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244 records · Page 4Linked to original sources

Geophysical identification of potential groundwater – surface water interactions in the Bonita Peak Mining District, San Juan County, Colorado

This report includes the results and interpretation of geophysical investigations to aid in the location, identification, and conceptual site model (CSM) development of the near surface groundwater and surface water hydrology of the Upper Cement Creek and California Gulch of the Animas Rivers within the Bonita Peak Mining Districts (BPMD). Mine influenced water (MIW) from numerous mine adits within the BPMD has altered the geochemistry and ecology of these ground and surface waters. Many studies of varying scales have investigated the geology, hydrogeology, geochemistry, and aqueous chemistry of these adits and impacted areas. Field investigations using non-invasive geophysical methods were conducted in the summer of 2019 to aid in identifying potential groundwater inputs to these streams and further the CSM of the near surface within and along these streams. Two field deployments were completed in August and September of 2019. In August 2019, Phase 1 was completed using multifrequency electromagnetic induction (EMI) and thermal infrared imaging (TIR) to measure the bulk electrical conductivity, magnetic susceptibility, and the temperature response at known and suspected groundwater seeps into the Upper Cement Creek and California Gulch stretches of these alpine streams. Results and interpretation from Phase 1 were used to co-locate stretches of these streams for further detailed fiber optic distributed temperature system (FODTS) monitoring of the temperature dynamics for submeter identification of potential groundwater seeps during Phase 2. Phase 2 included additional EMI measurements, FODTS measurements, and repeated some Phase 1 measurements for improved data quality. All these data were used for the combined qualitative interpretation identifying seep locations. The data from both Phase 1 and Phase 2 are available in the USGS data release at: https://www.sciencebase.gov/catalog/item/5f18a30082cef313ed84879b. These data include detailed near-surface electrical conductivity and magnetic susceptibility mapping, discrete TIR imaging, and several kilometers of FODTS data. These data were georeferenced and used to identify potential groundwater seeps into these streams. The results indicate a complex near surface geophysical and hydrogeologic regime. Seeps are classified and spatially correlated to the EMI, TIR, and geochemical sampling results. This report is a thorough compilation of the geophysical field efforts in the summer of 2019, the data processing, and interpretations of these data. These data alone should not be used for final interpretations of the complex hydrogeology within these alpine systems. Rather, these data should be combined with other known data from various investigations to further refine the CSM and guide decisions for future investigations, watershed protective measures, and other site decisions. Geographical information system (GIS) layers of these results are available to project managers for such integration and combined interpretations.

Colorado

Multi-scale predictors of Northern Long-eared Bat (Myotis septentrionalis) occupancy in the United States

Historically, Myotis septentrionalis (Northern Long eared Bat) was among the most common forest-interior species in North America. Largely due to high mortality from white-nose syndrome, this species has experienced severe population declines across its range. To create an updated species distribution map representing summer occupancy probabilities from 2017 to 2022, we integrated stationary acoustic data with live-capture data from the database of the North American Bat Monitoring Program into a multi-scale, multi-method occupancy modeling framework. Our results provide data-driven predictions with quantified uncertainty for summer occupancy probabilities for Northern Long-eared Bats at 2 spatial scales across the range of the species, while also accounting for inherent observation biases (e.g., imperfect detection).

Journal of North American Bat Research

Imaging of seismic discontinuities using an adjoint method

For imaging of seismic discontinuities at depth, reverse time migration (RTM) is a powerful method to apply to recordings of seismic events. It is especially powerful when an extensive receiver array, numerous seismic sources, or both, permit adequate reconstruction of incident and scattered wavefields at depth. Reconstructing either the incident or scattered wavefield at depth becomes less accurate when relatively few recordings of seismic events are available. Here we explore an inverse scattering approach to imaging discontinuities based on an adjoint method, employing sensitivity kernels (Frechet derivatives) that represent jumps in material properties across seismic-discontinuity surfaces. When combined with ray-based requirements on scattering geometry, it constitutes a powerful approach to determining the locations and amplitudes of the discontinuities, recovering only those properties that can be resolved by a spatially limited source and/or receiver distribution. This is illustrated by synthetic examples with local sources followed by a field example in a subduction zone setting

Washington

Deep syntectonic burial of the Anthracite belt, Eastern Pennsylvania

Fluid inclusion microthermometry and Raman spectroscopy of fluid inclusions in quartz veins from the Pennsylvanian rocks of the Anthracite belt, eastern Pennsylvania support a deep burial model of coalification in favor of focused orogenic hot fluid flow. High-temperature (250 to 255 °C) trapping of CH 4 ± CO 2 saturated aqueous fluids and CH 4 ± CO 2 inclusions indicate fluid trapping at depths of 11.5 to 13.4 km under a cover of Pennsylvanian to Permian(?) syntectonic load. In the folded rocks to the south of the Anthracite belt, CH 4 ± CO 2 fluid inclusions indicate a sediment load that was up to 16.3 km thick. Re -equilibrated aqueous fluid inclusions from veins in Silurian through Devonian rocks give the same range of trapping conditions but a wide range of fluid salinities suggesting that folding, fracturing, and meteoric recharge resulted in the intermixing of fluids from throughout the stratigraphic succession.

Pennsylvania

Solute transport and modeling of water quality in a small stream

An injection of chloride, sodium, and stable strontium was made at a constant rate for 3 hours into Uvas Creek, Santa Clara County, Calif., to determine the mass transport processes in a small stream. Five observation points were selected within a 610-metre reach of the stream below the injection site. Water samples were collected at the observation points during and immediately after the injection. A mathematical model of the stream was obtained by solving analytically and optimally the one-dimensional mass transport equation of the solutes in the stream. Comparison of field results with a simplified mathematical model indicates the dominance of convection in the behavior of sodium and chloride. The concentration of chloride and sodium can be closely simulated by the model. However, strontium cannot be well represented by the simplified model, which contains a first-order decay-type sink.

California

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

Statewide surficial geologic map of Nebraska underscores Quaternary landscape evolution from the High Plains to the Central Lowland

Surficial geologic mapping in Nebraska has been conducted primarily at the 1:24,000 scale since the mid-1990s, although there have also been limited efforts to map generalized Quaternary and surficial geology within the state and the region. We compiled and evaluated disparate maps (1:24,000–1:1,000,000) and datasets—including geologic, soil and soil parent material, and geomorphic maps as well as LiDAR derivatives—to produce a single 1:500,000 scale surficial geologic map of Nebraska that is the first of its kind. This new map provides a coarse-scale surficial geologic map that will be incorporated into a nationwide U.S. Geological Survey Quaternary geologic map. It also reflects the variation and uniqueness of physical landscapes in the state, where the Great Plains and Central Lowland physiographic provinces meet, further developing a richer interdisciplinary understanding of regional geomorphology in the heart of North America.

Nebraska

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

Prospectivity modeling of the NASA VIPER landing site at Mons Mouton near the Lunar South Pole

We use a high-resolution digital elevation model and a numerical thermal model to produce a variety of inputs for a water-ice prospectivity model for the Volatiles Investigating Polar Exploration Rover (VIPER) landing site. These input data are maps of topography, surface slope, surface aspect, surface curvature, maximum temperature, depth to ice stability, permanently shadowed regions (PSRs), distance to PSRs, and PSR density. This model predicts where water ice is most likely within the top meter of regolith, assuming plausible relationships between ice concentration and the various inputs. The model is designed to be adjusted in near-real time as data are collected during the VIPER mission. As such, it is a tool for both analyzing data from the mission as well as planning operations. Since the current model, at this point, relies only on orbital remote sensing, the final version will also be a tool to extrapolate the VIPER mission results across the lunar poles.

Planetary Science Journal

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

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

SUTRA— A code for simulation of saturated-unsaturated, variable-density groundwater flow with solute or energy transport—Documentation of the version 4.0 enhancements—Freeze-thaw capability, saturation and relative-permeability relations, spatially varying properties, and enhanced budget and velocity outputs

Version 4.0 of the Saturated-Unsaturated Transport (SUTRA) software code provides the capability to simulate the freezing and thawing of groundwater during energy transport simulations under saturated and unsaturated conditions. In addition to the types of hydrogeologic processes that SUTRA has been able to simulate in the past, this version can be used to study the effects of the freeze-thaw process on the flow and energy dynamics of hydrogeologic systems. The freeze-thaw simulation capability accounts for the latent heat of fusion and allows thermal property values to vary with changing total-water saturation, liquid-water saturation, and ice saturation. It allows the effective permeability of the porous medium to change as a result of freezing and thawing. This version also provides several user-selectable relations for the dependence of total-water saturation on fluid pressure, the dependence of liquid-water saturation on temperature during freezing and thawing, and the dependence of relative permeability on liquid saturation, as well as three user-selectable formulae for defining the bulk thermal conductivity of a mixture of solid grains, liquid water, ice, and air. For unsaturated simulations without freezing, the selectable total-water saturation relations eliminate the need for the user to program these and their associated relative-permeability functions, as had been required in previous SUTRA versions. Optional nonlinear dependence of fluid density on temperature, which covers the range from supercooled (about −50 degrees Celsius) to superheated (about 400 degrees Celsius), is also provided. Additionally, this version makes it possible to spatially vary parameters that, in previous versions of SUTRA, were required to be spatially uniform: solid-matrix properties, adsorption parameters, and parameters for production of solute mass or energy. Spatial variation is also allowed for the newly included freeze-thaw process parameters. Additional enhancements provide (1) output of water-mass and energy budgets that include values of all component terms in the governing balance equations, and (2) output of Darcy velocities (fluid fluxes), in addition to the velocity output provided by previous SUTRA versions. These enhanced outputs allow fuller interpretation of simulation results, especially for freeze-thaw phenomena. The set of processes simulated by this version of SUTRA are useful for studying a wide range of hydrogeologic system types, conditions, and questions. For cryohydrogeologic simulations, however, this version of the code is limited in that (1) it does not simulate thermomechanical effects of freeze-thaw, (2) pressure changes due to water density change during freezing are neglected, (3) ice saturation cannot exceed the initial porosity of the simulated medium, and (4) cryosuction, the migration of liquid water toward freezing fronts, is neglected. Furthermore, this version does not account for air flow or for water vaporization and sublimation under unsaturated conditions.

Techniques and Methods

Avian navigation: Comparing the olfactory navigational “map” and the infrasound direction-finding hypotheses to aeronautics

Animal navigation has long been a fascinating but bewildering subject. Humans and animals might well share similar navigational strategies because they developed within the same physical environments. A “map-and-compass” model has been proposed to explain the two-step avian navigational process, but the “map” step has remained elusive. Although scalar values from bicoordinate geomagnetic or atmospheric olfactory gradients have been considered foundational to the avian map, neither has proved convincing engendering decades of controversy. The olfactory map, and an alternative infrasound direction-finding (IDF) hypothesis, are discussed in this review. The olfactory map hypothesis currently requires extensive stable gradients of trace-odor ratios, but such gradients are highly unlikely within a turbulent and rapidly mixed lower atmosphere. The IDF hypothesis, on the other hand, postulates a two-step navigational model analogous to the maritime and aeronautical radio direction-finding technique. This review was also written to encourage further investigation, and direct testing, of the acoustic navigational process. The IDF hypothesis, at present, appears the better explanation of observed avian navigational behavior and accuracy within the atmosphere’s physical environment.

Journal of Comparative Physiology A

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

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

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

Localization of spatiotemporally heterogeneous subsurface flows using autoencoder-based deep learning framework for time-lapse self-potential tomography

Self-potential (SP) monitoring has emerged as a valuable method for characterizing subsurface hydrogeological features and processes due to its sensitivity to fluid-induced electrokinetic effects. Despite advancements in SP inversion, challenges remain in imaging groundwater dynamics from SP activities due to complex hydrological settings and transient noise. In this study, a deep learning autoencoder (AE)-based framework is proposed for the spatiotemporal localization of subsurface fluid movement from time-lapse SP tomography. Temporal segments of time-lapse numerical inversions were first derived from long-term SP monitoring conducted from a floodplain site in Oak Ridge, Tennessee, known for active hyporheic exchange. Subsequently, AE models based on vision transformer (ViT), convolutional long short-term memory (ConvLSTM), convolutional neural network, and temporal convolutional network were individually trained and compared on the SP tomography segments for reconstruction performance. Finally, the reconstruction error over time serves as an anomaly score to identify moments of active SP variation, whereas spatial distributions of errors within these moments are analyzed to image and localize regions associated with anomalous subsurface fluid movement. The results demonstrate that ConvLSTM- and ViT-AE are most capable for the localization task with contrasting error distributions and consistent delineation of anomalies. Applying the method to both SP arrays parallel and perpendicular to the stream produced consistent anomaly zones near a fault or karst feature, validating the robustness and generalization of the approach. These results demonstrate the potential of the proposed framework as a scalable and interpretable tool for spatiotemporal analysis of subsurface flow dynamics in complex hydrogeological systems.

Tennessee

Using probability difference to compare streamflow information of alternatives for efficient operation of monitoring networks

Efficient operation of streamflow monitoring networks requires investments in technology and labor that provide the greatest benefits from available resources. Economic analyses comparing the costs and benefits from different types of alternatives for monitoring have not been practical to implement. Streamflow information provides a generic measure of benefits that can be incorporated into operational decisions as an objective for monitoring networks. A methodology for comparing how accuracy, monitoring period, and monitoring instead of modeling affects streamflow information is developed from information-theoretic approaches for network design but contributes three novel features: (1) a probability-difference model for conditional probability of monotonically paired variables, (2) explicit discounting of unverified information that may exceed the accuracy of streamflow records, and (3) run analysis to account for non-stationarity in streamflow probabilities. Application of the methodology to the U.S. Geological Survey streamflow monitoring network indicates the value of monitoring period to reduce the uncertainty of streamflow probabilities and, thus, increase streamflow information. The methodology has important limitations, particularly for sites with non-perennial streamflow, but demonstrates that probability difference could be used to evaluate operational alternatives to increase the efficiency of monitoring networks.

PLOS Water