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USGS2024

Groundwater quality near the Placerita Oil Field, California, 2018

Groundwater-quality data and potential fluid-migration pathways near the Placerita Oil Field in Los Angeles County, California, were examined by the U.S. Geological Survey to determine if oil-field fluids (water and gas from oil-producing and non-producing zones) have mixed with groundwater resources. Six of the 13 new groundwater samples collected for this study contained petroleum hydrocarbons, thermogenic gas, inorganic chemical signatures, and (or) isotopic values consistent with potential mixing with fluids from hydrocarbon-bearing formations. For historical groundwater samples, benzene was the most detected petroleum hydrocarbon. The historical groundwater samples with a benzene concentration greater than 0.5 micrograms per liter were from environmental monitoring wells at industrial or commercial facilities unrelated to oil and gas development that, in many cases, have identified soil or groundwater contamination and were not typically analyzed for other constituents that could provide additional lines of evidence for potential mixing with oil-field fluids. Methane was not detected in any of the 12 historical samples with a reported measurement. Reviewing historical data revealed factors that could potentially adversely affect groundwater quality in the study area. These factors include modified hydraulic gradients caused by large volumes of water extracted from the main production area and reinjected downgradient into nonproducing zones, well-barrier failures in wells constructed in the northern part of the oil field before the 1970s, well-barrier failures in produced-water disposal wells downgradient from the main production area, and naturally occurring hydrocarbons at shallow intervals. The groundwater samples most geochemically similar to samples from hydrocarbon-bearing formations were in areas where hydrocarbons are naturally occurring at shallow intervals and where oil development is at shallow depths. Additional data for hydraulic heads, water quality, and formation temperatures at multiple depths in areas with large injection volumes and well-integrity issues are needed to evaluate whether those factors have contributed to mixing between fluids from oil-producing or injection formations and groundwater resources.

California↗
USGS1999

Simulation of the effects of development of the ground-water flow system of Long Island, New York

Extensive development on Long Island since the late 19th century and projections of increased urbanization and ground-water use makes effective water-resource management essential for preservation of the island's hydrologic environment and maintenance of a reliable source of water supply. This report presents results of a ground-water flow simulation analysis of the effects of development on the Long Island ground-water system. It describes ground-water levels, stream-flow, and the ground-water budget for the predevelopment period (pre-1900), the 1960's drought, and a more recent (1968-83) period with significant hydrologic stress. The report also presents estimated effects of a proposed water-supply strategy for the year 2020. Long Island has three major aquifers-the upper glacial (water-table), the Magothy, and the Lloyd aquifers-that are separated to varying degrees by confining units. Before development, recharge from precipitation entered the ground-water system at a rate of more than 1.1 billion gallons per day. An equal amount discharged to streams (41 percent), the shore (52 percent), and subsea boundaries (7 percent) . Urbanization and withdrawal of more than 400 Mgal/d (million gallons per day) from wells have resulted in local effects that include declines in ground-water levels, drying up and burial of streams and wetlands, reduction of ground-water recharge by increased overland flow to the ocean, a general decrease in ground-water discharge, and salt water intrusion. In some areas, the reduction in recharge is mitigated by leakage from water-supply and wastewater disposal lines, and infiltration of storm water through recharge basins. During 1968-83, a net loss of 240 Mgal/d from the ground-water system caused a decrease in ground-water discharge to streams (135 Mgal/d), to the shore (82 Mgal/d), and to subsea boundaries (23Mgal/d).The greatest adverse effects have been in western Long Island, where the most severe development has occurred. This analysis shows stream base flow to be highly sensitive to water-table fluctuations, and long streams to be more sensitive than short ones. A water-supply scenario for the year 2020 was simulated that employs redistribution of pumping centers to mitigate extreme local effects . Although the net stress on the ground-water system was projected to increase 57 Mgal/d (24 percent) above that of 1968-83, redistribution of ground-water withdrawals across the island would allow recovery of cones of depression in western Long Island, thereby reducing the threat of salt water intrusion and increasing base flow of some streams . The increased stress would cause a net decrease in base flow island wide of 44 Mgal/d; total base flow would be 281 Mgal/d - 39 percent below predevelopment levels or 14 percent below 1968-83 levels. The most severe effects would be in Nassau and western Suffolk Counties.

New York↗
USGS2024

Remote sensing evapotranspiration in ensemble-based framework to enhance cascade routing and re-infiltration concept in integrated hydrological model applied to support decision making

Integrated hydrological models (IHMs) help characterize the complexity of surface–groundwater interactions. The cascade routing and re-infiltration (CRR) concept, recently applied to a MODFLOW 6 IHM, improved conceptualization and simulation of overland flow processes. The CRR controls the transfer of rejected infiltration and groundwater exfiltration from upslope areas to adjacent downslope areas where that water can be evaporated, re-infiltrated back to subsurface, or discharged to streams as direct runoff. The partitioning between these three components is controlled by uncertain parameters that must be estimated. Thus, by quantifying and reducing those uncertainties, next to uncertainties of the other model parameters (e.g. hydraulic and storage parameters), the reliability of the CRR is improved and the IHM is better suited for decision support modelling, the two key objectives of this work. To this end, the remotely sensed MODIS-ET product was incorporated into the calibration process for complementing traditional hydraulic head and streamflow observations. A total of approximately 150,000 observations guided the calibration of a 13-year MODFLOW 6 IHM simulation of the Sardon catchment (Spain) with daily stress periods. The model input uncertainty was represented by grid-cell-scale parameterization, yielding approximately 500,000 unknown input parameters to be conditioned. The calibration was carried out through an iterative ensemble smoother. Incorporating the MODIS-ET data improved the CRR implementation, and reduced uncertainties associated with other model parameters. Additionally, it significantly reduced the uncertainty associated with net recharge, a critical flux for water management that cannot be directly measured and rather is commonly estimated by IHM simulations.

Sardon catchment↗
USGS2025

Land-based nutrient flux to a fringing reef: Insights from Ofu Island, American Samoa

Submarine groundwater discharge (SGD) is a critical driver of nutrient transport in coral reef ecosystems, shaping water quality, primary productivity, and overall reef health. This study quantifies SGD fluxes and associated nutrient dynamics in two reef flat pools within the Ofu Unit of the National Park of American Samoa: Papaloloa and Fatuana. A multi-method approach integrating unoccupied aerial system-based thermal infrared (UAS-TIR) surveys, radon-based SGD measurements, multichannel electrical resistivity tomography (ERT), and discrete water sampling was used to assess SGD rates and nutrient contributions. UAS-TIR imagery revealed cooler sea surface temperatures in both pools, indicative of SGD, with the higher fluxes observed in Papaloloa. Radon measurements revealed a strong inverse correlation between SGD rates and tidal stage, with a more immediate SGD response at Papaloloa due to its highly permeable calcareous sand and gravel substrate. In contrast, a 2–3-hour lag in SGD response at Fatuana suggests discharge from a more inland aquifer that has lower diffusivity. Nutrient concentrations correlated with temperature and salinity, confirming SGD as the dominant nutrient transport mechanism, whereas isotopic analyses indicated inputs from both groundwater and potential anthropogenic sources. Despite lower SGD flux at Fatuana, higher algal cover suggests additional factors influencing algal proliferation, including substrate availability and hydrodynamic conditions. Excess nutrient inputs from SGD may contribute to algal overgrowth, which threatens Ofu’s thermally tolerant corals by increasing competition for space and light. These findings underscore the complexity of SGD-mediated nutrient dynamics in reef environments and emphasize the need for integrated hydrological and ecological assessments to support effective reef conservation and management strategies.

American Samoa, Ofu Island, Olosega Island↗
USGS2025

Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system

Uranium (U) in rocks and soils of arid and semi-arid environments can be mobilized by irrigation and fertilization, posing environmental and health risks. Elevated U, along with selenium (Se) and nitrate (NO 3 ) co-constituents, necessitates careful monitoring and management. We developed a distributed-parameter numerical model to assess U pollution in an irrigated stream-aquifer system, applying it to a 552 km 2 region in Colorado's Lower Arkansas River Valley (LARV) over 14 years. A MODFLOW model, describing groundwater and stream flow, was coupled with an RT3D-OTIS model to portray reactive U transport. Calibration using the PESTPP-iES iterative ensemble smoother (iES) software indicated good agreement with observed U concentrations. The model revealed substantial and variable U levels across the LARV, highlighting potential hotspots and possible contributing factors, such as geological composition of the bedrock and near-surface shale and aquifer sediments derived from them, irrigation practices, and riparian landscape. U levels exceed the chronic standard (85th percentile = 30 μg/L, set by the US Environmental Protection Agency), which is the permissible regulatory threshold, in groundwater across 44 % of the region and along the river by an average factor of 2.9. Simulated average U concentrations in the non-riparian aquifer and river are 124 μg/L and 60 μg/L, respectively, compared with 112 μg/L and 62 μg/L for measured values. The average 85th percentile U concentration is 222 μg/L in the aquifer and 82 μg/L in the river. Average simulated U mass loading to the river is 0.17 kg/day per km, compared to an estimated 0.23 kg/day per km. Findings provide a baseline for comparing future simulated outcomes of alternative best management practices (BMPs) for U pollution mitigation and offer a methodology applicable to other irrigated regions.

Colorado↗
USGS2024

Development of a hydrogeologic visualization model for western Sarpy County, Nebraska

Population in western Sarpy County, Nebraska, has steadily increased over the last several decades and has led to increased groundwater use for domestic purposes. To meet the increase in demand, the Papio-Missouri River Natural Resources District is seeking to use all available sources of groundwater in western Sarpy County. Additionally, elevated groundwater nitrate plus nitrite as nitrogen concentrations were detected, indicating the need to better understand the groundwater quality of the area. Although the general geology of the area is understood, the area does not have detailed information on the extent of the various aquifers, particularly the Dakota aquifer. To characterize these aquifers, the Papio-Missouri River Natural Resources District invested in airborne electromagnetic surveys of the area to better understand the subsurface geology. Although these surveys improved understanding of the groundwater systems in the area, the Papio-Missouri River Natural Resources District wanted to integrate the subsurface information with available water-quality and groundwater-level data. In response, the U.S. Geological Survey, in cooperation with the Papio-Missouri River Natural Resources District, the Nebraska Natural Resources Commission, and the Nebraska Department of Natural Resources, assembled geologic, hydrogeologic and nitrate plus nitrite as nitrogen information for the selected area into a three-dimensional visualization computer software package called GeoScene3D. The completed GeoScene3D project was assembled to provide a visualization of the groundwater systems and associated water-quality results in Sarpy County and to provide the Papio-Missouri River Natural Resources District managers with information that can be used to make more informed groundwater resource-planning decisions in the future. This report details the development of a three-dimensional model created within GeoScene3D to visualize the subsurface, particularly the Dakota Sandstone in western Sarpy County.

Nebraska↗
USGS2025

Rebuilding a volcano one lava flow at a time—Visualizing the lava dome-building eruption in the crater of Mount St. Helens, 1982–1986

Between 1980 and 1986, the U.S. Geological Survey made a series of 1:2,000-scale topographic contour maps from aerial photographic surveys to monitor the eruption. These maps were made for operational purposes and were not intended for publication. Since then, advances in technology made it possible to digitize the original, highly detailed hardcopy maps and derive new digital data elevation models of the surface of the lava dome. These digital elevation models allow for the visualization of the progression of the eruption and reveal the rubbly, chaotic surface of the lava flows and dome. Additionally, these new data help fill gaps in the long-term record of topographic changes that have occurred at the volcano since the May 18, 1980, eruption.

Washington↗
USGS2026

Determining Volcanic Risk in Auckland (DEVORA) Research Programme—A transdisciplinary approach to address the challenge of distributed volcanism in an urban environment

The Determining Volcanic Risk in Auckland (DEVORA) Research Programme was launched in 2008 to address the challenges associated with monogenetic volcanism in an urban setting and to enhance volcanic risk management in Tāmaki Makaurau Auckland in Aotearoa New Zealand. It is a multi-agency, increasingly transdisciplinary (defined here as research that transcends traditional disciplinary boundaries by integrating diverse types of knowledge, perspectives, and methods from academic and non-academic participants to create novel solutions to complex problems), and collaborative research program jointly led by Waipapa Taumata Rau University of Auckland and Earth Sciences New Zealand (ESNZ; formerly GNS Science), with core funding from Natural Hazards Commission Toka Tū Ake (NHC; formerly the Earthquake Commission, EQC) and Te Kaunihera o Tāmaki Makaurau Auckland Council (AC). The primary research focus of DEVORA is to investigate the geologic history, volcanic hazards, and risk posed by the basaltic intraplate Auckland Volcanic Field. Disruption from ash fall and gas from other Aotearoa New Zealand volcanoes is also considered. DEVORA’s work to explore exposure and vulnerability in Tāmaki Makaurau Auckland is also useful for assessing risks from other non-volcanic natural hazards, such as seismic and tsunami hazards. The greater Tāmaki Makaurau Auckland region has an ethnically and socio-economically diverse population of approximately 1.7 million, representing about one-third of the Aotearoa New Zealand population, and hosts critical infrastructure of national significance. The size and nature of the populace, consequential economic base, and important infrastructure within Tāmaki Makaurau Auckland mean that the effects of a volcanic eruption would be felt nationally, including through the disruption of air travel to Aotearoa New Zealand. The hazards from such an eruption could potentially affect hundreds of thousands of people, businesses, and lifelines (critical infrastructure). A considerable challenge for emergency and risk managers is the monogenetic nature of the volcanic field. It is not known where or when the next eruption will occur, how much warning we may get before an eruption, nor how an eruption and its effects might unfold. In this contribution, we highlight the concept and collaborative intent of the DEVORA Programme and show how it has evolved over the 16 years since its inception. We describe how DEVORA has unified more than 100 researchers (including more than 50 graduate students) and numerous stakeholders to address key issues facing Tāmaki Makaurau Auckland and describe how research findings are being implemented into policy and communicated to stakeholder agencies and the public. We also illustrate the broader influence of the DEVORA Programme and provide some learnings that might benefit others embarking on similar integrated projects, especially those focused on distributed volcanism in and near populated areas.

Auckland↗
USGS2025

Grand Canyon landslide-dam and paleolake triggered by the Meteor Crater impact at 56 ka

This paper hypothesizes that the Meteor Crater impact in Arizona, USA, 56,000 years ago triggered landslides in Grand Canyon that dammed the Colorado River and formed Nankoweap paleolake. This is compatible with shock and earthquake physics for the impact that infer a M5.4 seismic event, attenuated to an effective magnitude of M3.5 at Grand Canyon. Results that support the hypothesis include radiocarbon dating of driftwood and luminescence dating of associated slack-water lake sediments that are preserved in caves up to 60 m above the modern Colorado River. Radiocarbon ages from two locations, including Stanton’s Cave, date the driftwood as 55.25 ± 2.44 ka (n = 4). Sediments associated with the driftwood gave a luminescence age of 56.00 ± 6.39 ka (n = 2). These six Grand Canyon dates, and three published ages for the Meteor Crater impact, show statistically indistinguishable results that support the hypothesis for a geologically instantaneous series of events with a mean age of 55.60 ± 1.30 ka. This work highlights the value of radiocarbon dating near the limits of the technique, integration of multiple dating methods, and seismic and landslide hazards associated with meteorite impacts in regions of extreme topography like Grand Canyon.

Arizona↗
USGS2025

Estimated ultimate recovery (EUR) Prediction for Eagle Ford Shale using integrated datasets and artificial neural networks

The estimated ultimate recovery (EUR) is an important parameter for forecasting oil and gas production and informing decisions regarding field development strategies. In this study, we combined site-specific geologic, completion, and operational parameters with the predictive capabilities of machine learning (ML) models to predict EURs of the wells for the Eagle Ford Marl Continuous Oil Assessment Unit. We developed an extensive dataset of wells that have produced from the lower and upper Eagle Ford Shale intervals and reduced the model complexity using principal component analysis. We tested the ML models and estimated the sensitivities of ML-predicted EURs to changes in the values of different input variables. The results of applying the optimized ML model to the Eagle Ford suggest that the approach developed in this study could be promising. The ML estimates of the EURs fit the DCA-based values with an R 2 ~ 0.9 and a mean absolute error of ~36 × 10 3 bbl. In the lower Eagle Ford Shale, the EUR estimates were found to be most sensitive to changes in porosity, net thickness of the interval, clay volume, and the API gravity of the oil; and that in the upper Eagle Ford Shale they were most sensitive to changes in the total organic carbon and water saturation, which suggests that it could be important to consider these parameters in assessing these intervals or close analogs.

Louisiana, Mississippi, Texas↗
USGS2025

Microbial ecology of permafrost soils: Populations, processes, and perspectives

Permafrost microbial research has flourished in the past decades, due in part to improvements in sampling and molecular techniques, but also the increased focus on the permafrost greenhouse gas feedback to climate change and other ecological processes in high latitude and alpine permafrost soils. Permafrost microorganisms are adapted to these extreme environments and remain active at low temperatures and when resources are limited. They are also an important component of global elemental cycles as they regulate organic matter turnover and greenhouse gas production, particularly as permafrost thaws. Here we review the permafrost microbiology literature coupled with an exploration of its historical aspects, with a particular focus on a new understanding advanced by molecular biology techniques. We further identify knowledge gaps and ways forward to improve our understanding of microbial contributions to ecosystem biogeochemistry of permafrost-affected systems.

Permafrost and Periglacial Processes↗
USGS2024

Inset groundwater-flow models for the Cache and Grand Prairie Critical Groundwater Areas, northeastern Arkansas

The water resources in the Mississippi alluvial plain, located in parts of Missouri, Kentucky, Tennessee, Mississippi, Louisiana, and Arkansas, supports a multibillion-dollar agricultural industry that relies heavily on pumping of groundwater for irrigation of crops and aquaculture. The primary source of groundwater for agricultural-related pumping is the Mississippi River Valley alluvial aquifer, which has declined in storage for decades; secondary groundwater sources include the middle Claiborne aquifer and Wilcox aquifer system. Two areas in northeastern Arkansas that lie within the Mississippi alluvial plain, part of the Cache and Grand Prairie regions, have been designated as Critical Groundwater Areas owing to decades of groundwater declines that resulted from past and current water use. The multidisciplinary Mississippi Alluvial Plain project, led by the U.S. Geological Survey, and funded by their Water Availability and Use Science Program, included objectives to develop numerical groundwater models in focus regions, including the part of the Cache and Grand Prairie regions of northeastern Arkansas. Two inset models were developed using the child model capabilities of MODFLOW 6, the U.S. Geological Survey’s Modular Hydrologic Model simulation software. Both models, called the Cache model and Grand Prairie model, simulated the groundwater system and surface-water/groundwater interactions for the Mississippi River Valley alluvial aquifer and underlying Tertiary-age aquifers and confining units to the Midway confining unit. Each model was spatially discretized into 500-meter x 500-meter orthogonal cells on a grid with 5-meter constant-thickness vertical layers that represented the Mississippi River Valley alluvial aquifer and increasing thickness layers for the aquifers and confining units below the alluvial aquifer. The Cache and Grand Prairie models were calibrated with the PEST++ iterative ensemble smoother Version 5 and employed high dimensional parameterization schemes of 13,740 and 30,436 parameters, respectively. The Cache mean absolute residual for groundwater-level observations within each model domain for the priority well was 1.58 meters. Grand Prairie mean absolute residuals for the alluvial aquifer and middle Claiborne aquifer groundwater-level observations were 2.71 and 10.78 meters, respectively. The groundwater budgets for the Cache and Grand Prairie models were characterized by substantial outflows to irrigation wells, which constituted about 52 and 54 percent of all outflows, with the primary source of water to those wells being releases from unconfined aquifer storage.

Arkansas↗
USGS2023

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions↗