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USGS2026

Decadal trends and occurrence of geogenic constituents and mixtures in groundwater across the continental United States

Worldwide, about 50% of the population is served by groundwater-sourced drinking water. Numerous groundwater quality assessments have found that geogenic constituents are among the most common contaminants in drinking-water aquifers. Documenting changing groundwater quality is a crucial aspect of water availability assessments. We assess trends and occurrence of geogenic constituent concentrations in groundwater across the continental United States using 3 decades of data from the U.S. Geological Survey’s National Water Quality Network. Thousands of groundwater wells were grouped into agricultural, urban, or domestic supply network types. Although most networks and constituents had no statistically significant change in concentration, many had increasing concentration trends, elevated concentrations, or both. Lithium, sodium, radium, sulfate, and uranium had increasing trends in more than 10% of the study networks. Urban and domestic well networks had increasing lithium and sodium trends more often than agricultural networks. Manganese most commonly increased in domestic well networks; uranium more commonly increased in agricultural and urban networks. Elevated concentration mixtures were widespread, and mixture complexities appeared to increase over time. Our results indicate that more than 2.3 million domestic-well users may be affected by elevated concentrations of one or more geogenic constituents.

continental United States↗
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

Factors affecting the distribution of water-bearing fractures in the bedrock aquifers of West Virginia

Bedrock aquifers cover 23,601 square miles within the State of West Virginia and comprise 97.4 percent of the surficial area within the State; the remaining 2.6 percent (621 square miles) consists of alluvial sand-and-gravel and glacial outwash aquifers bordering the State’s major rivers. While West Virginia’s alluvial aquifers have been studied extensively, bedrock aquifers have only been characterized for studies completed in a few areas in Jefferson, McDowell, and Monroe Counties. Bedrock aquifers are water supplies for public supply, agriculture, industry, and residential homeowner use. In this study, the U.S. Geological Survey, in cooperation with the West Virginia Department of Environmental Protection Division of Water and Waste Management, provides a statewide assessment of the occurrence and distribution of fractures within bedrock aquifers of the State and the various topographic, physiographic, and lithologic influences controlling the occurrence and distribution of bedrock fractures. The results of this study provide an increased understanding of the distribution of fractures in bedrock aquifers in West Virginia and help to verify trends that have been suspected for many years but were never well documented or verified by data. The results confirmed that the density of fractures and those that were determined to be water bearing decrease significantly with depth. A statistically significant difference in the density of fractures was observed at a depth of 215 feet for wells in the Appalachian Plateaus Physiographic Province’s and in the Valley and Ridge Physiographic Province’s aquifers; a higher density of fractures and water-bearing fractures were above a depth of 215 feet than below that depth. This is an important consideration when drilling wells for residential, commercial, industrial, or agricultural water supply. Abandoned underground coal mines are commonly believed to form large pools of water in the interconnected mine entries in abandoned room and pillar coal mines. Such pools of water can and do exist in abandoned underground coal mines, but many mines lack open entries and are held up by overburden strata and pillars that can collapse and form aquifers comprised of vast interconnected rubble zones (gob), especially in older mines. Data assessed for this study showed that shale-corrected values of effective porosity for limestone aquifers in West Virginia had a median value of 2 percent and an average value of 4 percent and generally are mineralized with low effective porosity. Argillaceous or sandy limestone has a median shale-corrected porosity of 4 percent and an average shale-corrected porosity of 5 percent. The median and average shale-corrected porosity of sandstone aquifers was estimated to be 14 percent, but the median shale-corrected porosity for argillaceous or calcareous sandstone was 5 percent and the average shale-corrected porosity for argillaceous or calcareous sandstone was 6 percent. Even though shale has a relatively high total sonic porosity compared to other lithologies, shale and siltstone had relatively low shale-corrected porosity, ranging from 0 to 2 percent. Well yields were previously documented to be highest in valley settings, lowest on hilltops, and intermediate on hillsides. Transmissivity data provided by this study confirm this general pattern within the Appalachian Plateaus Province; however, the Valley and Ridge Province does not follow this pattern. While still lowest on hilltop settings, the highest well yields were in hillside settings. The trend for the Valley and Ridge Province was likely skewed because of 9 high-yield wells specifically targeting deeper thin limestone units, such as the Tonoloway and Helderberg Limestones, at depths with transmissivity in excess of 2,000 feet squared per day in Mineral County, West Virginia, or targeting karst aquifers in Berkeley, Jefferson, or Greenbrier Counties, West Virginia. Finally, water-bearing fractures have been hypothesized to comprise a small number of all fractures within a typical bedrock well in West Virginia. Data collected for this study support this theory. A total of 3,403 fractures were identified during this study; 3,151 (92.6 percent) of those fractures are low-transmissive, and only 252 (7.4 percent) fractures are water-bearing. Even though a well may contain many fractures, less than 8 percent are considered water-bearing fractures.

West Virginia↗
USGS2025

Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona

Managed aquifer recharge is a widespread practice for storing water in the subsurface as groundwater. At a managed aquifer recharge facility in southern Arizona, groundwater-level and repeat microgravity data were collected to monitor aquifer response. These data were used to inform parameter identification for an unsaturated-zone flow model used to simulate the recharge process. The facility, the Southeast Houghton Artificial Recharge Project (SHARP), consists of 3 surface basins (about 27,600 square meters [6.8 acres] total surface area) where recycled water is distributed in recharge cycles lasting several months, with dry periods in between. During the study period, December 2020–December 2022, Tucson Water (the City of Tucson’s water utility) reported 6.56×10 6 cubic meters of water (5,320 acre-feet) recharged. Monitoring included groundwater-level observations at 3 monitoring wells and repeat microgravity measurements at as many as 22 locations (some stations were destroyed between surveys). Six gravity surveys were carried out using absolute- and relative-gravity meters. Large gravity increases, more than 250 microgals, were observed during the first repeat survey, 3.5 months after the start of recharge, but only in the immediate vicinity of the recharge basins. Data show that water moved downward to the water table, and storage changes in the unsaturated zone away from the facility were likely minimal. Gravity decreased at stations more than 1 kilometer from the facility, consistent with regional groundwater-level changes. Groundwater-level increases in wells adjacent to the recharge basins began 2 months after the second repeat gravity survey, and 5.5 months after recharge began. Unsaturated-zone flow modeling was carried out using software that simulates water movement and parameter estimation. Model calibration was carried out by minimizing an objective function calculated from the differences between simulated and observed groundwater levels, and between simulated and observed repeat microgravity data. Including repeat microgravity data in the objective function reduced the uncertainty in estimated parameter values for saturated hydraulic conductivity and saturated water content. Modeling indicated that the unsaturated zone between the recharge basins and the water table does not become saturated even after 685 days of simulated infiltration. This gradual wetting may account for increasing infiltration rates over time, as hydraulic conductivity increases with increasing water content. Unsaturated-zone water content decreased rapidly between recharge cycles. Model-simulated groundwater mounding extended about 1 kilometer from the center of SHARP after the 685-day period following the onset of recharge.

Arizona↗
USGS1977

Acid-rain weathering of a metasedimentary rock basin, Herkimer County, New York

A geochemical balance of major chemical constituents of precipitation inflow with those of surface-water outflow was used to evaluate the effect of acid rainfall (average pH = 4.3) on weathering rates of metasedimentary rocks underlying a surface-water basin in New York State. Precipitation samples and surface-water samples show that approximately 45 percent of the net cation outflow is due to weathering by precipitation acidity. The remaining 55 percent of the cation load in the outflow is attributed to interactions between atmosphere, rock, and soil water in the unsaturated zone. Comparison of the acidity of acid precipitation and air-equilibrated distilled water suggests that since preindustrial time, precipitation acidity has probably increased weathering rates for this basin approximately 75 percent. The increased acidity of the precipitation may also increase the rate of dissolution of heavy metals from water-piping systems.

New York↗
USGS2024

Effects of drought and cloud-water interception on groundwater recharge and wildfire hazard for recent and future climate conditions, Kauaʻi, Oʻahu, Molokaʻi, Maui, and the Island of Hawaiʻi

The Water-budget Accounting for Tropical Regions Model (WATRMod) code was used for Kauaʻi, Oʻahu, Molokaʻi, Maui, and the Island of Hawaiʻi to estimate the spatial distribution of groundwater recharge, soil moisture, evapotranspiration, and climatic water deficit for a set of water-budget scenarios. The scenarios included historical and future drought conditions, and a land-cover condition where shrubland and forest within the cloud zone were converted to grassland. For the historical drought condition, island-wide mean annual recharge estimates range from a decrease of 30 percent (239 million gallons per day [Mgal/d]) for Kauaʻi to a decrease of 39 percent (2,706 Mgal/d) for the Island of Hawaiʻi, relative to the reference condition consisting of 1978–2007 rainfall and 2020 land cover. For the future drought condition, estimates of island-wide mean annual recharge range from a decrease of 40 percent (477 Mgal/d) on Maui to a decrease of 51 percent (116 Mgal/day) on Molokaʻi. Complete conversion of all shrubland and forest within the cloud zone to grassland for each drought condition produces estimated land-cover-related decreases in island-wide mean annual recharge (in addition to the drought-related decreases) of 11–12 Mgal/d on Oʻahu, 119–135 Mgal/day on Maui, and 689–849 Mgal/d on the Island of Hawaiʻi. The spatial distributions of increases in conditions indicative of moisture stress and potential wildfire hazard were quantified using the relative frequency of soil moisture less than a selected threshold value (monthly mean soil moisture less than 0.074, expressed as a fraction of available water capacity), evapotranspiration less than a selected threshold value (monthly evapotranspiration less than 0.96 inches), and climatic water deficit greater than a selected threshold value (monthly climatic water deficit greater than 0.77, expressed as fraction of potential evapotranspiration). For the historical drought condition, the greatest increases in the relative frequency for the moisture-stress indicators occur across parts of east and southwest Kauaʻi; central, east, and west Oʻahu; central Molokaʻi; central Maui and low- to mid-altitude parts of West Maui volcano; and the northwestern and southern parts of the Island of Hawaiʻi. For the future drought condition, the greatest increases in the relative frequency of the moisture-stress indicators occur across parts of west Kauaʻi; central and west Oʻahu and Molokaʻi; a band of mid-altitude area on the southern slope of West Maui volcano and across the southwestern slope of Haleakalā; and mid-altitude areas of the northwestern and southern parts of the Island of Hawaiʻi. Complete conversion of all shrubland and forest within the cloud zone to grassland for each drought condition results in land-cover-related increases in the relative frequency of moisture-stress indicators around Kaʻala in the Waiʻanae Range and the southeastern part of the Koʻolau Range on Oʻahu, the southern part of West Maui volcano and the southwestern slope of Haleakalā on Maui, and the upland regions of the western and southern parts of the Island of Hawaiʻi.

Hawaii↗
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

Seismic tomography 2023

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early‐career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. It remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

Bulletin of the Seismological Society of America↗
USGS2026

The United States Magnetotelluric Array and the National Impedance Map

The United States Magnetotelluric Array (USMTArray) data set, collected in the years 2006–2024, consists of more than 1,700 long-period magnetotelluric stations covering the entirety of the contiguous United States on a quasi-regular 70 km grid. Funding across multiple federal agencies was critical to sustaining this effort to its completion. Important components of the project included active guidance and participation from the MT community, the open and timely availability of all data, and the application of consistent instrumentation and robust data processing. Together with parallel advancement in the development of publicly available three-dimensional (3D) inversion codes, the USMTArray has revitalized the US magnetotelluric community and increased the visibility of magnetotellurics within the Earth-science community. Taken as a whole, these data are visualized as the National Impedance Map, which, together with a 3D synthesis conductivity model of the nation, reveals the electrical architecture of the contiguous US. USMTArray data are used by researchers worldwide for fundamental and applied studies, including investigations of continental architecture and evolution, estimation of hazards to critical infrastructure due to geomagnetic storms, and assessment of the nation's undiscovered geothermal and mineral resources. We here review the history and development of the project, discuss the challenges and successes in its execution, present the National Impedance Map and synthesis conductivity model, and highlight the breadth of research stemming from this rich data set.

conterminous United States↗
USGS2026

Decadal trends in the quality of groundwater used for public drinking-water supply in California, 2004–2023, California groundwater ambient monitoring and assessment program, priority basin project

This study provides a comprehensive assessment of decadal changes in the quality of groundwater used for public drinking-water supply at 444 monitoring sites across California during 2004–2023. We assessed decadal step trends in groundwater quality for 145 water-quality constituents and geochemical indicators statewide and across geographic and land-use based network groups. We evaluated the statistical significance of directional changes (predominant increase or decrease of constituent concentrations) and the magnitude of those changes across all network groups. Uranium showed the most widespread directional and high-magnitude increases of all constituents with regulatory benchmarks statewide, particularly in the agriculture-dominated Central Valley as well as urban- and desert-dominated regions of Southern California. Fluoride and perchlorate showed the most widespread directional and high-magnitude decreases of all constituents with regulatory benchmarks statewide, which were also most pronounced in Southern California. Although arsenic and nitrate did not often register significant directional changes across network groups, they showed widespread, high-magnitude changes in both directions (increase and decrease) at levels often exceeding 10 percent of respective regulatory benchmarks statewide. Triazine herbicides (atrazine and simazine) and the gasoline oxygenate methyl tert-butyl ether (MTBE) showed significant directional decreases statewide, but not at levels considered to be of high magnitude compared to respective regulatory benchmarks. We observed significant directional and high-magnitude increases of total dissolved solids (TDS) statewide, which were most pronounced in agricultural areas. Analysis of explanatory geochemical indicators indicated that prevalent statewide increases of alkalinity and calcium were the predominant components of the observed statewide increases in TDS by mass. Widespread increases in groundwater alkalinity and calcium across agricultural and urban areas may be related, in part, to warm-season irrigation and other anthropogenic factors that have shifted soil weathering dynamics over the long term. Increasing alkalinity concentrations were related to increasing uranium concentrations, particularly in areas with aquifer materials derived from granitic rocks. Conversely, increasing calcium concentrations were related to decreasing fluoride concentrations, particularly in areas where fluoride occurred naturally at elevated concentrations. Decrease of perchlorate, triazine herbicides, and MTBE are likely related to decreased anthropogenic source inputs over time and natural attenuation in aquifers.

EarthArXiv↗
USGS2025

Geologic map of the Greater Antilles and Virgin Islands

Introduction The geologic map of the Greater Antilles and Virgin Islands is a compilation of information from the literature, integrated to provide a seamless geologic map of the region. This map was prepared to serve as a base map for a mineral resource assessment of the region. Several small-scale regional geologic maps of the region have been prepared in the past. This report supersedes an earlier version of the geologic map of the Greater Antilles and the Virgin Islands that was released as U.S. Geological Survey (USGS) Open-File Report 2019–1036. For this report, the regional geologic overview shown on sheet 1 covers Cuba; the island of Hispaniola, which includes Haiti and Dominican Republic; Jamaica; the Cayman Islands; Puerto Rico; and the U.S. and British Virgin Islands. Sheet 2 shows the geology of Cuba and Cayman Islands, sheet 3 the geology of Jamaica, sheet 4 the geology of Hispaniola, and sheet 5 the geology of Puerto Rico and Virgin Islands. Accompanying the maps are three tables: table 1 lists the map units (in alphabetical order by map-unit label), their ages, and the countries or territories in which they can be found. These are listed in alphabetical order for ease in locating unit names from the symbols on the maps. Table 2 is a list of sources for the geologic map compilation of Puerto Rico. Table 3 shows formations in the Devil’s Race Course Group of Jamaica.

Greater Antilles, Virgin Islands↗
USGS2026

Decadal trends in the quality of groundwater used for public drinking-water supply in California, 2004–23, California Groundwater Ambient Monitoring and Assessment Program, Priority Basin Project

This study provides a comprehensive assessment of decadal changes in the quality of groundwater used for public drinking-water supply at 444 monitoring sites across California during 2004–23. We assessed decadal step trends in groundwater quality for 145 water-quality constituents and geochemical indicators statewide and across geographic and land-use based network groups. We evaluated the statistical significance of directional changes (predominant increase or decrease of constituent concentrations) and the magnitude of those changes across all network groups. Uranium showed the most widespread directional and high-magnitude increases of all constituents with regulatory benchmarks statewide, particularly in the agriculture-dominated Central Valley as well as urban-and desert-dominated regions of Southern California. Fluoride and perchlorate showed the most widespread directional and high-magnitude decreases of all constituents with regulatory benchmarks statewide, which were also most pronounced in Southern California. Although arsenic and nitrate did not often register significant directional changes across network groups, they showed widespread, high-magnitude changes in both directions (increase and decrease) at levels often exceeding 10 percent of respective regulatory benchmarks statewide. Triazine herbicides (atrazine and simazine) and the gasoline oxygenate methyl tert -butyl ether showed significant directional decreases statewide, but not at levels considered to be of high magnitude compared to respective regulatory benchmarks. We observed significant directional and high-magnitude increases of total dissolved solids statewide, which were most pronounced in agricultural areas. Analysis of explanatory geochemical indicators indicated that prevalent statewide increases of alkalinity and calcium were the predominant components of the observed statewide increases in total dissolved solids by mass. Widespread increases in groundwater alkalinity and calcium across agricultural and urban areas may be related, in part, to warm-season irrigation and other anthropogenic factors that have shifted soil weathering dynamics over the long term. Increasing alkalinity concentrations were related to increasing uranium concentrations, particularly in areas with aquifer materials derived from granitic rocks. Conversely, increasing calcium concentrations were related to decreasing fluoride concentrations, particularly in areas where fluoride occurred naturally at elevated concentrations. Decrease of perchlorate, triazine herbicides, and methyl tert -butyl ether are likely related to decreased anthropogenic source inputs over time and natural attenuation in aquifers.

California↗
USGS2026

Decoding the oxidative digestion mechanism for polystyrene nanoplastic detection in the Great Lakes using a customizable Raman spectral processing algorithm

Despite the concerns surging around nanoplastics (NPs) regarding their prevalence and bioavailability in freshwater systems, robust detection of NPs in complex environmental matrices is hindered by the lack of standardized sample pretreatment and a mechanistic understanding of oxidative digestion. Here, we systematically investigate the interaction between hydrogen peroxide (H 2 O 2 ) and polystyrene (PS) NPs during digestion in deionized (DI) water and four environmental matrices from in and around the Great Lakes Basin. To facilitate high-throughput analysis, we develop Pre_peak, a customizable Raman spectral processing algorithm that achieves >99% accuracy for both NP identification and interference rejection, allowing reliable NP quantification via pixel counting and systematic decoding of the oxidative digestion mechanisms. In DI water, varying H 2 O 2 doses from 0 to 30% has negligible effects on the recovery and Raman signal intensity of PS NPs over 24 hours of digestion. However, morphological changes and aggregation of PS NPs are observed when the H 2 O 2 dose exceeds 20%. Prolonged digestion further leads to progressive NP loss. In natural waters, the optimal dosage and digestion duration depend on matrix characteristics, including dissolved organic matter (DOM) and ion composition. This study provides mechanistic insights into NP–oxidant interactions and underscores the need for matrix-tailored digestion protocols to advance standardized NP detection in freshwater environments.

Great Lakes↗
USGS2024

Geophysical identification of potential groundwater – surface water interactions in the Bonita Peak Mining District, San Juan County, Colorado

This report includes the results and interpretation of geophysical investigations to aid in the location, identification, and conceptual site model (CSM) development of the near surface groundwater and surface water hydrology of the Upper Cement Creek and California Gulch of the Animas Rivers within the Bonita Peak Mining Districts (BPMD). Mine influenced water (MIW) from numerous mine adits within the BPMD has altered the geochemistry and ecology of these ground and surface waters. Many studies of varying scales have investigated the geology, hydrogeology, geochemistry, and aqueous chemistry of these adits and impacted areas. Field investigations using non-invasive geophysical methods were conducted in the summer of 2019 to aid in identifying potential groundwater inputs to these streams and further the CSM of the near surface within and along these streams. Two field deployments were completed in August and September of 2019. In August 2019, Phase 1 was completed using multifrequency electromagnetic induction (EMI) and thermal infrared imaging (TIR) to measure the bulk electrical conductivity, magnetic susceptibility, and the temperature response at known and suspected groundwater seeps into the Upper Cement Creek and California Gulch stretches of these alpine streams. Results and interpretation from Phase 1 were used to co-locate stretches of these streams for further detailed fiber optic distributed temperature system (FODTS) monitoring of the temperature dynamics for submeter identification of potential groundwater seeps during Phase 2. Phase 2 included additional EMI measurements, FODTS measurements, and repeated some Phase 1 measurements for improved data quality. All these data were used for the combined qualitative interpretation identifying seep locations. The data from both Phase 1 and Phase 2 are available in the USGS data release at: https://www.sciencebase.gov/catalog/item/5f18a30082cef313ed84879b. These data include detailed near-surface electrical conductivity and magnetic susceptibility mapping, discrete TIR imaging, and several kilometers of FODTS data. These data were georeferenced and used to identify potential groundwater seeps into these streams. The results indicate a complex near surface geophysical and hydrogeologic regime. Seeps are classified and spatially correlated to the EMI, TIR, and geochemical sampling results. This report is a thorough compilation of the geophysical field efforts in the summer of 2019, the data processing, and interpretations of these data. These data alone should not be used for final interpretations of the complex hydrogeology within these alpine systems. Rather, these data should be combined with other known data from various investigations to further refine the CSM and guide decisions for future investigations, watershed protective measures, and other site decisions. Geographical information system (GIS) layers of these results are available to project managers for such integration and combined interpretations.

Colorado↗
USGS2026

Tracking baseflow supply dynamics using SWOT data from small groundwater-dominated lakes

In situ surface-water monitoring strategies are biased towards larger perennial streams and lakes and are generally not designed to track mechanisms of baseflow supply contributed by the dynamic storage of aquifers. Additionally, small (< 1 km 2 ) groundwater-influenced lakes and wetlands globally have little in situ monitoring infrastructure. We explored the utility of remotely sensed Surface Water Ocean Topography Satellite (SWOT) data, collected from 2023 onward, to characterise the seasonal and multi-year water-level trends of groundwater flow-through kettle lakes distributed across the permeable sediments of eastern Massachusetts, USA. This analysis indicated that water levels for kettle lakes with areas down to approximately 0.05 km 2 are resolvable in the study area. Our examination of 17 kettle lakes found that SWOT water-surface elevation data closely tracked groundwater levels in adjacent monitoring wells where available, including the timing of seasonal patterns (highest levels generally in late spring), although there was some variation between years and there was a substantial lag in the timing of high water levels for a lake located downgradient from a 30-m-thick vadose zone. Furthermore, SWOT-observed water-level increases in kettle lakes tracked with baseflow increases in two adjacent groundwater-dominated streams, as would be expected from increased hydraulic gradients. Unlike spectral remote sensing, SWOT data are generally not affected by cloud cover, resulting in a potential for groundwater-dominated lakes to be sentinels of dynamic storage patterns, including identification of baseflow drought lags, which are currently ill-defined hydrological processes. SWOT monitoring of groundwater-influenced surface waters shows potential for augmenting existing monitoring wells and streamgages as continuous monitors of groundwater levels and baseflow supply in permeable terrain.

Massachusetts↗
USGS2024

Managing basin-scale carbon sequestration: A tragedy of the commons approach

The Tragedy of the Commons is a well studied problem in the literature of ecology, economics, and environmental policy which illustrates the deleterious consequences of managing common pool resources when individual and social incentives are misaligned. In this work, we apply a simple model of carbon sequestration in a deep saline aquifer by two neighboring geologic CO 2 storage (GCS) operators to begin investigating if a Tragedy of the Commons framework applies to GCS. Specifically, we consider the pressure space as a “commons” because the injection by each firm at its own well increases the downhole injection pressure at both wells. We assume that a firm will decrease its injection rate if the downhole pressure at its well exceeds a predefined maximum (i.e., exceeds the “pressure limit”). With this assumption in place, we find that the same injection flowrates are optimal for both wells, regardless of whether they are owned by the same firm or competing firms. This suggests that GCS may not be best represented by a pure Tragedy of the Commons framework under our initial assumptions. However, there could be economic incentives or contractual obligations that may result in either or both GCS operators being unwilling to reduce their injection rates. Thus, we conclude the conference paper with a discussion of future extensions of our approach that may demonstrate closer alignment with the Tragedy of the Commons, including explicit definitions of pore-space rights, firm uncertainty regarding the parameters of the Theis equation, and the potential role of unitization.

Conference Paper↗
USGS2026

The digital archivist: Automating legacy macroseismic data processing using large language models

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor‐intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 M L 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground‐motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

Seismological Research Letters↗
USGS2025

Analyzing multi-year nitrate concentration evolution in Alabama aquatic systems using a machine learning model

Rising nitrate contamination in water systems poses significant risks to public health and ecosystem stability, necessitating advanced modeling to understand nitrate dynamics more accurately. This study applies the long short-term memory (LSTM) modeling to investigate the hydrologic and environmental factors influencing nitrate concentration dynamics in rivers and aquifers across the state of Alabama in the southeast of the United States. By integrating dynamic data such as streamflow and groundwater levels with static catchment attributes, the machine learning model identifies primary drivers of nitrate fluctuations, offering detailed insights into the complex interactions affecting multi-year nitrate concentrations in natural aquatic systems. In addition, a novel LSTM-based approach utilizes synthetic surface water nitrate data to predict groundwater nitrate levels, helping to address monitoring gaps in aquifers connected to these rivers. This method reveals potential correlations between surface water and groundwater nitrate dynamics, which is particularly meaningful given the lack of water quality observations in many aquifers. Field applications further show that, while the LSTM model effectively captures seasonal trends, limitations in representing extreme nitrate events suggest areas for further refinement. These findings contribute to data-driven water quality management, enhancing understanding of nitrate behavior in interconnected water systems.

Alabama↗