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Results for “Geochemistry: Exploration, Environment, Analysis”

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633 records · Page 32Linked to original sources
USGS2024

The new self-anchored suspension (SAS) San Francisco Bay Bridge- Its response to a small earthquake

This paper presents a summary of previously published work (Celebi 2023) related to the new Self-Anchored Suspension (SAS) bridge that went into service within the last decade as a replacement for the older truss bridge spanning between Yerba Buena Island and Oakland, California, within the San Francisco Bay Area. During the October 19, 1989 M6.9 Loma Prieta earthquake, which occurred ~100 km south of the Bay Bridge, a section of the upper deck of the truss bridge fell onto the lower deck – thus closing this important lifeline between San Francisco and Oakland. The SAS is unique, self-anchored, and suspended by a single tower that is pivotal in trafficking the cable and hanger system to support the decks. The SAS bridge is extensively instrumented by the California Geological Survey’s Strong Motion Instrumentation Program (CSMIP). There are approximately 85 channels of accelerometers in the seismic monitoring system that recorded the October 14, 2019 Mw4.6 Pleasant Hill earthquake. The data allow a complex but identifiable coupled response of the deck, tower, and cable system. Both acceleration and displacement time-history data are used to extract significant frequencies using system identification methods, including spectral analyses. Results are compared to those from finite-element-model (FEM) analyses carried out during the design and analysis process of the bridge in 2002 (Nader et al. 2002). There are differences between FEM analyses results and those from the low amplitude shaking caused by a seismic event. An apparent frequency (period) of the SAS bridge is assessed (approximately 5.2 seconds). In a plot of deck length versus period, there is an almost linear relationship with periods of other regular suspension bridges, such as the Golden Gate Bridge and the Carquinez Bridge, both in the San Francisco Bay.

California↗
USGS2025

A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed

Seasonal shifts from runoff to groundwater dominance influence daily headwater stream temperatures, especially where local groundwater input is strong. This input buffers temperature during hot periods, supporting cold-water habitats. Recent studies use air–water temperature signal metrics to identify zones of strong stream–groundwater connectivity. While Previous studies used air–water signal ratios as proxies for groundwater influence but were limited to specific sites and periods, without dynamic forecasting. This study is the first to forecast daily A r as a spatiotemporal signal using a Graph Convolutional Network–Long Short-Term Memory (GCN-LSTM) model. The model was trained using hydroclimate data (air temperature, precipitation, shortwave radiation, streamflow) and watershed physical features (e.g., sand content, slope). Results showed high predictive skill, achieving R 2 (NSE, RMSE) of 0.86 (0.73, 0.0004) for one-day-ahead to 0.52 (0.50, 0.0009) for seven-days ahead forecasts. Prior studies often have not explicitly incorporated spatial hydrogeologic drivers, but this model explicitly incorporates them to assess their impact on A r forecasting and stream-groundwater connectivity. Feature analysis identified mean sand, elevation, slope, clay, and TWI as key predictors of A r . Stronger groundwater signals appeared in hillslopes, elevations, and tributaries, highlighting watershed influence on streamflow. However, limitations include reliance on historical air–water temperature patterns for training and limited representation of extreme climate conditions. Despite these limitations, unlike previous studies relying on measured in-situ stream and air temperature, this study forecasts A r directly from climate and physiographic features after training, avoiding in-situ data requirements. Findings aiding predictions of stream ecosystem resilience.

New York↗
USGS1983

Base flow and ground water in upper Sweetwater Valley, Tennessee

The upper Sweetwater Valley area has a flow system with complex interaction between surface and ground water. A water budget study indicated that during dry years approximately three-fourths of the annual flow to Sweetwater Creek may be derived from ground-water sources. Hydrograph analysis showed seasonal variation of recharge to the ground-water flow system. Streamflow records were analyzed to estimate the frequency of low flow of Sweetwater Creek at river mile 16.7, and indicated the lowest average flow for 1 day in 20 years to be about 5.1 cubic feet per second. Two periods of base-flow measurements of Sweetwater Creek identified channel reaches with significant gains and losses of streamflow. Base flow measurements also showed interbasin transfer of water among sub-basins of the valley. Major flow surpluses were associated with areas in which the majority of flow originated at a spring. Topographically low areas adjacent to the main stem of Sweetwater Creek generally have surplus flow. Topographically higher areas generally have deficient surface outflow unless significant spring flow occurs in the basin. Ground-water recharge occurs by water draining into sinkholes, faults, and fractures. Ground-water flow is regionally diffused across formation strikes from the topographically low areas unless the water is exposed to highly permeable formations or impervious formations. Ground water infiltrates the highly permeable formations and flows along strike. Ground water encountering impervious formations may discharge at small springs at the contact, or may reroute along the contact if the upgradient rock is sufficiently permeable or has well developed secondary porosity. Groundwater discharges to streams at innumerable seeps and at a few large springs. Areas of ground-water flow up-gradient of large springs are hypothesized as likely areas of significant ground-water reservoirs.

Tennessee↗
USGS2024

Static and dynamic strain in the 1886 Charleston, South Carolina, earthquake

During the 1886 Mw 7.3 Charleston, South Carolina, earthquake, three railroads emanating from the city were exposed to severe shaking. Expansion joints in segmented railroad tracks are designed to allow railroad infrastructure to withstand a few parts in 10,000 of thermoelastic strain. We show that, in 1886, transient contractions exceeding this limiting value buckled rails, and transient extensions pulled rails apart. Calculated values for dynamic strain in the meizoseismal region are in reasonable agreement with those anticipated from the relation between strain and moment magnitude proposed by Barbour et al. (2021) and exceed estimated tectonic strain released by the earthquake by an order of magnitude. Almost all of the documented disturbances of railroad lines, including evidence for shortening of the rails, can thus be ascribed to the effects of dynamic strain changes, not static strain. Little or no damage to railroads was reported outside the estimated 10 −4 dynamic strain contour. The correspondence between 10 −3 and 2×10 −4 contours of dynamic strain and Mercalli intensity 9 and 8, anticipated from the dependence of each quantity on peak ground velocity, suggests it may be possible to use railroad damage to quantitatively estimate shaking intensity. At one location, near Rantowles, ≈20 km west of Charleston, a photograph of buckled track taken one day after the earthquake has been cited as evidence for shallow dextral slip and has long focused a search for a causal fault in this region. Photogrammetric analysis reveals that the buckle was caused by transient contraction of <10 cm with no dextral offset. Our results further weaken the evidence for faulting in the swamps and forests south of the Ashley River in 1886, hitherto motivated by the photograph and limited macroseismic evidence for high‐intensity shaking.

South Carolina↗
USGS2025

Do Graviquakes exist?

The “Graviquake” model, proposed in 2015 as an alternative to the elastic dislocation model, posits that normal faults are passive features dominated by coseismic gravitational collapse into a dilated crustal wedge, and that normal faulting is fundamentally distinct from strike‐slip and reverse faulting. Developed using finite‐element modeling before the 2016 central Apennines earthquake sequence, the model was revamped based on interpreted Differential Interferometric Synthetic Aperture Radar data from these events and used as evidence for a gravitational collapse episode. However, this interpretation relies on miscalculated elevation changes and is not corroborated by independent geophysical and seismological observations. Our analysis exposes fundamental flaws in the Graviquake model. By assuming that faults are passive players, it underrepresents the dynamic role of strain accumulation and release in rocks adjacent to faults. The hypothesized rapid expulsion of overpressurized fluids appears inconsistent with observed diffusion rates and lacks supporting seismological evidence. Part of the uplifted–subsided volume imbalance is likely an artifact arising from data processing, and in part is a transient effect due to the delayed response of the lower crust. Moment tensor analyses detect no isotropic components indicative of gravitational collapse, and observed ground motion and stress‐drop levels remain fully consistent with elastic dislocation theory. In addition, finite‐element modeling of normal faulting replicates observed surface deformation without invoking a collapsing wedge. The Graviquake model proposes a representation of normal‐faulting mechanics that differs significantly from established models and observations. Gravity does play a role in normal faulting, but the elastic dislocation theory remains the definitive framework of fault mechanics. Reinterpreting the 2016 earthquakes as a cascade of gravitational episodes, based on incorrect data processing and modeling, fails to substantiate the Graviquake hypothesis. Persistence in advocating this model could mislead seismic hazard assessment and undermine our understanding of normal faulting.

Bulletin of the Seismological Society of America↗
USGS2026

Birds, breakpoints, and baselines: How citizen science data can reveal ecological boundaries in Kenya’s Upper Tana watershed

Tropical watersheds are increasingly threatened by climate change, land-use conversion, and resource extraction, yet conventional biodiversity monitoring in these systems is often spatially and temporally limited. Citizen science offers a complementary approach, enabling biodiversity data collection over large areas that can supplement professional scientific surveys. We analyzed 10 years (2012–2022) of Upper Tana Watershed bird data from the Kenya Bird Map project, covering 114 pentads (9 × 9 km) within a 17,000 km 2 watershed to assess patterns of bird community composition and distribution across this watershed and to also evaluate the effects of environmental variables, seasonality, and sampling effort to help inform improvements in future citizen science projects. Citizen (or community) scientists recorded 575 species (>50% of Kenya’s total avifauna) in 74 families. Asymptotic species accumulation indicates that most probable species present in the watershed were detected. Threshold indicator taxa analysis revealed distinct ecological boundaries along elevation (∼1,500 m), precipitation (∼1,100 mm), and mean temperature (∼19°C) gradients, corresponding to a turnover from xeric savanna to mesic montane forest assemblages. Notably, bird communities showed little seasonal differentiation between wet and dry periods, consistent with dominance by resident year-round species. Data limitations including uneven survey distribution and frequency, absence of abundance metrics, and coarse representation of local environmental conditions that likely reduced our ability to detect fine-scale species–habitat relationships. Addressing these gaps through spatially balanced sampling at greater resolution, greater survey frequency in underrepresented areas, and improved capture of habitat metrics could strengthen the use of citizen-science bird data for watershed bioassessment. Our findings demonstrate that structured citizen-science initiatives can identify ecological boundaries and inform adaptive management of tropical socio-ecological systems under rapid environmental change.

Upper Tana watershed↗
USGS2024

Simulated effects of projected 2014–40 withdrawals on groundwater flow and water levels in the New Jersey Coastal Plain

Abstract Groundwater flow between 2014 through 2040 was simulated in the New Jersey Coastal Plain based on three withdrawal scenarios. Two of the scenarios were based on projected population trends and the assumption of water conservation; the nominal water-loss scenario projected a status quo in the efficiency of water loss in the delivery systems whereas the optimal water-loss scenario projected a better water-loss efficiency resulting in less withdrawals. The third scenario assumes that all wells will withdraw water at their full allocation level which is generally much more than reported withdrawals in 2013 or projected under the other two scenarios. Maps and summaries of heads and drawdowns are presented for nine confined aquifers. All the aquifers have areas with heads below sea level by 2040. Of the three scenarios, the drawdowns are most extreme in the full allocation scenarios; there are large areas of head decline greater than 20 feet in 5 of the 9 confined aquifers. The exceptions are the Vincentown aquifer, despite some areas of large drawdown in the vicinity of wells, and the three Potomac-Raritan-Magothy (PRM) aquifers where withdrawals are regulated by Critical Area restrictions. The nominal and optimal water-loss scenarios have some areas of head declines; most are less than 15 feet. The simulation of these scenarios shows some extensive areas of head recovery as well—especially in the aquifers that are regulated by the Critical Area restrictions. Budgets of inflow and outflow components were calculated for 44 hydrologic budget areas (HBAs). The budget analysis shows that the water movement is complex and varies based on the aquifer geometry and location of pumping wells. Flow components between the unconfined and confined parts of the system were summarized by HUC11 (hydrologic unit code 11) basins.

New Jersey↗
USGS2025

A scientific vision and roadmap for earthquake rupture forecast developments, a USGS perspective

We articulate a scientific vision and roadmap for the development of improved Earthquake Rupture Forecast models, which are one of the two main modeling components used in modern seismic hazard and risk analysis. One primary future objective is to provide fully time-dependent models that include both elastic rebound and spatiotemporal clustering nationwide, which is particularly important for shorter-term hazard and risk considerations (e.g., earthquake insurance products). We also discuss the importance and perennial challenges associated with quantifying epistemic uncertainties, including those associated with deformation-model slip rates, un-quantified sampling errors with respect to off-fault seismicity, and any spatial covariances. The need for more physics-based approaches is also emphasized, as is the benefit of adding model valuation (quantifying usefulness) to our verification and validation protocols. Given the multidisciplinary and system-level nature of this activity, modular design is critical. Future updates will also draw from best-available science by both the United States Geological Survey and the external community. The primary goal of this paper is to highlight plans that guide research and facilitate community engagement with model development, especially with respect to lowering the entry barrier for early career scientists and engineers. The paper is written so readers can focus on the sections that interest them most (see table of contents), with the Introduction and Discussion providing a stand-alone overview and summary.

Bulletin of the Seismological Society of America↗
USGS2026

Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)

Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.

Alaska↗
USGS2025

World minerals outlook—Cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium through 2029

Given the rapid expansion in the demand for mineral commodities that underpin worldwide economic growth and technological advancement, information regarding expected country-level mine production and production capacity is becoming increasingly important to industry stakeholders, end users, and policymakers. Production capacity can limit future supply, depending on how rapidly that capacity is able to expand. Current capacity can be evaluated on the basis of past production. Decreases to future capacity can be taken into account from announcements of planned shutdowns of mines or processing facilities, which are frequently publicized well in advance of such closures. Likewise, capacity expansions, which usually involve multiple stages—such as permitting, financing, and construction (all of which take time)—can also be estimated. As such, it is possible to evaluate midterm future capacity based on estimates of today’s capacities along with consideration of future investment plans. This World Minerals Outlook provides estimated capacities for cobalt, gallium, helium, lithium, magnesium, palladium, platinum, and titanium for 2025 through 2029. The results of this analysis indicate that two mineral commodities important to the manufacture of lithium-ion batteries—cobalt and lithium—are expected to have large capacity growth in the next few years, likely owing to expectations for increased demand for these batteries. For gallium, helium, palladium, and platinum, capacity is expected to remain stable or exhibit moderate growth. Still, these expected capacity levels are higher than current production, allowing for future production growth. The production capacity outlook is opaque for magnesium and titanium metal, which have a significant fraction of current production in nonmarket economies, such as China and Russia. Ultimately, though, where free market conditions prevail, full utilization of capacity potential for those commodities is likely to depend on supply deficits and prices that are above production costs.

Scientific Investigations Report↗
USGS2026

Long-term intermittent connection between the western Snake River Plain and Columbia basin: A two-phased incision history of Hells Canyon

For more than a century, researchers have debated the route of the Snake River across the northern Cordillera and U.S. Pacific Northwest, including the associated incision history of Hells Canyon. Here, we use detrital zircon U-Pb provenance analysis of Miocene strata upstream and downstream of Hells Canyon to constrain the evolution in fluvial pathways over time. Downstream of Hells Canyon, we show that the ca. 10−6 Ma Clarkston Heights gravel was dominantly sourced from the nearby Salmon and Clearwater rivers but also with substantial input from drainages that now flow into the western Snake River Plain. These same western Snake River Plain drainages were contributing to time-equivalent Lake Idaho strata, upstream of Hells Canyon, indicating a Hells Canyon fluvial connection between the western Snake River Plain and Columbia basin before 6 Ma. Results from Lake Idaho strata suggest a two-phased lacustrine history in the western Snake River Plain: Before ca. 6.0 Ma, lake strata were derived from local tributaries, suggesting that the western Snake River Plain was isolated from the modern upper Snake River system. Between ca. 4.3 Ma and 2.2 Ma, the source area expanded to include eastern tributaries in conjunction with migration of high-standing topography of the Yellowstone hotspot. Our results challenge the long-held hypothesis of “capture” of the Snake River through Hells Canyon. Instead, we infer that Hells Canyon was a long-established route for outflow of lakes occupying the western Snake River Plain, possibly intermittently, during a ca. 10−2 Ma phase of slow regional incision, followed by rapid incision in Hells Canyon starting ca. 2 Ma in conjunction with erosion of the topographic barrier impounding Lake Idaho.

Idaho, Oregon↗
USGS1998

Peak-discharge frequency and potential extreme peak discharge for natural streams in the Brazos River basin, Texas

The 2-, 5-, 10-, 25-, 50-, and 100-year peak discharges were estimated for 186 streamflow-gaging stations with at least 8 years of data for natural streams in and near the Brazos River Basin, Texas. Multiple regression equations were developed to estimate peak-discharge frequency for the 2-, 5-, 10-, 25-, 50-, and 100-year recurrence intervals for each of three hydrologic regions that compose the Brazos River Basin. The equations for each region are a function of significant basin characteristics (explanatory variables). The significant explanatory variables among six that were tested are the contributing drainage area and stream slope for regions 1 and 2 and the contributing drainage area for region 3. For the three sets of equations, the coefficient of determination ranges from 0.59 to 0.93, and the standard error ranges from 0.184 to 0.391 log units. A larger coefficient of determination and a lower standard error generally are associated with the equations for hydrologic regions 2 and 3. Statistics from the regression analysis allow computation of the prediction interval associated with a given significance level for a peak-discharge frequency estimate. The regression equations can be used to estimate peak discharges for sites at, near, or away from sites with streamflow-gaging stations. The potential extreme peak-discharge curves as related to contributing drainage area were estimated for each of the three hydrologic regions from measured extreme peaks of record at 186 sites with streamflow-gaging stations and from measured extreme peaks at 37 sites without streamflow-gaging stations in and near the Brazos River Basin. The potential extreme peak-discharge curves generally are similar for hydrologic regions 1 and 2, and the curve for region 3 consistently is below the curves for regions 1 and 2, which indicates smaller peak discharges.

Texas↗
USGS2026

The mineral chemistry networks of tin and tungsten reflect metallogenic eras of the Mesozoic

Continental remobilization is a crucial driver of metallogenesis and the formation of ore deposits. Some of the world’s largest mineral deposits of the economically valuable elements tin (Sn), tungsten (W), gold (Au), copper (Cu), lead (Pb), and zinc (Zn) formed during the Mesozoic Era. Additionally, the chemistry and distribution of the elements Sn and W have been investigated in previous studies to understand planetary formation and differentiation processes. These two elements are largely co-located during certain South China Mesozoic metallogenic events but are not co-located during other time periods in the same regions. Here, we investigated the mineral chemistry network similarities and dissimilarities of Sn and W to understand their mineral formation and distribution during the Mesozoic Era and throughout Earth history. Mineral chemistry network community detection analysis and electronegativity associations among mineral constituent elements of Sn minerals and W minerals indicate that the elements have similar chemistry among their oxide minerals. However, Sn forms a much wider range of minerals that also contain S compared to W, which occurs in a limited number of S-containing minerals. The divergent constituent element interactions among S-containing Sn minerals and W minerals reflect the redox sensitivity and importance of oxygen (O) fugacity in Sn mineral formation. Conversely, extensive W mineral deposits are known to form at both high and low O fugacities. The similarities and differences between the mineral chemistry networks of Sn and W reflect the mineral distribution of the two elements in the Sn-W mineralization event from 160 to 139 Ma vs. the Sn–uranium (U) mineralization event from 125 to 98 million years ago (Ma). The mineral chemistry and distribution of Mesozoic Sn and W deposits illustrate the contrasting importance of redox and O fugacity on the mineral formation of different elements, and the dynamic crustal evolution that took place during this period of Earth history.

Geosciences↗
USGS2025

Site response and wave propagation effects in the eastern United States

Fourier amplitude spectra from regional earthquakes in the eastern United States are used in a parametric inversion for source, path, and site effects. Five earthquakes are selected for analysis during the installation of the United States National Seismic Network (US), Earthscope’s USArray Transportable Array (TA), and other temporary arrays to maximize station coverage. A global search algorithm is used to solve for site response from 0.1 to 15 Hz, corner frequency, geometrical spreading ( r - γ ), and frequency dependent anelastic attenuation in the form Q(f) = Q o f α . Tradeoff between moment and geometric spreading is handled by fixing the moment. The tradeoff between corner frequency and Q(f) is solved by selecting the value of corner frequency that minimizes an objective function defined over all stations. Values of site response and attenuation parameters show a strong spatial correlation with the physiographic provinces of the eastern United States. Site response for the Atlantic Coastal Plain is consistent with previous work using spectral ratios relative to a reference site, defined by strong resonance peaks correlated with the thickness of sediments. Site response for the other physiographic provinces is markedly different from the coastal plain, with a lack of distinct resonance peaks and a broad moderate high at frequences from 0.1 to 0.5 Hz consistent with the hard-rock geology of the regions. Like site response, Q(f) has a strong correlation with physiographic province, showing lower values on the coastal plain and higher values inland. Geometric spreading exponent, γ, decreases with increasing hypocenter distance from just above 1 at a few tens of kilometers to 0.9 at 500 km. The limited range in geometric spreading values is attributed to starting the Fourier transform window at the S ‐wave arrival for all distances and averaging over multiple wave types.

eastern United States↗
USGS2012

Development of vegetation based soil quality indices for mineralized terrane in arid and semi-arid regions

Soil quality indices (SQIs) are often management driven and attempt to describe key relationships between above- and below-ground parameters. In terrestrial systems, indices that were initially developed and modified for agroecosystems have been applied to non-agricultural systems in increasing number. We develop an SQI in arid and semi-arid ecosystems of the Western US impacted by different types of geologic mineralization using the relationship between vegetation community parameters and soil abiotic and biotic properties. We analyze these relations in soils associated with three different mineralization types: podiform chromite, Cu/Mo porphyry, and acid-sulfate gold vein systems at four different sites in California and Nevada. Soil samples were collected from undisturbed soils in both mineralized and nearby unmineralized substrates as well as from waste rock and tailings. Aboveground net primary productivity (ANPP), canopy cover and shrub density were measured for the vegetative communities. Minimum data sets were developed based on correlations between the soil and vegetation parameters, refined using principal components analysis, scored using non-linear functions, and combined into an overall SQI. The indices are comprised of one or two microbial parameters and three to six abiotic parameters, the latter consisting of nutrients and metals. Given the preliminary development of this approach, the parameters and combinations to arrive at an SQI for a given site cannot at this time be correlated or compared with that of another site. This SQI approach provides a means of quantifying disturbed ecosystem recovery resulting from mining, and could be applied to other disturbances in a way that readily distills the information for potential use by land managers. However, severely disturbed areas with little to no aboveground biomass, such as unreclaimed tailings, have likely crossed an ecological threshold that precludes the use of this type of monitoring tool.

California↗
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↗
USGS2025

Modeling seawater intrusion along the Alabama coastline using physical and machine learning models to evaluate the effects of multiscale natural and anthropogenic stresses

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.

Alabama↗
USGS1998

Technique for simulating peak-flow hydrographs in Maryland

The efficient design and management of many bridges, culverts, embankments, and flood-protection structures may require the estimation of time-of-inundation and (or) storage of floodwater relating to such structures. These estimates can be made on the basis of information derived from the peak-flow hydrograph. Average peak-flow hydrographs corresponding to a peak discharge of specific recurrence interval can be simulated for drainage basins having drainage areas less than 500 square miles in Maryland, using a direct technique of known accuracy. The technique uses dimensionless hydrographs in conjunction with estimates of basin lagtime and instantaneous peak flow. Ordinary least-squares regression analysis was used to develop an equation for estimating basin lagtime in Maryland. Drainage area, main channel slope, forest cover, and impervious area were determined to be the significant explanatory variables necessary to estimate average basin lagtime at the 95-percent confidence interval. Qualitative variables included in the equation adequately correct for geographic bias across the State. The average standard error of prediction associated with the equation is approximated as plus or minus (+/-) 37.6 percent. Volume correction factors may be applied to the basin lagtime on the basis of a comparison between actual and estimated hydrograph volumes prior to hydrograph simulation. Three dimensionless hydrographs were developed and tested using data collected during 278 significant rainfall-runoff events at 81 stream-gaging stations distributed throughout Maryland and Delaware. The data represent a range of drainage area sizes and basin conditions. The technique was verified by applying it to the simulation of 20 peak-flow events and comparing actual and simulated hydrograph widths at 50 and 75 percent of the observed peak-flow levels. The events chosen are considered extreme in that the average recurrence interval of the selected peak flows is 130 years. The average standard errors of prediction were +/- 61 and +/- 56 percent at the 50 and 75 percent of peak-flow hydrograph widths, respectively.

Maryland↗