Lithochronologic units and mineral deposits of the Appalachian Orogen from Maine to Alabama
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As part of a U.S. Geological Survey study in cooperation with the Bureau of Reclamation and the Pueblo of Acoma, New Mexico, and the Pueblo of Laguna, New Mexico, a digital three-dimensional geologic framework model was constructed for the Rio San Jose and its surface-water drainage basin in west-central New Mexico. This three-dimensional model defines the altitude, thickness, and extent of 18 geologic units for use in a regional numerical hydrologic model. The model included an undifferentiated Proterozoic basement layer, 13 consolidated Paleozoic and Mesozoic rock units, and 4 Cenozoic units. Model input data were compiled from published cross sections, well data, structure contour maps, selected geophysical data, and data derived from geologic maps and structural features in the study area. These data were used to construct faulted surfaces that represent the upper and lower subsurface geologic unit boundaries. The digital three-dimensional geologic framework model combines faults, the altitude of the tops of each geologic unit, and boundary lines depicting the subsurface extent of each geologic unit. The digital three-dimensional geologic model described in this report and the corresponding data release represents the generalized geometry of the subsurface geologic units; it reproduces with reasonable accuracy the input geologic data and is consistent with previously published subsurface conceptualizations of the region. The geologic framework model is at a scale and resolution appropriate for use as the foundation for a numerical hydrologic model of the study area.
Produced water (i.e., a mixture of returned injection fluids and geologic formation brines) represents the largest volumetric waste stream associated with petroleum production in the United States. As such, produced water has been the focus of intense study with emphasis on understanding the geologic origin of the fluids, environmental impacts of unintended or intentional release, disposal concerns, and their commodity (e.g., lithium) potential. However, produced water geochemistry from many active petroleum plays remain poorly constrained leading to knowledge gaps associated with the origin of brine salinity and parameters (e.g., radium levels) that can impact treatment, disposal, and possible reuse. Here we evaluate the major ion geochemistry, radium concentrations, and stable water isotope composition of ~120 produced water samples collected from 17 producing unconventional petroleum wells in Weld County, Colorado from the Late Cretaceous Niobrara Formation. This sample set encompasses eight produced water time series from four new wells across production days 0 to ~365 and from four established wells across production days ~1000 to ~1700. Additionally, produced water from nine other established Niobrara Formation wells were sampled at discrete time points ranging from day 458 to day 2256, as well as hydraulic fracturing input fluids. These results expand the available Niobrara Formation produced water geochemical data, previously limited to few wells sampled within the first year of production, allowing for the heterogeneity of major ions and radium to be evaluated. Furthermore, we explore the geochemical relationships between major ion ratios and stable water isotope composition to understand the origin of salinity in Niobrara Formation brines from the Denver-Julesburg Basin. These findings are discussed with perspective toward potential treatment and reuse of Niobrara produced water prior to disposal.
The U.S. Geological Survey’s (USGS) Lithologic Core Storage Library (CSL) at the Idaho National Laboratory stores more than 120,000 feet of drill core that is accessible to the public for research and sampling. To effectively convey the physical and descriptive properties of the drill core, USGS staff at the Idaho National Laboratory Project Office log the drill core and publish the lithologic logs as data releases. The logs provide essential data on the lithology, texture, mineralogy, alteration, and other physical properties of the core, which serve as valuable information for researchers to guide their research and sampling efforts. To ensure consistent, quality, and dependable lithologic logs, this document outlines the procedures and expectations for logging drill core at the CSL. This document describes the processes for storing, photographing, and logging core, and includes a variety of resources, reference materials, and appendixes designed to standardize and aid the logging process. Following the procedures outlined in this document will produce consistent, detailed logs that facilitate dependable observations and serve as an easy reference for researchers and other interested parties.
Advances in remote sensing, spatial data collection, hydraulic and geospatial models, and the maturation of landscape ecology during the early 2000s spurred the concept of rivers as landscapes or ‘riverscapes’. Since that time, the Upper Mississippi River Restoration (UMRR) Program - one of the world’s longest running large-river ecosystem restoration and monitoring programs - has applied landscape ecological principles to the Upper Mississippi River System (UMRS). I examine spatial patterns of aquatic nutrient concentrations, submersed aquatic vegetation, and fish and mussel communities, finding that within-river patterns are often patchy in nature, likely resulting from how nutrient processes and community traits interact with spatial variability in hydraulic exchange patterns. Local-scale patchy spatial patterns in the UMRS are embedded in system-scale longitudinal gradients and a hierarchical view of the river has provided a foundation for strategic river restoration planning. Key Words: Aquatic Habitat, hydraulic connectivity, patch, restoration, riverscape
Mercury (Hg), and specifically methylmercury (MeHg), is a contaminant of global concern to humans and wildlife, but there is still limited understanding of its effects on many taxa. Amphibians are closely associated with water, where Hg is converted to MeHg, and high concentrations of MeHg can reduce survival of amphibians in the wild. However, limited non-lethal proxies exist for estimating MeHg bioaccumulation in amphibian larvae, which could be used to reduce destructive sampling and allow sampling of imperiled species. We evaluated whether tail clips were indicative of whole-body MeHg concentrations of larval amphibians, whether dragonflies were an effective bioindicator of Hg concentrations of larval amphibians, and compared MeHg bioaccumulation in predatory caudate (salamanders, newts) and non-predatory anuran (frogs, toads) larvae. Tail-clip and whole-body MeHg concentrations were strongly correlated, especially for caudates. There was high variability among sites and species, but caudates had higher MeHg than anurans, and MeHg concentrations of caudates and anurans were strongly correlated. Dragonflies were a weak indicator of MeHg for anurans but strong indicators for larval caudates, likely because caudates and dragonflies are carnivorous and occupy similar trophic positions. Our study revealed that sampling tails can be an effective non-destructive index of whole-body MeHg for larval amphibians and demonstrates differences in MeHg bioaccumulation related to trophic position in larval amphibians and dragonflies. All post-embryo life stages for a broad suite of amphibian species can now be sampled non-lethally for MeHg, allowing for a broader examination of population-level effects and focus on imperiled species that cannot be sampled destructively.
No abstract available.
No abstract available.
Over the last 30 years, a substantial literature has evolved on the use of machine learning (ML) to assess, predict, and improve the efficiency of coalbed methane (CBM) recovery. In the United States, the production of CBM declined as shale gas production matured, but CBM continues to be an important energy resource in other parts of the world. ML applications that have the potential to improve CBM reservoir management and production forecasts, and to increase exploration and operational efficiency, are still of significant interest. The integration of geostatistical techniques into the CBM ML applications has been largely absent but represents an opportunity for improvement. The literature demonstrates the widespread interest in, and applicability of, ML algorithms applied to CBM problems, and that they continue to result in improvements in predictive performance. However, (1) much of the research is more academic than operational, (2) many results are based on simulations, or small or proprietary datasets, (3) ML performance information can be inconsistent and sometimes entirely omitted, (4) most methodologies are unique to the specific CBM situation and likely not generalizable, (5) no standard data repositories are available to directly compare the performance of competing algorithms, and (6) the spatial component is often omitted. Finally, relatively new ML protocols involving causality analysis and reinforced learning, as well as hybrid workflows combining both supervised and unsupervised learning, are anticipated to dominate the future investigations. Integration of geostatistical and geospatial analysis with ML should enhance performance.
Wastewater treatment plant (WWTP) discharges can be a source of organic contaminants, including pesticides, to rivers. An integrated model was developed for the Potomac River watershed (PRW) to determine the amount of accumulated wastewater percentage of streamflow (ACCWW) and calculate predicted environmental concentrations (PECs) for 14 pesticides in non-tidal National Hydrography Dataset Plus Version 2.1 stream segments. Predicted environmental concentrations were compared to measured environmental concentrations (MECs) from 32 stream sites that represented a range of ACCWW and land use to evaluate model performance and to assess possible non-WWTP loading sources. Statistical agreement between PECs and MECs was strongest for insecticides, followed by fungicides and herbicides. Principal component analysis utilizing optical fluorescence and ancillary water quality data identified wastewater and urban runoff sources. Pesticides that indicated relatively larger sources from WWTPs included dinotefuran, fipronil, carbendazim, thiabendazole, and prometon whereas imidacloprid, azoxystrobin, propiconazole, tebuconazole, and diuron were more related to urban runoff. In addition, PECs generally comprised a low proportion of MECs, which indicates possible dominant loading sources beyond WWTP discharges. Cumulative potential toxicity was higher for sites with greater ACCWW and/or located in developed areas. Imidacloprid, fipronil, and carbendazim accounted for the largest portion of predicted potential toxicity across sites. The chronic aquatic life toxicity benchmarks for freshwater invertebrates were exceeded for 82 % of the imidacloprid detections ( n = 28) and 47 % of the fipronil detections ( n = 19). These results highlight the ecological implications of pesticide contamination from WWTP discharges and also the potential legacy effects from accumulated soil and groundwater sources. Pesticide management strategies that mitigate both current and historical impacts may improve the health of aquatic ecosystems.
Subterranean estuaries (STE) in salt marshes are biogeochemically active zones where interactions between terrestrial groundwater and seawater drive complex cycling of carbon and trace elements, influenced by mineral dissolution. These systems, characterized by fine-grained organic-rich peat overlying permeable coastal aquifers, play a crucial role as a blue carbon sink, yet their geochemical dynamics remain poorly understood. We investigated dissolved trace elements, carbon, silica, and radium isotopes in a salt marsh STE (Sage Lot Pond, Waquoit Bay, MA) over seasonal and annual cycles. Our results reveal that groundwater and estuarine water circulation through marsh peat and aquifer sediments leads to enrichments of dissolved organic and inorganic carbon (DOC and DIC), Si, Ba, and Mn, with variable source/sink behavior of Fe and net removal of U. Submarine groundwater discharge dominated Ba fluxes, whereas pore water drainage from marsh peat acted as the main sink for U and source of Si. Fe cycling was variable, with terrestrial Fe largely removed as groundwater passed through the STE, consistent with Fe-sulfide and amorphous phase formation. Radium isotope ratios identified two distinct subsurface flow pathways, influenced by metal-oxide cycling and organic matter breakdown. Si production was decoupled from DIC, suggesting Si originates from mineral alteration, whereas DIC results from both mineral weathering and microbial respiration. Silicate mineral alteration, coupled with marsh pore water drainage, accounts for up to 16% of annual DIC exports (66 g C m −2 y −1 ), highlighting the importance of STEs in coastal carbon and trace element cycling, especially as marshes face environmental change.
We consider the similarities and differences between earthquake and microtremor horizontal‐to‐vertical spectral ratios (eHVSR and mHVSR, respectively) using a dataset of 161 sites in southern California. Quantitative comparisons are made in terms of the eHVSR and mHVSR lognormal median curves, as well as the frequencies and amplitudes associated with the fundamental‐ and higher‐mode resonances where present. The results show only 58% of the eHVSR–mHVSR pairs agree in terms of their median curve and only 25% of the eHVSR–mHVSR pairs agree in terms of shared resonances, which increases to 68% if flat HVSRs are considered equivalent. Furthermore, while the shared resonances match very well in terms of frequency (root mean square error, RMSE, <0.11 Hz), the amplitudes of those resonances do not agree (RMSE >1.6). These findings demonstrate that while eHVSR and mHVSR agree at some sites, they are not equivalent at all sites. To investigate if the agreement between eHVSR and mHVSR could be related to features of the microtremor data, earthquake recordings, and/or the site conditions, three machine learning (ML) models at varying levels of interpretability are presented. The ML models—which include multivariate logistic regression, gradient‐boosted trees, and support vector machines—show only partial success at using site‐specific data to predict whether eHVSR and mHVSR will likely agree in terms of their median curve (accuracy of 78%) and number of resonances (accuracy of 84%). Therefore, we conclude that while eHVSR and mHVSR can be quite similar in terms of resonant frequencies at some sites, they are not identical at all sites. Furthermore, preliminary evidence shows that the agreement of eHVSR and mHVSR can be predicted a priori given features of the microtremor measurements, earthquake recordings, and site conditions, although a larger dataset will be necessary for developing a robust predictive model.
Seawater intrusion threatens groundwater resources in coastal regions, including southern Baldwin County, Alabama, where the freshwater-saltwater interface dynamics remain poorly understood. To address this gap, this study uses combined physics-based and machine-learning models to quantify seawater intrusion caused by natural (storm surges) and anthropogenic (human activities) perturbations. The long short-term memory network and wavelet analysis were used to assess vertical aquifer vulnerabilities, revealing that the shallow part of the Coastal lowlands aquifer system (CL1) in the southern Baldwin County region is more susceptible to sea level rise and groundwater extraction than deeper aquifers. Based on these findings, a cross-sectional numerical model (physics approach) for the CL1 aquifer was developed to evaluate tidal and storm surge effects, using Tropical Storm Claudette (June 2021) as a case study. Results showed that tidal fluctuations had a minimal impact on the saltwater-freshwater interface location, whereas storm surges caused substantial inland movement, with effects lasting for nine months. The steady-state version of the three-dimensional (3D) physical model predicted seawater intrusion across the entire area, and convolutional neural network-based modeling further validated the model results. The 3D physical model was also applied to a smaller area to assess human impact on the saltwater interface due to two groundwater pumping scenarios (± 50% of the baseline pumping rate). Results revealed that a 50% increase in groundwater withdrawals caused seawater to advance ~ 320 m inland, whereas a 50% reduction led to a ~ 270-meter retreat. This study highlights the vulnerability of Alabama’s shallow coastal aquifers to seawater intrusion due to storm surges and human activities, and demonstrates that combining physics-based models with machine learning approaches can improve groundwater predictions, though its accuracy depends on the availability of site-specific data.
Wildfire substantially alters aquatic ecosystems by inducing moderate to catastrophic physical and chemical changes. However, the relations of environmental and watershed variables that drive those effects are complex. We present a Driver-Factor-Stressor-Effect (DFSE) conceptual framework to assess the current state of the science related to post-wildfire water-quality. We reviewed 64 peer-reviewed papers using the DFSE framework to identify drivers, factors, stressors, and effects associated with each study. A total of five drivers were identified and ranked according to their frequency of occurrence in the literature: atmospheric processes > fire characteristics > ecologic processes and characteristics > land surface characteristics > soil characteristics. Commonly reported stressors include increased nutrients, runoff, and sediment transport. Furthermore, although several different factors have been used at least once to explain water-quality effects, relatively few factors outside of precipitation and fire characteristics are frequently studied. We identified several gaps indicating the need for long-term monitoring, multi-factor studies, consideration of organic contaminants, consideration of groundwater, and inclusion of soil characteristics. This assessment expands on other reviews and meta-analyses by exploring causal linkages between influential variables and overall effects in post-wildfire watersheds. Information gathered from our assessment and the framework itself can be used to inform future monitoring plans and as a guide for modeling efforts focused on better understanding specific processes or to mitigate potential risks of post-wildfire water quality.
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To assess changes in substrate conditions and the efficacy of artificially placed substrates at select sites on the Kootenai River near Bonners Ferry, Idaho, the U.S. Geological Survey, in cooperation with the Kootenai Tribe of Idaho, completed repeat bathymetric, velocimetric, and underwater videography surveys. Collectively, three project sites throughout the Kootenai River make up the Substrate Enhancement Pilot Project (SEPP), an effort intended to improve spawning and egg incubation viability at locations identified to be aquatic habitat limited for the endangered Kootenai River white sturgeon (Acipenser transmontanus). Following the placement of coarse substrates at each site, bathymetric, velocimetric, and underwater videography data were collected from 2012 to 2022 to assess the role of deposition and erosion on maintaining suitable white sturgeon spawning and incubation substrates. Minimal erosion and deposition occurred at all Substrate Enhancement Pilot Project sites, according to interannual and intra-annual net volumetric changes between bathymetric surveys. Depending on the timing of bathymetric surveys relative to the annual peak streamflow conditions, isolated locations of deposition or erosion were observed at each site and the potential for deposition or erosion was supported by measured mean depth-averaged velocities. This study concluded that variability of deposition and scour were common at each site throughout the monitoring period and may be attributed to fluctuations in streamflow. Repeat bathymetric, underwater videography, and velocity mapping surveys were used to verify the interstitial spaces and surfaces of substrates at each SEPP site remained free of fine sediments for intervals longer than a year but were susceptible to deposition between high streamflow events.