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Results for “Journal of Comparative Physiology A”

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

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USGS2024

Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications

The US Geological Survey’s (USGS) ShakeMap system provides a rapid characterization of strong ground shaking in areas directly affected by an earthquake. This study focuses on studying the aggregate effects of macroseismic shaking estimates from ShakeMap, expressed in terms of modified Mercalli intensity (MMI), when accounting for the uncertainty in forecasted ground motions. We use a Monte Carlo approach to generate numerous spatially correlated realizations of ground motions by utilizing a combination of circulant embedding and kriging techniques for efficiently handling the correlations. We then assessed the aggregate effects of shaking by looking at bin counts across these realizations. We demonstrate that the aggregate shaking regarding the mean macroseismic intensity estimates (from the ShakeMap output) is a biased representation of the aggregate shaking when shaking uncertainty is included. Incorporating shaking uncertainty can help to improve various downstream earthquake impact applications, such as the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) overall earthquake fatality distribution or estimates of shaking-induced ground failure impacts from consequential earthquakes.

Earthquake Spectra Journal↗
USGS2026

Synthesizing a twelve-year sediment trap time series of planktic foraminiferal flux in the Gulf of America (Mexico)

Sediment trap time series provide powerful frameworks for testing hypotheses about planktic foraminiferal assemblage composition, seasonality, and geochemical responses to environmental variability, all of which are central to improving paleoceanographic reconstructions. We present high resolution foraminiferal assemblage data from a long-running sediment trap (2008–2020) in the northern Gulf of America (Mexico). This study summarizes the species composition, seasonality, and size distribution of the fifteen most abundant species of planktic foraminifera, which account for 98% of total flux. Foraminiferal flux peaks in winter and reaches a minimum in summer, following the seasonal pattern of primary production in the northern Gulf. Winter assemblages are dominated by non-spinose taxa, whereas spinose taxa prevail during summer. Across nearly all species, average monthly test size covaries with temperature, independent of seasonal flux trends. Notably, Trilobatus sacculifer and Neogloboquadrina dutertrei show a significant decline in relative abundance and flux during 2017–2020, nearly disappearing from the assemblage.

Journal of Foraminiferal Research↗
USGS2024

Groundwater-Surface water interactions research: Past trends and future directions

Interactions between groundwater and surface water sustain groundwater-dependent ecosystems and regulate river temperature and biogeochemical cycles, amongst many other processes. These interactions occur in freshwater environments including rivers, springs, lakes, and wetlands, and in coastal environments via tidal pumping, submarine groundwater discharge, and seawater intrusion. Here, we explore groundwater-surface water interactions research using bibliometric analyses of titles, abstracts, and keywords from 20,275 journal papers published between 1970 and 2023 extracted from Scopus. Analyses show that research into groundwater-surface water interactions is highly multi-disciplinary, with growing contributions from the social and biological sciences. The number of groundwater-surface water interactions papers is rapidly increasing with over 1200 papers published per year since 2020. Drawing on our data-driven approach and expert knowledge, we synthesise current research trends and identify critical future research directions. Despite the thousands of papers on groundwater-surface water interactions, important processes are still difficult to quantify or predict at meaningful spatial scales to inform water-resources management. We see benefits in future groundwater-surface water interactions research focusing on: (1) using new technologies including internet-of-things-based sensors, uncrewed vehicles, and remote-sensing approaches for data collection to inform groundwater-surface water interactions at large scales, (2) seeking approaches to upscale site-specific findings to better inform management, and (3) continuing the movement towards multi-disciplinary investigations to better inform the understanding of groundwater-surface water interactions and processes that will enable better management outcomes.

Journal of Hydrology↗
USGS2024

Twentieth century extreme precipitation detected in a high-resolution, coastal lake-sediment record from California

California faces increasing economic and societal risks from extreme precipitation and flooding associated with atmospheric rivers (ARs) under projected twenty-first century climate warming. Lake sediments can retain signals of past extreme precipitation events, allowing reconstructions beyond the period of instrumental records. Here, we calibrate AR-related extreme precipitation from the last century to proxy data from lake sediments collected in the latitudinal zone of the highest frequency landfall for modern ARs in California. Excursions in erosional proxy data (Ti/Al) are positively and significantly correlated (r median = 0.45, p median = 0.04) with modern records of integrated vapor transport (IVT, kg m −1 s −1 ), a key metric of AR intensity, using correlations that incorporate age-model uncertainty. Despite the land-use change near the study site, the data suggest intense and long-lasting AR storms are identifiable in this sedimentary record. These results allow conservative inferences concerning past extreme hydrology at this site.

California↗
USGS2024

Self-guided decision support groundwater modelling with Python

The GMDSI tutorial notebooks repository provides learners with a comprehensive set of tutorials for self-guided training on decision-support groundwater modelling using Python-based tools. Although targeted at groundwater modelling, they are based around model-agnostic tools and readily transferable to other environmental modelling workflows. The tutorials are divided into three parts. The first covers fundamental theoretical concepts. These are intended as background reading for reference on an as-needed basis. Tutorials in the second part introduce learners to some of the core concepts parameter estimation in a groundwater modelling context, as well as providing a gentle introduction to the PEST, PEST++ and pyEMU software. Lastly, the third part demonstrates how to implement highly-parameterized applied decision-support modelling workflows. The tutorials aim to provide examples of both “how to use” the software as well as “how to think” about using the software. A key advantage to using notebooks in this context is that the workflows described run the same code as practitioners would run on a large-scale real- world application. Using a small synthetic model facilitates rapid progression through the workflow.

Journal of Open Source Education↗
USGS2025

National population exposure and evacuation potential in the United States to earthquake-generated tsunami threats

Previous efforts to characterize tsunami threats to people have focused primarily on individual scenarios in specific areas but have not recognized multiple scenarios across an entire country. This study addresses this gap by quantifying population exposure and evacuation potential in the United States to 102 earthquake-related, tsunami-hazard zones, including 92 local scenarios, 8 distant scenarios, and 2 probabilistic products. Geospatial path-distance modeling quantified evacuation potential and the influence of departure delays. We focused on residents to support other national, multi-hazard risk analyses. Millions of residents are in distant-tsunami zones, and hundreds of thousands of residents are in local-tsunami zones. In 41 scenarios, there is at least one resident that may have insufficient time to evacuate before wave arrival. Tens of thousands of residents may have insufficient time to evacuate from local tsunamis that impact the U.S. Pacific Northwest or Puerto Rican coastlines. The largest improvements in evacuation potential may come from reducing departure delays in some areas but may involve vertical-evacuation structures or changing land use in other areas.

International Journal of Disaster Risk Reduction↗
USGS2026

Groundwater spatial variability within an atoll island: Assessing shallow aquifer heterogeneity with geophysical and physicochemical measurements

This study examines the spatial variability of shallow groundwater on Dhigelaabadhoo Island using electromagnetic induction surveys, groundwater monitoring, and sediment analyses. The research reveals how variations in island morphology—such as differences in elevation, reef flat width, and sediment composition—affect the spatial distribution of groundwater lenses and the overall aquifer dynamics. Saltwater intrusion is especially pronounced in low elevated areas, with narrow reef flat plate and areas where higher hydraulic conductivity—driven by the presence of coarser sediments—is observed, whereas regions characterized by finer sediments, higher elevation, and wider reef flat plates tend to support more symmetric and less saline groundwater lenses. The geophysical investigations reveal that tidal oscillations alter groundwater movement by markedly changing water levels and conductivity, thereby underscoring the critical need to account for temporal dynamics in atoll coastal aquifer systems and the importance of integrating tidal dynamics into the aquifer zone. The findings highlight the significant role of intrinsic morphological and external hydrodynamic factors in shaping groundwater distribution on atoll islands, offering critical insights for sustainable freshwater resource management.

Dhigelaabadhoo Island↗
USGS2025

Divide and conquer: Separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process – the probability of the existence of a seismic phase (detection probability) and the probability of correctly identifying the phase arrival time (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labeled phase arrival time, and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks) and the height of the peaks are taken as “probability” of the picks. Here, we show that this “probability” represents neither the detection nor the timing probabilty because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multi-class classifier to obtain a probability mass function to address the timing probability. This new approach makes the deep learning-based phase picking process more interpretable and gives us options to logically control seismic monitoring workflows.

Geophysical Journal International↗
USGS2025

Exploring the science and data foundation for Federal public lands decisions

Public lands provide diverse resources, values, and services worldwide. Laws and policies typically require consideration of science in public lands decisions, and resource managers are committed to science-informed decision-making. However, it can be challenging for managers to use, and document the use of, science and data in their decisions. To better understand science and data use in Federal public lands decisions in the United States, we assessed the number, type, and age of documents cited in 70 Environmental Assessments (EAs) completed by the Bureau of Land Management (BLM) in Colorado from 2015–2019. We focused on the BLM, as they manage the largest area of public lands in the United States. We selected Colorado as our study area, as actions proposed on BLM lands in Colorado are representative of those across the nation. Fifty percent of citations were categorized as science and 23% as data. EAs contained an average of 17 citations (range 0–111), with documents analyzing effects of oil and gas development and recreation actions including the highest and lowest mean number of citations (41 and 6, respectively). Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. Journal articles were the most cited type of document (26% of citations) followed by non-BLM inventories (13%). Forty-seven percent of citations were relatively recent (2010 or later); the oldest citation was from 1927. Commonly analyzed resources with the highest mean number of citations were socioeconomics, mineral resources, and noise. Fourteen of 33 commonly analyzed resources included <1 citation on average. Actions and resources with no or few citations represent opportunities for strengthening the transparent use of science and data in public lands decision-making.

Colorado↗
USGS2026

Keeping pace: Migrating sea lampreys adjust swim speed in response to shifting water velocity to maintain a constant ground speed

Upstream migrating fish must balance energetic costs with environmental and ecological constraints. Theoretical models predict that fish can conserve energy by adjusting swim speed in response to changing water velocity, but detailed field tests of these predictions remain rare. We used fine-scale acoustic telemetry and hydrodynamic modeling to track adult sea lamprey (Petromyzon marinus) migrating through a river and evaluated how movement speeds varied with environmental conditions and individual traits. Swim speed increased with faster water velocities, while ground speed remained constant, supporting the hypothesis that lampreys regulate swim effort to maintain a fixed migration pace. The average ground speed aligned with a predicted optimum of ∼1 body length per second. Both swim and ground speeds declined slightly in deeper water, suggesting a trade-off between movement efficiency and predator avoidance. These findings provide field-based support for a theoretical model of energy optimization and underscore how migratory fish adaptively adjust behavior to local hydrodynamic conditions. Our results highlight the value of using high-resolution tracking and environmental modeling to reveal behavioral tactics that underlie efficient migration strategies.

Michigan↗
USGS2026

Detecting snow avalanche activity using infrasound: Hooker Valley, New Zealand

Snow avalanches pose considerable hazards to people and infrastructure in alpine environments. Traditional avalanche monitoring relies on meteorological data and visual observations, which can be limited in scope and timeliness. Infrasound offers a promising complementary monitoring tool by detecting the low-frequency sound waves generated by avalanches. Here, we present infrasound and camera observations during a 50-day field campaign in the Hooker Valley of Aoraki/Mount Cook National Park, New Zealand. Our study detected seven avalanches with the cameras, whereas the infrasound system identified only one of these events, which was the largest and occurred under conditions that likely favoured infrasound propagation. The infrasound system recorded numerous other events not captured by the cameras, indicating the benefit of further investigation to determine their sources. These findings highlight the potential of infrasound technology for detecting avalanches and providing broad spatial coverage, capturing events in areas not monitored by cameras, while also showcasing limitations in infrasound capabilities. The limited detection of smaller avalanches underscores the opportunity for further research to enhance detection capabilities and understand environmental influences such as snow cover and wind noise. Overall, this study emphasises the utility of multidisciplinary monitoring techniques to improve avalanche detection in alpine environments.

Hooker Valley↗
USGS2026

Identifying overlap between native fish movements and a possible seasonal Grass Carp deterrent in the Sandusky River, Ohio, USA

Riverine fishes are vulnerable to habitat fragmentation caused by interrupted access to vital habitats. Fragmentation using artificial structures can be used to limit the spread of invasive fishes by inhibiting movement between critical habitats. Thus, tradeoffs exist between maintaining connectivity for native species and restricting movement of invasive fishes. A nonphysical deterrent has been proposed to prevent invasive Grass Carp ( Ctenopharyngodon idella ) from reaching spawning habitats in the Sandusky River, a tributary to Lake Erie, during late spring–summer. However, this timing overlaps with spawning periods of a suite of native fishes. We used acoustic telemetry and ichthyoplankton surveys to examine movement and spawning activity of multiple native species and to assess potential impacts of deterrent operation on reproduction. All species used the proposed deterrent location during the Grass Carp spawning period, and their movements corresponded with larval fish collections, indicating upstream spawning. These findings suggest the deterrent could unintentionally restrict native species’ access to essential habitats. Balancing habitat connectivity and invasive species control will likely depend on species-specific responses and careful timing of deterrent operation.

Ohio↗
USGS2026

Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

Journal of Hydrology↗
USGS2026

Subsurface water ice mapping on Mars: A probabilistic approach

Subsurface water ice deposits on Mars are an important resource for potential future human exploration. They are also an indicator of the planet’s past climate. However, the distribution of subsurface water ice in Mars’s midlatitudes is uncertain because spacecraft imagery cannot directly observe subsurface ice in most cases. Various spacecraft remote sensing instruments are sensitive to subsurface water ice, including thermal imaging spectrometers, radar sounders, and neutron spectrometers. Geomorphic analyses of images can also implicate subsurface ice. Building upon the data products from the Mars Subsurface Water Ice Mapping project, we provide a probabilistic framework to jointly interpret existing data and estimate the likelihood of subsurface water ice in the Martian midlatitudes between 60 ∘ S and 60 ∘ N with uncertainty. Broadly, we find that near-surface ice is likely present poleward of ∼45 ∘ in both the northern and southern hemispheres. However, closer to the equator, existing remote sensing data cannot uniquely constrain the presence of subsurface water ice. Our probabilistic results provide a framework for quantifying the abundance of ice on Mars, and our uncertainty estimates allow future analysis and exploration to target regions of high uncertainty.

Planetary Science Journal↗
USGS2026

Variability and consistency in wildfire susceptibility: Insights from a national compilation

Background Wildfire risk in the United States is rising and remains a land management priority. The quantitative wildfire risk assessment (QWRA) framework integrates fuels, topography, weather and values at risk to estimate the potential change in value from wildfire. Within this, response functions (RFs) represent how values respond to fire intensity. These are often based on expert judgment, but variation across assessments is unclear. Aims This study uses data from the US Geological Survey (USGS) Wildfire Hazard and Risk Assessment Clearinghouse to characterize consistency and variation across categories and contexts. Methods We applied descriptive statistics to summarize RFs, using tables, box-and-whisker plots and heat maps stratified by highly valued resource or asset (HVRA) category and spatial scale. Key results RFs and value definitions vary, especially for ecosystem-related resources. Some functions, such as for buildings in the wildland–urban interface (WUI), translate well across contexts, while others require more input. Conclusions Some functions are broadly transferable, while others need customization. This analysis provides references and starting points for improvement to RFs in QWRAs. Interpretations Expanding the clearinghouse and dataset and building more transparency in expert elicitation can build trust among communities, agencies and end-users, and can support efficient use of limited resources to mitigate wildfire risk.

International Journal of Wildland Fire↗
USGS2026

Opportunities for the U.S. Geological Survey’s National Seismic Hazard Model to improve seismic risk assessment of critical infrastructure.

As fragility and risk modeling techniques and computational capabilities evolve, complemented by moving toward more routine and systematic seismic risk assessment of all buildings and critical infrastructure, the authors pose a few critical questions to investigate how the U.S. Geological Survey (USGS) National Seismic Hazard Models (NSHMs) can be used and enhanced further to serve such issues. In this paper, we use three examples from multiple sectors to (1) identify the role of USGS NSHMs in evaluating seismic risks to critical infrastructure, (2) quantify potential impacts from NSHM enhancements (i.e., [i] hazard curves for the vertical component of ground motion, [ii] stochastic event sets, and [iii] maps of probabilistic ground failure hazards), and (3) clarify the feasibility of relevant NSHM improvements. We illuminate that NSHMs are commonly used in location-specific performance assessments, whereas earthquake effects on critical infrastructure can be widespread across large geospatial regions. Further, we found that without the NSHM extensions considered here, risk can be severely underestimated, e.g., neglecting ground failure hazards can underestimate regional loss by a factor of two or more. Although many challenges remain, we developed example prototypes to clarify the feasibility of the NSHM extensions, which can facilitate improved management of risks to critical infrastructure.

Earthquake Spectra Journal↗
USGS2024

Earthquake cycle mechanics during caldera collapse: Simulating the 2018 Kīlauea eruption

In multiple observed caldera-forming eruptions, the rock overlying a draining magma reservoir dropped downward along ring faults in sequences of discrete collapse earthquakes. These sequences are analogous to tectonic earthquake cycles and provide opportunities to examine fault mechanics and collapse eruption dynamics over multiple events. Collapse earthquake cycles have been studied with zero-dimensional slider-block models, but these do not account for the complicated interplay between fluid and elastic dynamics or for factors such as the heterogeneous fault properties and non-vertical ring fault geometries often inferred at volcanoes. We present two-dimensional axisymmetric mafic piston-like collapse earthquake cycle models that include rate-and-state friction, fully-dynamic elasticity, and compressible viscous fluid magma flow. We demonstrate that collapse earthquake intervals and magnitudes are highly sensitive to inertial effects, evolving stress fields, fault geometry, and depth-varying fault friction. Given the consistent earthquake cycles observed in most eruptions, this suggests that ring faults can quickly stabilize and often become nearly vertical at depth. We use the well-monitored 2018 collapse sequence at Kı̄lauea as a case study. Our model can produce many features of Kı̄lauea seismic and geodetic observations, except for a significant amount of interseismic slip, which cannot be readily explained with simple rate-and-state friction parameterizations.

Hawaii↗
USGS2024

Taking heat (downstream): Simulating groundwater and thermal equilibrium controls on annual paired air–water temperature signal transport in headwater streams

Headwater stream temperature often exhibits spatial variation at the kilometer-scale, but the relative importance of the underlying hydrogeological processes and riverine perturbations remains poorly understood. In this study, we investigated the relative importance of groundwater (GW) and other processes on downstream annual stream temperature signal characteristics using deterministic heat budget model (HFLUX) scenarios within an idealized stream reach representative of mountainous forested conditions. We summarized annual stream thermal regimes from the relationship of paired sinusoidal air and water temperature signals (amplitude ratio, phase lag, and mean ratio). Results showed that downstream changes in annual temperature depended on the thermal gradient between water and the hypothetical equilibrium temperature (where all heat fluxes sum to zero). GW inflow, riparian shading, and the boundary input signal were the most significant factors affecting downstream annual water temperature signals, while flow volume and channel dimensions impacted how quickly annual temperature signals changed. Effects of GW were dominated by advective rather than conductive heat exchange processes, but conduction played a larger role when GW input was more spatially diffuse. Our results indicated several mechanisms by which local processes may affect stream thermal resilience to disturbances and can help guide management of wildfire and climate change.

Journal of Hydrology↗