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184 recordsLinked to original sources
USGS2025

Assessing flood water infiltration and storage in a restored floodplain

In urban areas, floodplain restoration is gaining prominence as a strategy for restoring the natural functions of floodplain ecosystems and reducing flood risk. This has spurred research into potential interactions between floodwaters, the hyporheic zone, and the floodplain aquifer. An urban restored stream in Wisconsin, USA, was used as a case study to examine four methods to estimate floodplain infiltration and storage during overbank floods. We characterised flood-related infiltration over a 4-year period from 2018 through 2021 by simultaneously and continuously measuring groundwater levels and vertical temperature profiles with stream water levels linked to high-resolution flood inundation maps. High-resolution topographic data helped to quantify surface floodplain storage and the unsaturated soil volume relative to flood stage. Infiltration estimates from the simple methods align well with those from the more complex methods; however, the complex methods provide additional insights about the factors influencing infiltration. Results from all methods indicate that the volume of water that vertically infiltrates during floods is likely small relative to the total volume of the flood, with 0.08%–0.52% of flood water infiltrating into the floodplain, on average. Spatially variable vertical hydraulic gradients, driven by flood depth, groundwater level, and permeability, imply heterogeneous patterns of infiltration across the floodplain. Gradients favourable for infiltration typically occurred during the onset of flooding but, over the study period, were mostly (98% of the time) favourable for groundwater discharge to the channel (non-flood periods). These findings highlight the importance of considering surface-groundwater dynamics, floodplain soils, and unsaturated floodplain volume in defining the benefits of floodplain infiltration for flood attenuation.

Wisconsin↗
USGS2026

Continental-scale prediction of hydrologic signatures and processes

Understanding how dominant hydrologic processes and their drivers vary across diverse continental-scale landscapes is critical for hydrologic modeling and water management applications. Our research addresses this question by synthesizing large-sample watershed datasets, Caravan and GAGES-II, and developing random forest models to identify patterns in hydrologic function. We assessed dominant processes by examining hydrologic signatures – summary indicators of watershed function derived from hydroclimatic time series and random forest models across 14 146 gauged United States watersheds. The results reveal clear continental-scale gradients in hydrologic processes, including baseflow, overland flow, storage, and water balance losses. Our map of dominant processes highlights, for example, the transition from baseflow to fast responses and back to baseflow along the elevation gradient from the Appalachian spine, through the Piedmont, to the Eastern Coastal Plain; a distinct outer ring around the Great Lakes region; and sharp contrasts between coastal and inland processes in the West. Variable importance analysis from random forest models show that processes in the western U.S. are primarily controlled by climate, whereas in the eastern U.S., soil, geology, and topography play larger roles, with distinct human influences apparent in urban areas. Our approach of estimating dominant processes and their drivers facilitates extending process knowledge from research watersheds to the continental scale, assessing current hydrological understanding, and evaluating hydrological model structures.

conterminous United States↗
USGS2025

High-pass corner frequency selection and review tool for use in ground-motion processing

Raw seismological waveform data contain noise from the instrument’s surroundings and the instrument itself that can dominate recordings at low and high frequencies. To use these data in ground‐motion modeling, the effects of noise on the signals must be reduced and the signals’ usable frequency range identified. We present automated procedures to efficiently reduce low‐frequency noise that are implemented in the software package gmprocess. These procedures check for, and as needed remove, low‐frequency artifacts in the displacement record using polynomial fits, which can be used in combination with existing signal‐to‐noise ratio (SNR)‐based corner‐frequency selection procedures. The automated selections are then efficiently verified and refined using a graphical user interface (GUI) that plots relevant ground‐motion time series and spectra and tracks modifications to signal processing parameters. We demonstrate these procedures using recordings from the 2020 M 5.1 Sparta, North Carolina, and the 2013 M 4.7 southern Ontario earthquakes. Data processed with the SNR‐only and polynomial criteria for these events contain displacement artifacts in 37% and 23% of processed traces, respectively. Records with remaining artifacts are corrected manually using the GUI. These processing steps illustrate the workflow for efficient data processing with quality control.

Seismological Research Letters↗
USGS2025

Rupture process of the Mw7.0 December 5, 2024 Offshore Cape Mendocino earthquake

The Mw7.0 December 5, 2024 Offshore Cape Mendocino earthquake ruptured a km long portion of the east-west trending Mendocino fault zone (MFZ). In order to clarify the rupture process, we assemble three-component seismograms from regional seismic stations, horizontal coseismic displacement vectors derived from Global Navigation Satellite System (GNSS) time series, and a Sentinel-1 ascending interferogram. These data are interpreted with a model of slip distributed on two vertical fault planes representative of the eastern MFZ and spanning the ~70 km length of the aftershock zone. Assuming right-lateral strike slip, we find that the rupture initiates in the oceanic mantle at 20-30 km depth and proceeds unilaterally updip and toward the east. Early aftershocks locate adjacent to the peak slip areas, tracking the coseismic rupture propagation from oceanic mantle to shallower depth and implying a significant role of static stress transfer in driving aftershocks in an ocean plate environment.

California↗
USGS2025

Geochemistry and thermometry of magnetite veins and replacements in iron ore deposits from the Iron Springs district, SW Utah, USA: Relation to magmatic and hydrothermal processes

Ore-genesis, texture, chemical compositions, and thermometry of magnetite were used to better evaluate the origins of iron ore deposits across the Iron Spring district, Utah. Trace element compositions, determined by LA-ICP-MS, were used to calculate temperatures based on X Mg numbers and characterize the trace element signatures of magmatic and hydrothermal magnetite. Magnetite occurs as coarser crystalline grains within veins, breccias, and cavities along with finer crystalline replacements. Magnetite is most commonly intergrown with apatite, phlogopite, and carbonate in veins, breccias, and cavities where apatite occurs separately from the other gangue minerals. The results using empirical trace element discrimination diagrams generally suggest that the magnetite is overall of hydrothermal origin regardless of textural variations or field relationships. The X Mg numbers of the magnetite in the magnetite-apatite ores, however, are suggestive of high temperature magmatic conditions; whereas those of vein, breccia, and replacement occurrences containing other gangue minerals are suggestive of lower temperature hydrothermal processes.

Utah↗
USGS2026

A process-based model for forecasting wave runup along the coast of Georgia

Wave runup is an important nearshore process that impacts total water level, sediment transport, and coastal design. Current methods for forecasting wave runup implement an empirical model that considers offshore wave height, wave period, and generalized beach slope. In this study, the authors generated wave runup forecasts from offshore wave conditions and a system of polynomial equations derived from numerical simulations at three different still water datums for each beach profile. They developed a process-based methodology that incorporated site-specific cross-shore topobathy into the phase-resolving numerical model. A comparison between the system of equations, deterministic hydrodynamic simulations, and observed high-water marks was made using Hurricanes Matthew (2016) and Irma (2017) for 12 cases, and it showed that the polynomials were capable of being consistent with the results from full simulation runs, while not requiring hours of runtime when a forecast was needed—the differences between the polynomial and the observed high water marks ranged from 3 to 32 cm for the Irma hindcast and 9–70 cm for Matthew. Then, using forcings from Hurricanes Ian and Nicole (2022), the model predicted the occurrence of dune collision, overwash, and inundation for the coast of Georgia and suggested that wave runup was impacted by the still water level and local topobathy.

Georgia↗
USGS2026

High‐resolution surface deformation and slip distribution observations for the 2023 Kahramanmaraş, Türkiye, earthquake sequence help constrain the rupture process

Splay, or branch, faults are a common geometric feature of earthquake surface ruptures and may provide constraints on the rupture behavior of an earthquake. The 2023 M w 7.8 Pazarcık and M w 7.5 Elbistan, Türkiye, earthquakes are examples of ruptures with multiple small splays, and the Pazarcık earthquake nucleated on a splay fault, the Narlı fault, before rupturing bilaterally on the East Anatolian fault (EAF). Here, we present 3‐m‐resolution surface displacement from subpixel correlation of Planet Dove optical images for the entirety of both ruptures with corresponding surface slip distributions. For a 30‐km‐long study region spanning the Narlı‐EAF intersection, we compare surface slip derived from five data sets with different resolutions (on‐the‐ground, WorldView, Planet Dove, Sentinel‐2, and Sentinel‐1) to elucidate complementary information. In addition, we integrate information from the surface expression of faulting with published dynamic rupture simulations and rupture process studies to constrain a rupture evolution for the Pazarcık earthquake that is consistent across data sets. This work highlights the complementary nature of disparate surface slip data sets and the role that high‐resolution surface displacement information, including from fault splays, can play in constraining nonunique rupture models and refining understanding of the earthquake rupture process.

Bulletin of the Seismological Society of America↗
USGS2026

A roadmap for identifying and interpreting physical processes and national water model prediction bias associated with baseflow index regimes across the contiguous United States

Understanding how groundwater–surface water interactions shape streamflow variability is critical for diagnosing low flow behavior and prediction bias in continental scale hydrologic models. We present a process informed framework that links observed baseflow (BF) dynamics, watershed attributes, and National Water Model (NWM) performance across the contiguous United States. Using daily observed streamflow from 797 reference quality streamgages, we developed monthly baseflow index (BFI) signatures using a streamgage specific, calibrated digital filter. Hierarchical clustering of these signatures identified seven distinct BFI regimes capturing regional and seasonal variability. We evaluated NWM v3.0 retrospective streamflow performance within each regime using multiple hydrograph and flow duration curve-based metrics. Model skill varied systematically across regimes: mixed flow systems were simulated most accurately, while predominantly BF dominated and quickflow dominated regimes exhibited substantially poorer performance. Across nearly all regimes, the NWM underestimated observed BFI magnitude and frequently failed to reproduce seasonal BF patterns, indicating systematic biases in simulated low flow contributions. To relate these regimes to potential process controls, we trained a Random Forest classifier using static watershed attributes and applied Shapley Additive Explanations to identify features most strongly associated with each regime. Results highlight regionally varying influences, including the dominant role of snow fraction and seasonal runoff timing in snow dominated basins and the importance of evapotranspiration and aridity in quickflow dominated systems. Collectively, these findings demonstrate how hydrologic signatures combined with interpretable machine learning can diagnose regime specific model biases and generate process-based hypotheses about limitations in large scale hydrologic prediction systems.

contiguous United States↗
USGS2025

Natural source zone depletion of crude oil in the subsurface: Processes controlling mass losses of individual compounds

At many petroleum hydrocarbon spill sites, residual spilled product forms a long-term source of groundwater contamination. The phrase source zone natural depletion is used to refer to the mass loss rates. Overall mass lost under environmental conditions was analyzed using conservative biomarker concentrations for a 1979 oil spill in northern Minnesota, USA. After 40–41 years, an average of 50% of the mass was lost with values ranging from 22% to 57% depending on location. It is also important to understand the composition changes in the source. To understand controls on the losses of individual compounds, concentrations of volatile hydrocarbons in oil samples were compared with aqueous solubilities, and pore-space oil saturations. The results of the comparison show that losses of the oil compounds were controlled by pore-space oil saturations, solubility, and susceptibility to degradation under methanogenic conditions. Compounds that degrade under methanogenic conditions, including toluene, o -xylene, and n -alkanes are more depleted compared to benzene, ethylbenzene, and m - and p -xylene for which losses are dominated by dissolution. These rates and compound-specific behaviors form a foundation for improved modeling approaches and risk analyses.

Minnesota↗
USGS2025

Noble and base metal distribution and processes affecting ore tenors in the disrupted lower stratigraphy of the Stillwater Complex, USA

Exploration continues for contact-style Ni-Cu sulfide and chromitite-associated PGE mineralization in ultramafic rocks of the Stillwater Complex. At the Iron and Chrome Mountain areas, massive sulfides occur along the complex’s footwall contact and anomalous concentrations of PGE+Au are associated with the three lowermost chromitite seams. Southeast of Chrome Mountain, magmatic layering is highly disrupted by the presence of faults, magmatic breccias, serpentinized discordant dunites, pyroxenite pegmatoids, and disaggregated chromitite seams. The bulk rock chemistry, sulfide chemistry, and noble metal mineralogy of samples from this area were examined to determine the deportment of PGE and processes that led to enrichments in PGE, Au, Cu, Co and Ni. Results show that a sulfide liquid was the principal collector of PGE. If sulfide liquid was initially deposited with chromite, it was disaggregated or redistributed by subsequent melt or fluid infiltration, which may have resulted in the offset of peak PGE(+Cu, Ni) from peak Cr 2 O 3 concentrations, and upgraded PGE tenors. Upon cooling, PGE exsolved from sulfides to form discrete bismuth tellurides, arsenides, arsenic sulfides, antimonides, and alloys, commonly along the margins of sulfide globules. Calculated metal tenors are highest in the disseminated sulfides southwest of Chrome Mountain, whereas massive and net-textured sulfides near the Iron Mountain-Camp zone represent monosulfide solid solution cumulates. At progressively shallower levels, higher metal tenors combined with lower S/Se ratios are consistent with increasing R-factors from 100 to 100,000. Serpentinization and talc-tremolite alteration resulted in S loss through partial replacement of sulfides by secondary silicate+carbonate+magnetite+sulfide assemblages, further upgrading Ni-Cu-PGE tenors. The present work shows that processes responsible for the disruption of magmatic layering and post-magmatic fluid alteration along the intrusion’s lower contact led to noble and base metal enrichments.

Montana↗
USGS2025

Characterization of the hydrogeologic framework, groundwater-flow system, geochemistry, and aquifer hydraulic properties of the shallow groundwater system in the Wilcox and Lorraine process areas of the Wilcox Oil Company Superfund site near Bristow, Oklahoma, 2022

The Wilcox Oil Company Superfund site (hereinafter referred to as “the site”) was formerly an oil refinery northeast of Bristow in Creek County, Oklahoma. Historical refinery operations contaminated the soil, surface water, streambed sediments, alluvium, and groundwater with refined and stored products at the site. The Wilcox and Lorraine process areas are where the highest concentrations of volatile organic compounds, semivolatile organic compounds, polycyclic aromatic hydrocarbons, and trace elements (including metals) (collectively hereinafter referred to as “contaminants”) were measured in a local shallow perched groundwater system within the alluvium (hereinafter referred to as the “alluvial aquifer”) at the site during previous site assessments. In order to understand the potential migration of contaminants through the soil and groundwater in these areas, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, investigated aquifer characteristics of the alluvial aquifer in the Wilcox and Lorraine process areas of the site to (1) document hydraulic conductivity and other aquifer characteristics of the alluvial aquifer that govern contaminant fate and transport, (2) describe the geospatial extent and concentration of the contaminants in the alluvial aquifer in the Wilcox and Lorraine process areas, and (3) describe the geochemical controls pertaining to oxidation and reduction governing the fate and transport and the degradation potential of contaminants in the groundwater. Various data were compiled and collected to evaluate the aquifer characteristics at the site including the hydrogeologic framework, groundwater-flow system, geochemistry, and hydraulic properties of the aquifer. A total of 20 new (2022) groundwater monitoring wells were installed at the site to collect data used to supplement groundwater-level altitude and groundwater-quality data collected from older, existing groundwater monitoring wells and piezometers. Data compiled and collected for the study were used to evaluate the characteristics of the alluvial aquifer at the site. These aquifer characteristics are defined by the hydrogeologic framework, groundwater-flow system, geochemistry, and hydraulic properties of the aquifer.

Oklahoma↗
USGS2026

A review and synthesis of post-wildfire shifts in hydrologic processes and streamflow generation mechanisms

Critical water supply watersheds in the western United States (WUS) are impacted by wildfires, with potential negative effects on water quality and quantity. Scientific understanding is currently insufficient to deliver estimates of wildfire consequences for water quantity that are regionally accurate. Regional variability in the directionality and magnitude of post-wildfire shifts in streamflow generation fuels uncertainty in estimates of wildfire effects on water supply. In this work we provide a narrative review of wildfire effects on hydrologic processes and the resulting changes in streamflow generation mechanisms with a focus on the WUS, incorporating other global regions when pertinent. A conceptual model summary of wildfire effects on streamflow generation emphasizes: (1) precipitation seasonality, (2) synchrony of precipitation and potential evapotranspiration, (3) net shifts in interception, evaporation, and transpiration relative to total annual precipitation, (4) vegetation changes, including compensatory uptake and type conversion, (5) degree of overlap in rainfall rates and infiltration, (6) fire extent and severity, (7) burn scar positioning (e.g. in headwaters or proximal to watershed outlet), (8) scale-dependent groundwater leakage, (9) near-surface water storage reduction, and (10) soil to groundwater connectivity. Ongoing gaps and challenges include separating the influences of precipitation variability, water withdrawals, and post-fire land management; compound and overlapping disturbances; and lack of pre-fire data. Notable future opportunities include: harnessing ever-improving gridded and remotely sensed precipitation and fire-effects data; linking geophysical, isotopic tracer, and geochemical signatures to diagnose hydrologic changes; leveraging physically based and data-driven model advancements; and analyzing streamflow generation recovery trajectories across diverse watersheds.

western United States↗
USGS2026

The digital archivist: Automating legacy macroseismic data processing using large language models

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor‐intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 M L 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground‐motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

Seismological Research Letters↗
USGS2025

Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration

Model criticism, discrimination, and selection methods often rely on calibrated model outputs. Because calibration can be computationally expensive, model criticism can first be undertaken by assessing model outputs obtained from limited prior parameter ensembles. However, such prior-based methods are often heuristic and do not formalize the notion of balancing model consistency with data and model complexity (i.e., model adequacy). We present a new framework to discriminate among candidate models prior to calibration that formalizes prior-to-calibration model adequacy into a metric to implicitly balance prior model output data coverage with model complexity represented by prior output (co)variance. The prior model adequacy metric “Mahalanobis distance deviation” quantifies the deviation of (a) the set of squared Mahalanobis distances of data from a prior model output distribution from (b) the set of squared Mahalanobis distances of data from their own distribution. A new data worth metric “discernment value” is also presented which quantifies the value of data for screening less-adequate models prior to calibration. Discernment value is calculated from the change in variance of a weighted average of prior model outputs from all candidate models due to less-adequate model outputs receiving lower weight. The framework is demonstrated using a one-dimensional groundwater flow model with eight possible configurations. A synthetic data network is used to test the framework. Results show the framework identifies the candidate models most similar to the true model used to create the synthetic data. Discernment values show variation in the value of different data types and locations for screening less-adequate models.

Water Resources Research↗
USGS2026

Is satellite-derived bathymetry vertical accuracy dependent on satellite mission and processing method?

This research focusses on three satellite-derived bathymetry methods and optical satellite instruments: (1) a stereo photogrammetry bathymetry module (SaTSeaD) developed for the NASA Ames stereo pipeline open-source software (version 3.6.0) using stereo WorldView data; (2) physics-based radiative transfer equations (PBSDB) using Landsat data; and (3) a modified composite band-ratio method for Sentinel-2 (SatBathy) with an initial simplified calibration, followed by a more rigorous linear regression against in situ bathymetry data. All methods were tested in three different areas with different geological and environmental conditions, Cabo Rojo, Puerto Rico; Key West, Florida; and Cocos Lagoon and Achang Flat Reef Preserve, Guam. It is demonstrated that all satellite derived bathymetry (SDB) methods have increased accuracy when the results are aligned with higher-accuracy ICESat-2 ATL24 track bathymetry data using the iterative closest point (ICP). SDB vertical accuracy depends more on location characteristics than the method or optical satellite instrument used. All error metrics considered (mean absolute error, median absolute deviation, and root mean square error) can be less than 5% of the maximum bathymetry depth penetration for at least one method, although not necessarily for the same method for all sites. The SDB error distribution tends to be bimodal irrespective of method, satellite instrument, alignment, site, or maximum bathymetry depth, leading to the potential ineffectiveness of traditional error metrics, such as the root mean square error. However, our analysis demonstrates that performing detrending where possible can achieve an error distribution as close to normality as possible for which error metrics are more diagnostic.

Florida↗
USGS2026

Potential impacts of groundwater pumping on stream temperature are greatest in streams with substantial cold groundwater inflows

Groundwater pumping-induced reductions in streamflow (known as ‘streamflow depletion’) have been documented worldwide, but potential impacts of streamflow depletion on stream temperature are not well understood. Here, we use two types of models to identify potential impacts of pumping on stream temperature across the conterminous United States (CONUS) to determine which aspects of a stream's annual thermograph (thermal signatures) can be used to monitor and manage streamflow depletion impacts on stream temperature. We used long-term streamflow and stream temperature data from 30 streamgages across CONUS and surrogate models of streamflow depletion to analyse potential stream temperature impacts at each site. We compared two different stream temperature modelling approaches: (i) a process-based energy balance model and (ii) statistical regression models based on air temperature and stream discharge. We calculated a suite of thermal signatures under depleted and non-depleted conditions for each stream and found that maximum annual 7-day temperature and annual temperature range are potentially the most sensitive to streamflow depletion, with potential changes of at least 2°C at > 70% of the sites when using the process-based model. We also found that the regression-based models predicted much less sensitivity of stream temperature to streamflow depletion than the process-based model. This work provides an initial evaluation and sensitivity analysis of the potential impacts of streamflow depletion on stream temperature. We demonstrate that stream temperature may be most sensitive to pumping in streams with a high proportion of flow sourced from relatively cold groundwater inputs, and that regression-based stream temperature models may underpredict stream temperature changes caused by streamflow depletion.

conterminous United States↗
USGS2025

A joint Gaussian process model of geochemistry, geophysics, and temperature for groundwater TDS in the San Ardo Oil Field, California, USA

Decline in availability of fresh groundwater has expanded interest in brackish groundwater resources; however, the distribution of brackish groundwater is poorly understood. Water resources in sedimentary basins across the United States often overlie oil and gas development. Mapping of groundwater total dissolved solids (TDS) using data from oil well geophysical logs has become an important technique for identifying fresh and brackish groundwater. Existing geophysical log analysis methods use porosity and temperature to relate formation resistivity to TDS. Typically, natural geothermal gradients are used to estimate temperature at the location of collected resistivity. However, in thermally enhanced oil fields, steam is injected into the subsurface to mobilize high viscosity oil, creating variable temperature distributions. Furthermore, TDS derived from resistivity also depends on the fractions of dominant ions. Typically, chloride and bicarbonate fractions must be determined. It is also necessary to model TDS across many geologic units with heterogenous porosity distributions. Collectively, each quantity used to estimate TDS (resistivity, porosity, temperature, bicarbonate fraction) varies in space and time, and available data points are rarely collocated. Here, we present a new method of mapping groundwater TDS that continuously models each quantity together with a joint Gaussian process. This method enables mapping fresh and brackish water with practically available data. We apply this method to the San Ardo Oil Field in Monterey County, California, where steam injection occurs. In some areas of the aquifer system overlying the oil zone, the temperature is ∼75 °C, roughly twice the natural background value. Groundwater TDS is typically <1,500 mg/L in the aquifer and increases with depth to ∼9,000 mg/L in the oil-producing zone. A low-permeability clay layer delineates the fresh and brackish water, likely by inhibiting surface recharge from penetrating the deeper zones, allowing higher-TDS connate water to remain in place. Weaker lateral TDS trends may be controlled by recharge patterns associated with the Salinas River. Our model reveals with high certainty that groundwater has freshened in one localized part of the oil-producing zone and suggests with less certainty that more widespread freshening has also occurred. The lowering of TDS was possibly from decades of low-TDS steam injection and the associated fluid production and disposal operations.

California↗