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1,663 records · Page 77Linked to original sources

Analyzing multi-year nitrate concentration evolution in Alabama aquatic systems using a machine learning model

Rising nitrate contamination in water systems poses significant risks to public health and ecosystem stability, necessitating advanced modeling to understand nitrate dynamics more accurately. This study applies the long short-term memory (LSTM) modeling to investigate the hydrologic and environmental factors influencing nitrate concentration dynamics in rivers and aquifers across the state of Alabama in the southeast of the United States. By integrating dynamic data such as streamflow and groundwater levels with static catchment attributes, the machine learning model identifies primary drivers of nitrate fluctuations, offering detailed insights into the complex interactions affecting multi-year nitrate concentrations in natural aquatic systems. In addition, a novel LSTM-based approach utilizes synthetic surface water nitrate data to predict groundwater nitrate levels, helping to address monitoring gaps in aquifers connected to these rivers. This method reveals potential correlations between surface water and groundwater nitrate dynamics, which is particularly meaningful given the lack of water quality observations in many aquifers. Field applications further show that, while the LSTM model effectively captures seasonal trends, limitations in representing extreme nitrate events suggest areas for further refinement. These findings contribute to data-driven water quality management, enhancing understanding of nitrate behavior in interconnected water systems.

Alabama

Status of water-quality conditions in the United States, 2010–20

Degradation of water quality can make water harmful or unusable for humans and ecosystems. Although many studies have assessed the effect of individual constituents or narrow suites of constituents on freshwater systems, no consistent, comprehensive assessment exists over the wide range of water-quality effects on water availability. Using published studies, data, and models completed at regional or national scales in the United States during 2010–20, this chapter moves towards a comprehensive assessment by summarizing how selected anthropogenic and geogenic water-quality constituents affect national-scale water availability for human and ecosystem needs. Several types of human health, agricultural, ecological, and beneficial-use standards or thresholds were used to provide context for categorizing surface-water and groundwater quality. Water availability for human and ecological use is limited by elevated concentrations of geogenic and anthropogenic constituents in surface and groundwater. Elevated concentrations of five geogenic constituents (arsenic, manganese, strontium, radium, and adjusted gross alpha) are common in groundwater and collectively affect the drinking water supply to over 30 million people. Surface water sourced drinking water supplies are impaired in about a third of assessed stream miles, most commonly because of non-mercury metals and salinity. Health-based violations at community water systems may disproportionately affect socially vulnerable communities. Ecological water uses are predominantly limited by nutrients, sediment, temperature, pathogens, salinity, and pesticides. Water availability for human and ecological use is adversely affected by human activities including human contaminant sources (for example, wastewater, agriculture), processes (for example, dredging, groundwater pumping), or permanent landscape modifications (for example, dams, urbanization). Primary contaminant sources vary spatially and include fertilizer and manure, atmospheric deposition, wastewater treatment plants, urban land, and a range of natural sources. Contaminants of emerging concern, contaminants without regulatory thresholds, and mixtures of geogenic and anthropogenic water contaminants also contribute to ecological degradation and human exposure.

conterminous United States

Forecast, monitor, adapt: A multi-agency strategy to protect people from postfire debris flows

In 2020, a wildfire burned across Glenwood Canyon in Colorado, USA. A history of postfire debris flows in the region and a hazard assessment for the burn area indicated that potentially life-threatening debris flows could be triggered by rainfall within months of a wildfire. As a result, four government agencies evaluated strategies to help mitigate hazards, including the loss of human life, that may be associated with debris-flow events. After the fire, 26 large debris flows occurred in the summer of 2021 and three sediment-laden flows occurred in the summer of 2023, but there were no major injuries or fatalities reported. We found that integrating hazard assessment/ forecasting, monitoring, and adaptation scenarios was a successful strategy for reducing postfire debris-flow risks to human life (including injuries and fatalities). Weather forecasts and estimates of debris-flow triggering rainfall thresholds, likelihood, and volume were used to anticipate the timing, location, and magnitude of debris-flow events. Rainfall monitoring and detailed recordkeeping of storms that triggered debris flows were used to validate and update debris-flow warning thresholds that varied with time following the wildfire. Although the governmental agencies working in this burn area had distinct and differing agency mandates, they were able to integrate information to reduce the risk of debris-flow events to human life.

Colorado

Patterns and drivers of cliff erosion in Big Sur, California, USA using repeat photogrammetry, 2017–2023

Seacliff erosion in steep terrain poses major risks to transportation and critical infrastructure. In Big Sur, California, USA, seacliff erosion threatens the sustainability of the central coast stretch of California State Route 1, a transportation corridor that is critical to the region's economy. Published cliff retreat rates for the region range from 1 to 40 cm yr −1 , highlighting that high-resolution, process-based studies could enhance understanding of the causes of spatial and temporal variability. We quantified cliff erosion and investigated its drivers along ∼13 km of the Big Sur coastline at week–month timescales during the late fall to early spring wet seasons between January 2017 and June 2023 by analyzing 3D point clouds developed from aerial imagery using four-dimensional structure-from-motion (4D SfM) photogrammetry techniques. We calculated cliff face retreat rates of 2.23 ± 3.06 cm yr −1 (mean ±1 σ ), an order of magnitude lower than long-term estimated rates for the region (which included large deep-seated landslides), but in line with short-term rates reported across California. Change detection imagery comparison, cliff profiles through time, and statistical analysis reveal a cyclical cliff evolution process in which erosion by wave action at the cliff base destabilizes the cliff and primes it for subsequent failure during precipitation events. Although more erosion by volume could be attributed to precipitation-induced increases in soil moisture (784 m 3 km −1 yr −1 ) compared with erosion attributed to wave power (282 m 3 km −1 yr −1 ), our observations underscore the coupled nature of these processes in driving cliff evolution, consistent with established theory and observations.

California

Wave propagation in layered soil deposits

Recent advances in the general theory of viscoelastic waves and rays in layered media provide a rigorous mathematical framework for site-specific, soil-response models used for earthquake resistant design. The advances provide general closed-form anelastic solutions for the classic problems of the response of a stack of soil layers to S and P waves, ray theory for reflected and refracted waves, Rayleigh- and Love-Type surface waves, and head waves. These general solutions valid for anelastic media regardless of the amount of material damping yield new insights regarding the characteristics of seismic waves and their ray paths that are not provided by conventional models. They provide corresponding numerical ground-response models and ray-tracing computation algorithms that account for changes in velocity and attenuation of anelastic waves associated with changes in inhomogeneity of the waves induced by anelastic soil and soil-rock boundaries. These anelastic effects manifest themselves as variations in amplitude response, amplitude attenuation, raypath location, and travel time as observed at the Earth’s surface. Implications of these anelastic effects for soil-response models used for earthquake resistant design are provided herein.

Conference Paper

USGS addresses needs for lithium calibration and quality control materials for pLIBS analysis

Lithium (Li) is a globally important commodity used for energy storage, national defense, human health, and advanced technologies. Lithium resource development requires identifying deposits with elevated concentrations and optimal mineralogy, typically associated with select clays and pegmatites. Lithium is a light, highly reactive alkali metal with low atomic mass that is difficult to detect and quantify using conventional portable geochemical techniques such as X-ray fluorescence (XRF). However, portable laser-induced breakdown spectroscopy (pLIBS) is a powerful analytical technique for lithium exploration due to its ability to analyze solids quickly with minimal preparation. The expanded utility of pLIBS is hampered by the lack of matrix-matched calibration and quality control (QC) materials. The United States Geological Survey (USGS) has developed in-house lithium calibration and QC materials for lithium in clay and pegmatite matrices to address this limitation. We present the workflow and implementation of a custom-built matrix specific calibration on a SciAps Z-300 pLIBS, using proprietary Profile Builder software. The implementation of the custom calibration and quality control standards enables us to collect semiquantitative results directly from the pLIBS while in the field. Ultimately, this calibration has improved confidence in sample selection and collection in the field, providing more efficient site characterization.

Conference Paper

Examining 22 years of ambient seismic wavefield at Mount St. Helens

An increase in seismic activity precedes most volcanic eruptions. Whereas event-based forecasting approaches have been successful, some eruptions remain unanticipated, resulting in casualties and damage. Our study leverages the recent advancements in ambient field seismology. We explore features extracted from continuous ambient fields using traditional methods, for example, peak ground velocity, peak ground acceleration, root mean square, root median square, real-time seismic amplitude measurement, and novel methods (displacement seismic amplitude ratio and spectral width). In addition, we explore unsupervised learning of higher order wavelet features using scattering networks. We find that combining all the methods was necessary to disentangle the effects of seismic sources from structural changes at Mount St. Helens. Although the ambient wavefield-based approach does not yield additional or more significant precursory signals than event-based methods at Mount St. Helens, our study demonstrates that the ambient wavefield provides supplementary information, mainly about structural changes and complements traditional methods. The ambient seismic wavefield offers additional insights into long-lasting processes. We find enhanced wave attenuation correlating with geochemical measurements. We interpret this as ongoing structural changes, such as dome growth or the evolution of the volcanic conduit system. On annual and decadal timescales, we interpret seasonal seismic attenuation in the shallow subsurface as groundwater fluctuations, corroborated by observations at the nearby Spirit Lake level. This multimethod approach at Mount St. Helens sheds light on a volcanic system’s underlying dynamics and structure.

Washington

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

Results of phytoplankton sampling at National Stream Quality Accounting Network stations in Montana, 1975 water year

Twelve National Stream Quality Accounting Network stations were operated in Montana during the 1975 water year. The network was established for the purpose of acquiring a base of hydrologic data for use by agencies engaged in water-resources planning on a national or regional scale. Among the characteristics analyzed were phytoplankton identification and cell counts. Samples consisted of composites of equal aliquots, collected at the center of each quartile of flow, using modified suspended-sediment samplers and sediment collection techniques. Identification and counting were done using the Sedgwick-Rafter cell method. Cell counts ranged from 21 cells per millilitre at Flathead River at Flathead, British Columbia to 27,000 cells per millilitre at Yellowstone River near Sidney. The class Bacillariophyceae was most abundant in both number and variety at all sampling sites. Anabaena and Aphanizomenon of the phyllum Cyanophyta were found at six stations and two stations respectively. These two genera of blue-green algae often become abundant in enriched waters resulting in nuisance conditions.

Montana

2024 Crustal Deformation Modeling Workshop report

The 2024 Crustal Deformation Modeling Workshop was held June 10–14 at the Colorado School of Mines. The workshop included two days of tutorials on using PyLith for crustal deformation modeling, followed by three days of science talks and discussions. The workshop focused on four primary themes: ● Constraining long-term fault slip rates and their uncertainties using geodetic and geologic data; ● Earthquake cycle modeling with a focus on constraining models using seismic and geodetic data; ● Interaction of fluids and faulting; and ● Separating contributions of surface loading and tectonic loading in crustal deformation. The complete agenda is available on the CIG website.

Conference Paper

Relatively stable pressure effects and time-increasing thermal contraction control Heber geothermal field deformation

Due to geological complexities and observational gaps, it is challenging to identify the governing physical processes of geothermal field deformation including ground subsidence and earthquakes. In the west and east regions of the Heber Geothermal Field (HGF), decade-long subsidence was occurring despite injection of heat-depleted brines, along with transient reversals between uplift and subsidence. These observed phenomena contradict current knowledge that injection leads to surface uplift. Here we show that high-yield production wells at the HGF center siphon fluid from surrounding regions, which can cause subsidence at low-rate injection locations. Moreover, the thermal contraction effect by cooling increases with time and eventually overwhelms the pressure effects of pressure fluctuation and poroelastic responses, which keep relatively stable during geothermal operations. The observed subsidence anomalies result from the siphoning effect and thermal contraction. We further demonstrate that thermal contraction dominates long-term trends of surface displacement and seismicity growth, while pressure effects drive near-instantaneous changes.

California

Techniques for estimating magnitude and frequency of floods on streams in Indiana

Equations are presented for estimating the magnitude and frequency of floods at ungaged sites on unregulated and nonurban streams in Indiana. The equations were developed by multiple-regression, analysis of basin characteristics and peak-flow statistical data from 242 gaged locations in Indiana, Ohio, and Illinois. The State of Indiana was divided into seven areas on the basis of the regression analysis. A set of equations for estimating peak discharges with recurrence intervals of 2, IO, 25, 50, and 100 years was developed for each area. Significant basin characteristics in the equations are drainage area, channel length, channel slope, mean annual precipitation, storage, precipitation intensity, and a runoff coefficient. Standard errors of estimate for the equations range from 24 to 45 percent. Methods are also presented for estimating flood magnitude and frequency at sites on gaged streams. Flood-frequency data based on observed peaks are given for 270 gaged locations. Twenty of these are on regulated streams, and six are on urban streams. Basin characteristics are also included car 245 of the gaged locations on unregulated and nonurban streams. No techniques are given for estimating flood magnitude and frequency at ungaged sites on regulated or urban streams. A rainfall-runoff model was tlsed to synthesize long-term peak data at 11 gaged locations on small streams. Flood-frequency curves developed from the long-term synthetic data were combined with curves based on short-term observed data to provide weighted estimates of flood magnitude and frequency at the rainfall-runoff stations.

Indiana

Creation of aerial camera system boresight installations in Bangor, Maine; Monroe, Louisiana; and Bassville Park, Florida

Aerial camera systems rely on boresights for defining internal and external metrics. The U.S. Fish and Wildlife Service’s Migratory Bird Surveys Branch required boresights to calibrate their camera systems for creating georeferenced imagery that can then be used in geographic information systems. The U.S. Geological Survey created high-accuracy boresight installations in Bangor, Maine, in July 2024; Monroe, Louisiana, in September 2024; and Bassville Park, Florida, in January 2025 to provide this metric-defining capacity to the U.S. Fish and Wildlife Service. This U.S. Geological Survey Data Report details the methods and results of the boresight installation process and provides camera operators with the data needed to use each of the installations.

Florida, Louisiana, Maine

Recharge rates and aquifer hydraulic characteristics for selected drainage basins in middle and east Tennessee

Quantitative information concerning aquifer hydrologic and hydraulic characteristics is needed to manage the development of ground-water resources. These characteristics are poorly defined for the bedrock aquifers in Middle and East Tennessee where demand for water is increasing. This report presents estimates of recharge rate, storage coefficient, diffusivity, and transmissivity for representative drainage basins in Middle and East Tennessee, as determined from analyses of stream-aquifer interactions. The drainage basins have been grouped according to the underlying major aquifer, then statistical descriptions applied to each group, in order to define area1 distribution of these characteristics. Aquifer recharge rates are estimated for representative low, average, and high flow years for 63 drainage basins using hydrograph analysis techniques. Net annual recharge during average flow years for all basins ranges from 4.1 to 16.8 in/yr (inches per year), with a mean value of 7.3 in. In general, recharge rates are highest for basins underlain by the Blue Ridge aquifer (mean value11.7 in/yr) and lowest for basins underlain by the Central Basin aquifer (mean value 5.6 in/yr). Mean recharge values for the Cumberland Plateau, Highland Rim, and Valley and Ridge aquifers are 6.5, 7.4, and 6.6 in/yr, respectively. Gravity drainage characterizes ground-water flow in most surficial bedrock aquifer in Tennessee. Accordingly, a gravity yield analysis, which compares concurrent water-level and streamflow hydrographs, was used to estimate aquifer storage coefficient for nine study basins. The basin estimates range from 0.002 to 0.140; however, most estimates are within a narrow range of values, from 0.01 to 0.025. Accordingly, storage coefficient is estimated to be 0.01 for all aquifers in Middle and East Tennessee, with the exception of the aquifer in the inner part of the Central Basin, for which storage coefficient is estimated to be 0.002. Estimates of aquifer hydraulic diffusivity are derived from estimates of the streamflow recession index and drainage density for 75 drainage basins; values range from 3,300 to 130,000 ft^2/d (feet squared per day). Basin-specific and site-specific estimates of transmissivity are computed from estimates of hydraulic diffusivity and specific-capacity test data, respectively. Basin-specific, or areal, estimates of transmissivity range from 22 to 1,300 ft^2/d, with a mean of 240 ft^2/d In general, areal transmissivity is highest for basins underlain by the Cumberland Plateau aquifer (mean value 480 ft^2/d) and lowest for basins underlain by the Central Basin aquifer (mean value 79 ft^2/d). Mean transmissivity values for the Highland Rim, Valley and Ridge, and Blue Ridge aquifer are 320,140, and 120 ft^2/d respectively. Site-specific estimates of transmissivity, computed from specific-capacity data from 118 test wells in Middle and East Tennessee range from 2 to 93,000 ft^2/d with a mean of 2,600 ft^2/d Mean transmissivity values for the Cumberland Plateau, Highland Rim, Central Basin, Valley and Ridge, and Blue Ridge aquifers are 2,800,1,200, 7,800, 390, and 65Oft Id, respectively.

Tennessee

Gulf Coast Basin CORE-CM initiative final report

The Bureau of Economic Geology at the University of Texas at Austin (UT-BEG) is leading the Gulf Coast Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) Initiative to assess the potential to produce critical minerals (CMs), including rare earth elements (REEs) from coal, coal ash, and produced water related to oil and gas production, and related materials (alumina processing waste [red mud], heavy mineral sands, graphite, and zeolite) within the Gulf Coast Basin. This project represents the first phase in a long-term program and provides reconnaissance data that will be foundational for future work by assessing resources and suggesting plans to be conducted in future work and expanding stakeholder engagement. The project includes several tasks designed to identify, characterize, and assess several necessary aspects for development of CMs and REEs in the Gulf Coast Basin.

Gulf Coast basin

What 25+ years of "Did You Feel It" intensities tell us about shaking in California

“When will the Big One happen?” is a question that people often have for earthquake scientists. But while waiting for the “Big One” to occur, people will usually experience frightening or damaging shaking from multiple relatively smaller‐magnitude earthquakes. Given this context, it raises the question: “Where does most of the damage come from?” Could smaller, yet more frequent, earthquakes account for the majority of reported impactful shaking? To explore this question, we consider reports of earthquake damage and felt shaking experiences from a catalog of community‐collected intensity values from the U.S. Geological Survey’s “Did You Feel It?” system. Comparing these intensities to expectations from a ground‐motion model, we find that earthquakes of magnitudes smaller than expected are responsible for most reported intensities of community decimal intensities (CDI) 4.5 and above (moderate and higher shaking intensity levels). (Here “expected value” is meant in its mathematical sense of the mean or equivalently median shaking intensity.) We also present a regional analysis of observed earthquake shaking for specific areas, detailing the maximum intensity experienced within a predetermined area. We identify several instances of M < 4.5 events that generated maximum intensities of CDI > 5 in regions in California surrounding the cities of Eureka, San Francisco, Los Angeles, and San Diego. Our results motivate the need to include smaller‐magnitude earthquakes in communications about earthquake hazard and risk reduction.

California

Did they feel it? Legacy maroseismic data illuminates an engimatic 20th century earthquake

The challenges and the importance of preserving legacy instrumental records of earthquakes are now well-recognized (e.g., Richards & Hellweg, 2020, https://doi.org/10.1785/0220200053 ). Seismologists may not be aware of parallel challenges and opportunities with legacy macroseismic data for earthquakes in the United States. For much of the 20th century, macroseismic data were collected by a series of U.S. government agencies using a standard questionnaire distributed on postcards. Published summaries of postcards provide macroseismic data akin to modern Did You Feel It? questionnaire responses. In this paper we focus on the M 6.5 Fickle Hill, California earthquake, on 21 December 1954 (Hellweg et al., 2025) as a proof-of-concept, illustrating the potential of what we dub Did They Feel It? (DTFI) data to improve our understanding of significant 20th century U.S. earthquakes for which instrumental data are sparse. Legacy macroseismic data interpreted following modern conventions can potentially constrain traditional ShakeMaps at a level of detail and accuracy that in some respects rival maps for modern earthquakes. The updated ShakeMap for the 1954 Fickle Hill earthquake, also drawing from recently published media and first-person accounts, supports the location, depth, and stress drop value estimated from available instrumental data (Hellweg et al., 2025).

California

Wetland sedimentation and vegetation patterns near selected highway crossings in West Tennessee

Wetland sedimentation and vegetation patterns at 11 highway crossings in West Tennessee were studied from 1987 to 1989. The purpose of the study was to investigate potential adverse effects of highway crossings on wetlands. Sedimentation rates, determined from root-burial depths, were highly variable. Average rates offine-grained deposition ranged from 0.005 to 0.033 foot per year for stations in locally ponded areas and from -0.002 to 0.039 foot per year for stations in drained areas. Sedimentation rates upstream from highway crossings were not significantly different from downstream rates at 8 of the 11 study sites. Three study sites had significantly greater sedimentation rates downstream. Sand splays were observed downstream from bridges at most study sites. Vegetation patterns and tree growth appear most strongly related to hydropetiod, defined as the average length of time an area is covered by water each year. The influence of sedimentation on tree growth is difficult to separate from the influence of hydroperiod because areas with high sedimentation rates typically have long hydroperiods. Estimated hydroperiod increased no more than 1 percent because of backwater from the highway crossings at the 11 study sites, while the estimated average depth of flood-plain inundation increased by an average of 6 percent.

Tennessee