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USGS2025

James Buttle review: The characteristics of baseflow resilience across diverse ecohydrological terrains

The dynamic storage of aquifers is the portion of groundwater that can potentially drain to any given point along a stream to create baseflow. Baseflow typically occurs year-round in perennial streams, though the characteristics and stability of dynamic storage are often most important to instream processes during extended dry periods (without precipitation and snowmelt) when runoff and quickflows are minimised. The term ‘baseflow resilience’ is defined for this review as the tendency of baseflow in streams to maintain a consistent volume and water quality year to year while under stress from climate variability and extremes, along with anthropogenic stressors such as water withdrawals, land use change, and water quality degradation. ‘Baseflow resilience’ has, in part, a user-defined meaning spanning water supply and water quality variables of primary interest. Watershed characteristics that directly impact resilience can often produce non-intuitive feedbacks that enhance some attributes of baseflow while simultaneously impairing others. For example, permeable stream corridor geology creates strong stream-groundwater hydrologic connectivity, yet fast groundwater drainage via preferential high-permeability flowpaths can lead to streamflow not being sustained during extended dry periods. Also, shallow groundwater sources are generally more immediately vulnerable to extreme events, warming, salinization, transpiration, and precipitation drought, compared to deeper groundwater. Yet baseflow drought in streams influenced by deeper groundwater can lag precipitation drought by years, and contaminant legacies may propagate through deep groundwater flowpaths to receiving waters for decades to centuries. Finally, irrigation withdrawals can intercept groundwater that would have drained to streams, and the application of irrigation may leach contaminants from the soil zone by unnaturally raising water tables, yet irrigation return flows can sustain baseflow and groundwater-dependent habitats in semiarid areas. This review covers the concept of hydrologic resilience in the context of stream baseflow processes and summarises the common hydrogeological controls on, and multiscale stressors of, dynamic groundwater storage. Further, we present several quantitative metrics to assess a range of water supply to water quality baseflow characteristics using both broadly available and boutique data types, a subset of which are demonstrated using data from the Delaware River Basin, USA.

Delaware River Basin↗
USGS2024

Perchlorate, metals, organic compounds, and lead isotopes in groundwater, surface water, shallow groundwater, and soil within and near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022

The Middleton Municipal Airport–Morey Field (C29) is in the City of Middleton and adjacent to the towns of Middleton and Springfield, Wisconsin. Nearby homes in the towns rely on private drinking water wells, and residents are concerned about the potential contamination of groundwater and surface water by airport activities, including flights by small aircraft that use leaded aviation fuel and a fireworks display in July 2021. The U.S. Geological Survey, in cooperation with the Town of Middleton, completed a study in 2022 to characterize the occurrence and sources of perchlorate, metals (including lead), and organic compounds in samples of groundwater, surface water, shallow groundwater, and soils within and near the airport. Lead isotopes were also measured to determine sources of lead by comparing samples to environmental references. Magnitudes of concentrations from samples of water and soil collected in 2022, and their spatial patterns across site locations, indicate the fireworks display in July 2021 was a likely source of perchlorate and metals in the airport study area. The highest perchlorate concentration was measured in surface water at the southeastern corner of the airport near the fireworks launch site; the highest concentrations of fireworks-associated metals were measured in shallow groundwater near the same location. Fireworks were not the only possible source of perchlorate and metals in the airport study area because both were also detected upgradient and away from the fireworks launch site. Ratios of lead isotopes indicate that lead measured in water and soil within the airport study area was primarily sourced from background atmospheric lead deposition or Wisconsin galena lead ore. However, two groundwater samples (one upgradient and one downgradient from the airport; both with concentrations less than 1 microgram per liter) had isotopic signatures matching leaded aviation fuel sold at the airport.

Wisconsin↗
USGS2025

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

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

Alaska↗
USGS2025

Earthquake probabilities and hazards in the U.S. Pacific Northwest

Earthquakes and their cascading consequences pose a significant threat to the people, environment, infrastructure, and economy of the U.S. Pacific Northwest. The Pacific Northwest is susceptible to three types of earthquakes: deep (intraslab) earthquakes, subduction zone (megathrust) earthquakes, and shallow crustal earthquakes. For each of these earthquake types, earth scientists can use a variety of methods to estimate the probability of occurrence for future events, which constrains seismic hazard and informs building codes. The timing of past earthquakes indicates that there is an 85-percent chance of a magnitude 6.5 or greater deep earthquake in the Puget Sound region; a 10-15-percent chance of an approximately magnitude 9 earthquake on the Cascadia Subduction Zone; and a 17-percent chance of a magnitude 6.5 or greater crustal fault earthquake in the Puget Sound region in the next 50 years. Individuals and communities can take simple steps to prepare for and reduce the impact of future earthquakes.

California, Oregon, Washington↗
USGS2025

Uncertainty reduction for subaerial landslide-tsunami hazards

Subaerial rock slopes may generate a tsunami by rapidly moving into the water. Large uncertainty in landslide characteristics propagates into large uncertainty in tsunami hazard, making hazard assessment more difficult for land and emergency managers. Once a potentially tsunamigenic landslide is identified, it may not be clear which landslide characteristics contribute most significantly to uncertainty in the tsunami hazard. Our aim is to document the relative worth of different landslide characteristics (e.g., size, material properties) for reducing uncertainty in landslide-tsunami hazard assessments. Isolating the relative importance of specific landslide characteristics may inform prioritization of data collection and improve efficiency in understanding hazard. To accomplish this, we generated a set of 288 landslide-tsunami simulations in which we systematically varied the size and material properties of possible failure extents at the Barry Arm landslide complex in northwestern Prince William Sound, Alaska, USA. We find that for landslides smaller than the receiving waterbody, the landslide volume has the strongest effect on resulting wave characteristics and thus the highest leverage on reducing uncertainty in tsunami hazard. In contrast, for landslides substantially larger than the waterbody, the duration of rapid movement of the landslide has the highest leverage. Based on our results, we propose a classification scheme for subaerial landslides based on the relative size of the landslide and waterbody. Additionally, our results support the generation of a tsunami height transfer function between existing tide gages and a nearby coastal city. These results have direct implications for the practice of operational early warning.

Alaska↗
USGS2024

System characterization report on the Earth Surface Mineral Dust Source Investigation (EMIT) sensor

Executive Summary This report addresses system characterization of the Earth Surface Mineral Dust Source Investigation (EMIT) sensor, an imaging spectrometer developed by the National Aeronautics and Space Administration. This report is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior) and radiometric performances. Results of these analyses indicate that the EMIT sensor has a band-to-band geometric performance in the range of −0.355 to 0.210 pixel with a few exceptions of shortwave infrared channels. Geometric offset relative to the Landsat 8 Operational Land Imager ranged from −15.966 meters (−0.266 pixel) to 43.844 meters (0.731 pixel). Offset of a radiometric comparison ranged from −0.016 to 0.025, and slope of a radiometric comparison ranged from 0.837 to 0.985. EMIT agreed with Radiometric Calibration Network measurements within 5 percent across most of the spectral channels.

Open-File Report↗
USGS1977

Leachate plumes in ground water from Babylon and Islip landfills, Long Island, New York

Landfills operated by the Towns of Babylon and Islip in southwest and central Suffolk County contain urban refuse, incinerated garbage, and scavenger (cesspool) waste; some industrial refuse is deposited at the Babylon site. The Islip landfill was started in 1933, the Babylon landfill in 1947. The landfills are in contact with and discharge leachate into the highly permeable upper glacial aquifer (hydraulic conducitvity 190 to 500 ft/d [feet per day]). The aquifer is 74 feet thick at the Babylon landfill and 170 feet thick at the Islip landfill. The leachate-enriched water occupies the entire thickness of the aquifer beneath both landfills, but hydrologic boundaries retard downward migration of the plumes to deeper aquifers. The Babylon plume is 1,900 feet wide at the landfill and narrows to about 700 feet near its terminus 10,000 feet from the landfill. The Islip plume is 1,400 feet wide at the landfill and narrows to 500 feet near its terminus 5,000 feet from the landfill. Hydrochemical maps and sections show the distribution of the major chemical constituents of the plumes. The most highly leachate-enriched ground water obtained was from the Babylon site; it contained 860 mg/L (milligrams per liter) sodium, 110 mg/L potassium, 565 mg/L calcium, 100 mg/L magnesium, 2,700 mg/L bicarbonate, and 1,300 mg/L chloride. Sulfate was notably absent or in low concentration in most parts of both plumes. Nitrogen in plume water was mostly in the form NH4+, and concentrations as high as 90 mg/L were found; concentrations of nitrogen as N in the plume were less than 10 mg/L. As much as 440 mg/L iron and 190 mg/L manganese were found in the leachate-enriched water. Samples were also tested for arsenic, boron, cadmium, cobalt, chromium, copper, mercury, nickel, lead, selenium, strontium, and zinc. Boron was more or less ubiquitous and was found in concentrations as high as 2 mg/L. Organic carbon was found in concentrations as high as 2,250 mg/L in the most highly leachate-enriched water but attenuated rapidly to less than 20 mg/L. Dissolved-solids concentrations near the landfills were between 400 and 3,000 mg/L at Babylon and between 500 and 1,500 mg/L at Islip. Ground-water temperatures near the landfills exceed those in ambient water by as much as 7°C at Babylon and 16°C at Islip. Heat contributed by the landfills was mostly dissipated within 0.4 mi of the landfill, butat Islip, the warm leachate-enriched water extended 0.5 mi downgradient. The entrance of leachate into the less dense ground water as pulsations after rainfall may explain the presence of high leachate enrichment near the bottom of the aquifer. A comparison of the physical characteristics of leachate-enriched ground water with those of ambient water suggests that the downward movement of leachate results from its greater density. Simulation of the movement and dispersion of the Babylon plume with a mathematical dispersion model indicated the coefficient of longitudinal dispersion to be about 60 ft 2 /d (feet squared per day) and the ground-water velocity to be 1 ft/d. However, the velocity determined from the hydraulic gradient and public-supply wells in the area was 4 ft/d, which would cause a plume four times as long as that predicted by the mathmatical dispersion model. At the Islip site, the plume was one-third the length calculated on the basis of the age of the landfill. The shortness of the plumes has not been explained; it may be a result of the leachate's having been too dilute to form a plume during the early years of the landfills.

New York↗
USGS2025

Spatiotemporal variability of algal biomass and nitrate in Owasco and Seneca Lakes in the Finger Lakes Region, New York, in 2019

Cyanobacterial harmful algal blooms (CyanoHABs) have become increasingly common, threatening the security of water resources globally. The U.S. Geological Survey conducted high-resolution nearshore mapping surveys using boat-mounted multiparameter sondes and nitrate sensors during the summer and fall of 2019 on Owasco Lake and Seneca Lake, two lakes with documented CyanoHABs in the Finger Lakes region of New York State. Discrete sensor measurements and water-quality samples were collected at fixed points along survey routes and continuous data were generated at open-water monitoring platforms. This investigation examined whether water-quality information from nearshore surveys was representative of open-water conditions and if nearshore surveys could be used to identify areas with localized nearshore CyanoHABs and potential sources of nutrients not captured by tributary sampling. In addition to comparisons across methods, nearshore concentrations of nitrate and chlorophyll were evaluated relative to tributary outlets, cyanobacterial abundance and biovolume at discrete locations, and the locations of near-surface CyanoHABs that were designated as “confirmed with high toxins” by the New York State Department of Environmental Conservation. Nitrate and chlorophyll concentrations were comparable across methods for each lake, although concentration ranges were typically higher for nearshore mapping datasets than for nearshore discrete datasets. Nearshore surveys indicated areas of nitrate enrichment that varied temporally in both lakes. Orthophosphate was not routinely detected. Across methods, median chlorophyll concentrations were higher for the summer survey than for the fall survey in Owasco Lake. Nearshore chlorophyll concentrations varied more temporally in Owasco Lake than in Seneca Lake. Phytoplankton and cyanobacterial abundance and biovolume were about five times higher in Owasco Lake than in Seneca Lake. Cyanobacteria dominated the phytoplankton community in most samples, and Microcystis comprised the bulk of the cyanobacterial biovolume. The most abundant potential cyanotoxin-producing (specifically microcystins) genera were Microcystis , Synechococcus , Aphanocapsa , and Pseudanabaena . The cyanobacterial community composition was comparable between open-water monitoring platforms and nearshore samples. Microcystins were detected in seven survey samples from Owasco Lake, in one survey sample from Seneca Lake, and in one sample each from the open-water monitoring platforms on Owasco and Seneca Lakes that were collected about 7 days before the fall surveys. Microcystin detections were not consistently associated with high cyanobacterial cell counts or cyanotoxin-producing genera. Results from nearshore surveys were comparable to open-water monitoring platforms and discrete nearshore observations in the absence of nearshore or open-water CyanoHABs in these systems during the study. Patterns of nearshore concentrations of nitrate and chlorophyll from nearshore surveys may aid in the identification of areas with localized nitrate loading and shifts in phytoplankton abundance and community composition.

New York↗
USGS2026

Reassessing water availability in the Nile River Basin using satellite-based irrigation water use accounting

Existing estimates of irrigation areas and water use in the Nile River Basin vary widely and are based on inconsistent data and methodologies. This study leverages advances in remote sensing to provide an up-to-date and consistent basin-wide reassessment of water use in the Nile River Basin. Land cover and actual evapotranspiration data from 2013 to 2022 were used to quantify irrigated areas, irrigation water use, and the average naturalized water yield. Across the basin, 7.1 million hectares of irrigated land consume an average of 72.5 ± 2.6 billion cubic meters (BCM) of blue water annually. Egypt and Sudan together account for 92% of the irrigated area and 97% of the irrigation water use. The basin’s average naturalized yield, evaluated at Dongola station, is determined to be between 108 and 114.4 ± 3.2 BCM. Although conservative, this updated analysis indicates the basin’s average naturalized yield is 14%–20% higher than the previous naturalized yield estimate (95 BCM) and 29%–36% higher than the commonly cited observed flow of 84 BCM, which is frequently treated as the total basin-wide available water. Importantly, the study underscores that the 84 BCM represents flow at the Aswan gauging station after upstream consumptive uses, not the total water available in the basin under naturalized conditions. This distinction is critical for accurate water accounting, planning, and governance in this water-scarce basin. This study demonstrates the value of open-source remote sensing resources in data-scarce regions while emphasizing the need for region specific validation and bias correction for improved accuracy.

Nile River Basin↗
USGS2026

Microtextural characteristics of adularia in banded quartz veins from the Midas low-sulfidation epithermal deposit, Nevada

High-grade ores at the Miocene Midas low-sulfidation epithermal deposit in northern Nevada are confined to crustiform quartz veins containing abundant adularia. Micro-X-ray fluorescence elemental mapping reveals that adularia is a common gangue mineral occurring in colloform bands, bands showing bladed textures, and bands with dendritic terminations. The adularia aggregates have delicate shapes and are comprised of stacked, submillimeter crystals hosted by fine-grained quartz. The textural evidence suggests that the adularia aggregates originally formed within a gel-like, noncrystalline silica matrix, which subsequently transformed into quartz. This indicates that the adularia did not precipitate in open space along the vein walls. Correlative microscopy, involving scanning electron microscopy-based automated mineralogy and optical petrography, demonstrates that bands containing abundant adularia are not the primary host to ore minerals. The ore minerals occur in different bands within the crustiform veins, implying that adularia and ore mineral precipitation did not always occur simultaneously. It is hypothesized here that fluid flow at Midas involved intermittent short-lived events of fluid flashing, causing rapid solute supersaturation in the liquid. During each flashing event, different amounts of vapor were produced along a given vein. Compositional differences between adjacent bands in the crustiform quartz veins may, therefore, be linked to variations in the amount of vapor formed during each flash event.

Nevada↗
USGS2025

Critical minerals in orogenic (gold) and Coeur d’Alene-type mineral systems of the United States

Orogenic and Coeur d’Alene-type mineral systems are produced by metamorphic devolatilization of thick volcanic or siliciclastic sedimentary rock sequences and the focused flow of hydrothermal fluids upwards along crustal-scale faults. Most orogenic systems are found along the Cordilleran orogen, stretching from California northwards into Alaska, whereas most Coeur d’Alene-type systems occur in the Proterozoic Belt Basin in Idaho and Montana. Although the deposit types in these systems are exploited for precious and base metals, potential exists for the production of critical minerals necessary for current (2025) societal needs in the United States. Publicly available geochemical data compiled for these mineral systems, coupled with mineralogical characteristics, indicate that several critical minerals could potentially be recovered from unmined resources and processed mine waste: arsenic, antimony, tellurium, cobalt, and tungsten from orogenic gold deposits and zinc, antimony, arsenic, and manganese from Coeur d’Alene-type systems. These critical minerals reside primarily in arsenopyrite (arsenic), scheelite (tungsten), siderite (manganese), sphalerite (zinc), tetrahedrite (antimony and arsenic), stibnite (antimony), and telluride (tellurium) minerals.

continental United States↗
USGS1998

Stream habitat characteristics at selected sites in the Georgia-Florida coastal plain

Habitat characterization is part of a multidisciplinary approach to water-quality assessment implemented by the National Water-Quality Assessment Program. Habitat data were collected in the Georgia-Florida Coastal Plain study unit at 24 sites during 1993-95. Data were collected for habitat characteristics at three spatial scales: basin, segment, and reach. Basin data include physiography, land resource provinces, and land use, providing a description of the environmental setting at each site. Segment data include length, gradient, and sinuosity. A Kendall correlation analysis performed on segment characteristics and the log-of-basin area showed a correlation between segment gradient and the log-of-basin area and a correlation between sinuosity and segment length. Reach data consist of field-collected measurements of both instream and riparian habitats. Sand and detritus were the most common channel-bed substrates among the sampled sites. Measurements of channel width, water depth, and bank width and height were used to create cross-sectional profiles of each sampled area. Elevations of selected durations plotted on cross sections illustrated the percentage of time that the banks were inundated at each site. Sites were divided into two groups based on duration of bank inundation (less than or equal to 1 percent and greater than 1 percent). Bank woody vegetation was also sampled and a clustering algorithm known as Two-Way INdicator SPecies ANalysis (TWINSPAN) was used to analyze these data. TWINSPAN divided the sites into two groups based on their vegetation composition. A statistical comparison of the two types of site groups (duration of bank inundation and vegetation) was performed. The significant association between these groups was consistent with the hypothesis that inundation frequency affected riparian vegetation.

Florida, Georgia↗
USGS2024

Simulated mean monthly groundwater-transported nitrogen loads in watersheds on the north shore of Long Island Sound, 1993–2022

Elevated nitrogen loads are pervasive in the Long Island Sound, an estuary that receives freshwater and nutrients from both surface-water and groundwater discharge. Surface-water nitrogen loads to the Long Island Sound are relatively well characterized, but less is known about groundwater-transported nitrogen loads. Prior work on the northern shore of Long Island Sound (Connecticut and areas of New York and Rhode Island) suggested that groundwater travel times are relatively short (median less than 2 years) and that decade-long nutrient legacies are not widespread. Because the travel times are short, groundwater flow and nutrient loads likely vary substantially between months. In the current study, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency’s Long Island Sound Study and the Connecticut Department of Energy and Environmental Protection, developed a set of models to better characterize spatial and temporal patterns of groundwater-transported nitrogen loading from atmospheric deposition, septic systems, and fertilizers within the study area. The models provide an estimate, with uncertainty, of groundwater-transported nitrogen loads in the study area, filling a key gap in the nitrogen budget for Long Island Sound. The models also highlight the spatial and temporal variation in nitrogen loading throughout the study area. The modeling workflow involved four models. (1) A soil-water-balance model was developed by using the Soil-Water-Balance software to simulate groundwater recharge across the study area for water years 2005 through 2022. The simulated mean monthly recharge from the soil-water-balance model was used as input into a groundwater-flow model. (2) The groundwater-flow model was developed by using the MODFLOW 6 software and data for water years 1993 through 2022 and simulates average monthly hydrologic conditions. The groundwater-flow model was calibrated by using the Iterative Ensemble Smoother method within the PEST++ software. The Iterative Ensemble Smoother method generates an ensemble of sets of parameter values, with each set producing reasonable simulated hydrologic parameter values. (3) An ensemble of MODPATH particle-tracking simulations were run to generate particle flow paths and travel times, with each simulation using a different set of the flow model parameters. (4) A nitrogen load model uses the MODPATH simulation outputs to track nitrogen from the land surface through multiple attenuation zones until it discharges into fresh or saline surface water. As with the groundwater-flow model, the nitrogen model simulated average monthly groundwater-transported nitrogen loads for water years 1993 through 2022. One novel aspect of the nitrogen load model is that the nitrogen attenuation parameters were calibrated to observed nitrogen loads. Across the ensemble of simulated nitrogen loads, the median study-area-wide monthly simulated nitrogen loads from the aquifer to Long Island Sound throughout the year ranged from 900 to 18,600 kilograms of nitrogen per day, with a median load of 5,100 kilograms of nitrogen per day. The simulated loads were based on average monthly conditions for water years 1993 through 2022. Loads were highest during the winter and early spring and lowest during the late summer. However, simulated travel times for groundwater and nitrogen loads discharged to Long Island Sound during summer were longer than travel times for groundwater and loads discharged during the winter, indicating that, on average, groundwater discharged during summer traveled along different, and longer, flow paths, than groundwater discharged during winter. This indicates that summer loads would respond more slowly to changes in nitrogen inputs at the water table than winter loads. Over the entire study area, approximately 15 percent of the simulated load is from atmospheric deposition sources, 30 to 40 percent is from fertilizer, and 50 to 60 percent is from septic systems. The final analysis of the study involved simulating the change in groundwater-transported nitrogen load in response to upgrading septic systems or reducing fertilizing inputs to areas of turf grass. Both management interventions reduced the groundwater-transported nitrogen load, and reductions were greater in areas with greater loads from septic systems or turf-grass fertilizers. The delay between management actions and substantial reductions in groundwater-transported nitrogen loads varied seasonally; loads during the late summer months remained elevated longer than the winter loads.

Connecticut, Rhode Island↗
USGS2025

Wangyanite, PdNi8S8, a new Pd end-member mineral of the pentlandite group from the J-M reef, Stillwater Complex, Montana, USA

Wangyanite (IMA2024-008a), ideally PdNi 8 S 8 , is a Pd end-member mineral of the pentlandite group that was discovered in the J-M reef of the Stillwater Complex, Montana, USA. Wangyanite occurs as anhedral-subhedral granular crystals 200–400 µm in size, associated with isoferroplatinum, braggite, pentlandite, and chalcopyrite interstitial to plagioclase grains within anorthosite. Wangyanite exhibits a yellowish brown color with a black streak and a metallic luster. It is brittle with uneven fractures, and has a calculated density of 5.14 g/cm 3 . The mineral does not show discernible pleochroism, bireflectance, or anisotropy. It has an average composition of 9.95 wt.% Pd, 31.95 wt.% Ni, 25.02 wt.% Fe, 0.57 wt.% Co, 31.74 wt.% S, totaling 99.23 wt.%. The empirical formula, based on eight sulfur atoms per formula unit, is (Pd 0.76 Co 0.08 ) Σ0.84 (Ni 4.39 Fe 3.60 ) Σ7.99 S 8 . Wangyanite has a cubic cell with a space group of Fm -3 m (#225), having lattice parameters of a = 10.1167(12) Å, V = 1035.4(4) Å 3 , and Z = 4. Its crystal structure has been solved by single-crystal three-dimensional electron diffraction study. The strongest X-ray diffraction lines of wangyanite are claculated at [ d in Å ( I %)( hkl )]: 5.841(14.03)(111), 3.050(100)(311), 1.947(29.16)(115,333), 1.264(11.66)(800), 3.577(8.79)(220), 2.920(20.82)(222), and 2.321(9.34)(331). Wangyanite shares the same crystal structure as pentlandite, but the octahedrally coordinated site is mainly occupied by Pd in wangyanite. Based on the textural features and previous experimental Pd-Fe-Ni-S phase system, wangyanite could form by peritectic reaction between braggite, pentlandite and sulfide liquid. These mineral associations are stable in a Ni-Pd-rich sulfide melt system at about 550 °C or even lower temperature. Therefore, wangyanite can potentially serve as an indicator of the presence of Pd-rich residual melts. The mineral is named in honor of Prof. Christina Yan Wang, a well-known researcher on platinum-group element (PGE) occurrences and enrichment mechanisms in mafic-ultramafic intrusions, notably those deposits related to the Emeishan large igneous province in China.

Montana↗
USGS2024

Representation of surface-water flows using Gradient-Related Discharge in an Everglades Network

The Everglades Depth Estimation Network interpolates water-level gage data to produce daily water-level elevations for the Everglades in south Florida. These elevations were used to estimate flow vectors (gradients and directions) and volumetric flow rates using the Gradient-Related Discharge in an Everglades Network (GARDEN) application developed by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers. Flow rates in both the east-west and north-south directions were computed on a 400-meter square grid using modified parameters in the Manning’s equation. The frictional resistance parameter in the Manning’s equation was calibrated to measured flow rates at coastal creeks fed by Everglades Depth Estimation Network boundary flows. Levees and other features that act as barriers to flow were defined as “no-flow” grid cells where vectors were set to zero. The flow volume magnitudes were calibrated with 2020 daily values of coastal river flows, and verification was performed using 2021 data. Within a given day, the measured coastal river flows fluctuate more than the GARDEN boundary flows because of tidal and wind forcings. Because the GARDEN boundary flows were the upstream water source for the coastal rivers, calibration focused on matching average daily flow volumes rather than daily fluctuations. The Pearson’s correlation coefficient is 0.766 for the 2020 calibration period and 0.566 for the 2021 verification period. Applying GARDEN to periods with hydraulic-control-structure releases allows the propagation of structure flows to be seen in the daily flow-vector maps along with the multiday response of flows farther downgradient. Flow vectors may be overestimated near control structures because of difficulties in resolving the water gradient downstream from the structure. Flow vectors farther from the structure are more accurate than those near the structure.

Florida↗
USGS2025

Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs

Oil and gas reservoirs represent suitable containers to sequester carbon dioxide (CO 2 ) in a supercritical state because they are accessible, reservoir properties are known, and they previously contained stored buoyant fluids. However, planners must quantify the relative magnitude of the CO 2 storage resource in these reservoirs to formulate a comprehensive strategy for CO 2 mitigation. Even reconnaissance-type estimates of CO 2 storage resources of known oil and gas reservoirs may require complicated calculations involving 1) estimates of recoverable oil and gas, 2) reservoir properties (depth, temperature, pressure, etc.), and 3) the physical qualities of the retained fluids. We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO 2 storage resources in reservoirs capable of hosting CO 2 in a supercritical state. ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. The proposed methods and models provide an effective and novel way to more rapidly and directly determine the subsurface CO 2 storage capacity of oil and gas reservoirs around the world, information that operators, researchers, and policymakers alike require to meet energy transition and decarbonization goals.

Frontiers in Enviornmental Science↗
USGS2025

Beyond the mangroves: A global synthesis of tidal forested wetland types, drivers and future information opportunities

There is increasing awareness of the global diversity of tidal forested wetlands (TFWs) and their significance in the provision of ecosystem services. These ecosystems, including mangrove forests, tidal freshwater forested wetlands, supratidal forests and transitional forests together span multiple climatic zones, geomorphic settings, and inundation and salinity regimes. We utilise case studies across five continents to demonstrate the state of knowledge among TFWs. Intertidal mangroves are the best-defined of the TFWs thanks to decades of research on their geomorphology, hydrology and ecology across their broad distribution. Non-mangrove forest settings, however, demonstrate more diverse hydrological, biochemical and vegetation conditions. In many cases, non-mangrove forests are situated at upper intertidal or supratidal elevations, where surface waters and groundwater are subject to interactions between tides freshwater inputs. Salinity datasets show variations ranging from tidal freshwater forested wetlands and ‘low-salinity mangroves’ to mesohaline or marine salinities, often with high temporal variability. While the floristic composition of non-mangrove forests vary among biogeographic regions, locally dominant TFW species are commonly distributed beyond the tidal niche into non-tidal wetland and upland forests. This presents challenges for traditional remote sensing approaches to ecosystem mapping, which are mostly lacking for non-mangrove forests. Geomorphic approaches and developments in machine learning offer opportunities to address this.

Preprint↗
USGS2021

Geology, mineralogy, and cassiterite geochronology of the Ayawilca Zn-Pb-Ag-In-Sn-Cu deposit, Pasco, Peru

The Ayawilca deposit in Pasco, Peru, represents the most significant recent base-metal discovery in the central Andes and one of the largest undeveloped In resources globally. As of 2018, it hosts an 11.7 Mt indicated resource grading 6.9% Zn, 0.16% Pb, 15 g/t Ag, and 84 g/t In, an additional 45.0 Mt inferred resource grading 5.6% Zn, 0.23% Pb, 17 g/t Ag, and 67 g/t In, and a separate Sn-Cu-Ag inferred resource of 14.5 Mt grading 0.63% Sn, 0.21% Cu, and 18 g/t Ag. Newly obtained U–Pb dates for cassiterite by LA-ICP-MS (22.77 ± 0.41 and 23.05 ± 2.06 Ma) assign the Ayawilca deposit to the Miocene polymetallic belt of central Peru. The polymetallic mineralization occurs as up to 70-m-thick mantos hosted by carbonate rocks of the Late Triassic to Early Jurassic Pucará Group, and subordinately, as steeply dipping veins hosted by rocks of the Pucará Group and overlying Cretaceous sandstones-siltstones of the Goyllarisquizga Group. Relicts of a distal retrograde magnesian skarn and cassiterite (stage pre-A) were identified in the deepest mantos. The volumetrically most important mineralization at Ayawilca comprises a low-sulfidation assemblage (stage A) with quartz, pyrrhotite, arsenopyrite, chalcopyrite, Fe-rich sphalerite, and traces of stannite and herzenbergite. Stage A sphalerite records progressive Fe depletion, from 33 to 10 mol% FeS, which is compatible with the observed transition from low- to a subsequent intermediate-sulfidation stage (B) marked by the crystallization of abundant pyrite and marcasite. Finally, during a later intermediate-sulfidation stage (C) sphalerite (up to 11 mol% FeS), galena, native bismuth, Cu-Pb-Ag sulfosalts, siderite, Mn-Fe carbonates, kaolinite, dickite, and sericite were deposited. This paragenetic evolution shows striking similarities with that at the Cerro de Pasco Cordilleran-type polymetallic deposit, even if at Ayawilca stage C did not reach high-sulfidation conditions. The occurrence of an early retrograde skarn assemblage suggests that the manto bodies at Ayawilca formed at the transition between distal skarn and skarn-free (Cordilleran-type) carbonate-replacement mineralization. Mineral assemblages define a T- f S 2 evolutionary path close to the pyrrhotite-pyrite boundary. Buffering of hydrothermal fluids by underlying Devonian carbonaceous phyllites of the Excelsior Group imposed highly reduced conditions during stage A mineralization (log f O 2 < − 30 atm). The low f O 2 favored efficient Sn mobility during stages pre-A and A, in contrast to other known ore deposits in the polymetallic belt of central Peru, in which the occurrence of Sn minerals is minor. Subsequent cooling, progressive sealing of vein walls, and decreasing buffering potential of the host rocks promoted the shift from low- (stage A) to intermediate-sulfidation (stages B and C) states. LA-ICP-MS analyses reveal significant In contents in Fe-rich sphalerite (up to 1.7 wt%), stannite (up to 1908 ppm), and chalcopyrite (up to 1185 ppm). The highest In content was found in stage A sphalerite that precipitated along with chalcopyrite and stannite, thus pointing to the early, low-sulfidation assemblage as prospective for this high-tech metal in similar mineral systems. Indium was likely incorporated into the sphalerite crystal lattice via Cu + + In 3+ ↔ 2 Zn 2+ and (Sn, Ge) 4+ + (Ga, In) 3+ + (Cu + Ag) + ↔ 4 Zn 2+ coupled substitutions. Indium incorporation mechanisms into the stannite and chalcopyrite crystal lattices remain unclear.

Pasco↗