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USGS2023

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions↗

USGS2026

Integrating habitat suitability and climate constraints to predict nonnative fish invasion risk for U.S. streams and inland lakes

Introduction: Nonnative fishes in streams and inland lakes can substantially alter aquatic ecosystems by degrading habitat conditions, competing with native species, and restructuring food webs. Identifying invasion hotspots can inform proactive management and prevention of nonnative species establishment. Methods: In this study, we identified streams and lakes across the conterminous United States that are vulnerable to invasion by 18 nonnative stream and 28 nonnative lake fish species. Habitat suitability models were developed separately for stream and lake species across nine ecoregions using natural and anthropogenic predictors, and species occurrences were predicted by integrating model results with climate match scores based on comparisons between environmental conditions in species’ native and potential nonnative ranges. We classified areas with both high habitat suitability and strong climate similarity as having high invasion potential and generated hotspot maps by stacking species-level predictions. Results: Florida exhibits the highest invasion risk for both habitat types. Stream hotspots were concentrated near major metropolitan areas, whereas lake hotspots were more widely distributed across the Great Lakes basin and the northeastern U.S. Twelve species were predicted to invade both habitat types, with goldfish ( Carassius auratus ) and pirapitinga ( Piaractus brachypomus ) showing particularly high invasion potential. Discussion: These findings provide a comprehensive assessment of nonnative freshwater fish invasion risk and support targeted monitoring and management strategies.

conterminous United States↗

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↗

USGS2026

A temporal look at the influence of topographic amplification on earthquake-triggered landslides in 3D seismic simulations

Earthquakes are a primary trigger for landslides, often leading to catastrophic consequences. While numerous studies have explored the spatial distribution of earthquake-triggered landslides, understanding the interaction between seismic waves and topography remains a critical challenge. Topographic irregularities can cause seismic wave amplification, altering ground shaking, and can trigger landslides that are challenging for predictive models to anticipate. This study investigates the spatial and temporal evolution of topographically amplified landslides, focusing on coseismic landslides triggered by the Mw 7.5 mainshock of the 2018 Papua New Guinea earthquake and post-seismic landslides associated with its four aftershocks, each exceeding Mw 6.0. We employ low-frequency, three-dimensional numerical ground shaking simulations and data-driven multivariate analyses to examine how landslides evolved from the coseismic to post-seismic periods. Our findings reveal a spatial shift in landslide distribution, in which the mainshock triggered slope failures predominantly on steep hillslopes, and the aftershocks triggered landslides on gentler slopes, often near geologic boundaries. We attribute this transition partly to the earthquake legacy effect of the mainshock, where the mainshock caused weakening of these hillslopes, making them more prone to failure when aftershocks occur. Additionally, the concentration of failures along geologic contacts in the post-seismic phase suggests that site amplification, stemming from contrasts in subsurface materials, exerts a key influence on landslide occurrence. Although not explicitly captured in our current numerical simulations, this mechanism warrants further investigation for more accurate hazard modeling.

JGR Solid Earth↗

USGS2025

Dendroseismological investigation of redwood trees along the North Coast section of the San Andreas Fault

Sequoia sempervirens (coast redwood) tree rings have the potential to annually resolve late-Holocene earthquakes on the northern San Andreas Fault based on direct (e.g., physical damage) and indirect (e.g., co-seismic environmental change) impacts, but scarcity of suitable samples and challenges crossdating this long-lived species have limited progress. More precise dating of the pre-1906 (penultimate) earthquake can improve hazard assessment and understanding of rupture segmentation. We target old trees (maximum >815 yr) along the North Coast section of the fault (increment cores via rope-climbing, 11 living trees; plunge cuts, 23 stumps) and employ complementary disturbance detection methods including radial-growth averaging (tree- and series-level), cataloging anatomical indicators (e.g., traumatic resin ducts, TRD), and dating structural components (e.g., reiterated trunks, leans). Multi-centennial ring-width chronologies at Fort Ross (1569−2023) and Gualala (1397−2023) promote continued study with incomplete crossdating limiting utilization of some series. Growth pulses (reductions, releases) and TRD dispersed across the record reflect dynamic environments that obfuscate detection of earthquake signals. The 1906 earthquake did not leave strong signatures on most trees, and when it did, within-tree response varied from normal presentation to discoloration, TRD, and missing rings. Synchrony of indicators at both locations identified 1678−1680 (6 of 15 trees) and 1698−1700 (8 of 16 trees) as the strongest disturbances among dated rings in the time range of the penultimate earthquake, peaking at 1698 (15.7 % of possible growth and anatomical indicators), but the triggering mechanisms for these events are unknown.

California↗

USGS2026

Earthquake ground-motion model adjustments for the San Francisco Bay area

We develop adjustments to ergodic ground‐motion models (GMMs) to improve their performance in the San Francisco Bay Area (SFBA). GMMs are widely used in hazard assessments to estimate characteristics of ground shaking based on known properties of the source, path, and site. Such models are often developed using datasets containing records from various regions, resulting in models that represent median ground‐motion behavior, which may not adequately represent ground motions within subregions. This is true for the SFBA, where ground motions attenuate more rapidly with distance than in many other parts of California that dominate GMM databases. To support improved seismic hazard estimates in the SFBA, we calculate regional constants and anelastic attenuation coefficient adjustments relative to two commonly used ergodic GMMs: BSSA14 ( Boore et al. , 2014 ) and ASK14 ( Abrahamson et al. , 2014 ). These adjustments are obtained for a suite of ground‐motion intensity measures (peak ground acceleration, peak ground velocity, and 5%‐damped pseudospectral acceleration at oscillator periods ranging from 0.075 to 10 s) using mixed‐effects regression. Use of the regionally adjusted models reduces the overall bias by up to 0.5 natural log units for BSSA14 and up to 0.6 natural log units for ASK14. We demonstrate one application of our attenuation adjustments and their implications in an earthquake early warning case study of the 2014 M 6.0 South Napa earthquake. The predicted extent of shaking using the adjusted models better matches observed shaking at large source‐to‐site distances, especially for lower shaking intensities, thus potentially reducing overalerting. We encourage the use of our model adjustments when ergodic models are considered for seismic hazard studies in the SFBA.

California↗

USGS2025

Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record

Large surface-rupturing intraplate earthquakes in stable continental regions (SCRs) are uncommon globally and have recurrence intervals of thousands to hundreds of thousands of years based on the paleoseismic and geomorphic record, challenging accurate active fault identification in these regions. To constrain the timescales of preservation for scarps created by surface ruptures from dip-slip earthquakes, we use a two-dimensional scarp diffusion model for typical intraplate settings and explore which parameters influence fault scarp preservation. These parameters include the coseismic vertical surface offset, the recurrence interval of similar magnitude earthquakes, diffusivity (as a proxy for mean annual precipitation rate), and the erodibility of the surficial material. We constrain parameter ranges from a compilation of historical surface ruptures in intraplate settings in a variety of climates, including the Central and Eastern United States, Australia, Europe, Central Asia (Mongolia, China), India, and West Africa. The timescales of scarp preservation from landscape evolution modeling agree well with observations of scarp preservation in low-strain SCR and intraplate tectonic settings, with some notable exceptions for Australian scarps. We find that the erodibility of the surficial material and earthquake recurrence interval have a stronger effect on the timescales of scarp preservation than diffusivity or coseismic vertical surface offset. Our model results may aid in identifying and characterizing subtle, slow-moving active faults in low-strain SCR and intraplate tectonic settings for different tectonic, geomorphic, and climatic characteristics. Accurate fault locations and characterization from the landscape record has implications for both probabilistic seismic and fault displacement hazard analyses.

Journal of Geophysical Research Solid Earth↗

USGS2024

Testing megathrust rupture models using tsunami deposits

The 26 January 1700 CE Cascadia subduction zone earthquake ruptured much of the plate boundary and generated a tsunami that deposited sand in coastal marshes from northern California to Vancouver Island. Although the depositional record of tsunami inundation is extensive in some of these marshes, few sites have been investigated in enough detail to map the inland extent of sand deposition and depict variability in tsunami deposit thickness and grain size. We collected 129 cores in marshes of the Salmon River estuary in Oregon and reanalyzed 114 core logs from a 1987–88 study that mapped the inland extent of circa 1700 CE sandy tsunami deposits. The ca. 1700 CE tsunami deposit in the Salmon River estuary is easily recognized in cores ≤1 m deep in which a buried marsh peat is overlain by a well sorted sand bed with a sharp lower contact that thins and fines inland. We use tsunami deposit data and models of sandy tsunami sediment transport (using Delft3D-FLOW) to test 15 rupture models that could represent a ca. 1700 CE earthquake. At least 12–16 m of slip offshore of the Salmon River, which results in 0.8–1.0 m of coastal coseismic subsidence, is required to match the ca. 1700 CE sand deposit's inland extent, which is consistent with models of heterogeneous megathrust slip in ca. 1700 CE. Our methods of detailed tsunami deposit mapping, combined with sediment transport modeling, can be used to test models of megathrust ruptures and their tsunamis to potentially improve earthquake and tsunami hazard assessments.

JGR Earth Surface↗

USGS2025

Multi-scale geophysical imaging of a hydrothermal system in Yellowstone National Park, USA

Little is known about the local plumbing systems that fuel Yellowstone’s famous hot springs, geysers and mud pots. A multi-method, multi-scale geophysical investigation was carried out in the Obsidian Pool Thermal Area (OPTA) to: (i) delineate the lateral extent of the hydrothermal area and associated surface features; (ii) estimate the dimensions of the upflow zone and identify its main controlling structures; (iii) assess fluids circulation pathways from depth to surface. Ground and airborne geophysical data were acquired to connect local and regional scales, from shallow to large depths. Maps of surface electrical resistivity show a strong correlation with hydrothermal features. At in-termediate depths, electrical resistivity permits delineating the upper limit of the upflow zone, while Poisson’s ratio highlights differences in subsurface fluid content. Combining these results with surface observations and topographic information, we speculate that differential mixing of hydrothermal and fresh water could explain the wide diversity of features observed at OPTA. Low electrical resistivity observed at large depths also suggest that a vast upflow zone, controlled by rhyolite flows and conjugate faults, underlies the OPTA. We speculate that hydrothermal fluids rise along fractures and reach the surface in topographic lows to form hydrothermal features. Our results show that synoptic, multi-scale geophysical measurements provide a roadmap for understanding where and how geologic heterogeneity, topography, fluid-gas separation, and the mixing of thermal and meteoric waters conspire to produce the wide variety of Yellowstone’s renowned hydrothermal features.

Wyoming↗

USGS2026

The use of fluorite geochemistry and machine learning to identify critical mineral systems

Fluorite (CaF 2 ) is a potential pathfinder to critical mineral and rare earth element (REE) deposits but its application has been limited to a narrow range of mineralization types. I show that fluorite is a robust recorder of mineralization fertility by applying statistical and machine-learning methods to a new global fluorite geochemical database. Distinct median rare earth and trace element patterns are observed among deposit types and genetic environments. Fluorite associated with carbonatites and REE deposits are relatively enriched in Sr and have minimal Eu anomalies. These characteristics define new bivariate discrimination diagrams that correctly identify 78% of carbonatite-related fluorite and 88% of fluorite from REE deposits. Random forest classifiers were developed for a wide range of mineralization types and genetic settings. Trained solely on rare earth element patterns, these models achieve accuracies of 77–79%. Higher classification accuracies (up to 88–96%) are obtained when including elements such as Sr, highlighting the significance of trace elements for optimal fluorite classification. The recognition of diagnostic fluorite compositional fingerprints, particularly in REE-fertile systems, underscores its potential as a pathfinder and indicator for critical mineral exploration in F-bearing environments.

Mineralium Deposita↗

USGS2024

Factors contributing to pesticide contamination in riverine systems: The role of wastewater and landscape sources

Wastewater treatment plant (WWTP) discharges can be a source of organic contaminants, including pesticides, to rivers. An integrated model was developed for the Potomac River watershed (PRW) to determine the amount of accumulated wastewater percentage of streamflow (ACCWW) and calculate predicted environmental concentrations (PECs) for 14 pesticides in non-tidal National Hydrography Dataset Plus Version 2.1 stream segments. Predicted environmental concentrations were compared to measured environmental concentrations (MECs) from 32 stream sites that represented a range of ACCWW and land use to evaluate model performance and to assess possible non-WWTP loading sources. Statistical agreement between PECs and MECs was strongest for insecticides, followed by fungicides and herbicides. Principal component analysis utilizing optical fluorescence and ancillary water quality data identified wastewater and urban runoff sources. Pesticides that indicated relatively larger sources from WWTPs included dinotefuran, fipronil, carbendazim, thiabendazole, and prometon whereas imidacloprid, azoxystrobin, propiconazole, tebuconazole, and diuron were more related to urban runoff. In addition, PECs generally comprised a low proportion of MECs, which indicates possible dominant loading sources beyond WWTP discharges. Cumulative potential toxicity was higher for sites with greater ACCWW and/or located in developed areas. Imidacloprid, fipronil, and carbendazim accounted for the largest portion of predicted potential toxicity across sites. The chronic aquatic life toxicity benchmarks for freshwater invertebrates were exceeded for 82 % of the imidacloprid detections ( n = 28) and 47 % of the fipronil detections ( n = 19). These results highlight the ecological implications of pesticide contamination from WWTP discharges and also the potential legacy effects from accumulated soil and groundwater sources. Pesticide management strategies that mitigate both current and historical impacts may improve the health of aquatic ecosystems.

Potomac River watershed↗

USGS2025

Emerging investigator series: Post-wildfire sediment geochemical characterization reveals manganese reactivity and a potential link to water quality impairment in the Gallinas Creek watershed, New Mexico

Water quality post-wildfire is often impaired by increased turbidity and elevated concentrations of elements such as manganese (Mn) and iron (Fe). Precipitation events exacerbate these issues, due in part to increased erosion and transport of sediment from hillslopes to surface water. Both Mn and Fe are major redox-active elements in sediments that drive a variety of biogeochemical cycles, precipitate adsorptive phases, and can themselves be drinking water contaminants. By investigating Mn and Fe sediment geochemistry in post-wildfire sediment deposits, related water quality hazards can be assessed. To establish and strengthen this connection, we analyzed the geochemistry of sediment deposits and surface water in the Gallinas Creek watershed, New Mexico over 1.5 years post-wildfire. Analyses included particle size analysis, water extractions, sequential extractions and aqua regia extractions to determine metal partitioning in sediment deposits. Data demonstrate Mn concentrations were distributed across labile and reactive fractions, such as the exchangeable and oxyhydroxide fractions, while Fe concentrations were mainly associated with the residual fraction. Manganese concentrations in aqua regia extractions and several fractions of sequential extractions were also strongly and significantly correlated with fine-grained sediment while the same pools of Fe concentrations were not. Dissolved Mn concentrations in surface water were elevated (>50 μg L −1 ) multiple times over the 1.5 years post-wildfire, highlighting a relationship between sediment geochemistry and water quality. This work shows Mn in sediments mobilized post-wildfire has an influence on water quality and highlights how further investigation into Mn sediment redox processes and mineralogy post-wildfire can inform risk assessments and resource management.

New Mexico↗

USGS2026

Channel morphology and large wood control postfire debris-flow erosion and deposition

Runoff-generated debris flows are a known response to wildfire, and accurately predicting the volume of these debris flows is important for estimating the magnitude of downstream hazards. Prior data collection efforts have focused on debris-flow volume measurements at catchment outlets, but few studies have considered how erosion and deposition modulate the volume of sediment arriving at catchment outlets. This study takes advantage of a high-resolution dataset to document the factors that control the total debris-flow volume reaching the catchment outlet during a fatal postfire debris flow. Using pre- and post-event airborne lidar, satellite imagery and field mapping, we found that a postfire debris flow in the Black Hollow catchment in northern Colorado eroded 136,000 ± 30,000 m 3 and redeposited 27,000 ± 7,500 m 3 in the main channel. Most of the in-channel deposition (52% by volume) occurred where a confined channel reach transitioned to an unconfined channel reach downstream, allowing the flow to widen and deposit material. Wood jams played multiple roles in the debris-flow dynamics, both nucleating deposition (25% of the deposit volume was stored behind wood jams) and exacerbating erosion (50% of the total erosion occurred downstream from a wood dam break). The remaining deposition occurred due to spatial changes in channel slope as well as deposition observed at newly formed channel bars. Using these data in this study, we identified topographic and vegetation metrics that can be used (pre-event) to anticipate where deposition may occur in channels prior to a debris flow.

Colorado↗

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↗

USGS2025

Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system

Uranium (U) in rocks and soils of arid and semi-arid environments can be mobilized by irrigation and fertilization, posing environmental and health risks. Elevated U, along with selenium (Se) and nitrate (NO 3 ) co-constituents, necessitates careful monitoring and management. We developed a distributed-parameter numerical model to assess U pollution in an irrigated stream-aquifer system, applying it to a 552 km 2 region in Colorado's Lower Arkansas River Valley (LARV) over 14 years. A MODFLOW model, describing groundwater and stream flow, was coupled with an RT3D-OTIS model to portray reactive U transport. Calibration using the PESTPP-iES iterative ensemble smoother (iES) software indicated good agreement with observed U concentrations. The model revealed substantial and variable U levels across the LARV, highlighting potential hotspots and possible contributing factors, such as geological composition of the bedrock and near-surface shale and aquifer sediments derived from them, irrigation practices, and riparian landscape. U levels exceed the chronic standard (85th percentile = 30 μg/L, set by the US Environmental Protection Agency), which is the permissible regulatory threshold, in groundwater across 44 % of the region and along the river by an average factor of 2.9. Simulated average U concentrations in the non-riparian aquifer and river are 124 μg/L and 60 μg/L, respectively, compared with 112 μg/L and 62 μg/L for measured values. The average 85th percentile U concentration is 222 μg/L in the aquifer and 82 μg/L in the river. Average simulated U mass loading to the river is 0.17 kg/day per km, compared to an estimated 0.23 kg/day per km. Findings provide a baseline for comparing future simulated outcomes of alternative best management practices (BMPs) for U pollution mitigation and offer a methodology applicable to other irrigated regions.

Colorado↗

USGS2024

Anaerobic biodegradation of perfluorooctane sulfonate (PFOS) and microbial community composition in soil amended with a dechlorinating culture and chlorinated solvents

Perfluorooctane sulfonate (PFOS), one of the most frequently detected per - and polyfluoroalkyl substances (PFAS) occurring in soil, surface water, and groundwater near sites contaminated with aqueous film-forming foam (AFFF), has proven to be recalcitrant to many destructive remedies, including chemical oxidation. We investigated the potential to utilize microbially mediated reduction (bioreduction) to degrade PFOS and other PFAS through addition of a known dehalogenating culture, WBC-2, to soil obtained from an AFFF-contaminated site. A substantial decrease in total mass of PFOS (soil and water) was observed in microcosms amended with WBC-2 and chlorinated volatile organic compound (cVOC) co-contaminants — 46.4 ± 11.0 % removal of PFOS over the 45-day experiment. In contrast, perfluorooctanoate (PFOA) and 6:2 fluorotelomer sulfonate (6:2 FTS) concentrations did not decrease in the same microcosms. The low or non-detectable concentrations of potential metabolites in full PFAS analyses, including after application of the total oxidizable precursor assay, indicated that defluorination occurred to non-fluorinated compounds or ultrashort-chain PFAS. Nevertheless, additional research on the metabolites and degradation pathways is needed. Population abundances of known dehalorespirers did not change with PFOS removal during the experiment, making their association with PFOS removal unclear. An increased abundance of sulfate reducers in the genus Desulfosporosinus (Firmicutes) and Sulfurospirillum (Campilobacterota) was observed with PFOS removal, most likely linked to initiation of biodegradation by desulfonation. These results have important implications for development of in situ bioremediation methods for PFAS and advancing knowledge of natural attenuation processes.

Science of the Total Environment↗

USGS2026

Suitability of ground-motion models for seismic hazard assessment in Puerto Rico and the U.S. Virgin Islands

We perform linear mixed-effects analyses with a ground-motion dataset to evaluate how well ground-motion models (GMMs) fit active crustal, subduction interface, and subduction intraslab earthquakes in Puerto Rico and the US Virgin Islands. Most of the GMMs reproduce the spatial variation in peak ground motions with earthquake magnitude and rupture distance but predict ground motions 0.3–1.0 natural log units (35%–270%) greater than observations. Two GMMs developed for Puerto Rico that are based on ground-motion records from mostly magnitude 4–5 earthquakes do not perform as well. We attribute the period-dependent overprediction in observed ground motions to differences between the observed site response and the linear site response in the GMMs. Consequently, we developed region-specific GMMs by adjusting the period-dependent linear site response coefficients and period-dependent constant coefficients to remove most of the bias between predicted ground motions and observations. For the analysis, we compile ground-motion records and process waveforms to build a dataset with 10,127 records at 72 stations from 849 magnitude 4.0–6.4 earthquakes between 1 January 2006 and 31 March 2024. The earthquakes include active crustal, subduction interface, and subduction intraslab events. We evaluate the GMMs using the time-averaged shear wave speed in the top 30 m ( ), which we compile from site surveys and proxy values computed from horizontal to vertical spectral ratios. Site terms exhibit strong consistency across GMMs and crustal and subduction earthquakes, indicating that the linear mixed-effects analysis successfully isolates the effects of local site response. The event terms show little spatial correlation and more substantial variability than in other regions, which we attribute to uncertainties in the earthquake magnitudes. This analysis guides the selection of the GMMs for the 2025 update of the National Seismic Hazard Model for Puerto Rico and the US Virgin Islands.

Puerto Rico, U.S. Virgin Islands↗

USGS2021

Remote sensing-based actual evapotranspiration assessment in a data-scarce area of Brazil: A case study of the Urucuia Aquifer System

The large groundwater reserves of the Urucuia Aquifer System (UAS) enabled agricultural development and economic growth in the western Bahia State, in northeastern Brazil. Over the last several years, concern has grown around the aquifer’s diminishing water levels, and water balance (WB) studies are in demand. Considering the lack of measured actual evapotranspiration (ET a ), a major component of the water cycle, this work uses the Operational Simplified Surface Energy Balance (SSEBop) model to estimate ET a , and compares it to basin-scale estimates from the Soil Moisture Accounting Procedure (SMAP) monthly model and from an annual WB closure method, based on gridded meteorological data and the Gravity Recovery and Climate Experiment (GRACE) product. Additionally, a comparative assessment of different versions of the SSEBop parameterization was performed. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery was used to implement eight different versions of the SSEBop algorithm over the UAS between 2000 and 2013. SSEBop and SMAP ET a yielded similar seasonal patterns, with correlation coefficient (r) up to 0.65, mean difference (MD) of 0.8 mm/month and mean absolute difference (MAD) of 18.5 mm/month. Comparison of SSEBop annual ET a estimates to annual SMAP and WB closure estimates yielded low MD (12.1 and −7.3 mm/year, respectively) and MAD (82.5 and 82.8 mm/year, respectively), but also low r values (0.00 and 0.37, respectively). The comparison of the different SSEBop versions indicated the need to incorporate a calibration step of the aerodynamic heat resistance (r ah ) parameter. SSEBop results were also used for land cover and drought monitoring. Analysis indicates that agriculture, associated with an increasing trend of atmospheric evaporative demand, is responsible for the decrease in groundwater levels and streamflow in the studied time period.

Urucuia Aquifer System↗