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USGS2024

Satellite interferometry landslide detection and preliminary tsunamigenic plausibility assessment in Prince William Sound, southcentral Alaska

Regional mapping of actively deforming landslides, including measurements of landslide velocity, is integral for hazard assessments in paraglacial environments. These inventories are also critical for describing the potential impacts that the warming effects of climate change have on slope instability in mountainous and cryospheric terrain. The objective of this study is to identify slow-moving landslides in the Prince William Sound region, southcentral Alaska, United States, which has had rapid deglaciation since the mid-1800s, and assess their tsunamigenic plausibility. We use an automated time series persistent scatterer interferometric synthetic aperture radar processing method with 7 years of Sentinel-1 data (2016–22) to identify 43 slow-moving slopes with average velocities ranging from approximately 0.2 to 21 millimeters per year. Landslide presence is confirmed using aerial imagery and previous landslide inventory records. We assess the tsunamigenic plausibility of the landslides using empirically derived estimates of landslide mobility based on modeled landslide volumes. Of the identified landslides, our preliminary analysis suggests that 11 have tsunamigenic potential if they were to fail rapidly and catastrophically. Although our estimate of tsunamigenic plausibility is preliminary and can be refined with additional observations and analyses, it can be used to prioritize ongoing and future hazard assessment, surveillance, and research efforts.

Alaska↗
USGS2024

Upper crustal seismic velocity structure of the Hayward fault zone, San Francisco Bay, California, USA: Results from the 2016 East Bay Seismic Experiment (EBSI-16)

We developed Vp, Vs, Vp / Vs ratio, and Poisson’s ratio models of the uppermost crust (<4 km depth) from the eastern San Francisco (SF) Bay (California, USA) to near the Calaveras fault along a 15-km-long, linear profile. Upper crustal velocities are highly variable beneath, west, and well east of the Hayward fault. We observe eight notable features, from west to east: (1) Near San Francisco Bay, there is an ~2-km-wide structure with high Vp / Vs ratios (up to 5) and Poisson’s ratios (up to 0.48) extending from the surface to the base of our model, which we suggest the structure is a near-vertical fault that lies along a straight-line projection between the Silver Creek fault to the south and the Point Richmond fault to the north. The structure may be part of an ~90-km-long fault along the eastern SF Bay. (2) The western East Bay Plain, the lower lying area between the bay and the hills, includes up to 800 m of low-velocity sediments ( Vp ~1600–3000 m/s, Vs ~500 m/s to ~1000 m/s), underlain by higher velocity basement rocks ( Vp ~3000–5800 m/s; Vs ~1000–1500 m/s). (3) Between ~1 km and 3 km east of the Bay shoreline, sediments thin in a series of steps (likely faults) toward the Hayward fault. (4) Between ~3 km west and ~1 km east of the Hayward fault (at the East Chabot fault) at depths greater than 1 km, basement Vp (up to 6000 m/s) and Vs (up to 2800 m/s) are high, and Vp / Vs ratios (<2) and Poisson’s ratios (<0.3) are low, suggesting crystalline rocks. Furthermore, a near-vertical zone of low Vp / Vs ratios and Poisson’s ratios is between near-surface traces of the Hayward and East Chabot faults, likely corresponding to the San Leandro Gabbro of Ponce et al. (2003) . (5) Eastward of the East Chabot fault in the upper 1.5 km, basement Vp (~3000 m/s to ~4200 m/s) and Vs (~1200–2000 m/s) are lower than those west of the fault. (6) In the eastern Hayward/Oakland Hills, there are zones of laterally varying, high- and low-velocity ( Vp ~2500–3000 m/s) Jurassic–Cretaceous and Tertiary sediments in the shallow subsurface that likely extend much deeper than imaged. (7) Seismic energy that propagates westward from sources east of the Hayward fault (HF) appear weaker than energy that propagates eastward from sources west of the HF, suggesting that the HF acts as a partial barrier to shallow seismic energy propagation into the more populated eastern SF Bay area. (8) Unlike many fault zones, it appears that the active trace of the Hayward fault (in our study area) is not cored by a prominent, low-velocity zone relative to rocks to the east and west of the active trace. However, the active trace does mark a prominent change from relatively higher velocities to the west and lower velocities to the east.

California↗
USGS2024

Water-quality characteristics of the Red River of the North and tributaries in the Fargo-Moorhead metropolitan area, North Dakota, 2019–22

The Flood Risk Management Project was initiated in 2008 in the Fargo-Moorhead metropolitan area to reduce flood risk, flood damages, and flood protection costs in the Fargo-Moorhead metropolitan area. In cooperation with the U.S. Army Corps of Engineers, the U.S. Geological Survey initiated a water-quality monitoring study to describe the water-quality characteristics of the Red River of the North and its tributaries in the Fargo-Moorhead metropolitan area during the preconstruction period of the Flood Risk Management Project from October 1, 2019, to October 1, 2022. The monitoring study included the collection of discrete and continuous water-quality data and streamflow monitoring at selected sites that integrated and enhanced existing monitoring programs within the study area. Discrete samples collected at 10 sites in the Fargo-Moorhead metropolitan area were analyzed for major ions, trace elements, nutrients, suspended sediment, pesticides, and fecal indicator bacteria. In general, major ion concentrations were higher at sites on the tributaries (Wild Rice, Sheyenne, and Maple Rivers) compared to sites on the Red River of the North. In general, bicarbonate, calcium, magnesium, and sulfate represented most of the dissolved ions measured in samples collected at the 10 sites. Calcium, chloride, fluoride, potassium, silica, and sodium were also measured in samples, but they represented a smaller portion of the total dissolved ions. Sulfate was the most dominant dissolved ion that had the highest concentrations among the major ions measured in samples. A total of 18 trace elements were analyzed in discrete samples. Several of the trace elements had concentrations below the laboratory reporting level in all of the samples, including antimony, beryllium, cadmium, chromium, silver, and thallium. Sites on the Wild Rice River generally had the highest concentrations of arsenic, barium, boron, manganese, and nickel compared to the other sites. Nutrients analyzed in discrete samples included filtered and unfiltered concentrations of ammonia, nitrate plus nitrite, phosphorus, and organic carbon. The median filtered ammonia concentration at most sites was less than the laboratory reporting level of 0.03 milligram per liter as nitrogen except for the Sheyenne River at Harwood, North Dakota (U.S. Geological Survey [USGS] station 05060400), and Red River of the North near Georgetown, Minnesota (USGS station 05062130). The lowest median unfiltered nitrate plus nitrite concentration was measured at sites on the Red River of the North upstream from the Fargo-Moorhead metropolitan area and the highest median was at sites on the Red River of the North downstream from the Fargo-Moorhead metropolitan area compared to all other sites. The increase in nitrate plus nitrite concentrations could reflect the effect of the wastewater-treatment plant discharge that enters the Red River of the North upstream from the site located downstream from the Fargo-Moorhead metropolitan area and from urban runoff. Phosphorus (unfiltered) concentrations were generally higher at sites on the Maple and Sheyenne Rivers compared to the other sites and were higher at sites on the Red River of the North downstream from the Fargo-Moorhead metropolitan area compared to sites upstream on the Red River of the North. Suspended-sediment concentrations were generally highest at sites in the Sheyenne River and lowest in the upstream Red River of the North sites. Suspended-sediment concentration was highly variable in samples collected at the 10 sites, mostly influenced by the occurrence of snowmelt and rainfall-runoff events. The Sheyenne River near Kindred, N. Dak. (USGS station 05059000) had the largest range in sediment concentrations in samples collected at the 10 sites. For all sites other than the Sheyenne River near Kindred, N. Dak., 95 percent or more of the suspended sediment had particle diameter sizes less than 0.0625 millimeter in 50 percent of the samples (median). Of the 102 pesticides and pesticide degradates analyzed, 45 constituents had no detectable concentrations in any of the 17 samples collected at five sites. The remaining 57 pesticides had at least one detection in the samples collected at the five sites. The sites on the Wild Rice River (near Abercrombie, N. Dak., USGS station 05053000, and near St. Benedict, N. Dak., USGS station 05053500) and Sheyenne River near Kindred, N. Dak., had fewer pesticide detections compared to the Maple River below Mapleton, N.Dak. (USGS station 05060100) and the Red River of the North at Fargo, N. Dak (USGS station 05054000) and near Georgetown, Minn. Patterns in annual loads generally followed the same pattern as streamflow at the 10 sites for water years 2020–22. A water year is the 12-month period from October 1 to September 30 and is designated by the calendar year in which it ends. The greatest loads for all constituents were delivered at the two downstream sites on the Red River of the North; sites that also had the highest annual streamflows among the sites and the greatest loads were delivered in water year 2020 when the highest streamflows occurred at the sites. Likewise, the least loads for most constituents were at the Maple River and were least in 2021 compared to the other years because of low-streamflow conditions. Water-quality measurements continuously recorded at the Red River of the North at Hickson, N. Dak. (USGS station 05051522); Red River of the North at Fargo, N. Dak.; and Red River of the North near Georgetown, Minn. included water temperature, specific conductance, dissolved oxygen, pH, and turbidity. Specific conductance values were similar for the Red River of the North near Hickson, N. Dak., and Red River of the North at Fargo, N. Dak., when compared to the Red River of the North near Georgetown, Minn. that had higher values than the other two sites. Dissolved oxygen concentrations and pH were similar among the three sites on the Red River. The patterns in turbidity were mostly related to streamflow conditions and were similar among the three sites on the Red River of the North.

Minnesota, North Dakota↗
USGS2024

Mafic alkaline magmatism and rare earth element mineralization in the Mojave Desert, California: The Bobcat Hills connection to Mountain Pass

Occurrences of alkaline and carbonatite rocks with high concentrations of rare earth elements (REE) are a defining feature of Precambrian geology in the Mojave Desert of southeastern California. The most economically important occurrence is the carbonatite stock at Mountain Pass, which constitutes the largest REE deposit in the United States. A central scientific goal is to understand the genesis of the carbonatite ore body in the context of widespread REE-rich igneous activity. A swarm of mafic alkaline (shonkinite) dikes has been mapped and sampled at Bobcat Hills, 65 km southeast of the Mountain Pass mine. Whole-rock geochemistry and zircon geochronology demonstrate a clear affinity to the ca. 1.4 Ga Mountain Pass intrusive system. Bobcat Hills dikes have comparably high REE concentrations (La ∼1,000× chondritic) and an error-weighted mean 207 Pb/ 206 Pb zircon crystallization age of 1,426 ± 2 Ma (2 σ ). Unlike the alkaline intrusions at Mountain Pass, which have abundant inherited zircon from Paleoproterozoic basement rocks and crustally influenced oxygen isotope compositions (δ 18 O zircon = 6.5–7.5‰), the Bobcat Hills dikes lack any evidence of crustal assimilation and have oxygen isotope values that overlap a mantle range (Bobcat Hills average δ 18 O zircon = 5.6 ± 0.3‰). The dikes were a high-temperature, early center of mafic alkaline magmatism in the Mojave Desert that serve as a snapshot of melt generation from a spatially extensive, metasomatized mantle source. We propose that modification of the crust over many tens of Myr at Mountain Pass created an environment that favored crustal assimilation and enabled ascent of late-stage, REE-rich carbonatite magmas.

California↗
USGS2024

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↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2024

The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters

Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 ( m / z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r 2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r 2 = 0.93), praseodymium (Pr) (r 2 = 0.94) and samarium (Sm) (r 2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.

Journal of Geochemical Exploration↗
USGS2024

Improving crop-specific groundwater use estimation in the Mississippi Alluvial Plain: Implications for integrated remote sensing and machine learning approaches in data-scarce regions

Study region The Mississippi Alluvial Plain (MAP) in the United States (US). Study focus Understanding local-scale groundwater use, a critical component of the water budget, is necessary for implementing sustainable water management practices. The MAP is one of the most productive agricultural regions in the US and extracts more than 11 km 3 /year for irrigation activities. Consequently, groundwater-level declines in the MAP region pose a substantial challenge to water sustainability, and hence, we need reliable groundwater pumping monitoring solutions to manage this resource appropriately. New hydrological insights for the region We incorporate remote sensing datasets and machine learning to improve an existing lookup table-based model of groundwater use previously developed by the U.S. Geological Survey (USGS). Here, we employ Distributed Random Forests, an ensemble machine learning algorithm to predict annual and monthly groundwater use (2014–2020) throughout this region at 1-km resolution, using pumping data from existing flowmeters in the Mississippi Delta. Our model compares favorably with the existing USGS model, with higher R 2 (0.51 compared to 0.42 in the previous model), and lower root mean square error (RMSE) and mean absolute error (MAE)— 0.14 m and 0.09 m, respectively in our model, compared to 0.15 m and 0.1 m in the previous model. Therefore, this work advances our ability to predict groundwater use in regions with scarce or limited in-situ groundwater withdrawal data availability.

Journal of Hydrology Regional Studies↗
USGS2024

Complex landslide patterns explained by local intra-unit variability of stratigraphy and structure: Case study in the Tyee Formation, Oregon, USA

Lithology and geologic structure are important controls on landslide susceptibility and are incorporated into many regional landslide hazard models. Typically, metrics for mapped geologic units are used as model input variables and a single set of values for material strength are assumed, regardless of spatial heterogeneities that may exist within a map unit. Here we describe how differences in bedding thickness, grain size, inferred uniaxial compressive strength, and bedding dip control the inherent susceptibility of slopes to deep-seated failure within a single mapped geologic unit - the Tyee Formation of Oregon, USA. The Tyee, which covers over 15,000 km2 and underlies much of the Oregon Coast Range, comprises gently folded alternating beds of sandstone and siltstone deposited as turbidites, forming a 2-km thick Eocene submarine fan which has been uplifted and exhumed through the Cenozoic. Deep-seated landslides are widespread in the Tyee, but form a complex spatial pattern such that landslide density ranges from 0 to 24% of the total landscape area. These slides are often extensive and sufficiently deep to reduce local hillslope gradients, resulting in a strong negative correlation between landslide density and mean local slope. Mean annual precipitation and predicted strong ground motions from Cascadia earthquake scenarios also fail to explain the spatial distribution of deep-seated landslides. Consequently, landslide stability models, which are strongly influenced by landscape slope, pore-water pressure, and seismic acceleration, yield landslide susceptibility maps which are broadly anti-correlated with mapped deep-seated landslide density. Through a multivariable linear regression model, we show that much of the variance in deep-seated landslide density can be explained by variability of intra-unit stratigraphic and structural characteristics, which we measure at 128 sites across two study areas totaling ∼3000 km2. Our results suggest bedding dip is only weakly correlated to landslide density, but strongly influences landslide failure style. Subtle increases in bedding dip, even in the gently folded Tyee Formation, result in a substantially higher likelihood of a landslide being cataclinal, or parallel to bedding. Overall, we find a slight majority of landslides fail within these cataclinal slopes, and that these landslides tend to be larger than non-cataclinal landslides. We also show that the lithological and structural properties that influence landslide susceptibility are distinct for these two populations of landslides. Our results demonstrate how localized, intra-unit, geologic variability can exert strong control on landslide susceptibility and failure style. This suggests that in some locations, landslide hazard models could be significantly improved by incorporating detailed, spatially variable, geologic properties rather than relying solely on generalized geologic map units.

Oregon↗
USGS2024

Updated three-dimensional temperature maps for the Great Basin, USA

As part of the periodic update of the geothermal energy assessments for the USA (e.g., last update by Williams and others, 2008), a new three-dimensional temperature map has been constructed for the Great Basin, USA. Williams and DeAngelo (2011) identified uncertainty in estimates of conductive heat flow near land surface as the largest contributor to uncertainty in previously published temperature maps. The new temperature maps incorporate new conductive heat flow estimates developed by DeAngelo and others (2023). Predicted temperatures at depth are compared with representative measurements (for conductively dominated conditions), showing good agreement under relatively simple uniform conditions. Inputs included radiogenic heat production for all layers of 1.89 μW/m 3 , effective bulk thermal conductivity of 2.7 W/m/°C for all rocks underlying sedimentary basins, and a previously published (Williams and DeAngelo, 2011) empirically driven estimate of increasing thermal conductivity with depth in sedimentary sequences. The resulting three-dimensional temperature model is published in a USGS data release associated with this manuscript (Burns and others, 2023).

Arizona, California, Idaho, Nevada, Oregon, Utah↗
USGS2024

Summary of annual repeat magnetotelluric surveys of the Geysers geothermal field

As part of a multi-year project, funded by the California Energy Commission, annual magnetotelluric (MT) surveys have been collected at The Geysers geothermal field in northern California with the goal of measuring temporal changes within the steam field. The repeat surveys started in 2021 and repeated a 2017 survey (Peacock et al., 2020) with further extension to the southern part of the geothermal field. Temporal variations in the MT transfer functions are observed to be spatially coherent and compartmentalized. Mapping residual phase tensor ellipses demonstrates the direction of maximum change is often aligned with existing fracture orientations. Three dimensional inversion of the MT data, using the inversion results from previous years as the starting model, indicates that the steam reservoir has generally become more resistive over time (~10%), suggesting more steam in the field. A few pockets within the steam field have become more electrically conductive over time and are collocated with injection wells, suggesting either more fluid content in those zones, less steam, or more saline fluids.

California↗
USGS2024

Land-use interactions, Oil-Field infrastructure, and natural processes control hydrocarbon and arsenic concentrations in groundwater, Poso Creek Oil Field, California, USA

Like many hydrocarbon production areas in the U.S., the Poso Creek Oil Field in California includes and is adjacent to other land uses (agricultural and other developed lands) that affect the hydrology and geochemistry of the aquifer overlying and adjacent to oil development. We hypothesize that the distributions of hydrocarbons and arsenic in groundwater in such areas will be controlled by complex interactions between mixed land uses, oil-field infrastructure, and natural processes. In 2020–2021, samples of groundwater and surface water were collected and analyzed for a large suite of inorganic and organic chemicals and isotope and gas tracers to test this hypothesis. Those data are supplemented with ancillary data on historical geochemistry, hydrology, geology, and oil-field infrastructure. Hydrocarbons in groundwater (e.g., methane through pentane gases and benzene) are associated with natural processes (e.g., fault offsets or transition in sediment depositional environment) and oil-field infrastructure (e.g., fluid-migration pathways associated with uncemented annulus in oil wells or unlined pits). Arsenic concentrations >10 μg per liter (μg/L; maximum concentration 12.9 μg/L) are associated with natural processes in old, high-pH groundwater, and more recent recharge of water from natural and/or engineered recharge processes. Along the southwest margin of the oil field, pumping for drinking-water and irrigation supplies in combination with engineered groundwater recharge produce a depression in groundwater elevations where groundwater with elevated sulfate concentrations from agricultural areas and groundwater with hydrocarbons from the oil field mix to produce a zone of sulfate reduction that removes hydrocarbons and arsenic from groundwater but produces elevated sulfide (S 2- ) concentrations (maximum concentration 29 mg per liter, mg/L). In this study, multiple approaches were required to resolve the overlapping effects of land uses, oil-field infrastructure, and natural processes on the distributions of hydrocarbons and arsenic in groundwater. The combined use of geographic, historical, physical, chemical, isotopic, and other information to constrain processes could be a useful approach for studies in other hydrocarbon-production areas. This is particularly important where land uses affect aquifer hydrology to an extent that causes mixing of groundwaters with different chemical compositions.

California↗
USGS2024

A great tsunami earthquake component of the 1957 Aleutian Islands earthquake

The great 1957 Aleutian Islands earthquake ruptured ∼1200 km of the plate boundary along the Aleutian subduction zone and produced a destructive tsunami across Hawaiʻi. Early seismic and tsunami analyses indicated that large megathrust fault slip was concentrated in the western Aleutian Islands, but tsunami waves generated by slip in the west cannot explain the large observed runup in Hawaiʻi far to the southeast. Recently mapped 1957 geologic deposits on eastern Aleutian Islands suggest occurrence of very large nearby slip. Jointly modeling tsunami runup along the eastern Aleutian and Hawaiian Islands together with tide gauge recordings across the Pacific resolves 12-26 m shallow slip along 600 km of the eastern Aleutian Islands in addition to modest, deeper western slip inferred from seismic records. The eastern near-trench slip results in an M W 8.3-8.6 tsunami earthquake component of the M W 8.6-8.8 rupture, comparable in size to the adjacent 1946 Aleutian tsunami earthquake to the east. The reexamination of the 1957 rupture confirms the tsunami hazards posed by the eastern Aleutian subduction zone to Hawaiʻi and lays the groundwork for investigation of large prehistoric earthquakes through modeling tsunami runup inferred from stratigraphic observations to constrain their rupture processes.

Alaska↗
USGS2024

Subducting plate structure and megathrust morphology from deep seismic imaging linked to earthquake rupture segmentation at Cascadia

The origin of rupture segmentation along subduction zone megathrusts and linkages to the structural evolution of the subduction zone are poorly understood. Here, regional-scale seismic imaging of the Cascadia margin is used to characterize the megathrust spanning ~900 km from Vancouver Island to the California border, across the seismogenic zone to a few tens of kilometers from the coast. Discrete domains in lower plate geometry and sediment underthrusting are identified, not evident in prior regional plate models, which align with changes in lithology and structure of the upper plate and interpreted paleo-rupture patches. Strike-slip faults in the lower plate associated with oblique subduction mark boundaries between regions of distinct lower plate geometry. Their formation may be linked to changes in upper plate structure across long-lived upper plate faults. The Juan de Fuca plate is fragmenting within the seismogenic zone at Cascadia as the young plate bends beneath the heterogeneous upper plate resulting in structural domains that coincide with paleo-rupture segmentation.

Oregon, Washington↗
USGS2024

Surficial geology and Quaternary fault map of the Las Vegas Valley, Clark County, Nevada

The Surficial Geology and Quaternary Fault Map of the Las Vegas Valley, Clark County, Nevada is a 1:50,000-scale compilation of published 1:24,000-scale geologic maps integrated with new field and desktop mapping. This geologic map compilation and GIS database are part of a broader study on the Quaternary faults in the Las Vegas Valley, the results of which are summarized in this report. The map compilation utilized a variety of digital base maps to evaluate the characteristics of surficial deposits and Quaternary fault scarps including lidar data in undeveloped parts of the valley and orthorectified historical aerial photos in the urbanized center of the valley. The map distinguishes twenty surficial map units including alluvial-fan and ephemeral-wash deposits, groundwater discharge deposits of the Las Vegas Formation, and alluvium deposits of Las Vegas Wash. Quaternary faults include the Quaternary Las Vegas Valley fault system in the center of the valley and the Frenchman Mountain fault system along the eastern margin. All Quaternary fault traces in the valley were evaluated, and the previously published fault mapping was modified as needed. The new mapping and uniform correlation of surficial deposits displaced by Quaternary faults yields a consistent valley-wide characterization of the recency of fault activity. The map and GIS database include a Quaternary geochronology compilation of 119 previously published surficial deposit ages of various types, 35 new luminescence ages, and 3 new radiocarbon ages. The new age data further bracket the ages of the Las Vegas basin Quaternary stratigraphy and provide new constraints on the timing of Quaternary fault activity.

Nevada↗
USGS2024

Diel temperature signals track seasonal shifts in localized groundwater contributions to headwater streamflow generation at network scale

Groundwater contributions to streamflow sustain aquatic ecosystem resilience; streams without significant groundwater inputs often have well-coupled air and water temperatures that degrade cold-water habitat during warm low flow periods. Widespread uncertainty in stream-groundwater connectivity across space and time has created disparate predictions of energy and nutrient fluxes across headwater networks, hindering predictions of cold-water habitat resilience under climate change scenarios. Recently, annual paired air and water temperature signals have been harnessed to indicate stream water thermal sensitivity and the dominance of deep versus shallow groundwater influence, although the utility of diel air–water temperature signal metrics for hydrologic inference has remained unexplored. Here we analyzed two consecutive years of locally paired, air–water temperature data from 47 headwater stream sites in the Catskill Mountains, New York, USA, and discovered characteristic seasonal patterns in diel temperature signal sinusoid metrics (amplitude ratio, phase lag, and mean ratio) driven by shifts in streamflow generation mechanisms and stream network position. Hydrologic interpretations of observed patterns were supported by stream heat budget model scenarios and additional analysis of paired air–water temperature data from two streams in Shenandoah National Park, Virginia, USA, with well characterized stream-groundwater connectivity. We found that within smaller tributaries, streamflow generation transitions from runoff to groundwater dominance were driven by hillslope drying during seasonal periods of lower precipitation. This was evidenced by significant correlations (p < 0.01) between daily water:air temperature signal amplitudes (non-linear decreases of ∼ 50 %) and derived base-flow index at 22 of the 28 sites, indicating enhanced local groundwater influence on streamflow promotes decoupling of diel air–water temperature signals. Additionally, ratios between daily water:air temperature signal means were lower in tributaries (∼0.68) when compared to main-stem (∼0.8) sites, increasing linearly throughout the observational period. In conceptual stream heat budget models, groundwater inflow had minimal effects on daily phase lags (∼0.2 hr), but increases in fractional groundwater discharge (0–50 %) depressed daily amplitude (∼20 % to 50 %) and mean ratios (∼15 %), supporting the sensitivity of daily metrics to interpreted changes in seasonal groundwater contributions to streamflow. During observational periods (i.e., April through October 2021 and 2022), significant differences (p < 0.01) between tributary and main-stem air–water metrics occurred when base-flow contributions were highest (∼0.93 vs. ∼ 0.68), as sites lower in the network had daily temperature metrics dominated by stream channel thermal inertia, rather than local groundwater connectivity, showing enhanced air–water diel signal coupling during warmer, drier periods. Divergent air temperature coupling across the network was interpreted as being driven by distance from local groundwater source zones, additional lateral groundwater inflows do not contribute a meaningful fraction to channel discharge lower in the network. Given the growing footprint of stream temperature observations, diel air–water temperature signals can provide distributed metrics sensitive to upstream groundwater discharge. Consequently, these metrics can support ongoing efforts by resource managers and researchers seeking to forecast the resilience of cold-water habitat to climate warming and changing precipitation regimes in mountain headwater streams.

New York, Virginia↗