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1,663 records · Page 88Linked to original sources

Rapid earthquake magnitude classification via P-wave strains from borehole strainmeters and Distributed Acoustic Sensing

Distributed Acoustic Sensing (DAS) offers a promising approach for earthquake early warning (EEW) in settings where seismic networks are costly to maintain. By repurposing fiber-optic cables as dense strainmeter arrays, DAS enables real-time earthquake detection wherever those fibers are accessible. However, poor azimuthal coverage and challenges in estimating magnitude from strain measurements remain key hurdles in applying for earthquake monitoring. Here, we develop a machine learning method to distinguish large (M≥5.4) earthquakes from smaller ones within the first 4 seconds of a strain waveform after a P-wave arrival without determining location. Using ensemble decision tree models trained on borehole strainmeter data (3.5≤M≤7.1) and tested on onshore DAS waveforms (including the 2024 M7 Offshore Cape Mendocino earthquake), we find that low-frequency (0.2–0.5 Hz) continuous wavelet transform coefficients are the strongest predictors of magnitude, in addition to strain amplitude. Both DAS and borehole strainmeters effectively capture long-period strain signals, making these findings valuable for EEW systems. Our method shows high precision compared to the real-time EEW system, ShakeAlert®, supporting the position that DAS is a viable technology for earthquake monitoring and magnitude classification.

California

Turbidite correlation for paleoseismology

Marine turbidite paleoseismology relies on the assumption of synchronous triggering of turbidity currents by earthquake shaking to infer rupture extent and recurrence. Such inference commonly depends on age dating and correlation of the physical stratigraphy of deposits carried by turbidity currents (i.e., turbidites) across great distances. Along the Cascadia subduction zone, which lies offshore the Pacific Northwest, USA, turbidite facies in core photographs, X-ray computed tomography images, and magnetic susceptibility (MS) data exhibit differences in character over relatively short distances, which implies that not all deposits can be correlated with confidence. Thus, subjective correlation based on expected similarity over great distances and weak age constraints does not independently support paleoseismic models. We present a new method for correlating turbidites along the Cascadia margin that can yield a more objective and repeatable stratigraphic framework to underpin earthquake recurrence. We use dynamic time warping to correlate MS logs and measure correlation coefficients of core pairs to evaluate correlation strength. We then compare these measures to a distribution of correlation coefficients of randomly generated turbidite sequences and find that only a small number of core pairs can be correlated more confidently than randomly stacked turbidites. This methodology promises a more robust correlation strategy for future stratigraphic studies.

Oregon, Washington

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation

Using a time-of-travel sampling approach to quantify per- and polyfluoroalkyl substances (PFAS) stream loading and source inputs in a mixed-source, urban catchment

Understanding per- and polyfluoroalkyl substances (PFAS) mass distribution in surface and groundwater systems can support source prioritization, load reduction, and water management. Thirteen sites within an urban catchment were sampled utilizing a time-of-travel sampling approach to minimize the influence of subdaily fluctuations in mass from PFAS point sources and to quantify PFAS and ancillary chemical loads from various PFAS sources. A larger increase in perfluoroalkyl sulfonate (PFSA) loads (8 to 11 μg/s, up to 618%) than in perfluoroalkyl carboxylate (PFCA) loads (no change to 3.4 μg/s, up to 122%) was observed at sites below tributaries influenced by military bases with known groundwater discharge. Point discharges from two sewage treatment plants (STPs) resulted in increases in PFCA and PFSA loads that were similar (6 and 10 μg/s respectively) below the first STP and greater for PFCA compared to PFSA loads (23 and 13 μg/s respectively) below the second STP. Overall, percent increases in total PFAS load ranged from 20 to 277% for military base inputs and 44 to 77% for STP inputs. A focus catchment that represents only 14% (76.9 km 2 ) of the drainage area at the most downstream site (544 km 2 ) accounted for about 70% of PFSA and 40% of PFCA loads observed at the most downstream site. Results show that by using a time-of-travel sampling approach in mixed, urban settings with several PFAS sources, it is possible to quantify stream loads from individual PFAS sources, thereby improving source attribution and providing actionable data for water-resource managers.

ACS ES&T Water

Assessment of density pattern retention of generalized data for 1:100,000-scale United States topographic maps

Cartographic generalization reduces the complexity of geographic data to produce legible, smaller-scale displays that retain essential information and logical geographic patterns. Generalization is a vital process in topographic map production. An important challenge in this process is managing and evaluating consistency across scale in the density and spatial distribution of map features such as buildings, roads, streams, water bodies, and elevation contours. Density patterns in these features reflect underlying physiographic conditions, which include factors such as bedrock geology, tectonics, climate, and landforms. Assessments of an acceptable level of change in feature density patterns are critical to ensuring the readability, usability, and accuracy of generalized maps and data. Preserving realistic density patterns across mapping scales also supports sustainable development goals in cartography, by helping to prioritize and communicate the relative reliability of geospatial data at specific scales.

Conference Paper

Smectite-rich horizons in Inceptisols trigger shallow landslides in tropical granitic terranes

Puerto Rico was affected by >70,000 landslides in the wake of 2017 Hurricane Maria, and landslide prevalence was especially high in the Utuado region in the Cordillera Central. Landslide density was highest where soil parent material is granodiorite; landslide slip surfaces tended to be shallow (<60 cm), and often were mobilized rapidly and with long runout distances. This study combines field observations with soil mineralogy (bulk and clay fractions), soil geochemistry (bulk fraction), and soil strength as determined by field cone penetrometer testing (CPT) to test the hypothesis that clay-rich subsoil horizons function as slip planes when water-logged. Soil pits were excavated to depths of ∼200 cm in Ultisols on an undulating plateau and to ∼100 cm in Inceptisols on steep slopes (36-43 o ) that flank the plateau and cone penetrometer tests (CPT) were done within 2 m of the soil pit. Six pits were located adjacent to scarps from previous landslides, enabling analysis of soil profiles downward through extrapolated slip surfaces. Results from X-ray diffraction (XRD), X-ray fluorescence (XRF) and thermogravimetric analysis (TGA) indicate that soils are heterogeneous, often with subsoil horizons enriched in clay minerals and immobile elements (Al, Fe, Ti). Inceptisols on steep slopes often contain smectite-rich horizons at 30–60 cm depth that appear to function as slip surfaces; in other Inceptisols, such horizons are not present and landslide susceptibility is potentially lower. In Ultisols, soil mineralogy is dominated by kaolinite with minor halloysite, and increased kaolinite content at soil depths ≥80 cm at some sites suggests potential slip surfaces enhancing probability of landslides. The origin of clay-rich horizons appears to be (1) fractures in granodiorite that facilitate water flow and leaching, accelerating mineral dissolution during early weathering stages, and (2) smectite-rich buried soils under permeable colluvium likely deposited by a prior mass wasting event. Where clay-rich layers occur beneath more-permeable horizons, rapid infiltration then absorption of water in clay-rich subsoil horizons causes decreased shear strength and increased landslide susceptibility.

Puerto Rico

Land-based nutrient flux to a fringing reef: Insights from Ofu Island, American Samoa

Submarine groundwater discharge (SGD) is a critical driver of nutrient transport in coral reef ecosystems, shaping water quality, primary productivity, and overall reef health. This study quantifies SGD fluxes and associated nutrient dynamics in two reef flat pools within the Ofu Unit of the National Park of American Samoa: Papaloloa and Fatuana. A multi-method approach integrating unoccupied aerial system-based thermal infrared (UAS-TIR) surveys, radon-based SGD measurements, multichannel electrical resistivity tomography (ERT), and discrete water sampling was used to assess SGD rates and nutrient contributions. UAS-TIR imagery revealed cooler sea surface temperatures in both pools, indicative of SGD, with the higher fluxes observed in Papaloloa. Radon measurements revealed a strong inverse correlation between SGD rates and tidal stage, with a more immediate SGD response at Papaloloa due to its highly permeable calcareous sand and gravel substrate. In contrast, a 2–3-hour lag in SGD response at Fatuana suggests discharge from a more inland aquifer that has lower diffusivity. Nutrient concentrations correlated with temperature and salinity, confirming SGD as the dominant nutrient transport mechanism, whereas isotopic analyses indicated inputs from both groundwater and potential anthropogenic sources. Despite lower SGD flux at Fatuana, higher algal cover suggests additional factors influencing algal proliferation, including substrate availability and hydrodynamic conditions. Excess nutrient inputs from SGD may contribute to algal overgrowth, which threatens Ofu’s thermally tolerant corals by increasing competition for space and light. These findings underscore the complexity of SGD-mediated nutrient dynamics in reef environments and emphasize the need for integrated hydrological and ecological assessments to support effective reef conservation and management strategies.

American Samoa, Ofu Island, Olosega Island

Decadal shifts in groundwater age detected by environmental tracers across California, USA

Groundwater age offers important insight into recharge, storage, and contamination risk. Although models predict age changes can be driven by pumping and climate variability, direct observational evidence remains limited. Here, we analyzed paired environmental tracer suites (tritium, carbon-14, and tritiogenic helium-3) collected a decade apart from 268 wells across California to assess the prevalence of groundwater age transience. Travel-time distribution models and statistical tests indicated age transience at 29% of sites, occurring most often in agricultural regions, such as the San Joaquin Valley and Southern Coast Ranges, where large carbon-14 changes coincided with substantial nitrate and chloride shifts. Sites with tritiogenic helium-3 data showed more frequent age transience, underscoring the value of multi-tracer data sets. These results provide the first regional evidence of widespread groundwater age change and a method for detecting changing water balances with implications for groundwater sustainability and water quality.

California

Critical review of mercury methylation and methylmercury demethylation rate constants in aquatic sediments for biogeochemical modeling

Mercury is a toxin that causes neurological impairments in adults, is particularly harmful for fetuses and children, and is deadly in severe cases, making it a worldwide health concern. Methylmercury (MeHg) is the environmentally relevant form of mercury (Hg) because it biomagnifies along the food chain. Methylmercury is mainly produced in aquatic sediments via methylation of inorganic Hg (Hg(II)) and transformed back via demethylation. Because transformation rates determine MeHg concentrations, quantification of methylation and demethylation rates is needed to inform management of MeHg. Published rate constants for Hg(II) methylation ( 𝑘 𝑚 ) and MeHg demethylation ( 𝑘 𝑑 ) vary greatly, stemming partly from differences in experimental methods. We conducted a comprehensive review of rate laws, evaluated published rate constants, and performed biogeochemical simulations to assess variability in reported 𝑘 𝑚 and 𝑘 𝑑 . Based on selected studies employing the same pseudo-first-order rate law and similar experimental methods, we found that 𝑘 𝑚 = 0.04 ± 0.03 d −1 is a reasonable range for wetland sediments. Over a number of environments, maximum 𝑘 𝑑 was smaller at sites without Hg source ( 𝑘 𝑑 = 0.5 d −1 ) than at sites with identified Hg source ( 𝑘 𝑑 = 1.8 d −1 ). Larger variability and higher uncertainty in 𝑘 𝑑 compared to 𝑘 𝑚 highlight the need for more research on MeHg demethylation rates. This critical review: (a) aids the design of future experimental studies of 𝑘 𝑚 and 𝑘 𝑑 ; (b) provides guidance for comparing rate constants from different studies; (c) presents a biogeochemical reaction model to assess rate constants; and (d) informs selection of 𝑘 𝑚 and 𝑘 𝑑 values from the literature for use in model simulations.

Critical Reviews in Environmental Science and Tech

Satellite time series analysis to quantify changing climax ciénegas using a state and transition model approach

Ciénegas are rare wetlands in arid landscapes of the North American Southwest, historically providing critical ecological and hydrological functions but increasingly threatened by changing climate and land use pressures. This study quantifies changes in ciénega condition and floodplain dynamics using a state-and-transition model (STM) informed by expert knowledge and remote sensing. Key factors include woody plant encroachment, water availability, and soil aggradation. We mapped 31 ciénegas with high-resolution imagery and analyzed Landsat data (1985–2023) to assess vegetation health and moisture using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII). Results show substantial interannual variability in phenology, water stress, and soil moisture, with regional drying and elevation strongly influencing ciénega resilience. We classified ciénegas into three functional states—healthy, desiccated, and dormant—and mapped their 2023 condition. Trend analyses indicate most ciénegas exhibit greening despite drought, though localized variability underscores the need for site-specific management. None are in a stable climax (reference) state; rather, they transition among states in response to external drivers. Increasing woody plant cover and surface drying, likely linked to declining regional water tables, favor deep-rooted species over wetland grasses—a pattern mirrored in adjacent control plots. Spatially explicit analysis revealed intra-ciénega variability often masked by aggregated data, highlighting the importance of high-resolution monitoring. Seasonal and long-term trends provide context for understanding ciénega dynamics, including degradation and restoration pathways. This study emphasizes the importance of groundwater conservation and demonstrates how remote sensing supports long-term monitoring. The STM framework offers a practical tool for adaptive management to sustain freshwater resources in arid environments.

Arizona, New Mexico

Compositional and structural mapping of Northwest Africa 15507 angrite

Angrite meteorites represent interesting sampling of planetary crustal environments. Quench-textured angrites with strong crystal zoning originated from the shallow surface region, with evidence of reducing conditions during solidification. Plutonic angrites have more coarse-grained igneous and metamorphic textures with comparatively less zoning and are interpreted as having equilibrated at greater depth. Plutonic angrites contain the minerals magnetite Fe 3 O 4 comprised of Fe 2+ and Fe 3+ , and rhönite, where Fe 3+ is required by inspection of mineral stoichiometry. NWA 15507 is a plutonic angrite with a microgabbroic texture (mean grainsize ∼1.4 mm) composed of zoned Al-Ti-augite, Ca-bearing olivine, anorthite, with accessory kirschsteinite, rhönite, hercynite, low-Ni kamacite, merrillite, Ti-free magnetite and troilite [ 1 ]. Rhönite analyzed by electron-probe microanalysis (EPMA) has the formula Ca 2.04 (Mg 0.32 Fe 2+ 4.25 Fe 3+ 0.47 Ti 0.33 Al 0.61 )(Si 3.74 Al 2.26 )O 20 , where Fe 3+ was estimated by stoichiometric analysis. During preliminary cathodoluminescence (CL) analysis, complex subgrain and oscillatory zoning was observed in the anorthite. In this study we use a combined approach of electron probe microanalysis (EPMA), cathodoluminescence (CL), electron-backscatter diffraction (EBSD), and laser ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS) to further investigate the anorthite and distribution of Fe 3+ in NWA 15507.

Microscopy and Microanalysis

Remote compositional analyses of space-weathered lunar maria

Visible-to-shortwave infrared (VSWIR) reflectance spectroscopy has revolutionized our understanding of planetary surface compositions. However, space-weathering processes on airless bodies complicate quantitative compositional analyses. Here, we present a framework to isolate the signatures of space weathering in VSWIR spectra of lunar maria by leveraging radiative transfer modeling under the assumptions that (i) a space-weathered target can be expressed as a mixture of fresh and fully space-weathered components and (ii) remaining signatures can be modeled by including agglutinates as an end-member component. We first validate this approach against laboratory spectra of space-weathered Apollo mare soils of known mineral compositions using a probabilistic Markov Chain Monte Carlo implementation of the Hapke radiative transfer model. Second, we illustrate how this approach can be applied to orbital Moon Mineralogy Mapper data. The proposed space-weathering correction workflow for lunar maria could be expanded to other lunar lithologies and applied to existing and future data sets.

Planetary Science Journal

Simulating human behavior under earthquake early warning

Earthquakes are a rapid-onset hazard where advance planning and learning plays a key role in mitigating injuries and death to individuals. Recent advances in earthquake detection have resulted in the development of earthquake early warning (EEW) systems. These systems can provide advance warning to predetermined geographic regions that an earthquake is in progress, which may result in individuals receiving warning seconds before significant shaking is felt at their location. This additional time could allow individuals to take more effective protective actions during the immediate disaster. To demonstrate this, we created an agent-based simulation of a basic apartment that allowed us to randomly and repeatedly simulate an individual receiving and responding to an EEW message. The results of our preliminary simulation show that, in our study environment, earthquake early warning alerts have the potential to allow for sufficient time for individuals to take protective actions.

Washington

Morphodynamics of snow barchans at Concordia Station, Antarctica

Barchans are crescent-shaped dunes that form and migrate under unimodal wind regimes in areas of low sediment availability. While sand barchan morphodynamics has been extensively studied, snow barchans remain poorly documented. Here, using hourly time-series images taken near Concordia Station, Antarctica, we measure the sizes (lengths 0.3 m to 13 m, widths 0.4 m to 7.5 m) and migration rates (0.13 m h −1 to 3.5 m h −1 ) of 44 populations of snow barchans during 2017–2022. We compare this dataset with established height–velocity and length-width relationships for sand barchans in both air and water. Our results show that snow barchans follow the same scaling as sand barchans, allowing us to estimate a characteristic sintering (bonding of snow particles) time of about one day. This sintering process limits the size of snow barchans when active, reduces their aspect ratios, and, once wind falls below the transport threshold, explains their preservation over a few years. During wind events, migrating barchans are too small to maintain their shape and orientation, making them highly responsive to fluctuations in wind direction. Thus, studying snow barchans improves understanding of an elementary bedform encountered in multiple environments and also of the surface properties of snow on different timescales, offering insights into snow accumulation and wind-blown snow in ice cores.

Geomorphica

Assessing environmental drivers of denitrification in restored riverine floodplains

Restoration of impaired floodplains is an increasingly prevalent strategy for alleviating water quality concerns and reducing downstream flooding at watershed scales. Floodplains temporarily store water and slow flow velocity to promote sedimentation during overbank flooding and remove inorganic nitrogen from floodwater and groundwater via denitrification. Evaluating the impacts of different restoration strategies on denitrification can inform more strategic investments into floodplain modifications that improve water quality outcomes. Our research investigates how denitrification rates in floodplains respond to environmental factors that are actionable from an engineering perspective through design and water resources management. We seasonally measured soil denitrification enzyme activity and various environmental characteristics in 4 floodplains with different restoration design and management approaches at the confluence of the Wabash and Tippecanoe Rivers in Indiana, United States. Our results showed that denitrification rates in an agricultural floodplain were significantly lower than in restored floodplains with native vegetation. Certain soil conditions characteristic of floodplain wetlands were associated with higher denitrification, particularly elevated total nitrogen, moisture, silt, and organic matter contents. Vegetation species composition was correlated with denitrification rates. This link may reflect the direct effects of vegetation on soil conditions, such as supplying labile organic carbon, or indirect effects, such as vegetation acting as an indicator of hydrologic regime and land use. Denitrification seasonally varied, peaking in winter when nitrate supply from rivers draining agricultural watersheds in the region is also high. Substrate limitation of soil denitrification enzyme activity was most significant during the summer when overbank flooding, which replenishes soil nitrogen stocks, rarely occurs. Our findings indicate that denitrification capacity will likely be maximized in riverine floodplains that are restored as wetlands with diverse native vegetation and enhanced hydrologic connectivity. Such restoration activities promote higher denitrification rates via elevated moisture, fine sediment deposition, and soil organic matter.

Tippecanoe River, Wabash River

Indirect mineral import reliance and provenance

Mineral commodity supply chain analyses rely on international trade data reported by individual countries as quantities of a mineral commodity form imported from (or exported to) a partner. However, export quantities frequently exceed a country’s domestic production, or occur when no production data are reported, suggesting that the trade partner is merely an intermediary in a transshipment. These discrepancies can result in misleading conclusions regarding supply chain vulnerabilities and dependencies. We present a two-stage methodology to reconcile gaps between reported material sources and actual producers. First, we construct trade networks for specific mineral forms, treating production as a type of import to distinguish producing nations from entrepôts. By tracing flows through these networks, we attribute a target country’s imports to original producers via both direct (in a single trade link) and indirect (transferring through intermediaries) pathways. Second, these production-attributed flows are incorporated into multi-stage supply chains to determine the upstream provenance of feedstock for domestic refining and processing. This approach provides a more representative picture of trade reliance. For example, while the United States (U.S.) Geological Survey reports no imports of unwrought antimony metal from Russia in 2022 (U.S. Geological Survey (2025). Mineral Commodity Summaries 2025. 10.3133/mcs2025), our analysis reveals that over 16% of U.S. imports can be traced back to Russian mining through intermediate processing in countries such as China, India, and Vietnam. Additionally, our analysis of the aluminum supply chain shows that while the U.S. is reported as 52% net import reliant on aluminum materials in 2022, it is 100% reliant on foreign bauxite, 7% of which arrived indirectly. This unreported reliance, which is predominantly tied to bauxite mined in Brazil (43%) and Jamaica (28%), highlights our methods ability to capture the supply chain’s dependence on foreign feedstock that may be missing in single-stage trade data.

Mineral Economics

Future water constraints on United States lithium mining under climate change

Lithium is necessary for low-carbon technologies that combat climate change, but lithium extraction is water-intensive. Changes in temperature and precipitation arising from climate change are altering water distribution, which could further strain supplies for new mines and industry, farms, and households. Here we explored how climate change, water use, and mining siting could impact lithium mining in the United States. We analyzed whether there would be sufficient water available to support the single existing and 22 proposed U.S. lithium mines at mid-century under four socioeconomic-climate scenarios and five climate models. Though dependent on socioeconomic-climate scenario, climate model, and lithium deposit type, available water supply in most subbasins would likely be unable to support new mines’ water demands, or even non-mining water demands from other sectors. Water scarcity could hinder the ability of the United States to produce enough lithium to meet domestic demand thereby necessitating higher imports.

conterminous United States