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358 records · Page 18Linked to original sources
USGS2026

Season and antecedent conditions impact concentration-discharge relationships for dissolved organic carbon and alkalinity in southeast Alaskan watershed

Fluvial export of dissolved carbon plays an important role in watershed-scale biogeochemistry. Predicted changes in climate are expected to impact watershed hydrologic regimes, and in turn, the sources and export of dissolved carbon from watersheds. Here, we utilize high resolution measurements of discharge and dissolved carbon concentration to examine how concentration-discharge (CQ) relationships vary seasonally and during high flow events over the main runoff season (May–October) in a temperate forested watershed in Southeast Alaska. Concentration-discharge relationships for dissolved organic carbon (DOC) and alkalinity demonstrated strong seasonal patterns, with more linear relationships in May and June versus other months. Changing power law model slopes ( b values; the exponent in a power law regression between runoff and carbon yields) indicated potentially shifting watershed sources (biogenic vs. geologic) and contrasting dominant flowpaths (shallow vs. deeper groundwater) for DOC and alkalinity over the sampling period. During the largest storm event of the study, DOC and alkalinity b values shifted from an overall pattern of transport (mean b = 1.58 values >1.0 indicate transport limitation) and source limitation (mean b = 0.48, values <1.0 indicate source limitation) to chemostatic (DOC, b = 0.99; alkalinity, b = 1.019). In June through August, patterns in hysteresis index suggest that CQ relationships were altered when storms followed in close succession to each other. Together, these findings indicate that seasonal and antecedent flow conditions play a role in dissolved carbon export from forested watersheds. Understanding these dynamics, particularly during winter months, will become increasingly important as changes to hydroclimate impact riverine carbon export.

Alaska↗
USGS2025

Invasion of perennial sagebrush steppe by shallow-rooted exotic cheatgrass reduces stable forms of soil carbon in a warmer but not cooler ecoregion

Soil organic carbon ('SOC') in drylands comprises nearly a third of the global SOC pool and has relatively rapid turnover and thus is a key driver of variability in the global carbon cycle. SOC is also a sensitive indicator of longer-term directional change and disturbance-responses of ecosystem C storage. Biome-scale disruption of the dryland carbon cycle by exotic annual grass invasions (mainly Bromus tectorum, 'Cheatgrass') threatens carbon storage and corresponding benefits to soil hydrology and nutrient retention. Past studies on cheatgrass impacts mainly focused on total C, and of the few that evaluated SOC, none compared the very different fractions of SOC, such as relatively unstable particulate organic carbon (POC) or relatively stable, mineral-associated organic carbon (MAOC). We measured SOC and its POC and MAOC constituents in the surface soils of sites that had sagebrush canopies but differed in whether their understories had been invaded by cheatgrass or not, in both warm and relatively colder ecoregions of the western USA. MAOC stocks were 36.1% less in the 0–10 cm depth and 46.1% less in the 10–20 cm depth in the cheatgrass-invaded stands compared to the uninvaded stands of the warmer Colorado Plateau, but not in the cooler and more carbon-rich Wyoming Basin ecoregion. In plots where cheatgrass increased SOC, it was via unstable POC. These findings indicate that cheatgrass effects on the distribution of soil carbon among POC and MAOC fractions may vary among ecoregions, and that cheatgrass can reduce forms of carbon that are otherwise considered stable and 'secure', i.e. sequestered.

Environmental Research Communications↗
USGS2025

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California↗
USGS2026

Localization of spatiotemporally heterogeneous subsurface flows using autoencoder-based deep learning framework for time-lapse self-potential tomography

Self-potential (SP) monitoring has emerged as a valuable method for characterizing subsurface hydrogeological features and processes due to its sensitivity to fluid-induced electrokinetic effects. Despite advancements in SP inversion, challenges remain in imaging groundwater dynamics from SP activities due to complex hydrological settings and transient noise. In this study, a deep learning autoencoder (AE)-based framework is proposed for the spatiotemporal localization of subsurface fluid movement from time-lapse SP tomography. Temporal segments of time-lapse numerical inversions were first derived from long-term SP monitoring conducted from a floodplain site in Oak Ridge, Tennessee, known for active hyporheic exchange. Subsequently, AE models based on vision transformer (ViT), convolutional long short-term memory (ConvLSTM), convolutional neural network, and temporal convolutional network were individually trained and compared on the SP tomography segments for reconstruction performance. Finally, the reconstruction error over time serves as an anomaly score to identify moments of active SP variation, whereas spatial distributions of errors within these moments are analyzed to image and localize regions associated with anomalous subsurface fluid movement. The results demonstrate that ConvLSTM- and ViT-AE are most capable for the localization task with contrasting error distributions and consistent delineation of anomalies. Applying the method to both SP arrays parallel and perpendicular to the stream produced consistent anomaly zones near a fault or karst feature, validating the robustness and generalization of the approach. These results demonstrate the potential of the proposed framework as a scalable and interpretable tool for spatiotemporal analysis of subsurface flow dynamics in complex hydrogeological systems.

Tennessee↗
USGS2025

Landsliding follows signatures of wildfire history and vegetative regrowth in a steep coastal shrubland

Five years after the deadly and destructive 9 January 2018 Montecito debris flows (Santa Barbara County, California, USA), an atmospheric river storm on 9 January 2023 triggered widespread landsliding that affected many of the same drainages in the Santa Ynez Mountains. Using high-resolution aerial imagery, we identified >10,000 landslides over an ∼160 km 2 area. Most of the landslides were shallow (<1 m in depth) translational debris slides that initiated on steep (∼40°), south-facing hillslopes, with the highest incidence of landsliding in a sandstone-dominated bedrock unit. The landslides mobilized into debris flows and delivered substantial quantities of sediment downstream, which contributed to costly infrastructure impairments. We detected order-of-magnitude differences in landslide density across the study area that could not be attributed to variations in geomorphology (topographic aspect and slope), geology (bedrock type), or hydrology (seasonal antecedent rainfall, peak hourly storm rainfall intensity, total storm rainfall), which are usually considered relevant factors for shallow landsliding. Rather, we found that vegetation regrowth following wildfire was likely a relevant factor associated with the highly variable landslide densities. Hillslopes with less and different types of vegetation regrowth after fire appear to have been more susceptible to shallow landslides. We identify a possible vegetation control on postfire landsliding, which highlights an opportunity for hypothesis testing using more advanced techniques to track the evolution of vegetation cover and vegetation type in steep shrubland environments following wildfire.

California↗
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↗
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↗
USGS2026

Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach

Ciénegas are rare wetlands in arid landscapes of the North American Southwest, historically providing critical ecological and hydrological functions but increasingly threatened by changing climate and land use pressures. This study quantifies changes in ciénega condition and floodplain dynamics using a state-and-transition model (STM) informed by expert knowledge and remote sensing. Key factors include woody plant encroachment, water availability, and soil aggradation. We mapped 31 ciénegas with high-resolution imagery and analyzed Landsat data (1985–2023) to assess vegetation health and moisture using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII). Results show substantial interannual variability in phenology, water stress, and soil moisture, with regional drying and elevation strongly influencing ciénega resilience. We classified ciénegas into three functional states—healthy, desiccated, and dormant—and mapped their 2023 condition. Trend analyses indicate most ciénegas exhibit greening despite drought, though localized variability underscores the need for site-specific management. None are in a stable climax (reference) state; rather, they transition among states in response to external drivers. Increasing woody plant cover and surface drying, likely linked to declining regional water tables, favor deep-rooted species over wetland grasses—a pattern mirrored in adjacent control plots. Spatially explicit analysis revealed intra-ciénega variability often masked by aggregated data, highlighting the importance of high-resolution monitoring. Seasonal and long-term trends provide context for understanding ciénega dynamics, including degradation and restoration pathways. This study emphasizes the importance of groundwater conservation and demonstrates how remote sensing supports long-term monitoring. The STM framework offers a practical tool for adaptive management to sustain freshwater resources in arid environments.

Arizona, New Mexico↗
USGS2024

Bioconcentration of per- and polyfluoroalkyl substances and precursors in fathead minnow tissues environmentally exposed to aqueous film-forming foam-contaminated waters

Exposure to per- and polyfluoroalkyl substances (PFAS) has been associated with toxicity in wildlife and negative health effects in humans. Decades of fire training activity at Joint Base Cape Cod (MA, USA) incorporated the use of aqueous film-forming foam (AFFF), which resulted in long-term PFAS contamination of sediments, groundwater, and hydrologically connected surface waters. To explore the bioconcentration potential of PFAS in complex environmental mixtures, a mobile laboratory was established to evaluate the bioconcentration of PFAS from AFFF-impacted groundwater by flow-through design. Fathead minnows ( n = 24) were exposed to PFAS in groundwater over a 21-day period and tissue-specific PFAS burdens in liver, kidney, and gonad were derived at three different time points. The ∑PFAS concentrations in groundwater increased from approximately 10,000 ng/L at day 1 to 36,000 ng/L at day 21. The relative abundance of PFAS in liver, kidney, and gonad shifted temporally from majority perfluoroalkyl sulfonamides (FASAs) to perfluoroalkyl sulfonates (PFSAs). By day 21, mean ∑PFAS concentrations in tissues displayed a predominance in the order of liver > kidney > gonad. Generally, bioconcentration factors (BCFs) for FASAs, perfluoroalkyl carboxylates (PFCAs), and fluorotelomer sulfonates (FTS) increased with degree of fluorinated carbon chain length, but this was not evident for PFSAs. Perfluorooctane sulfonamide (FOSA) displayed the highest mean BCF (8700 L/kg) in day 21 kidney. Suspect screening results revealed the presence of several perfluoroalkyl sulfinate and FASA compounds present in groundwater and in liver for which pseudo-bioconcentration factors are also reported. The bioconcentration observed for precursor compounds and PFSA derivatives detected suggests alternative pathways for terminal PFAS exposure in aquatic wildlife and humans.

Environmental Toxicology and Chemistry↗
USGS2026

Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2017–22

The Cedar River alluvial aquifer is the source of drinking water in Cedar Rapids, Iowa. Production wells are completed in the alluvial aquifer approximately 40 to 80 feet below land surface. The City of Cedar Rapids and the U.S. Geological Survey have studied the groundwater-flow system and water quality of the aquifer in the vicinity of Cedar Rapids since 1992. Results of these studies documented hydrologic conditions, water quality, and geochemistry of the alluvial aquifer and interactions with the Cedar River. Water-quality samples were collected for studies involving well field monitoring, trends, source-water protection, groundwater geochemistry, surface-water–groundwater interaction, and pesticides in groundwater and surface water. Water quality was analyzed for dissolved major ions (boron, bromide, calcium, chloride, fluoride, iron, magnesium, manganese, potassium, silica, sodium, sulfate, and total dissolved solids), dissolved nutrients (ammonia as nitrogen, ammonia plus organic nitrogen as nitrogen, nitrite plus nitrate as nitrogen, nitrite as nitrogen, orthophosphate as phosphorus, and phosphorus), dissolved organic carbon, and selected pesticides. Physical characteristics (alkalinity, dissolved oxygen, pH, specific conductance, and water temperature) were measured on site and recorded for each water sample collected. This report presents the results of routine water-quality data-collection activities from October 2017 through September 2022. Methods of data collection, quality assurance, water-quality analyses, and statistical procedures are presented. Data include the results of water-quality analyses from quarterly sampling from monitoring wells, production wells, two water treatment plants, and the Cedar River at Blairs Ferry Road at Palo, Iowa, streamgage (U.S. Geological Survey station number 05464420), as well as monthly nutrient sampling from the Cedar River and Morgan Creek near Covington, Iowa, streamgage (U.S. Geological Survey station number 05464475).

Iowa↗
USGS2024

Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within parts of Bandera and Kendall Counties, Texas

The karstic Edwards and Trinity aquifers are classified as major sources of water in south-central Texas by the Texas Water Development Board. During 2019–23 the U.S. Geological Survey, in cooperation with the Edwards Aquifer Authority, mapped and described the geology and hydrostratigraphy of the rocks composing the Edwards and Trinity aquifers within parts of Bandera and Kendall Counties from field observations of the surficial expressions of the rocks. The thicknesses of the mapped lithostratigraphic and hydrostratigraphic units were also estimated from field observations in the study area. The Cretaceous rocks in the study area are part of the Trinity Group and Edwards Group. The groups, formations, and members are composed primarily of layers of marls, shales, and limestones. The limestones are composed of mudstone through grainstone, framestone and boundstone, dolomite, and argillaceous and evaporitic rocks. The principal structural feature in the study area is the Balcones fault zone. The Balcones fault zone is the result of late Oligocene and early Miocene extensional faulting and fracturing that was a result of the eastern Edwards Plateau uplift. In the Balcones fault zone, most of the faults in the study area are high-angle to vertical, en echelon, normal faults that are predominantly downthrown to the southeast. Hydrostratigraphically, the rocks exposed in the study area are those that contain the Edwards aquifer, the upper zone of the Trinity aquifer, and the middle zone of the Trinity aquifer. Descriptions of the hydrostratigraphic units, thicknesses, hydrologic function, porosity types, and field identification and observations are provided, including those for the informal Bandera and Love Creek hydrostratigraphic units of the Edwards aquifer, which were identified through the mapping for this study.

Texas↗
USGS2026

Streamflow, base-flow, and precipitation trends and simulated effects of groundwater withdrawals from the North Fork Red River aquifer on base flows upgradient from Lake Altus, western Oklahoma, 1980–2022

The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, used five scenarios created from a previously published numerical groundwater-flow model (1980–2013) and historical streamflow records (1980–2022) to investigate the relation between groundwater withdrawals from the North Fork Red River aquifer and inflows to Lake Altus from the North Fork Red River in western Oklahoma. The five scenarios were (1) a scaled-equal-proportionate-share (EPS) groundwater-withdrawal scenario, (2) a study-area-scaled-reported groundwater-withdrawal scenario, (3) a zonal-scaled-reported groundwater-withdrawal scenario, (4) a historical drought-threshold scenario, and (5) a base-flow and evapotranspiration depletion scenario. For the scaled-EPS groundwater-withdrawal scenario, EPS groundwater withdrawals were often much higher than reported groundwater withdrawals and greatly decreased base flows for most scale factors. For the study-area-scaled-reported groundwater-withdrawal scenario, base flows were reduced more but by smaller percentages during wet periods than during dry periods when scaling simulated reported groundwater withdrawals. For the zonal-scaled-reported groundwater-withdrawal scenario, scaling simulated reported groundwater withdrawals within selected zones with more groundwater withdrawals did not always affect base flows more than scaling reported groundwater withdrawals within zones with less groundwater withdrawals. For the historical drought-threshold scenario, curtailing groundwater withdrawals at the drought thresholds increased annual base flows to Lake Altus by about 1,169 to 3,665 acre-feet. For the base-flow and evapotranspiration depletion scenario, the distance between a groundwater well and a stream was a major factor affecting base flow to the North Fork Red River when increasing groundwater withdrawals; however, spatially variable hydrologic properties and saturated-zone evapotranspiration could also affect the relation between base flows and groundwater withdrawals.

Oklahoma↗
USGS2025

Characterization of stream water quality and groundwater levels in the Central Pine Barrens region, Suffolk County, New York, 2017–23

The area locally known as the “Central Pine Barrens” region, located in Suffolk County, New York, contains most of Long Island’s preserved and undeveloped land. This region overlays an aquifer system that provides potable groundwater for residents of Suffolk County. Between 2017 and 2023, the U.S. Geological Survey, in cooperation with the Central Pine Barrens Joint Planning & Policy Commission and the Town of Brookhaven, monitored groundwater levels and stream water quality in this region. Groundwater levels were measured monthly at five wells and continuously (15-minute intervals) at a sixth well. Water quality was monitored at five locations in the Carmans River and at two locations in the Peconic River, and samples were analyzed for major ions, trace elements, nutrients, pharmaceuticals, and pesticides. The major ion compositions at the sites were mainly sodium-chloride type waters, and compositions varied the most at the furthest upstream sites in both streams. Concentrations above aquatic-life criteria thresholds also occurred most frequently at the furthest upstream sites. The seasonal patterns of nutrient loads and concentrations varied between the Carmans and Peconic Rivers. Several organic compounds including pharmaceuticals, domestic use products, and pesticides were detected at low concentrations in both streams. Metformin was the most frequently detected pharmaceutical compound, and herbicides were the most frequently detected pesticide class. Water-quality conditions influenced by anthropogenic contributions are a result of current and historical land use, and these contributions include onsite wastewater disposal systems, commercial or domestic fertilizers and pesticides, and urban or industrial contaminants in road runoff. This study characterizes and improves understanding of the current hydrologic conditions in the Central Pine Barrens region and the study findings can help inform the development of plans to manage, protect, and restore water resources.

New York↗
USGS2024

Assessment of water levels, nitrate, and arsenic in the Carson Valley Alluvial Aquifer and the development of a data visualization tool for the Carson River Basin, Nevada

Residents of Carson Valley, Douglas County, Nevada, rely on the basin-fill alluvial aquifer underlying the valley for drinking water. Since the 1980s, groundwater levels and water-quality data have been collected to monitor the status of the aquifer system and to assist in planning efforts to address current (2024) and future demand. The U.S. Geological Survey (USGS), in cooperation with Douglas County, Nevada, evaluated trends in water levels, nitrate, and arsenic concentrations from a network of monitoring and domestic wells in Carson Valley. This work also assessed the monitoring well network to determine the suitability of wells for characterizing the occurrence of arsenic in the groundwater. Monitoring of constituents, such as nitrate and arsenic concentrations, is needed to assess changes in contaminant distribution and to evaluate the effect that changing land use and groundwater pumping has on their occurrence and transport. Results of the trend analysis indicate water levels are declining ( p <0.05) in 17 of 26 selected monitoring wells (65 percent). Areas with the largest change in water levels, with more than 20 feet of declines, were within the community areas of Johnson Lane, Ruhenstroth, South Agricultural, East Valley, and Fish Springs. Variations in water levels measured in wells from the Central Agricultural, Minden, Foothill, Alpine County (one well), and Gardnerville Ranchos areas show periods of increase and decrease over time, but they also maintain long-term declining trends ( p <0.05). Increases in nitrate concentrations in groundwater samples collected from 9 out of 14 selected monitoring wells (64 percent) are statistically significant ( p <0.05) within the Ruhenstroth, Gardnerville Ranchos, East Valley, Genoa, and Johnson Lane community areas. Samples collected from a well in Indian Hills/Jacks Valley indicated a decreasing trend in nitrate concentration over time. Nitrate concentrations in samples collected from wells in East Valley, Genoa, Johnson Lane, and Indian Hills/Jack Valley were consistently low (less than 3 milligrams per liter [mg/L]) and stable. Nitrate concentrations from selected wells in Johnson Lane and Garnerville Ranchos exceeded the U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) of 10 mg/L (as nitrogen) and have trends that are increasing over time. In 2022, a sample collected from Johnson Lane had a concentration (7.3 mg/L) below the MCL with an increasing trend over time. Temporal trend analyses for groundwater arsenic concentrations in Carson Valley could not be done because of a lack of temporal data. However, using available historical data, arsenic concentrations seem to be greater in groundwater from wells located on the eastern and northern areas of the valley than in wells located on the western or southern areas. Groundwater arsenic concentrations exceed 5 micrograms per liter (μg/L) in most samples collected from wells in Johnson Lane, Airport, Central Agricultural, and East Valley areas and in many cases exceed the U.S. Environmental Protection Agency (EPA) MCL of 10 μg/L. Data indicate that groundwater from domestic wells screened at deeper intervals are likely more vulnerable to elevated arsenic concentrations than shallower wells. A groundwater network evaluation for Carson Valley identified potential modifications in the sampling locations and frequency to better understand the effect of groundwater pumping in communities where municipal and domestic demand are greatest, potentially enhancing understanding of contaminant transport in these areas. Potential modifications to the active well network include reducing the frequency of sample collection from existing network wells (6 out of 11) that have consistently shown low and stable nitrate concentrations, adding wells in areas where data are sparse, and increasing the number of wells in areas with elevated groundwater nitrate concentrations. Including the analysis of arsenic in samples from the active groundwater monitoring well network will provide more detail on the temporal and spatial variability of arsenic concentrations. A visualization tool for the Carson River Basin was developed to provide access to discrete and near real-time hydrologic and water-quality data. The Carson River Basin Hydro Mapper (CBH; U.S. Geological Survey, 2023b) shows active and historical discrete water levels measured by the USGS and the State of Nevada Division of Water Resources, discrete groundwater nitrate and arsenic concentration data collected by the USGS, near real-time streamflow, and surface water levels for select waterbodies. The hydrologic data in the CBH provides resource managers, the public, and the scientific community with an easily accessible tool to present and communicate the most up-to-date information available about local and basin-wide water resources.

Nevada↗
USGS2026

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE↗
USGS2024

Iodine-129 in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2021–22

Between the 1950s and 1980s, wastewater generated at the Idaho National Laboratory contained Iodine-129 ( 129 I); this wastewater was discharged directly into the eastern Snake River Plain (ESRP) aquifer through a deep disposal well, unlined infiltration ponds, or leaked from distribution systems below industrial facilities. During 2021–22, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy and the Idaho Department of Environmental Quality Idaho National Laboratory Oversight Program, collected groundwater samples from 64 monitoring wells in the ESRP aquifer, 6 of which are part of a multilevel monitoring system, to determine the concentration of 129 I in the groundwater. These samples were analyzed by accelerator mass spectrometry as part of a long-term ongoing study to track trends and occurrences of this carcinogenic, long-lived radionuclide in the environment. Concentrations ranged from slightly above the locally determined background concentration of 5.4×10 −6 picocuries per liter, to just below the U.S. Environmental Protection Agency’s maximum contaminant level of 1 picocurie per liter. Discharge of wastewater containing 129 I has been discontinued to the aquifer, and long-term trends from a subset (n=15) of sampled wells show decreasing 129 I concentrations over the last three decades. Concentrations of 129 I in groundwater from monitoring wells near facilities at the Idaho National Laboratory are affected by episodic recharge from an ephemeral surface-water source and by the fracture-flow dominated hydrologic regime in the ESRP aquifer. The spatially focused sampling effort has also identified a low-level 129 I plume that affects long-term water quality near and downgradient from the Advanced Test Reactor Complex in the southwestern part of the facility that had not been clearly defined in previous sampling efforts, although the definition of the plume is somewhat limited by available data.

Idaho↗
USGS2024

Mapping karst groundwater flow paths and delineating recharge areas for springs in the Little Sequatchie and Pryor Cove watersheds, Tennessee

The Little Sequatchie River and Pryor Cove Branch, in southern Tennessee, drain the eastern escarpment of the Cumberland Plateau to the Sequatchie River near the southern end of the Sequatchie Valley. The Little Sequatchie River is the largest tributary to the Sequatchie River by drainage area, covering over 120 square miles. The hydrology of the two drainage areas has been largely altered by karst processes, which has caused the majority of the streams to sink at the contact between the Mississippian Pennington Formation and the underlying Mississippian Bangor Limestone. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service and Tennessee Department of Environment and Conservation, initiated a study in 2021 to map the karst groundwater pathways in both watersheds in order to delineate recharge areas for several springs. One of these springs, Sequatchie Cave, represents a significant habitat for two Species of Greatest Conservation Need, the Glyphopsyche sequatchie (Sequatchie caddisfly) and the federally endangered Marstonia ogmorhaphe (royal marstonia). Springs and springflow-dominated streams in the Little Sequatchie River valley and Pryor Cove also provide water for agricultural practices and serve as a drinking water source for nearby communities. During the study, a total of 25 dye injections were conducted over eight rounds from January 2022 through March 2023. Dye traces from these injections helped to delineate recharge areas for six major springs, ranging from 7.3 to 65.2 square miles in area. The majority of the dye traces remained subsurface (from sinkpoint to recovery site) for long distances, with karst groundwater travelling nearly 8 miles before resurfacing. The dye traces also had rapid traveltimes, often travelling hundreds to thousands of feet per hour. The goal of this project was to provide scientific data related to karst groundwater pathways and spring recharge areas to aid State and Federal agencies in making informed decisions to protect and preserve this unique and vulnerable karst system.

Tennessee↗
USGS1992

Description and effects of 1988 drought on ground-water levels, streamflow, and reservoir levels in Indiana

Documentation of the 1988 drought in Indiana was undertaken to aid water-management agencies and planners concerned with periods of below-normal precipitation and their effect on commercial, agricultural, and residential water use. Precipitation, temperature, Palmer Drought Severity Indices, and ground- and surface-water levels from water years 1988 and 1989 were compared to the historical record to evaluate severity, extent, and duration of the 1988 drought in Indiana. Three types of drought-climatological, hydrologic, and agricultural--occurred in most of Indiana during water years 1988 and 1989. The drought began toward the end of calendar year 1987 as annual precipitation decreased to 4.6 inches below the long term mean. By the end of September 1988, statewide precipitation deficits had increased to almost 8 inches below normal. High temperatures during the summer months increased the stress on crops, livestock, and people. Northwest Indiana experienced the second warmest June-August on record. Palmer Drought Severity Indices indicated that a moderate-to-severe drought had occurred in Indiana during most of 1988. Ground-water levels were affected substantially in many areas of the State. Record low-water levels were observed at 12 of the 20 monitoring wells included in this report. A go-day ground-water emergency was declared in parts of northwestern Indiana. Streamflow throughout the State was affected to varying degrees by the drought. Annual mean discharge in some rivers was only slightly less than the mean annual discharge, while others flowed at less than half that value. The effects of low streamflows were felt by many as electric power plants reduced or ceased production and public-water utilities requested conservation measures by their customers. Major reservoirs in the State approached or reached record low levels, causing water supplies as well as recreational activities to be diminished. Most major crops produced in Indiana were affected by the dry conditions. Average yields in 1988 ranged from 50 to 86 percent of 1987 yields.

Indiana↗