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735 records · Page 28Linked to original sources
USGS2025

Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed

Concentration-discharge (CQ) relations are commonly used to understand geochemical and hydrologic controls on the generation of solutes in watersheds. Despite the widespread application of CQ relations, this technique has been infrequently applied to acid mine drainage (AMD) sites, but the CQ framework may allow mechanistic understanding of remedial outcomes such as impoundment of water within underground mines. Results of CQ analyses and changes in metal loads in an AMD affected watershed in Colorado, USA indicate that dissolved loads increased at many individual locations following water impoundment within mine workings. Although increased loads were observed at most individual locations, these increases were offset by a large decrease in loading from the largest mine. A loading analysis that included data from an instream monitoring location showed a statistically significant decrease in Fe and Zn after bulkhead emplacement, indicating a net positive effect of bulkheads. Streams generally displayed dilution CQ patterns whereas mines and springs showed either flushing or chemostatic patterns prior to bulkheading, which transitioned to chemostatic patterns following bulkheading, indicating a transition from dynamic to equilibrium geochemical processes. Saturation indices for sulfide and secondary minerals indicated that mines and springs were near equilibrium for phases including schwertmannite, fluorite, and gypsum. Saturation indices vary through time for mines suggesting progressive leaching of sulfide minerals as the mass of available minerals in the mine workings decreases. Together, these diverse analyses provide an integrated understanding of the variability in solute generating processes in this watershed and may inform remediation plans for similarly affected sites by indicating the nature of mineralogic controls on water quality.

Colorado↗
USGS2026

Simulation of groundwater flow to evaluate hydrogeologic controls on a PFAS plume, Coakley Landfill Superfund Site, Rockingham County, New Hampshire

Per- and polyfluoroalkyl substances (PFAS), including perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), have been detected at combined concentrations above 2,000 nanograms per liter (ng/L) at groundwater seep locations near the Coakley Landfill Superfund site, in North Hampton, New Hampshire. The landfill was active from 1972 to 1985. An impermeable cap was placed on the landfill in 1998. The adjacent area to the Coakley Landfill has many water supply wells, and transport of PFAS compounds to the wells is a concern. Fracture anisotropy in the underlying bedrock aquifer complicates the understanding of PFAS transport because groundwater preferentially travels along fractures that may not align with the prevailing groundwater flow direction. In 2018, the U.S Environmental Protection Agency and the U.S. Geological Survey began an investigation of the groundwater flow from the Coakley Landfill site. This report describes the modification of a numerical groundwater-flow model for the local area around the Coakley Landfill and summarizes findings of the investigation. In addition, this report includes a brief description of PFOA and PFOS occurrence, a discussion of model construction, evaluation of model performance through calibration, and discussion of simulation results for two periods (before and after capping). Limitations are also discussed. Results show that simulated groundwater flow moves from the Coakley Landfill to the west and north. Advective transport modeling using particle tracking shows that groundwater from the landfill discharges primarily to streams to the west and north, and a small amount is transported to distal wells. Dilution of contaminants through advection and dispersion likely plays a role in whether PFAS compounds from the landfill will be detected above laboratory reporting levels at distal wells.

EarthArXiv↗
USGS2026

Water use in Louisiana, 2020

The U.S. Geological Survey (USGS), in cooperation with the Louisiana Department of Transportation and Development, collected water-withdrawal and water-use data from a 2020 inventory of water withdrawals in Louisiana. In 2020, approximately 8,700 million gallons per day (Mgal/d) of water was withdrawn from groundwater and surface-water sources in Louisiana, which represented a 0.22-percent decrease from 2015. Total groundwater withdrawals were about 1,900 Mgal/d, an increase of 7.1 percent from 2015, and total surface-water withdrawals were about 6,800 Mgal/d, a decrease of 2.1 percent from 2015 to 2020. Total water withdrawals, in million gallons per day, in 2020 for the various categories of use were as follows: public supply, 720; industry, 2,100; power generation, 4,100; rural domestic, 39; livestock, 7.0; rice irrigation, 930; general irrigation, 250; and aquaculture, 590. From 2015 to 2020, Louisiana’s total withdrawals for public supply increased by 1.4 percent, industry decreased by 2.3 percent, power generation decreased by 4.9 percent, rural domestic decreased by 1.2 percent, livestock increased by 11 percent, rice irrigation increased by 13 percent, general irrigation increased by 12 percent, and aquaculture increased by 20 percent. About 51 percent (approximately 960 Mgal/d) of all groundwater withdrawn was from the Chicot aquifer system and 24 percent (approximately 450 Mgal/d) was withdrawn from the Mississippi River alluvial aquifer. Since 2015, withdrawals from the Chicot aquifer system increased by 13 percent, and withdrawals from the Mississippi River alluvial aquifer increased by 18 percent. About 72 percent (4,900 Mgal/d) of all surface water withdrawn was from the Mississippi River main stem. This value represents a 1.1-percent decrease in withdrawals from 2015 to 2020. All water-withdrawal and water-use data presented in this report should be considered estimates. Because of rounding, totals and percentages presented in the tables, figures, and text in the report may differ slightly from totals or percentages calculated individually.

Louisiana↗
USGS2026

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

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

Tennessee↗
USGS2026

Multiple machine-learning estimation of groundwater levels and trends for the regional Mississippi River Valley alluvial aquifer

The Mississippi River Valley alluvial aquifer provides irrigation, public, and domestic water supplies across the south-central United States. Declining groundwater levels require improved characterization of changing conditions. Traditional potentiometric-surface mapping does not use all available water-level data or quantify uncertainty. To address these limitations, we developed a data-driven multiple machine-learning (MML) framework delivered through two open-source R packages. The covMRVAgen1 software assembles covariates to 155,960 monthly groundwater levels from 57,695 wells; the mmlMRVAgen1 software trains Cubist and Random Forest models, blends them, and makes 1-kilometer gridded predictions of monthly potentiometric surfaces for the period January 1980–December 2022. The MML approach provides a methodological foundation for region-scale spatiotemporal groundwater prediction and uncertainty quantification, generating 90-percent prediction limits with appropriate empirical coverage. Model performance is acceptable, with a root-mean-square error of about 4.2 feet, standard deviation of 24.82 feet, and a normalized Nash–Sutcliffe efficiency of 0.973.

Arkansas, Illinois, Louisiana, Mississippi, Missou↗
USGS2025

Rebuilding a volcano one lava flow at a time—Visualizing the lava dome-building eruption in the crater of Mount St. Helens, 1982–1986

Between 1980 and 1986, the U.S. Geological Survey made a series of 1:2,000-scale topographic contour maps from aerial photographic surveys to monitor the eruption. These maps were made for operational purposes and were not intended for publication. Since then, advances in technology made it possible to digitize the original, highly detailed hardcopy maps and derive new digital data elevation models of the surface of the lava dome. These digital elevation models allow for the visualization of the progression of the eruption and reveal the rubbly, chaotic surface of the lava flows and dome. Additionally, these new data help fill gaps in the long-term record of topographic changes that have occurred at the volcano since the May 18, 1980, eruption.

Washington↗
USGS2025

Groundwater flowpath characteristics drive variability in per- and polyfluoroalkyl substances (PFAS) loading across a stream-wetland system

Groundwater-dependent ecosystems in areas with industrial land use are at risk of exposure to a PFAS chemicals. We investigated one such system with several known PFAS source areas, where high and low permeability sediments (glacial) coupled with groundwater-lake and groundwater/surface-water interactions created complex ‘source to seep’ dynamics. Using heat-tracing and chemical methods, numerous preferential groundwater discharge zones were identified and sampled across the upper Quashnet River stream-wetland system in Mashpee, MA, USA, downgradient of Joint Base Cape Cod (JBCC). Surface-water and groundwater samples were analyzed for 40 PFAS compounds between March and October 2022. Samples were collected from groundwater seeps identified as preferential discharge points (PDPs), wells upgradient of the stream-wetland system, contributing flow-through kettle lakes, and along Quashnet River surface-waters. PFAS from sampled waters contained perfluorinated carboxylates (PFPea, PFHxA, PFNA), perfluorinated sulfonates (PFBS, PFPeS, PFHxS, PFOS), fluorotelomer sulfonates (6:2, 8:2 FtS), and perfluoroalkyl sulfonamides (PFOSA). Samples from PDPs and wells had measured PFAS concentrations ranging from non-detect to 4677 ng/L ng/L (mean = 418 ng/L, std. = 709 ng/L), and a range of deuterium excess values (3.2 to 15.9 per mil) indicative of varying degrees of groundwater-lake interaction prior to groundwater flowpath emergence at PDPs. Correlations ( p < 0.01) between deuterium excess, %PFAS precursors, and terminal PFAS compounds highlighted potential precursor transformations associated with lake-groundwater exchange along flowpaths sourcing PDPs. However, some seepages had higher total PFAS concentrations (>1000 ng/L) than upgradient kettle lakes despite showing lake (evaporative) isotopic signatures, indicating the potential for groundwater flowpath convergence at wetland discharge zones and the influence of lakebed PFAS precursor reactions. Results from these synoptic surveys address gaps in the existing PFAS literature by demonstrating the importance of subsurface fate and transport on PFAS compound concentrations and mass loading in preferential groundwater discharge zones.

Massachusetts↗
USGS2026

Distinguishing natural from mining-related metal sources by including streambank groundwater data in a stream mass loading study

Distinguishing stream metal loading caused by mine features from that caused by natural background sources remains challenging, yet this distinction is essential for making effective remedial decisions at many legacy mine sites. We combine a stream tracer injection and synoptic sampling study with data from shallow near-stream groundwater wells to estimate left-bank versus right-bank metal loading contributions at the 100-m spatial scale. The study was performed in the East Mancos River, a mountain headwater stream in Colorado, USA. The dominant source of elevated stream metal concentrations could be either groundwater infiltration through right-bank Doyle Mine waste piles or natural acid rock drainage from hydrothermally altered bedrock located mainly on the left bank. For the five metals of concern (Cu, Al, Zn, Cd, and Mn), we find that 15 % of the load contributed by diffuse groundwater inputs in the section potentially influenced by Doyle mine waste originates from the right bank. This right-bank potential mine contribution equates to only 3 % of the total watershed instream load for these metals. Furthermore, apparent 3 H/ 3 He groundwater ages in segments contributing most of the right-bank metal loading are sufficiently old (9–12 yr) to suggest that infiltration through the waste piles, located only 140–180 m from the stream, is unlikely. Estimated potential Doyle mine loading contributions can therefore be considered maximum values. Study results thus indicate that Doyle mine waste piles are a minor source of metal loading under low-flow conditions, and streambank groundwater data can provide valuable additional information in stream mass loading studies.

Colorado↗
USGS2025

Relationship between peak and cumulative ground motions from 49 Mw 3-6 earthquakes in the San Francisco Bay Area

We examine the relationship between peak ground velocity (PGV) and cumulative absolute displacement (CAD) for 49 M w 3 – 6 earthquakes in the San Francisco Bay Area (SFBA) and gain insight into the spatiotemporal partitioning of seismic energy in ground motion records with respect to source, path, and site effects. PGV and CAD are positively correlated, but there can be large deviations from the average trend. For example, ground motion records with either very long duration resonance or short pulse-like motions will have higher or lower CAD, respectively, but could have very similar PGV. We perform principal component analysis (PCA) on PGV-CAD for >7000 records in the SFBA with the goal of investigating what influences positive or negative anomalies in cumulative motions. PCA rotates the PGV-CAD datapoints into two principal components, where the one with the larger variance, which we call the “primary intensity” represents mostly the distance-dependence of ground motion amplitudes. The other principal component, which we call the “excess motion”, represents the deviation from cumulative motions that would be typical for a ground motion record with a given PGV. The excess motion will be positive in the case of records with long duration ringing and will be negative for short duration pulse-like ground motions. We find that excess motion is generally positive at sites in sedimentary basins and in soft sediments around the SF Bay. Excess motion is generally negative in the very near field, as well as at sites on hard bedrock. We discuss the findings here in terms of implications for seismic hazard applications and other wave propagation phenomena.

California↗
USGS2025

Four-band image mosaic of the Colorado River Corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2021 airborne image acquisition

In May 2021, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center acquired airborne multispectral high-resolution data for the Colorado River in the Grand Canyon, Arizona. The image data, which consist of four spectral bands (red, band 1; green, band 2; blue, band 3; and near infrared, band 4) with a ground resolution of 20 centimeters, are available as 16-bit unsigned-integer GeoTIFF files in Sankey and others (2024) (available online at https://doi.org/10.5066/P9BBGN6G ). The image files are projected in the State Plane Coordinate System, using the central Arizona zone (202) with the North American Datum of 1983 National Adjustment of 2011. The assessed spatial accuracy for these data is based on 47 ground-control points that were independent from the ground-control points used by the contractor for aerotriangulation and is reported at the 95-percent confidence level as 0.514 meter (m) and a root mean square error of 0.297 m. The intended uses of this dataset are primarily in support of scientific research and monitoring applications. Examples of these applications include high-resolution spatial and temporal change detection of the river channel, geomorphic landforms, riparian vegetation, and backwater and nearshore habitat, as well as other ecosystem-wide mapping. These imagery data also serve as reference material for field science mission planning, as base data for field data collection including community science activities, and as a highly detailed guide for technical boat operation during science activities such as reconnaissance for nighttime missions and navigating rapids during low flows.

Arizona, Nevada, Utah↗
USGS2026

Simulation of groundwater flow to evaluate hydrogeologic controls on a PFAS plume, Coakley Landfill Superfund site, Rockingham County, New Hampshire

Per- and polyfluoroalkyl substances (PFAS), including perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), have been detected at combined concentrations above 2,000 nanograms per liter (ng/L) at groundwater seep locations near the Coakley Landfill Superfund site, in North Hampton, New Hampshire. The landfill was active from 1972 to 1985. An impermeable cap was placed on the landfill in 1998. The adjacent area to the Coakley Landfill has many water supply wells, and transport of PFAS compounds to the wells is a concern. Fracture anisotropy in the underlying bedrock aquifer complicates the understanding of PFAS transport because groundwater preferentially travels along fractures that may not align with the prevailing groundwater flow direction. In 2018, the U.S. Environmental Protection Agency and the U.S. Geological Survey began an investigation of the groundwater flow from the Coakley Landfill site. This report describes the modification of a numerical groundwater-flow model for the local area around the Coakley Landfill and summarizes findings of the investigation. In addition, this report includes a brief description of PFOA and PFOS occurrence, a discussion of model construction, evaluation of model performance through calibration, and discussion of simulation results for two periods (before and after capping). Limitations are also discussed. Results show that simulated groundwater flow moves from the Coakley Landfill to the west and north. Advective transport modeling using particle tracking shows that groundwater from the landfill discharges primarily to streams to the west and north, and a small amount is transported to distal wells. Dilution of contaminants through advection and dispersion likely plays a role in whether PFAS compounds from the landfill will be detected above laboratory reporting levels at distal wells.

New Hampshire↗
USGS2024

Mapping the resistivity structure of Walker Ridge 313 in the Gulf of Mexico using the marine CSEM method

A marine controlled source electromagnetic (CSEM) campaign was carried out in the Gulf of Mexico to further develop marine electromagnetic techniques in order to aid the detection and mapping of gas hydrate deposits. Marine CSEM methods are used to obtain an electrical resistivity structure of the subsurface which can indicate the type of substance filling the pore space, such as gas hydrates which are more resistive. Results from the Walker Ridge 313 study (WR 313) are presented in this paper and compared with the Gulf of Mexico Gas Hydrate Joint Industry Project II (JIP2) logging while drilling (LWD) results and available seismic data. The hydrate, known to exist within sheeted sand deposits, is mapped as a resistive region in the two dimensional (2D) CSEM inversion models. This is consistent with the JIP2 LWD resistivity results. CSEM inversions that use seismic horizons provide more realistic results compared to the unconstrained inversions by providing sharp boundaries and architectural control on the location of the resistive and conductive regions in the CSEM model. The seismic horizons include: 1) the base of the gas hydrate stability zone (BGHSZ), 2) the top of salt, and 3) the top and bottom of a fine grained marine mud interval with near vertical hydrate filled fractures, to constrain the CSEM inversion model. The top of salt provides improved location for brines, water saturated salt, and resistive salt. Inversions of the CSEM data map the occurrence of a ‘halo’ of conductive brines above salt. The use of the BGHSZ as a constraint on the inversion helps distinguish between free gas and gas hydrate as well as gas hydrate and water saturated sediments.

Louisiana↗
USGS2024

On algorithmically determined versus traditional macroseismic intensity assignments

The utility of macroseismic data, defined as the effects of earthquakes on humans and the built environment, has been increasingly recognized following the advent of online systems that now produce unprecedented volumes of macroseismic intensity information. Contributed reports from the U.S. Geological Survey “Did You Feel It?” (DYFI) system ( Wald et al ., 1999 ) are used to generate intensity values with an algorithm based on seminal work by Dengler and Dewey (1998) . The algorithm was developed initially to reproduce intensity values assigned by expert opinion using questionnaire results collected by telephone survey. In this article, I discuss reasons why intensity values from (self‐selected) DYFI responses can differ from values that would be assigned by expert opinion given more complete data from randomly selected participants. For example, with the data used by Dengler and Dewey (1998) , intensities near 4 could be determined from the percentage of people who felt shaking in each town. With less spatially rich data from self‐selected participants, this percentage often cannot be determined reliably. Audible noises are key additional diagnostic criteria for modified Mercalli intensity (MMI) 4, but, although the DYFI system includes a question about noise, following Dengler and Dewey (1998) , the DYFI algorithm does not include a noise indicator. At the upper end of the scale, as defined the DYFI algorithm yields a maximum intensity value of 9.05, nominally corresponding to peak ground acceleration of 75% g . These and other factors can result in DYFI values that are low compared to traditional MMI values assigned using expert opinion, even absent factors that can bias traditional MMI assignments. Modern ground‐motion intensity conversion equations determined using DYFI intensities are expected to be appropriate for DYFI intensities, but the results of this study suggest that biases may be introduced if DYFI and traditional intensities are assumed to be interchangeable.

Seismological Research Letters↗
USGS2025

Determination of per- and polyfluoroalkyl substances in water by direct injection of matrix-modified centrifuge supernatant and liquid chromatography/tandem mass spectrometry with isotope dilution

A direct-injection liquid chromatography/tandem mass spectrometry method was developed to determine 34 per- and polyfluoroalkyl substances (PFAS), including selected branched isomers, in centrifuge supernatant of matrix-modified (amended with approximately 50 percent methanol) water samples. The method has been validated in reagent water, surface water, groundwater, and wastewater effluent. Other water types (for example, drinking water, untreated wastewater, and landfill leachate) have been analyzed by the method but not systematically validated. Recovery of isotope-dilution standards, added to each sample, may be used to assess method performance in nonvalidated matrices on a sample-by-sample basis. Using this method, PFAS concentrations were determined in the range of 2–2,000 nanograms per liter in water samples. This range can be extended by diluting concentrated samples. At circumneutral pH, most compounds are present in the environment in their ionized form, and data are reported as such (for example, perfluorooctanoic acid is referred to as “perfluorooctanoate” [PFOA], perfluorooctane sulfonic acid is referred to as “perfluorooctane sulfonate” [PFOS]). Sample preparation procedures were designed without the use of filtration and with minimum sample handling steps to mitigate procedural losses of target compounds due to sorption to surfaces. Further, isotope-dilution quantification allowed for the correction of bias that may result from procedural losses, matrix-induced signal suppression or enhancement, and other factors. Validation experiments to characterize bias and variability, method detection level, and holding time were done in four distinct water matrices—reagent water, surface water, treated wastewater effluent, and groundwater—at multiple concentration levels. Mean PFAS recoveries met data quality objectives of bias and variability studies in all four validation matrices except for two compounds with low and variable recovery in the reagent water matrix only. Isotope-dilution standards, treated as surrogate compounds, were analyzed in more than 1,500 customer-submitted environmental samples with aggregate recovery of 102.5±6.5 percent (mean±standard deviation). Maximum holding times for all target compounds in the four validation matrices were 28 days for refrigerated samples and 90 days for frozen samples.

Techniques and Methods↗
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↗
USGS1986

Regionalization of low-flow characteristics of Tennessee streams

Procedures for estimating 3-day 2-year, 3-day 10-year, 3-day 20-year, and 7-day 10-year low flows at ungaged stream sites in Tennessee are based on surface geology and drainage area size. One set of equations applies to west Tennessee streams, and another set applies to central and east Tennessee streams. The equations do not apply to streams where flow is significantly altered by activities of man. Standard errors of estimate of equations for west Tennessee are 24 to 32% and for central and east Tennessee 31 to 35%. Streamflow recession indexes, in days/log cycle, are used to account for effects of geology of the drainage basin on low flow of streams. The indexes in Tennessee range from 32 days/log cycle for clay and shale to 350 days/log cycle for gravel and sand, indicating different aquifer characteristics of the geologic units that sustain streamflows during periods of no surface runoff. Streamflow recession rate depends primarily on transmissivity and storage characteristics of the aquifers, and the average distance from stream channels to basin divides. Geology and drainage basin size are the most significant variables affecting low flow in Tennessee streams according to regression analyses. (Author 's abstract)

Tennessee↗
USGS2026

Spatial variation in effectiveness and costs of sagebrush restoration treatments across the western United States

Natural resource managers strive to improve restoration efficiency across the vast network of public lands of the United States, seeking the best return on investment through innovation, geographic prioritization, and adaptive management. This challenge is exemplified by ecosystems dominated by sagebrush ( Artemisia spp.), which occur across the western United States and have been degraded by increasing wildfire frequency driven by invasive plant spread, among other factors. However, both costs and effectiveness of sagebrush restoration can vary spatially due to management practices in addition to biotic and abiotic factors, and characterizing this variation could inform broad-scale planning. We leveraged published models of sagebrush recovery and treatment costs to predict and evaluate cost-effectiveness of aerial and drill seeding Artemisia spp. across 429 718 km 2 that overlapped 12 US states. Compared to natural recovery, effectiveness for both methods was generally low, yet effectiveness was often greater, and costs were always greater, for drill than aerial seeding, resulting in slightly higher cost-effectiveness on average for drill seeding. Cost-effectiveness for both treatments increased near major roads and in areas with more repeated burns. Cost-effectiveness also increased with predisturbance cover of sagebrush but decreased with herbaceous cover. However, we also identified areas where aerial seeding was more cost-effective than drill seeding, particularly with greater slope. Our results provide spatially explicit estimates and potential mechanisms of cost-effectiveness for two common seeding methods for sagebrush, which can help prioritize limited resources, guide land use, and improve restoration efficiency and effectiveness across public rangelands of the western United States.

western United States↗
USGS2025

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↗