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Hyperspectral (VNIR-SWIR) analysis of roll front uranium host rocks and industrial minerals from Karnes and Live Oak Counties, Texas Coastal Plain

VNIR-SWIR (400–2500 nm) reflectance measurements were made on the surfaces of various cores, cuttings and sample splits of sedimentary rocks from the Tertiary Jackson Group, and Catahoula, Oakville and Goliad Formations. These rocks vary in composition and texture from mudstone and claystone to sandstone and are known host rocks for roll front uranium occurrences in Karnes and Live Oak Counties, Texas. Spectral reflectance profiles, 569 in total, were reduced to 125 representative spectral signatures, which were analyzed using the U.S. Geological Survey's (USGS) Material Identification and Characterization Algorithm (MICA). MICA uses an automated continuum-removal procedure together with a least-squares linear regression to determine the fit of observed sample spectral absorption features to those of reference mineral standards in a spectral library. The reference minerals include various clay, mica, carbonate, ferric and ferrous iron minerals and their mixtures. In addition, absorption feature band-depth analysis was done to identify rock surfaces exhibiting absorption features related to uranium and zeolite minerals, which were not included in the command files used to execute MICA. Rocks from each of the four geologic units produced broadly similar spectral signatures as a result of comparable mineral compositions, but there were some notable differences. For example, Ca- and Na-montmorillonite was matched most frequently to the spectral absorption features in 2-μm (∼2000–2500 nm) wavelengths, while goethite occurred often at 1-μm (∼400–1000 nm) wavelengths. The latter is related to limonitic iron-staining in and around oxidized zones of the uranium roll front as described in previous papers. Rocks of the Jackson Group differed from those of the Catahoula, Oakville and Goliad units in that the former exhibited spectral features we interpret as being due to the presence of lignite-bearing mudstone layers. Goliad rocks exhibit spectral features related to dolomite, gypsum, anhydrite, and an unidentified green clay mineral that is possibly glauconite . Jackson Group rocks also exhibit weak but well-resolved absorption features at 964 and 1157 nm related to either or both zeolite minerals clinoptilolite and heulandite. These zeolite minerals and a few spectra exhibiting hydrous silica absorption features are indicative of alteration of volcanic glass in tuffaceous mudstone and claystone layers. A few sample spectra exhibited strong absorption features at around 1135 nm related to the uranium mineral coffinite. Both the 1135 nm coffinite and 1157 nm zeolite absorption features overlap somewhat, potentially making them difficult to distinguish without additional hyperspectral field, laboratory or remote sensing data. The results of this study were compared to mixtures of minerals described for ore, gangue and alteration minerals in deposit models for sandstone-hosted uranium, sedimentary bentonite and sedimentary zeolite. Use of these spectra can help facilitate mapping of both waste materials from the legacy mining of the above commodities, as well as future exploration and resource assessment activities.

Texas

Surface-wave relocation and characterization of the October 2023 tsunamigenic seismic unrest near Sofugan volcano, Izu Islands, Japan

A moderate-magnitude earthquake swarm occurred in the remote Izu Islands region of Japan between October 1 and 8, 2023. The swarm included 151 shallow earthquakes cataloged by the U.S. Geological Survey, which notably included a roughly 2.5-hr episode of 15 successive magnitude (M) < 5.5 earthquakes. Origin times were coincident with regionally recorded tsunami waves, but tsunamigenesis for moderate-magnitude earthquakes is uncommon, indicating that volcanic activity generated the ocean displacements. Leveraging a surface-wave relative relocation approach, we estimate precise epicentroid locations for the remote swarm. Final epicentroids and caldera analogs indicate a three-stage model to explain swarm activity: (a) caldera pressurization due to magma intrusion, (b) depressurization via dike propagation away from the caldera, and (c) eruption corresponding with caldera reactivation either by collapse or additional intrusion.

Sofugan volcano, Izu Islands

Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)

Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.

Alaska

Origin and evolution of mafic volcanism associated with 3 m.y. of andesite production at the Goat Rocks volcanic cluster, southern Washington Cascade Range

More than 3 m.y. of mafic volcanism near the Goat Rocks volcanic cluster in the southern Washington Cascade Range, USA, lends insight into the evolution of basalts and the subarc mantle at a long-lived, major arc volcanic locus. We contribute field observations, 40 Ar/ 39 Ar dates, paleomagnetic directions, and bulk rock and mineral compositions to characterize nine mafic units that erupted in association with the Goat Rocks volcanic cluster. The time frame of mafic volcanism, ca. 3.6 Ma to 60 ka, encompasses the lifespan of the central volcanic cluster (3.1 Ma to 115 ka), with a lull from ca. 2.7 Ma to 1.4 Ma. A climactic period of voluminous mafic activity and far-traveled lava flows, including construction of the Hogback Mountain shield volcano, coincided with voluminous andesite eruptions from the central volcanic cluster. The basaltic rocks in the Goat Rocks area are calc-alkaline to barely tholeiitic and have high field strength element depletion relative to large-ion lithophile elements characteristic of calc-alkaline basalts (CAB) of the Cascade volcanic arc. Unlike at neighboring andesitic volcanic centers (Mounts Adams, St. Helens, and Rainier), no other mafic end members such as high-aluminum olivine tholeiite (HAOT) or intraplate-type basalt (IPB) are present at or near the Goat Rocks volcanic cluster, although some of the calc-alkaline basalts in this study have IPB-like affinities. The Goat Rocks mafic units exhibit two main temporal trends in composition: (1) the most primitive basalts erupted earlier, compared to less primitive and more evolved compositions later, and (2) high field strength element concentrations are higher in the younger basalt units relative to the oldest two. In contrast to these temporal trends, the mafic units define two compositional groups that recur through time, a low-Sr and a high-Sr group, each with distinct trace element and Sr and Nd isotope ratios. Although radiogenic isotope ratios are generally aligned with High Cascades CAB and HAOT, some extend toward IPB of Mount Adams and Simcoe Mountains volcanic field. Olivine-dominated crystal fractionation at shallow pressure from a small range of parent magma compositions accounts for much of the variation among the basalts and basaltic andesites. A high-pressure fractionation model is plausible for only one of the youngest basalt units (basalt of Walupt Lake volcano). Mafic recharge and crustal assimilation accounts for the incompatible-element enriched composition of basaltic andesites erupted during construction of the largest andesitic centers, further supporting sustained basalt mass flux and thermal energy driving andesite genesis. We model the most primitive members of the Goat Rocks mafic units as partial melts of successively less depleted mantle in time. Variable degrees of fluxing with fluids and melts from subduction explain the distinction between high-Sr and low-Sr groups. We propose that mantle metasomatism by ancestral subduction and fluid-flux melting is heterogeneously distributed through the local subarc mantle and played a greater role in the genesis of the high-Sr basalt group. The limited range of primitive basalt types around the Goat Rocks volcanic cluster contrasts with the much greater diversity of basalts throughout the southern Washington to northern Oregon Cascade arc. On the other hand, the central volcanic cluster encompasses nearly the entire diversity observed at neighboring composite volcanoes. In the case of the Goat Rocks area at least, and perhaps attributable to the entire region, this means that the genesis of diverse intermediate magmas is independent from and does not require vastly different parental basalt compositions.

California, Oregon, Washington

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

Comptes Rendus. Géoscience

Per- and polyfluoroalkyl substances in waters associated with oil and gas development in the Denver Basin

Use of per- and polyfluoroalkyl substances (PFAS) in the petroleum industry could be a cause for concern due to the large volumes of produced water (PW) generated during oil and gas extraction, the reuse of these wastes in water-stressed regions, and adverse health outcomes related to PFAS exposures. However, PW PFAS characterization is nearly absent in the literature, and hydraulic fracturing (HF) chemical disclosures often omit the identities of additives as proprietary. Here we evaluate PFAS in PW samples from three petroleum wells in the Denver Basin during their first year of production. Total concentrations of targeted PFAS (Σ 40 PFAS) were < 35 ng/L in PW samples, with short-chain PFAS like perfluorobutanoic acid persisting throughout the sampled duration. Analysis of freshwater inputs for hydraulic fracturing (Σ 40 PFAS ~ 113 ng/L) and mixed fracture fluid (Σ 40 PFAS ~ 69 ng/L) indicated much of the targeted PFAS content was derived from the input water, and not from HF additives, however samples subjected to oxidation indicated the presence of PFAS precursors that would not be detected by targeted analysis. This study highlights that while PFAS content is low in the studied PWs, the potential for redistribution of PFAS in the environment may be a consideration for reuse applications.

Colorado, Nebraska, Wyoming

Deep-ocean macrofaunal assemblages on ferromanganese and phosphorite-rich substrates in the Southern California Borderland

Mineral-rich hardgrounds, such as ferromanganese (FeMn) crusts and phosphorites, occur on seamounts and continental margins, gaining attention for their resource potential due to their enrichment in valuable metals in some regions. This study focuses on the Southern California Borderland (SCB), an area characterized by uneven and heterogeneous topography featuring FeMn crusts, phosphorites, basalt, and sedimentary rocks that occur at varying depths and are exposed to a range of oxygen concentrations. Due to its heterogeneity, this region serves as an optimal setting for investigating the relationship between mineral-rich hardgrounds and benthic fauna. This study characterizes the density, diversity, and community composition of macrofauna (>300 μm) on hardgrounds as a function of substrate type and environment (depth and oxygen ranges). Rocks and their macrofauna were sampled quantitatively using remotely operated vehicles (ROVs) during expeditions in 2020 and 2021 at depths above, within, and below the oxygen minimum zone (OMZ). A total of 3,555 macrofauna individuals were counted and 416 different morphospecies (excluding encrusting bryozoans and hydrozoans) were identified from 82 rocks at depths between 231 and 2,688 m. Average density for SCB macrofauna was 11.08 ± 0.87 ind. 200 cm −2 and mean Shannon-Wiener diversity per rock (H′ [loge] ) was 2.22 ± 0.07. A relationship was found between substrate type and macrofaunal communities. Phosphorite rocks had the highest H′ of the four substrates compared on a per-rock basis. However, when samples were pooled by substrate, FeMn crusts had the highest H′ and rarefaction diversity. Of all the environmental variables examined, water depth explained the largest variance in macrofaunal community composition. Macrofaunal density and diversity values were similar at sites within and outside the OMZ. This study is the first to analyze the macrofaunal communities of mineral-rich hardgrounds in the SCB, which support deep-ocean biodiversity by acting as specialized substrates for macrofaunal communities. Understanding the intricate relationships between macrofaunal assemblages and mineral-rich substrates may inform effects from environmental disruptions associated with deep-seabed mining or climate change. The findings contribute baseline information useful for effective conservation and management of the SCB and will support scientists in monitoring changes in these communities due to environmental disturbance or human impact in the future.

California

3D semantic mapping of surface geological features

Semantic mapping in 3D is fundamental to a wide range of geoscientific studies and applications, including geomorphology, hazard assessment, and environmental monitoring. However, automatically segmenting geological features from large-scale photogrammetric datasets remains a significant challenge. We present a methodology to address this gap. Using overlapping images collected over environments of interest, Structure-from-Motion (SfM) produces georeferenced point clouds and estimates camera poses. Existing large vision models, such as Segment Anything Model, segment objects in the images, generating pixel-segmentation associations. To produce pixel-point associations, we project the points back onto the camera image planes. As objects are independently segmented across multiple images with different perspectives, we develop a segmentation mosaicking algorithm to build probabilistic point-segmentation associations that combines the pixel-segmentation associations and pixel-point associations. Our methodology is validated using both synthetic data generated by Kubric and real-world UAV-SfM data. The implementation is designed to be compatible with existing SfM software, including Agisoft and OpenDroneMap, for photogrammetry mapping in geoscience studies. As a case study, we apply our method to the semantic mapping of precariously balanced rocks (PBRs), which provide upper-bound constraints on historical ground motion shaking intensity. To support object-level identification of PBRs, we additionally integrated Grounding DINO, enabling text-prompted segmentation of features of interest within UAV imagery. This case study demonstrates the effectiveness of our method in generating a 3D semantic map of PBRs, enabling spatial distribution of PBR fragility for earthquake hazard analysis.

Computers & Geosciences

The Sand AbrasioN Device for Aeolian Research (SANDAR): A new experimental device for investigating how wind transport affects sand on Earth and Mars

On Earth and Mars, aeolian transport causes sand grains to become abraded, resulting in mineralogic and textural changes. Understanding how sands evolve, or mature, with transport via experimental studies is important for understanding the origins, geologic history, and cycling of sediments, as well as dust production. Previous experimental works have used a variety of methods to simulate aeolian transport in the laboratory, but practical limitations and similitude concerns have limited such research. Here, we present and validate the Sand AbrasioN Device for Aeolian Research (SANDAR), a modified air mill that uses pressurized air to circulate sand around a small abrasion chamber, simulating the effects of aeolian transport. This device is re-circulating to simulate long-distance transport, and it allows for repeated analyses of well-constrained sediment samples, revealing their evolution over time. It is compatible with the grain sizes (74–500 μm) and grain impact velocities (∼0.6–3.7 m/s) typically expected for natural aeolian environments, and is also adaptable for diverse applications simulating different wind conditions. We show that the SANDAR achieves similitude of kinetic energy with respect to saltating sand on both Earth and Mars. SEM and optical microscope imaging reveal that the SANDAR produces microtextures on the surfaces of sand grains similar to those found with natural aeolian transport, demonstrating that it effectively simulates the mechanical effects of aeolian processes. Thus, the SANDAR is a valid tool for use in experimental research to improve our understanding of sedimentary processes across the Solar System.

Aeolian Research

Land application of drill waste: A scope analysis

Drilling fluid waste land application, a process where drilling wastes are spread and tilled into the land surface, has become common in some petroleum-producing states, however, the potential benefits and risks of this practice are not well studied. Drilling fluids can be water- or oil-based and can have high concentrations of total soluble salts and total petroleum hydrocarbons. Comprehensive chemical characterization of these fluids is not well documented in the literature, and the extent of land application is largely unknown. We hypothesized that the land application of drill waste would fluctuate over time due to economic factors. To begin to understand the extent of historical and potential future land application, we analyzed data from over 5,800 drilling fluid land application permits collected by the Oklahoma Corporation Commission for years 2000, 2005, 2010, and 2015–2020. During the years studied, drilling fluid wastes were applied to more than 250,000 acres in Oklahoma, with over 54,000 thousand barrels (Mbbl) of liquids and nearly 21,000 Mbbl of solids applied. Land application is widespread (occurring in 59/77 counties), however recent drilling activity, land availability, and the economics of transportation have created conditions favorable for land application specifically in the Anadarko Basin. Land application can co-occur with sensitive areas, such as important groundwater and surface-water drinking sources and agricultural fields used for subsistence or feed crop production. Our approach for quantifying the extent of land application, along with further chemical characterization studies, can aid operators and land managers who are considering this practice in assessing the associated benefits and risks.

Oklahoma

Monitoring marine eruptions

Introduction Submarine volcanoes produce much of the same seismicity and eruptive activity as subaerial volcanoes and can pose hazards to society. Although they can be monitored with similar techniques and methods as described in other chapters of this volume, their submerged location brings unique challenges. This chapter addresses these challenges and provides recommendations for monitoring volcanoes fully or partly in marine environments to meet the capabilities described in other chapters of this volume. The United States and its territories host dozens of submarine volcanoes with most (around 60) in the Commonwealth of the Northern Mariana Islands. Approximately 20 of the Northern Mariana Islands submarine volcanoes are known to be hydrothermally active, and 10 have confirmed eruptions since the 1950s (for example, Baker and others, 2008; Tepp and others, 2019a). Nine of those volcanoes were considered by the National Volcanic Threat Assessment (Ewert and others, 2018) to have a combination of eruptive type and summit depth that poses a higher risk of hazardous eruptions, although only one was listed as a moderate (level 3) threat. Other notable submarine volcanoes of interest to the United States that have historically erupted are Axial Seamount off the Washington State coast, Kamaʻehuakanaloa in Hawaiʻi, and Vailuluʻu seamount in American Samoa. All of these, however, have a low risk of hazards because of their depth (greater than 600 meters below sea level) and eruptive type and so are not included in the National Volcanic Threat Assessment. In addition to submarine volcanoes, the submerged flanks of island volcanoes can also be a source of hazardous submarine eruptions—for example, the 1877 eruption of Mauna Loa, Hawai‘i, in Kealakekua Bay (Wanless and others, 2006). The most notable submarine eruption in recent times was the 2022 eruption of Hunga Tonga–Hunga Haʻapai in Tonga, which was one of the largest eruptions on Earth in the past 100 years. It created a massive volcanic plume, unprecedented shock waves, and far-reaching tsunami (Lynett and others, 2022). Other recent submarine eruptions in the Pacific Ocean Basin have produced subaerial plumes that reached aircraft heights (Carey and others, 2014) and large pumice rafts that can affect marine traffic and harbors (for example, Jutzeler and others, 2014; Kornei, 2019). These examples illustrate the potential hazards of major submarine eruptions. Yet, submarine volcanoes are largely unmonitored, and many eruptions occur that are unnoticed or only identified hours or days afterward. Within U.S. territory, submarine volcanoes in the Northern Mariana Islands have been known to produce eruptive activity that can affect society. Reports from fishermen and other marine vessels in the Northern Mariana Islands have noted underwater explosions, sea-surface discoloration, and bubbling water, all of which are known to be signs of submarine volcanic activity. South Sarigan seamount, located about 160 kilometers (km) north of Saipan, erupted in 2010 from greater than 150 meters below the sea surface, resulting in a gas and ash plume that reached more than 11.9 km into the atmosphere (for example, Searcy, 2013; Embley and others, 2014), high enough to affect international air traffic. Precursory and co-eruptive seismicity was detected on the regional Northern Mariana Islands seismic network (Searcy, 2013) and on global monitoring instruments (Green and others, 2013). Monitoring of submarine volcanoes is best accomplished with marine-based instrumentation, which is also useful for monitoring small island volcanoes that may not have the land area necessary for comprehensive subaerial monitoring. The primary marine-based instrumentation used for submarine volcanoes includes ocean-bottom pressure sensors to assess sea-floor deformation, ocean-bottom seismometers (OBSs) to detect seismicity, and both moored and ocean-bottom hydrophones to detect submarine explosions. Other sensors offer important monitoring data, such as turbidity, temperature, and chemistry of hydrothermal emissions. Marine-based instruments are typically deployed in campaign-style networks with no real-time telemetry owing to cost considerations and technical limitations. However, when necessary, marine instruments can be operated in real time using cables to transmit data to land-based facilities; other technologies for this purpose are in use or in development, such as acoustic transmission from the instrument to a moored buoy (Matsumoto and others, 2016) and a winch-based system with a satellite antenna that is part of the instrument mooring (Matsumoto and others, 2019). Emerging technologies for marine-based monitoring may be considered as part of a future monitoring plan. These technologies include ocean gliders and floats with on-board hydrophones that have been used to record earthquakes and submarine eruptions (for example, Matsumoto and others, 2013; Sukhovich and others, 2015) and fiber-optic cables that have been used as strainmeters to detect earthquakes (for example, Marra and others, 2018; Lindsey and others, 2019). Land-based instruments and satellites can also provide some capability for monitoring submarine volcanoes, but they provide more limited observations than marine-based instrumentation.

Scientific Investigations Report

Methods for quantifying interactions between groundwater and surface water

Driven by the need for integrated management of groundwater (GW) and surface water (SW), quantification of GW–SW interactions and associated contaminant transport has become increasingly important. This is due to their substantial impact on water quantity and quality. In this review, we provide an overview of the methods developed over the past several decades to investigate GW–SW interactions. These methods include geophysical, hydrometric, and tracer techniques, as well as various modeling approaches. Different methods reveal valuable information on GW–SW interactions at different scales with their respective advantages and limitations. Interpreting data from these techniques can be challenging due to factors like scale effects, heterogeneous hydrogeological conditions, sediment variability, and complex spatiotemporal connections between GW and SW. To facilitate the selection of appropriate methods for specific sites, we discuss the strengths, weaknesses, and challenges of each technique, and we offer perspectives on knowledge gaps in the current science.

Annual Review of Environment and Resources

Methods and guidelines for effective model calibration; with application to UCODE, a computer code for universal inverse modeling, and MODFLOWP, a computer code for inverse modeling with MODFLOW

This report documents methods and guidelines for model calibration using inverse modeling. The inverse modeling and statistical methods discussed are broadly applicable, but are presented as implemented in the computer programs UCODE, a universal inverse code that can be used with any application model, and MODFLOWP, an inverse code limited to one application model. UCODE and MODFLOWP perform inverse modeling, posed as a parameter-estimation problem, by calculating parameter values that minimize a weighted least-squares objective function using nonlinear regression. Minimization is accomplished using a modified Gauss-Newton method, and prior, or direct, information on estimated parameters can be included in the regression. Inverse modeling in many fields is plagued by problems of instability and nonuniqueness, and obtaining useful results depends on (1) defining a tractable inverse problem using simplifications appropriate to the system under investigation and (2) wise use of statistics generated using calculated sensitivities and the match between observed and simulated values, and associated graphical analyses. Fourteen guidelines presented in this work suggest ways of constructing and calibrating models of complex systems such that the resulting model is as accurate and useful as possible.

Water-Resources Investigations Report

The Long Island Sound and Watershed Metadata map application

The Long Island Sound and its watershed encompass an area of about 17,000 square miles and include the Connecticut, Housatonic, and Thames Rivers, which all drain to the sound. Dozens of organizations from government agencies, nonprofits, and Tribal Nations have developed projects and monitoring programs to analyze and protect the water resources of the watershed and sound. The abundance of data and lack of an existing searchable index require a centralized metadata repository to allow users to find water resources data more efficiently. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency and the Long Island Sound Study, has created an interactive map application to visualize and search for metadata information across organizations working to monitor and protect the Long Island Sound.

Connecticut, Massachusetts, New Hampshire, New Yor

An evaluation of the effects of different deicing salt application rates on three watersheds in Essex County, New York

The U.S. Geological Survey, in cooperation with the New York State Department of Transportation, evaluated the effects of different deicing salt application rates on surface water, groundwater, and highway runoff quality near State highways in northern New York. Three reaches of State highways were tested with different deicing treatments between October 2019 and November 2022: a salt-sand mixture (Treatment A), a salt mixture applied at a lower rate (Treatment B), and a control mixture consistent with typical deicing salt amounts and application rates. Data on pavement conditions and the quality of surface water, highway runoff, and groundwater were collected. Surface electromagnetic data were also collected. Surface-water and groundwater quality downgradient from the State highways were compared with water quality at upgradient locations. The percentage of snow or ice coverage was used to evaluate the effectiveness of the salt applications. This report provides an overview of the transport of deicing salt. The Treatment B watershed had deicing mixture applied more frequently than other highway reaches, which caused it to have the highest annual total chloride application. Despite differences in chloride application, flow-weighted mean chloride concentrations in highway runoff were comparable across treatments. Chloride concentrations were elevated in surface water and groundwater downgradient from highways relative to chloride concentrations upgradient from highways. A chloride mass balance, calculated for one treatment watershed, indicated that groundwater affected by legacy deicing practices may be contributing additional chloride to surface water. Spatial patterns from electromagnetic surveys show a shallow saline plume alongside the highway in that area. Differences in winter severity and pavement-surface conditions drove deicing salt applications in the treatment areas. This study found that several factors affect chloride loads in the watersheds, including variable winter conditions, adaptive snow and ice management, legacy management practices, and area-specific aquifer and groundwater conditions.

New York

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

Review and synthesis of the applications of machine learning to coalbed methane recovery

Over the last 30 years, a substantial literature has evolved on the use of machine learning (ML) to assess, predict, and improve the efficiency of coalbed methane (CBM) recovery. In the United States, the production of CBM declined as shale gas production matured, but CBM continues to be an important energy resource in other parts of the world. ML applications that have the potential to improve CBM reservoir management and production forecasts, and to increase exploration and operational efficiency, are still of significant interest. The integration of geostatistical techniques into the CBM ML applications has been largely absent but represents an opportunity for improvement. The literature demonstrates the widespread interest in, and applicability of, ML algorithms applied to CBM problems, and that they continue to result in improvements in predictive performance. However, (1) much of the research is more academic than operational, (2) many results are based on simulations, or small or proprietary datasets, (3) ML performance information can be inconsistent and sometimes entirely omitted, (4) most methodologies are unique to the specific CBM situation and likely not generalizable, (5) no standard data repositories are available to directly compare the performance of competing algorithms, and (6) the spatial component is often omitted. Finally, relatively new ML protocols involving causality analysis and reinforced learning, as well as hybrid workflows combining both supervised and unsupervised learning, are anticipated to dominate the future investigations. Integration of geostatistical and geospatial analysis with ML should enhance performance.

Book chapter

Assessment of western Oregon debris-flow hazards in burned and unburned environments

In the steep and mountainous environment of western Oregon, debris flows pose a considerable threat to property, infrastructure and life. Wildfire is commonly known to increase the susceptibility of steep slopes to debris flows, but the extent of this process in the western Cascades is not well understood. The US Geological Survey (USGS) currently estimates postfire debris-flow likelihood and triggering rainfall thresholds using a model calibrated to a southern California inventory of debris flows generated by excess runoff within the first year after fire. Because of a lack of available data, this model has not been tested in western Oregon, or in locations where postfire debris flows initiate via other mechanisms (e.g., shallow landslides or in-channel failures). Using repeat field observations and aerial imagery, we developed two new debris-flow inventories within and adjacent to the perimeters of five 2020 wildfires in western Oregon: Archie Creek, Holiday Farm, Beachie Creek, Lionshead and Riverside. The first inventory focuses on postfire debris flows (2020–2022); the second focuses on debris flows prior to fires (1995–2020). Our inventories of prefire and postfire debris flows were used to document initiation mechanisms in Oregon's western Cascades and to evaluate the effects of wildfire. We found that wildfire changed the distribution of debris-flow initiation mechanisms in the western Cascades. After the wildfires, annual rates of runoff-generated debris flows increased by 22% and the number of shallow landslide-initiated debris flows decreased by 17% relative to before the wildfires. Despite this shift, shallow landsliding was the dominant debris-flow initiation mechanism in both unburned and burned environments. We found the performance of the current USGS debris-flow likelihood model was degraded relative to other previously tested locations across the intermountain western United States. Our results highlight the need for improved postfire hazard assessment in western Oregon based on regional model calibration that is tuned to the dominant debris-flow initiation mechanisms.

Oregon