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Results for “Philosophical Transactions of the Royal Society B: Biological Sciences”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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1,687 records · Page 15Linked to original sources
USGS2024

Aboveground carbon stocks across a hydrological gradient: Ghost forests to non-tidal freshwater forested wetlands

Upper estuarine forested wetlands (UEFWs) play an important role in the sequestration of atmospheric carbon (C), which is facilitated by their position at the boundary of terrestrial and maritime environments but threatened by sea level rise. This study assessed the change in aboveground C stocks along the estuarine–riverine hydrogeomorphic gradient spanning salt-impacted freshwater tidal forested wetlands to freshwater forested wetlands in seasonally tidal and nontidal landscape positions. Standing stocks of C in forested wetlands were measured along two major coastal river systems, the Winyah Bay in South Carolina and the Savannah River in Georgia (USA), replicating and expanding a previous study to allow the assessment of change over time. Aboveground C stocks on these systems averaged 172.9 Mg C ha −1 , comparable to those found in UEFWs across the globe and distinct from the terrestrial forested ecosystems they are often considered to be a part of during large-scale C inventory efforts. Groundwater salinity conditions as low as 1.3 ppt were observed in conjunction with losses of aboveground C. When viewed in context alongside expected sea level rise and corresponding saltwater intrusion estimates, these data suggest a marked decrease in aboveground C stocks in forested wetlands situated in and around tidal estuaries.

Georgia, South Carolina↗
USGS2025

An exploration of the relative influence of physical models for Omori’s law

Omori’s law states that the rate of aftershocks decays as a function of inverse time. There are multiple physical explanations that we reduce into a nonlinear mixed effects relation of three terms: (1) a Rate/State expression that can account for static/dynamic and viscoelastic triggering caused directly by the mainshock, (2) a fluid diffusion triggering term, and (3) a randomized secondary triggering (cascade) term. We fit free physical-model parameters to an observed aftershock sequence through two nonlinear regression methods to find the relative contributions of physics-based models in an observed aftershock sequence. Results from both methods show that Rate/State models overpredict aftershock rates by ∼0–30%. Secondary aftershocks cause a net negative contribution (seismicity rate reduction that corrects overprediction by other terms) ranging between ∼0 and 30%. All regression solutions yield negative secondary triggering contributions without being guided to do so. A physical explanation for this is that aftershock occurrence relieves stress from the crust, ultimately causing the sequence to extinguish itself. Fluid diffusion triggering contributions range from ∼0 to 20%. Diffusion processes are observed to be shorter in time than the full duration of an aftershock sequence and they are also spatially limited, diminishing their influence. Our results apply to an aftershock decay curve from the 2016 Central Apennines earthquake sequence, meaning that our specific results may not be general. Our primary conclusion is that any one physical model cannot alone fit the observed sequence as well as the combination of three we investigated.

Frontiers in Earth Science↗
USGS2026

Estimating the importance of floating surface material to the total phosphorus transport in Silver Creek, Wisconsin using Particle Image Velocimetry

Various techniques are used to estimate nutrient delivery in streams that combine flow and water-quality data. However, the transport of surface floating material is difficult to measure, and is therefore typically neglected when stream sampling and in the estimated nutrient delivery. Here, we describe an approach to estimate the amount of material (duckweed ( Lemna genus), filamentous algae, and other macrophyte fragments) and associated nutrients (in this case, phosphorus, P) transported on the surface of Silver Creek, Wisconsin, to determine if this material is an important transport mechanism and if historical P loads were underestimated. This approach includes estimating the transport of surface material using 10 s videos collected every 15 min from a downward-looking camera installed beneath a bridge. The average velocity of the surface material was first determined using Large-Scale Particle Image Velocimetry (LSPIV), which uses short videos to analyze surface particle movement. The amount of surface material in each video was then computed using computer-vision techniques. The P load associated with the transported surface material was then estimated by combining surface velocities, coverage of floating material, and laboratory-measured P content. Surface material transported ~9–11% of the total summer P load and ~4–7% of the annual load in Silver Creek.

Wisconsin↗
USGS2026

Evaluating the effects of a multi-modal deterrent on upstream passage by invasive carp and native species

Invasive carp, including Silver Carp ( Hypophthalmichthys molitrix ) and Grass Carp ( Ctenopharyngodon idella ), are increasing their range within the Mississippi River Basin, threatening native fishes and ecosystem function. We conducted a 3-year field test of a multi-modal deterrent that uses sound, bubbles, and light to test its ability to impede upstream passage by invasive carp. The test was performed at a lock and dam on the Cumberland River, Kentucky, USA, using acoustic telemetry to track the movements of Silver Carp, Grass Carp, and several native fish species. When the deterrent was operating, the estimated probability of upstream lock passage was 53% lower (95% CI: 41%–63%) for Silver Carp but 74% higher (95% CI: 3%–190%) for Grass Carp compared to times when the deterrent was not operating. Paddlefish ( Polyodon spathula ) passage was reduced by 43% (95% CI: 71% reduction to 9% increase), although this was not statistically significant. We detected no significant effects on Freshwater Drum ( Aplodinotus grunniens ) or Smallmouth Buffalo ( Ictiobus bubalus ). However, sample sizes were small for these native species, limiting our ability to identify effects. Water temperature, tailwater elevation, and vessel lockages affected passage rates, although this varied among species.

Kentucky↗
USGS2026

Dynamic drainage reorganization in Eastern Tibet: Insights from the Yangtze River first bend

The modern drainage network of eastern Tibet is widely believed to have developed through a series of river capture and flow reversal events; however, the timing and mechanisms driving this reorganization remain contentious. Among these events, the river capture that formed the First Bend of the Yangtze River (YFB) stands out as both iconic and particularly debated. Here we present sedimentary provenance data from the Late Miocene–Quaternary Dali Basin, located south of the YFB, which indicate that a southward-flowing Jinsha River (i.e., the present-day upper Yangtze River) sourced sediment to the Dali basin at ∼7.4–6.4 Ma in a drainage configuration different from that of today. Because this interval postdates the initial establishment of a near-modern Jinsha River system prior to the Miocene, our results imply at least two discrete fluvial reorganizations occurred at the YFB—one preceding ∼7.4 Ma and another following ∼6.4 Ma. By integrating these findings with landscape evolution modeling, we infer that the initiation of rapid uplift of the Yulong-Haba Mountains and the Diancang Shan may have been responsible for these drainage reorganizations. These results underscore that Cenozoic drainage systems on the eastern Tibetan Plateau have evolved dynamically on a short timescale of ∼10 5 –10 6 -year, rather than remaining in a long-term stationary configuration on ∼10 7 -year timescales.

eastern Tibetan Plateau, first bend of the Yangtze↗
USGS2025

A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities

As wildfires increasingly affect water-supply watersheds, the demand for models to predict water-quality responses is increasing. This work reviews and synthesizes existing post-wildfire applications of water-quality models in the context of geographic and ecohydrological distribution, hydrologic and water-quality response process representation, model parameterization, model and input data scales, model calibration data availability, as well as calibration and performance evaluation approaches. Emphasis is placed on models that simulate water-quality output, rather than sediment and erosional response as the primary focus. Here, identified gaps and opportunities to advance the post-wildfire application of water-quality models include: 1. applying models in under-represented geographic and ecohydrologic regions, 2. simulating multiple streamflow generation mechanisms, including groundwater, with an emphasis on shifting dominant flow pathways as the landscape recovers following wildfire, 3. adding studies that include the simulation of metals, 4. incorporating more biogeochemical and in-stream processes to model applications, 5. applying finer spatial and temporal resolution of precipitation data input as well as finer spatial resolution hydrologic response units, 6. implementing fully distributed grid or element models or finer resolution response units to capture burn severity heterogeneity, 7. collecting enhanced water-quality data for model calibration and validation, 8. conducting model-intercomparison studies, and 9. developing model parameter value guidance in post-wildfire applications. These identified gaps and opportunities may assist users in deciding on key processes and approaches to consider in modeling post-wildfire water-quality conditions.

Science of the Total Environment↗
USGS2024

Revision of ModelMuse to support the use of PEST software with MODFLOW and SUTRA models

Executive Summary ModelMuse is a graphical user interface for several groundwater modeling programs. ModelMuse was updated to generate the input files for the parameter estimation software suite PEST. The software is used with MODFLOW or SUTRA models to run PEST-based parameter estimation and display the updated model inputs after parameter estimation. The PEST input files can also be used with the PEST++ version 5 software suite. Parameter estimation typically requires defining the parameters being adjusted during calibration and observations for assessing calibration quality. After a parameter is defined in ModelMuse, it can be applied to all or part of a model dataset. Pilot points—a parameterization device that facilitates higher levels of parameterization—can be used to assign spatially variable distributions of model inputs. Parameters can be applied to temporally varying features, such as boundary conditions, by either applying them to all the values in a series in one step or by applying separate parameters to individual members of a series. ModelMuse allows the definition of many observation types from various model output files. For MODFLOW 6 and SUTRA models, new options were added to ModelMuse to allow it to display the changed input after parameter estimation is complete. For MODFLOW–2005 and MODFLOW–NWT models, ModelMuse can import an entire model for visualization. An example illustrates the use of PEST with a MODFLOW 6 model in ModelMuse.

Techniques and Methods↗
USGS2025

Characterizing the scale of regional landslide triggering from storm hydrometeorology

Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a dimensionless index for landslide-inducing rainfall, A * , based on extremes of modeled soil water relative to its local climatology. We calibrate A * using four landslide inventories, comprising over 11 000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow-landslide-triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A * , along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past 20 years, and we test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.

California↗
USGS2025

Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs

Oil and gas reservoirs represent suitable containers to sequester carbon dioxide (CO 2 ) in a supercritical state because they are accessible, reservoir properties are known, and they previously contained stored buoyant fluids. However, planners must quantify the relative magnitude of the CO 2 storage resource in these reservoirs to formulate a comprehensive strategy for CO 2 mitigation. Even reconnaissance-type estimates of CO 2 storage resources of known oil and gas reservoirs may require complicated calculations involving 1) estimates of recoverable oil and gas, 2) reservoir properties (depth, temperature, pressure, etc.), and 3) the physical qualities of the retained fluids. We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO 2 storage resources in reservoirs capable of hosting CO 2 in a supercritical state. ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. The proposed methods and models provide an effective and novel way to more rapidly and directly determine the subsurface CO 2 storage capacity of oil and gas reservoirs around the world, information that operators, researchers, and policymakers alike require to meet energy transition and decarbonization goals.

Frontiers in Enviornmental Science↗
USGS2024

The dominance and growth of shallow groundwater resources in continuous permafrost environments

Water is a limited resource in Arctic watersheds with continuous permafrost because freezing conditions in winter and the impermeability of permafrost limit storage and connectivity between surface water and deep groundwater. However, groundwater can still be an important source of surface water in such settings, feeding springs and large aufeis fields that are abundant in cold regions and generating runoff when precipitation is rare. Whether groundwater is sourced from suprapermafrost taliks or deeper regional aquifers will impact water availability as the Arctic continues to warm and thaw. Previous research is ambiguous about the role of deep groundwater, leading to uncertainty regarding Arctic water availability and changing water resources. We analyzed chemistry and residence times of spring, stream, and river waters in the continuous permafrost zone of Alaska, spanning the mountains to the coastal plain. Water chemistry and age tracers show that surface waters are predominately sourced from recent precipitation and have short (<50 y) subsurface residence times. Remote sensing indicates trends in the areal extent of aufeis over the last 37 y, and correlations between aufeis extent and previous year summer temperature. Together, these data indicate that surface waters in continuous permafrost regions may be impacted by short flow paths and shallow suprapermafrost aquifers that are highly sensitive to climatic and hydrologic change over annual timescales. Despite the lack of connection to regional aquifers, continued warming and permafrost thaw may promote deepening of the shallow subsurface aquifers and creation of shallow taliks, providing some resilience to Arctic freshwater ecosystems.

Proceedings of the National Academy of Sciences↗
USGS2026

Spatially referenced watershed models for the binational Red–Assiniboine River Basin: Bayesian vs frequentist comparison

Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

Red–Assiniboine River Basin↗
USGS2025

Controls on water quality below a reclaimed surface coal mine, southeastern Montana

Coal mining and reclamation can have a profound influence on hydrogeologic systems, with clear consequences for groundwater quality, yet their long-term influence on downgradient water quality over time following reclamation is less well documented. Geochemical trends were evaluated in water quality downgradient of a fully reclaimed landscape at the former Big Sky Mine in the Rosebud Creek watershed (southeastern Montana, USA), over a 3-year period (2020–2022), including bond release in 2022. Within 6 km downgradient from the reclaimed area, sulfate concentrations decreased from approximately 3500 to 1800 mg l −1 within the Miller Coulee alluvial aquifer. Major ions, δ 34 S SO4 values, and residence time tracers suggest that the observed decreases in sulfate concentration result from a combination of dilution by mixed-age inflows and incomplete transit of the high salinity plume from the mine boundary. Both bedrock and alluvial aquifers of the Rosebud Creek corridor contained contributions of millennia-old regional groundwater, which may serve to mitigate mine-derived high salinity waters. Rosebud Creek, which traverses the outflow zone of Miller Coulee in the study area, exhibited high sulfate concentrations during low flows and consistent downgradient increases in sulfate concentration. The possibility of plume dynamics in Miller Coulee suggests that the greatest water quality impacts may not yet have reached Rosebud Creek.

Montana↗
USGS2026

Hazard potential of compound flooding from rainfall, storm surge, and groundwater in coastal New York and Connecticut

Compound flood events, the co-occurrence of multiple flood drivers, can result in flood hazard potential exceeding that of any single driver alone. To evaluate compound flooding in a semi-urbanized coastal area, historical records dating back to 1970 are used to study the co-occurrences of high precipitation, storm surge, and shallow groundwater conditions along the coastlines of New York and Connecticut. Joint return periods for coincident precipitation-surge events were computed using statistical dependence models and compared to the assumption of independence as a ratio, referred to here as a return period adjustment. Results indicate distinct seasonality where compound events in the area disproportionately occur in the cold season between October and April. Return period adjustments range from a factor of 1 to almost 9, demonstrating the range in precipitation-storm surge dependence across the study area. Across all 24 station triad locations, groundwater levels were elevated during times of precipitation- surge co-occurrence, reflecting the tendency for coastal storms and shallow groundwater conditions to co-occur seasonally. The result is a pseudo-trivariate compound flood hazard score and corresponding hazard map that integrates dependence between daily precipitation-surge events and overall monthly groundwater levels (as a precondition) into a relative compound hazard score. The location with the highest compound flood hazard score is on the south shore of Long Island, as well as locations across coastal Connecticut where groundwater levels compound the co-occurrence of heavy precipitation and storm surge.

Connecticut, New York↗
USGS2024

Simulated ground-motion records for the seismic assessment of monumental masonry structures

Earthquakes are natural disasters that can cause widespread devastation and loss of life. Simulated ground-motion records can be useful in regions with limited seismic stations or a history of damaging but infrequent earthquakes. This is especially true in areas with a high concentration of heritage masonry structures, which are especially susceptible to damage, as simulated records can be crucial in predicting their seismic response and protecting these buildings from seismic damage. Despite the importance of simulated earthquakes, few studies have investigated how effective they are compared to real earthquakes when assessing the structural response of heritage buildings. To address this knowledge gap, we employ two different simulation methods of the Mw 6.2 Faial earthquake, which occurred on July 9th, 1998, in the Azores, to replicate the recorded time-series at four available stations within an epicentral distance of 150 km. The study has two objectives: first, to validate the simulated records of the 1998 Faial earthquake using alternative stochastic ground-motion simulation approaches, and second, to determine how these approaches impact the seismic assessment of historic masonry structures. To accomplish these objectives, this study uses real and simulated ground-motion datasets to conduct non-linear response history analyses of the São Francisco Church, a monumental structure in Horta that sustained damage during the Faial earthquake. The results show that both simulation approaches yield structural responses similar to the observed records.

Conference Paper↗
USGS2026

Deep critical zone controls on shallow landslides

The deep critical zone (CZ) has long been recognized for its importance in influencing shallow landslides but was not considered feasible to include in slope stability models at the watershed scale. In this study, we demonstrate that simple approximations of the CZ in a fully coupled hydrologic and soil slope stability model can effectively capture the location, timing, and likely size of shallow landslides. To achieve this, we use coupled, process-based models that incorporate the effects of 1) deep CZ structures, 2) three-dimensional transient hydrology, and 3) multidimensional slope stability, calibrated with data from an intensively monitored field site. Our results show that the hydrologically active deep CZ guides groundwater flow, influencing where it drains from or exfiltrates to the soil mantle, producing distinct patterns of soil saturation and seepage forces at the soil-bedrock boundary. Deep conductive weathered critical zone drains the soil mantle, reducing the likelihood of destabilizing pore pressures, while the downslope thinning of the CZ forces groundwater to the surface. This creates localized instability and a tendency for similar-sized landslides across the landscape. In contrast, the absence of conductive weathered bedrock results in more widespread destabilizing pore pressures, leading to larger landslides and the likelihood of landslides earlier in a storm than in landscapes underlain by a deep CZ. Our findings suggest that first-order variations of deep CZ can provide physical explanations for variations observed in the susceptibility, magnitude, and timing of shallow landslides, and that CZ structure may be inferred from patterns and timing of landsliding.

Proceedings of the National Academy of Sciences↗
USGS2026

Hydrologic variability drives environmental and geospatial relationships in Smallmouth Bass (Micropterus dolomieu) distribution

Hydrologic variation is a primary driver of stream ecosystems. Changing hydrology can lead to assemblage shifts and alterations in suitable habitat for freshwater species. As climate change is predicted to alter flow patterns in addition to increasing water temperatures, insight into relationships between species occupancy, hydrology, and temperature is critical for understanding current and future distributions. We examined how hydrologic variability, temperature, and other environmental variables interact to influence Micropterus dolomieu (Smallmouth Bass) occurrence. We used Spatial Stream Network models, allowing for the incorporation of spatial autocorrelation along streams' unique dendritic network, to examine Smallmouth Bass occupancy across a range of hydrologic variation in the Ozark-Ouachita Interior Highlands, USA. Hydrologic variation was the main driver of Smallmouth Bass occurrence, with occurrence more likely in groundwater streams with low hydrologic variation and high flow permanence. For groundwater streams, occurrence was positively associated with summer stream temperature and negatively associated with annual stream temperature. As variation increased, more variables showed significant relationships with occurrence. Distance metrics were important for all models, however as hydrologic disturbance increased, flow connected distance played a lesser role and stream distance played a greater role. Hydrologic variability was the overarching determinant of Smallmouth Bass occurrence and strongly influenced the predictive importance of environmental variables and geospatial relationships. Greater hydrologic variability resulted in stronger statistical relationships between occurrence and environmental variables and an increased importance of system connectivity. As climate change alters hydrologic processes and streams become more variable, understanding and accounting for these shifting relationships is essential.

Arkansas, Kansas, Missouri, Oklahoma↗
USGS2026

From landslide susceptibility to risk assessment in the conterminous U.S.

Understanding the spatial distribution of landslide prone-areas and what consequences they may have is important for risk management and land-use planning. In the United States, although landslides occur in every state, a comprehensive landslide risk assessment is still missing. Existing efforts, such as the Federal Emergency Management Agency (FEMA)’s National Risk Index, rely on aggregated products and coarse cartographic units, limiting their geomorphological and practical accuracy. In this study, we present a methodological advance for landslide risk assessment across large areas with incomplete and sparse data. We apply our procedures to the conterminous United States by integrating geomorphologically meaningful partitions and spatial and temporal probability data-driven models. Landslide susceptibility is estimated using a Generalized Additive Mixed Model incorporating a bias capture/correction scheme to account for inventory inaccuracies (reference Area Under the Curve = 0.75). The exceedance probabilities of landslide occurrence are defined for three temporal scenarios (2, 5, and 10 year). Then, we explore the associated potential economic consequences for human settlements and agricultural areas. The findings indicate that the spatial variability of risk is primarily controlled by exposure rather than by susceptibility/hazard alone. The mean risk increases by ∼170% from the 2-year to the 10-year scenario. Beyond its quantitative outcomes, this study offers a blueprint for continental or sub-continental scale landslide risk assessments, demonstrating both the opportunities and current limitations.

Engineering Geology↗
USGS2026

Thermal detectability of subsurface water ice on Mars: A comparative analysis for the Subsurface Water Ice Mapping (SWIM) Project

We have developed a new global map of shallow ground ice distribution, SWIM23, based on Mars Global Surveyor Thermal Emission Spectrometer data and made systematic comparisons between this new map and two similar, previously developed data products. We have explored the origin of differences between the three ice maps by detailing technical and procedural differences in their development, by making global pixel-by-pixel comparisons, and by carrying out a series of one-dimensional thermal simulations to explore fundamental physical limitations of thermal ice-detection techniques. These efforts and the production of a composite thermal ice-consistency map supported integration of multiple geophysical data products relevant to ice detection in the upper meter of the Martian regolith into the larger Mars Subsurface Water Ice Mapping project. Our work also highlights fundamental physical limitations to thermal ice detection as a technique, particularly the rapid fall-off in ice detection sensitivity at depths >30 cm, which produces maximum uncertainty in the presence and depth of ice within regions preferred for potential human landing sites. A future Mars orbiter mission designed to detect ice and support crewed landing site selection in the midlatitude region should give payload priority to an instrument capable of probing the 1–5 m depth range (i.e., a high-frequency radar), over a next-generation thermal spectrometer, which is unlikely to offer clarity on ice table depths or lateral continuity of the ice table in the locations of highest interest.

Planetary Science Journal↗