Human health risk from manganese in groundwater
Machine learning is the key to uncovering where populations across the globe are at risk from manganese in their groundwater-sourced drinking water.
Geology topics
Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.
Machine learning is the key to uncovering where populations across the globe are at risk from manganese in their groundwater-sourced drinking water.
As Earth’s principal reservoir of organic carbon and microbial biomass, the deep subsurface hosts microorganisms capable of mobilizing this once-sequestered carbon. Contrary to standard assumptions of eukaryotic scarcity, this study documents abundant fungal communities, ranging from 4.2 × 10 3 to 6.8 × 10 3 fungal cells mL −1 , across a methane-producing organic-rich shale 247–556 meters below the surface. Although fungal:bacterial cell ratios ranged from 1:7028 to 1:713, application of biomass conversion factors developed for oceanic systems yielded a median fungal:bacterial biomass ratio of 1:4.7. 16S rRNA gene amplicons revealed bacterial and archaeal communities mirroring those found in well-characterized extremophilic, carbon-degrading environments, while sequencing of 18S rRNA gene and ITS rRNA spacer amplicons collectively identified a eukaryotic hotspot with 689 fungal OTUs across six phyla. The dominant fungal classes, Agaricomycetes and Dothideomycetes, are well-established degraders of recalcitrant carbon compounds at the surface, suggesting they may similarly contribute to organic matter degradation and ecosystem maintenance in the subsurface. Cultivation and isolation efforts yielded 205 fungal strains, including 13 candidate novel taxa, underscoring the deep subsurface as an underexplored eukaryotic habitat. Stable carbon isotopes indicate methane is predominantly generated via microbial conversion of the fossil carbon, while water isotopes suggest in situ geochemical conditions have been relatively stable since the Late Pleistocene, with subglacial recharge as a plausible mechanism for microbial introduction. Collectively, these findings suggest that fungi are underrecognized contributors to organic matter transformation and functional diversity in the deep biosphere, revealing a critical gap in our understanding of deep subsurface ecosystem processes.
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 114.1 trillion cubic feet of tight gas in the Berkine, Illizi, and Hamra Basins of northern Africa.
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 2.4 billion barrels of shale oil and 65.4 trillion cubic feet of shale gas in the Berkine, Illizi, Hamra, Murzuq, and Erdis Kufra Basins of northern Africa.
This report presents a comprehensive set of prospectivity maps for lithium in brines located within the playas of the Basin and Range Province of western United States. The prospectivity assessment is based on criteria established in the descriptive deposit model outlined in a previous U.S. Geological Survey report, with a focus on regional remote sensing methodologies. The playas within the study area have been systematically ranked according to several key factors, including size, the presence and abundance of source rocks, vegetation as an indicator of water availability, documented prospects, and data products derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor. Notably, the deposits in the playa of Clayton Valley make it stand out as the sole lithium brine-producing playa in the United States. The ASTER sensor provides optimal regional coverage, characterized by a 60-kilometer swath width and unique multispectral capabilities that are not available with other remote sensing instruments. This report and the accompanying maps are intended to serve as resources for further multidisciplinary assessments of lithium or other elements or commodities where prospectivity can be inferred from the presence of proxies such as alteration minerals.
Snow and ice-melt are essential for global water resources. Rising air temperatures are causing vegetation encroachment and shrubification of previously snow- and ice-covered landscapes, and precipitation regimes are changing. Collectively, these changes will likely affect the hydrology of mountain environments, although the exact ways in which the hydrology will change are poorly understood. Changing source waters (i.e., the proportion of ice-melt, snowmelt, rain and groundwater) affect the timing and magnitude of streamflow and affect stream temperature, sediment, solute and nutrient fluxes. We investigate spatial and seasonal source water contributions across sub-watersheds of the Nellie Juan River watershed on Alaska's Kenai Peninsula, which differ in glacier cover, elevation and land cover, using a space-for-time approach. To do so, we use a three-endmember mixing model to quantify the contribution of rain, snow/ice-melt and deep groundwater. We show that snow/ice-melt peak later in proglacial streams compared to non-glacial streams. Endmember contributions in non-glacial streams generally vary with elevation and season. We also found that groundwater is a major contributor to streamflow across the study area, contributing between 12% and 47% seasonally, and may become increasingly important as snowpack and ice-melt decrease. This research characterises the shift from a glacierised to a deglaciating landscape through the lens of source water contribution. Broadly, these findings could help improve understanding of how water resources in glacierised watersheds are affected by warming air temperatures.
Stream ecosystems worldwide face ongoing degradation, underscoring the urgent need for conservation and restoration. Regional analyses of stream condition have been limited by sparse spatial and temporal data, particularly at long time scales. To address this gap, we used observed data to predict annual biological condition for 360,893 small, nontidal stream reaches in the Chesapeake Bay watershed from 1985 to 2023 (39 years). Predictions were generated using random forest models trained on extensive benthic macroinvertebrate data sets and predictors including natural landscape features, land cover, and climate variables. Four biological metrics were assessed: percent Ephemeroptera, Plecoptera, and Trichoptera excluding Hydropsychidae (EPT-H), percent Ephemeroptera, percent clinger functional group, and the Index of Biological Integrity (IBI). Results revealed degraded biological conditions near Washington, D.C. and Baltimore, Maryland, with declining trends across all metrics in these urbanized areas. Spatial heterogeneity was evident: IBI and clinger percentages increased in many southern streams but declined in northern streams, whereas EPT-H and Ephemeroptera decreased watershed wide except in the Southeastern Plains bioregion. By 2021, watershed wide IBI improvements were predicted for 0.9–1.1% of stream length, falling short of management goals. This study demonstrates the utility of long-term data and machine learning for predicting stream condition, identifying key stressors, and guiding restoration and conservation site selection.
Climate, land-use, and disturbance drive long-term global trends in groundwater levels and streamflow. At large scales, these trends are typically considered separately, despite the well-established concept that groundwater and surface water comprise a single resource. Joint trend assessment at national scales is challenging because it requires pairing and aggregating data from spatially disparate streamflow and groundwater monitoring sites for which no established framework exists. Here, we evaluate alternative approaches for integrating groundwater and streamflow data to enable joint trend analysis—a critical step toward understanding how water-budget components respond concurrently and interactively to environmental drivers. Mann–Kendall trends were computed for individual groundwater (annual mean depth) and streamflow (annual low of 7 d averages) sites across the U.S over 21- (2000–2020), 31- (1990–2020), and 41-year (1980–2020) periods. Regional Kendall trends were calculated using five spatially contiguous and noncontiguous regional classifications for aggregation based on subsurface (e.g. aquifer, geology) and surface (e.g. watershed, landscape) characteristics. Site-level results revealed contrasting trends, with tendencies toward increasing low flows (wetting) and increasing groundwater depths (drying). Agreement between streamflow and groundwater trends increased with regional aggregation and longer timeframes, though persistent skew toward streamflow wetting and groundwater drying remained. Results varied by region and trend period, with notable consistencies: unified drying in the West/Southwest and wetting in the Upper Midwest. Directional mismatches in long-term trends were prominent in the High Plains and Mississippi Alluvial Plain, whereas near-term mismatches were most evident in the Northwest. Aggregation by hydrologic landscape regions (HLR) yielded the greatest agreement between groundwater and streamflow trends. These findings indicate that coupled responses may represent combined influences of climate, relief, and geology, as captured by HLR, more strongly than geography or geology alone. Integrated water availability assessments may benefit from a multi-characteristic classification framework to treat groundwater and surface water as a unified resource.
This study demonstrates that flow resistance in rivers, quantified via calibration of a modified Manning equation, can be estimated from channel hydrometric information available from globally derived data sets for a subset of river reaches in Alaska and with less certainty in a subset of river reaches in the contiguous United States. The channel morphometry data sets tested include the National Aeronautics and Space Administration (NASA) Surface Water Ocean Topography (SWOT) river database (SWORD) and U.S. Geological Survey (USGS) Scale Specific Sinuosity (S3) river channel morphometry metrics. It is found that for the subset of rivers considered, the meander length, number of active channels, maximum width, width variance, and slope of the channel are strongly correlated with the flow resistance term in the Manning equation. Analytical machine learned models were derived, and a statistical multiple regression model developed to map the flow resistance in rivers across Alaska that are contained in the SWORD data base. The study points to the possibility of global a priori estimation of flow resistance in rivers for application in remote sensing of river discharge from river water surface-width, slope and height measurements made by SWOT and other satellites.
Introduction Geochronology helps us understand Earth’s history by determining when important events, like volcanic eruptions, the rise of mountains, the formation of mineral resources, and changes in the landscape, happened. Geochronological data directly support geologic mapping and can inform decisions about geologic hazard mitigation, natural resource management, and infrastructure resilience. The U.S. Geological Survey (USGS) Geochron database provides access to more than 300,000 published, publicly available age measurements from more than 40,000 geological samples. This database is the result of a collaborative effort with State geological surveys and geoscientists from across the globe. The USGS Geochron database is the most comprehensive collection of geochronological data available for the United States. Users can view data through an interactive map explorer, download datasets, and integrate data into geospatial software or other analysis tools.
This is the third volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/ ). We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee ( gnc@usgs.gov ). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879 .
Introduction Geologic mapping in the southern Lake Champlain valley of New York and Vermont (fig. 1) has required evaluation of stratigraphic nomenclature used since the early 1900s. The paleogeography of the Cambrian and Ordovician adjacent to the Adirondack Highlands, the high-relief mountains of Proterozoic igneous and metamorphic rocks of northern New York, has impacted the lithostratigraphic succession, facies changes, and several hiatuses that occur within the package of clastic and carbonate rocks that demonstrates overall deepening consistent from the southern to northern Appalachians. The stratigraphic nomenclature used for the geologic mapping of the Cambrian and Ordovician strata of the study area is derived from evaluation of names put forth by previous workers from areas of northern New York and western Vermont. Descriptions of type localities or type sections and other criteria set forth by the North American Stratigraphic Code (North American Commission on Stratigraphic Nomenclature [NACSN], 2021) were consulted. The North American Stratigraphic Code states that lithostratigraphic units, such as the fundamental unit, the formation, be defined by lithic character and be mappable (NACSN, 2021, Article 24). However, some early workers (Walcott, 1912; Kay, 1937; Fisher and Hanson, 1951; Oxley and Kay, 1959) have defined stratigraphic units based on fossil content, which may or may not be facies dependent, and hence may not be mappable as lithostratigraphic units. Although preservation of older names takes priority in stratigraphic nomenclature (NACSN, 2021, Article 7), some do not have adequately defined stratotypes or are located a distance away with different lithologies than that in the study area. Biostratigraphy can be a helpful tool for understanding correlations and facies changes. Herein, conodont biostratigraphy is utilized to date and correlate separate lithologic units. Further, microfacies analyses of units through inspection of petrographic thin sections provide paleogeographic information that helps in understanding the genesis of geologic units.
This report documents the process and outcomes of a workshop convened by the U.S. Geological Survey in December 2024 to identify cascading postfire hazards and other effects stemming from the 2021 Dixie Fire in northern California and to explore potential intervention strategies. The Postfire Hazards and Consequences Workshop brought together stakeholders with expertise across disciplines relevant to postfire management. The two-day workshop applied the chains of consequences methodology developed by the Department of the Interior Strategic Sciences Group. Workshop participants identified key issues emerging from postfire conditions and discussed actionable strategies to enhance resilience in fire-prone regions. Findings revealed a complex network of interacting consequences, many of which transcended disciplinary boundaries and affected multiple sectors of society, underscoring the systemic nature of wildfire recovery challenges and indicating that long-term planning approaches could be integrated to help reduce society’s risks from wildfire.
The Everest Base Camp (EBC), a critical staging area for mountaineers attempting to summit Mount Everest, has seen a significant increase in human activity over the past few decades. The increasing number of climbers, trekkers, and support staff, particularly at the campsite area, has intensified environmental impacts on the Khumbu Glacier. This study investigates the effects of human activity at EBC, focusing on three contributors to glacier melt: global climate change, local fossil fuel consumption, and human urinary discharge. Through field data collected during the spring 2023 climbing season, this study examines the energy released through the use of liquefied petroleum gas (LPG), kerosene, and petrol for cooking, heating, and electricity, as well as the heat generated by human urinary discharge. The total heat energy released from these activities at EBC in the spring of 2023 was 849,174 ± 179,774 MJ, which would be sufficient to melt 2492 ± 528 tons of glacier ice and snow. Trends in land surface temperature at EBC and adjacent environments during the 1991–2023 period were calculated from Landsat 5, 7, and 9 satellite data. The 32-year Landsat record reveals that EBC surface temperature increased by 0.28 °C year −1 , which was roughly twice the rate of warming at the surface of Khumbu Glacier adjacent to EBC and about 15% higher than the temperature increase of the debris-covered terrain immediately to the north of EBC. The findings suggest that addressing these anthropogenic influences could help to preserve the Khumbu Glacier and support the sustainability of mountaineering in the region. This paper also takes a transformative approach and explores stable and safer locations in case there is a necessity to relocate the current EBC. Two sites have been identified southwest of the existing EBC, which, unlike the current supraglacial site, are situated on stable ground.
Marine Isotope Stage (MIS) 11 (424-374 ka) has long been an analog for Holocene climate, because it is the most recent interglacial period with similar orbital conditions. However, there is significant global and regional variability in the climate response to MIS 11 warmth. Here, we review sediment core records from across the Bering Sea to investigate changes in paleoceanographic conditions during Marine Isotope Stages 12-10. Sea ice was present over much of the Bering Sea during MIS 11, but today, none of the sites investigated are ever ice-covered. This suggests that sea ice regimes in the Bering Sea during MIS 11 were different to those of the Holocene. There are also regional differences in the response of sea ice to MIS 11 warming. At the Umnak Plateau, Southeastern Bering Sea, sea ice concentrations decline during deglaciation, but they remain high at the slope sites until Peak MIS 11. Sea ice re-advances over the Umnak Plateau during peak interglacial warmth, at the same time that it declines over the slope sites. Late MIS 11 is characterized by high concentrations of seasonal sea ice at the Umnak Plateau, whilst sea ice at the slope sites fluctuates between consolidated and unconsolidated ice cover. This east-west dichotomy may be explained by changes in the behavior of the Aleutian Low. Productivity increases dramatically during deglaciation due to increased upwelling and sea level rise bringing fresh nutrients into the oceans. This is characterized by increased diatom productivity, increased terrestrial carbon deposition, and laminations at all sites.
The long-term eruptive record of a region helps better elucidate magmatic processes at depth as well as volcanic hazards at the surface. Typically, reconstructing such records is done using proximal tephrostratigraphy and linking individual tephras to source volcanoes. These records, however, can only be accurately constructed if they are both well preserved and correctly linked to source volcanoes—not a trivial task, especially in areas such as Alaska that have experienced numerous glaciation events since the Pleistocene. This ultimately necessitates another way of assessing the long-term volcanic record such that these histories may be better discerned. Here we present data from 70 marine core tephras from the Gulf of Alaska, which have a virtually uninterrupted depositional record going back through the mid-Pleistocene. We utilize compositional data analysis techniques to quantify 37 eruptions over the span of eight cores, machine learning classification and conformal prediction algorithms to assign the most probable volcanic source(s) to each eruption, and multivariate distance-based metrics when machine learning classification algorithms are inappropriate. We find that the Mount Katmai magmatic system is the most probable volcanic source for analyzed tephras and that large volcanic centers such as Mount Katmai, Fisher Caldera, and Emmons Lake volcanic center have produced nearly invariant incompatible trace element ratio magmas, allowing for them to be confidently identified in long-term tephra records. This highlights the utility of trace elements for tephra studies, especially when paired with compositional data analysis, multivariate statistical tests, and petrologically informed discriminants.
Elevated groundwater salinity in coastal regions threatens the beneficial use of fresh groundwater. Coastal groundwater management typically focuses on preventing intrusion from modern sources of seawater; however, past geological processes can also leave a legacy of saline groundwater now hidden in the subsurface. Here, multiple extensive airborne electromagnetic surveys provide detailed evidence of residual salinity from a paleo-estuary filling a late Pleistocene incised valley impacting more than 10,000 km 2 that is now hidden beneath coastal Louisiana’s deltaic plain. Our results show that the three-dimensional pattern of saline groundwater beneath Louisiana mimics that of near-surface aquifers surrounding the modern Delaware Bay estuary, fingerprinting the signature of the past drowning of a large, incised valley of the Mississippi River following post-glacial sea-level rise. These findings demonstrate a new framework for understanding legacy sources of saltwater critical for managing stressed water resources along global coastlines.
Introduction In Wisconsin, high-quality elevation data can be utilized for improving agriculture and precision farming, natural resources conservation, and water supply planning, as well as management of flood risk, infrastructure, construction, water quality, forest resources, and many other business uses. Such data can be beneficial for the State’s responses to large rain events, flooding, coastal erosion along the Great Lakes, and urban and suburban development. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP; refer to sidebar) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better (table 1) to meet the many needs of the Nation and Wisconsin. The status of available and in-progress 3DEP baseline lidar data in Wisconsin is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification 2025 Rev. A (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment (Dewberry, 2012) identified user requirements and conservatively estimated that availability of lidar data would result in at least $11.18 million in new benefits annually to the State. The top 10 Wisconsin business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.