of Manning’s resistance equation in combination with multiple logistic regression models demonstrated channel stability can be estimated with a 0.845 goodness of fit for a validation dataset when using a combination of drainage area, width-to-depth ratio, sinuosity, and shear stress as the explanatory variables. Stream channel stability was extrapolated for 13,415 unvisited (not field observed) cross sections using the multiple logistic regression model and defined explanatory variables. Mapping of the ephemeral streams and their associated stabilities may be used by the Bureau of Land Management to prioritize areas for remediation or changes in management strategies to reduce sediment and salinity loading to the Colorado River. The study found channel stability within the ephemeral streams to be spatially variable, longitudinally discontinuous, and dictated by changes in channel bed slope. The stable ephemeral streams were relatively wide and shallow and often had smaller drainage areas with less potential for producing shear stresses capable of overcoming channel adhesion. A change in channel bed slope can provide the means necessary to generate shear stresses appropriate to initiate erosion and a subsequent stability transition to incising channels. Channel widening happens when either or both banks of an incising channel reach a critical height for mass wasting, or when channel curvature causes higher sidewall stress. Regardless, widening channels can promote increases in sinuosity and subsequently reduce steep channel bed slopes. Consequently, stable and widening channels can have comparable bed slopes, making channel bed slope a poor explanatory variable to predict channel stability overall, despite its function to initiate channel instability. The results were based on a surrogate 0.10 annual exceedance probability (AEP; return period equal to the 10-year flood) interval streamflow, although it was recognized fluctuations in streamflow would also affect channel stability. Past and current changes within the study area affect streamflow; therefore, mechanisms affecting erosion include land use disturbances, soil compaction, loss of vegetation cover, drought, less frequent and more extreme precipitation, and fires—which all intensify the potential runoff and erosion within the study area.

Colorado↗
USGS2024

Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand

On 14 February 2016, a magnitude (M)5.7 earthquake struck in Christchurch New Zealand (Aotearoa in the Maori language). The shaking caused damage to historic facades, power outages, cliff collapses, rock falls, and liquefaction but no reported injuries or fatalities. This Valentine’s Day earthquake was an aftershock in the Canterbury earthquake sequence (CES), which began on 4 September 2010 with the M7.1 Darfield Earthquake and included the destructive and fatal M6.2 Christchurch aftershock on 22 February 2011. This study, eight months after the Valentine’s Day earthquake and six years after the initiation of the CES, is the first to explore long-term aftershock forecast information and communication needs. The exploratory study also aimed to gather feedback on aftershock scenarios, an alternative form for communicating the forecast. The qualitative study involved workshops with emergency managers, public health officials, and members of the public in Christchurch. Key findings for long-term communication throughout an earthquake sequence include: 1. divergent earthquake experiences affect aftershock communication response and information needs; 2. understanding aftershock sequence behavior is foundational to sense-making when large aftershocks occur; 3. strategic earthquake sequence updates from the trusted science agency and local agencies could serve as important reminders for earthquake preparedness; 4. communication of aftershock forecast uncertainty could aid with both the credibility of the information and living with uncertainty, and 5. inclusion of impact information and preparedness advice into aftershock forecast scenarios could provide links to actionable information. The paper derives implications for research and practice of long-term communications during an aftershock sequence.

Christchurch↗
USGS2024

High resolution identification and quantification of diffuse deep groundwater discharge in mountain rivers using continuous boat-mounted helium measurements

Discharge of deeply sourced groundwater to streams is difficult to locate and quantify, particularly where both discrete and diffuse discharge points exist, but diffuse discharge is one of the primary controls on solute budgets in mountainous watersheds. The noble gas helium is a unique identifier of deep groundwater discharge because groundwater with long residence times is commonly enriched in helium. In this study, a portable mass spectrometer was used to measure longitudinal variation in dissolved helium concentrations in two mountainous rivers at high spatial resolution not feasible with traditional sampling techniques. Helium profiles were then simulated using a mass-balance model to quantify longitudinal variation in groundwater discharge to the receiving rivers. Results indicate helium concentrations were enriched by multiple orders of magnitude above atmospheric equilibrium in both rivers and that this persisted for up to 18 km below observed pulse inputs in the Colorado River. Helium mass-balance models match observed longitudinal patterns with the exception of sharp initial increases in helium observed in the rivers. Increased longitudinal groundwater discharge rates correspond to mapped geologic structures in both watersheds that likely transport deep geothermal water. Models show variable sensitivity to spatial assignment of input variables representing the groundwater source, illustrating the importance of collecting data from discrete groundwater discharges where possible. The methodology shows promise for field experiments designed to assess air–water exchange rates and to quantify total groundwater discharge from a combination of discrete and diffuse sources.

Colorado, Utah↗
USGS2000

Biodegradation of chlorinated ethenes at a karst site in middle Tennessee

This report presents results of field and laboratory investigations examining the biodegradation of chlorinated ethenes in a karst aquifer contaminated with trichloroethylene (TCE). The study site, located in Middle Tennessee, was selected because of the presence of TCE degradation byproducts in the karst aquifer and available site hydrologic and chlorinated-ethene information. Additional chemical, biological, and hydrologic data were gathered to evaluate whether the occurrence of TCE degradation byproducts in the karst aquifer was the result of biodegradation within the aquifer or simply transport into the aquifer. Geochemical analysis established that sulfate-reducing conditions, essential for reductive dechlorination of chlorinated solvents, existed in parts of the contaminated karst aquifer. Other areas of the aquifer fluctuated between anaerobic and aerobic conditions and contained compounds associated with cometabolism, such as ethane, methane, ammonia, and dissolved oxygen. A large, diverse bacteria population inhabits the contaminated aquifer. Bacteria known to biodegrade TCE and other chlorinated solvents, such as sulfate-reducers, methanotrophs, and ammonia-oxidizers, were identified from karst-aquifer water using the RNA-hybridization technique. Results from microcosms using raw karst-aquifer water found that aerobic cometabolism and anaerobic reductive-dechlorination degradation processes were possible when appropriate conditions were established in the microcosms. These chemical and biological results provide circumstantial evidence that several biodegradation processes are active in the aquifer. Additional site hydrologic information was developed to determine if appropriate conditions persist long enough in the karst aquifer for these biodegradation processes to be significant. Continuous monitoring devices placed in four wells during the spring of 1998 indicated that pH, specific conductance, dissolved oxygen, and oxidation-reduction potentials changed very little in areas isolated from active ground-water flow paths. These stable areas in the karst aquifer had geochemical conditions and bacteria conducive to reductive dechlorination of chlorinated ethenes. Other areas of the karst aquifer were associated with active ground-water flow paths and fluctuated between anaerobic and aerobic conditions in response to rain events. Associated with this dynamic environment were bacteria and geochemical conditions conducive to cometabolism. In summary, multiple lines of evidence developed from chemical, biological, and hydrologic data demonstrate that a variety of biodegradation processes are active in this karst aquifer.

Tennessee↗
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↗