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1,681 records · Page 22Linked to original sources
USGS2024

Perchlorate, metals, organic compounds, and lead isotopes in groundwater, surface water, shallow groundwater, and soil within and near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022

The Middleton Municipal Airport–Morey Field (C29) is in the City of Middleton and adjacent to the towns of Middleton and Springfield, Wisconsin. Nearby homes in the towns rely on private drinking water wells, and residents are concerned about the potential contamination of groundwater and surface water by airport activities, including flights by small aircraft that use leaded aviation fuel and a fireworks display in July 2021. The U.S. Geological Survey, in cooperation with the Town of Middleton, completed a study in 2022 to characterize the occurrence and sources of perchlorate, metals (including lead), and organic compounds in samples of groundwater, surface water, shallow groundwater, and soils within and near the airport. Lead isotopes were also measured to determine sources of lead by comparing samples to environmental references. Magnitudes of concentrations from samples of water and soil collected in 2022, and their spatial patterns across site locations, indicate the fireworks display in July 2021 was a likely source of perchlorate and metals in the airport study area. The highest perchlorate concentration was measured in surface water at the southeastern corner of the airport near the fireworks launch site; the highest concentrations of fireworks-associated metals were measured in shallow groundwater near the same location. Fireworks were not the only possible source of perchlorate and metals in the airport study area because both were also detected upgradient and away from the fireworks launch site. Ratios of lead isotopes indicate that lead measured in water and soil within the airport study area was primarily sourced from background atmospheric lead deposition or Wisconsin galena lead ore. However, two groundwater samples (one upgradient and one downgradient from the airport; both with concentrations less than 1 microgram per liter) had isotopic signatures matching leaded aviation fuel sold at the airport.

Wisconsin↗
USGS2026

Characterizing precariously balanced rocks (PBRs) in the eastern United States for estimating maximum past earthquake ground motions

Fragile geologic features (FGFs) can be used to estimate an upper bound to the strength of earthquake ground shaking in the past thousands to tens of thousands of years. FGFs could be especially useful in the eastern United States, where few active faults are available for paleoseismic studies and where low seismic attenuation means that an earthquake could damage FGFs at large distances. This article describes a pilot study of one form of FGF, precariously balanced rocks (PBRs), in the Blue Ridge of Virginia, ∼160 km from the central Virginia seismic zone (CVSZ) and ∼100 km from Virginia’s Giles County seismic zone (GCSZ). The main goal is to develop and refine methods for studying PBRs in the eastern United States. Photogrammetric 3D models of the rocks were used to locate their centers of mass and delineate their basal contacts, with the latter corroborated by wrapping a wire around the bases to verify the circumferences. Relations between hill geometry and amplification were used to estimate topographic amplification. Seismometers on the PBRs provided the frequencies, amplitudes, and directions of rocking after giving the rocks gentle pushes. The levels of ground shaking likely to topple the rocks were compared with the median hazard curves from the U.S. Geological Survey’s National Seismic Hazard Model and were used to map magnitudes of earthquakes in the nearby region likely to topple the rocks. Results indicate that an M w ≥ 7.5 earthquake is needed in the CVSZ or near the 2020 Sparta, North Carolina, earthquake to topple the two most fragile PBRs and that an earthquake of ~ M w 7–7.5 in the GCSZ is needed. The fragilities and estimated ages of the PBRs (20–40 ka) are thus consistent with the absence of such events in the historical record in the nearby region.

eastern United States↗
USGS2026

Spatio-temporal modeling for assessing geoenergy resources: A workflow applied to gas in place variation in coal beds

The ability to estimate spatio-temporal changes in hydrocarbon reservoir properties and energy resources within pore volumes is essential for optimizing production, reservoir management, geologic energy storage, and safety in underground mining operations. In coal seams, predicting remaining methane gas-in-place (GIP) is critical for quantifying producible gas and improving mine safety and productivity through effective ventilation planning. Although such changes are commonly evaluated using physics-based numerical simulation models, these approaches often require extensive data, calibration effort, and time. This study presents a spatio-temporal geostatistical modeling approach that bridges the gap between purely spatial models and full numerical simulations. The method is applied to a case study of coal seam degasification in the Mary Lee coal group, Black Warrior Basin, Alabama, USA, to estimate GIP evolution over time within a selected mining district. The analysis uses published data from prior natural gas production history-matching of degasification using vertical wells. Empirical spatial and temporal statistics were calculated for reservoir pressure and water saturation, and spatio-temporal variogram models were fitted to experimental variograms. These models provided the structural basis for spatio-temporal kriging, integrated with spatial estimates of time-invariant parameters (porosity, density, and thickness) to estimate GIP. This approach enabled estimation of GIP changes over time, including periods without data. Boxplots of GIP estimates indicated systematic depletion and decreasing spatial variability, reflecting the impacts of degasification. Comparison with cumulative gas production from empirical well records showed approximately 85% agreement based on a relative similarity metric. Spatio-temporal GIP estimates were also used to estimate methane emissions to longwall ventilation systems and compared with reported emissions from the U.S. EPA Greenhouse Gas Reporting Program, showing similar distributions (≈80%) given data limitations. Overall, this integrated modeling approach provides time-dependent GIP estimates with broader implications for resource assessment applications.

Alabama↗
USGS2023

Cursed? Why one does not simply add new data sets to supervised geothermal machine learning models

Recent advances in machine learning (ML) identifying areas favorable to hydrothermal systems indicate that the resolution of feature data remains a subject of necessary improvement before ML can reliably produce better models. Herein, we consider the value of adding new features or replacing other, low-value features with new input features in existing ML pipelines. Our previous work identified stress and seismicity as having less value than the other feature types (i.e., heat flow, distance to faults, and distance to magmatic activity) for the 2008 USGS hydrothermal energy assessment; hence, a fundamental question regards if the addition of new but partially correlated features will improve resulting models for hydrothermal favorability. Therefore, we add new maps for shear strain rate and dilation strain rate to fit logistic regression and XGBoost models, resulting in new 7-feature models that are compared to the old 5-feature models. Because these new features share a degree of correlation with the original relatively uninformative stress and seismicity features, we also consider replacement of the two lower-value features with the two new features, creating new 5-feature models. Adding the new features improves the predictive skill of the new 7-feature model over that of the old 5-feature model; albeit, that improvement is not statistically significant because the new features are correlated with the old features and, consequently, the new features do not present considerable new information. However, the new 5-feature XGBoost model has a statistically significant increase in predictive skill for known positives over the old 5-feature model at p = 0.06. This improved performance is due to the lower-dimensional feature space of the former than that of the latter. In higher-dimensional feature space, relationships between features and the presence or absence of hydrothermal systems are harder to discern (i.e., the 7-feature model likely suffers from the “curse of dimensionality”).

Geothermal Resources Council Transactions↗
USGS2025

A review of abrupt permafrost thaw: Definitions, usage, and a proposed conceptual framework

Purpose of Review We review how ‘abrupt thaw’ has been used in published studies, compare these definitions to abrupt processes in other Earth science disciplines, and provide a definitive framework for how abrupt thaw should be used in the context of permafrost science. Recent Findings We address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire. Summary Permafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic flow, threatening infrastructure and the cultures and livelihoods of northern communities. The term ‘abrupt thaw’ has emerged in scientific discourse over the past two decades to differentiate processes that rapidly impact large depths of permafrost, such as thermokarst, from more gradual, top-down thaw processes that impact centimeters of near-surface permafrost over years to decades. However, there has been no formal definition for abrupt thaw and its use in the scientific literature has varied considerably. Our standardized definition of abrupt thaw offers a path forward to better understand drivers and patterns of abrupt thaw and its consequences for global greenhouse gas budgets, impacts to infrastructure and land-use, and Arctic policy- and decision-making.

Current Climate Change Reports↗
USGS2025

Seismic response of rock towers at the Trona Pinnacles (U.S.A.) to the 2019 Ridgecrest earthquake sequence: Theory, observations, and models

We analyze the seismic response of a class of fragile geologic features (FGFs), referred to as rock towers (RTs) at the Trona Pinnacles, a group of RTs in southern California that suffered strong shaking during the 2019 Ridgecrest earthquake sequence. FGFs, including RTs, may provide maximum constraints on past earthquake shaking intensity, and thereby support probabilistic seismic hazard assessments (PSHAs). In a rare case study, we explore the hypothesis that RT structural integrity is time dependent, as damage accumulates progressively. We develop finite‐element method (FEM) models of the RTs using photogrammetric shape models. We validate the models by comparing numerical simulations of their response to broadband ground shaking with low‐intensity seismic recordings obtained at the Pinnacles. Results of our simulations are in good agreement with the seismic recordings of actual earthquake aftershocks. We next use the results of the FEM models to analyze the response and evolution of RTs. Our analyses elucidate the influence of geometry over their seismic response, providing a rationale that may explain the rarity of slender RTs at Trona: high‐aspect‐ratio structures that respond in bending develop detrimental tensile stresses that crack the rock, whereas low‐aspect‐ratio ones’ response also includes shearing, which does not compromise material integrity as much as tension. Field measurements with a rebound hammer support this finding, suggesting that the material around the base of slender rocks has been weakened relative to other parts of the RT. We also study how to define simplified mechanical models (“archetypes”) to predict the natural frequencies of RTs. Results from our work illuminate the fundamental mechanisms of seismic response and progressive failure of RTs, and open new avenues of research to potentially incorporate these geologic features as long‐return period constraints on PSHA, in ways analogous to those of the widely used precariously balanced rocks.

California↗
USGS2025

The GorDAS Distributed Acoustic Sensing experiment above the Cascadia locked zone and subducted Gorda Slab

The southernmost portion of the Cascadia Subduction zone in Northern California produces high rates of moderate and large earthquakes owing to subduction of the Gorda slab and deformation associated with the Mendocino Triple Junction. Distributed Acoustic Sensing (DAS) is rapidly advancing as a method for detecting earthquakes and imaging crustal structure. We have begun a long-term DAS monitoring experiment on buried telecom fiber in Arcata, California, with the goal of increasing the available recordings of moderate to large earthquakes as well as imaging seismogenic structures. We have recorded over a year's worth of data, including most aftershocks of the 2022 M w 6.4 Ferndale earthquake, though not the mainshock itself. The dataset includes numerous magnitude 3.5 and larger earthquakes including the 2023/01/01 M w 5.4 Rio Dell earthquake. Here we present initial results comparing an earthquake detection algorithm, run in real-time on the processing unit of the interrogator system, with both the ShakeAlert earthquake early warning system as well as a post-processed earthquake catalog developed with deep-learning phase-picker algorithms. The rapid onboard processing of the detector demonstrates the potential utility of DAS-based edge computing for earthquake early warning. We also verify the quality of the strain waveforms both in terms of peak amplitudes and waveform similarity using about five months of nodal seismometer data. These instruments were deployed roughly every 300 m along the ~15km long cable and validate large variations in peak strain over short distances that are seen in the DAS data. All data from time windows surrounding both the local and teleseismic earthquakes are publicly available, which will improve our understanding of both the performance of DAS systems in moderate earthquakes and earthquake hazards associated with the Gorda subduction zone.

California↗
USGS2024

Field evidence and indicators of rockfall fragmentation and implications for mobility

Rockfall fragmentation can play an important role in hazard studies and the design of protective measures. However, the current lack of modeling tools that incorporate rock fragmentation mechanics is a limitation to enhancing studies and design. This research investigates the fragmentation patterns of rockfalls and analyzes the resulting distribution of fragment sizes within corresponding rockfall deposits. We focus on small rock fragments, which provide insights into the dynamics of the rockfall event and can be used as input for numerical modeling. We analyzed multiple rockfall events from locations worldwide, each exhibiting different degrees of fragmentation. Using image analysis techniques, we mapped all visible blocks, determined their volumes, and measured the distances they travelled from the initial point of impact. A key finding is the identification of three indicators of fragmentation. First, in cases where fragmentation was largely absent, we observed a trend of increasing block size with distance from the impact point or source area, which aligns with previously published findings. However, for energetic rockfall events characterized by intense fragmentation, we observed that small fragments exhibited longer travel distances compared to larger fragments. This distinction allowed us to differentiate blocks primarily resulting from the disaggregation process from those primarily resulting from dynamic fragmentation, with implications for rockfall mobility. Second, although the size distribution of rockfall deposits exhibits a power-law scaling for volumes larger than a minimum size threshold corresponding to a rollover of the distribution, in some case studies a deviation from power-law scaling is observed, indicating a process of larger block comminution due to fragmentation. Third, we found that rockfalls with fragmentation experience reduced mobility, indicated by higher reach angles, and higher lateral dispersion showing a wider distribution of trajectories. We interpret these findings as being directly related to the energy-consuming nature of fragmentation, which prevents farther deposition of fragmented rock blocks.

Albacete province, Lombardy and Aosta Valley, Yose↗
USGS2026

Detecting earthquakes in noisy real-time GNSS data with deep learning for improved PGD magnitude estimation

To disseminate accurate and useful warnings, earthquake early warning (EEW) systems must quickly determine the size and location of an earthquake to estimate expected shaking. Traditional seismic‐based algorithms tend to underestimate the true magnitudes of large earthquakes, a phenomenon known as magnitude saturation. This limitation motivated the recent inclusion of Global Navigation Satellite Systems (GNSS) data into the U.S. Geological Survey’s ShakeAlert EEW system with the Geodetic First Approximation of Size and Time (GFAST) algorithm because GNSS data do not saturate with large ground motions. However, the noise levels of GNSS data are very high compared with traditional seismic data, which obscures P ‐wave arrivals and can result in less accurate magnitude estimations if displacement amplitudes are low, such as for lower magnitude earthquakes or large source–station distances. In this study, we develop a deep‐learning model that detects earthquakes in GNSS data and use the Ridgecrest, California, earthquake sequence as a case study to demonstrate how the model could act as a filter to reduce the amount of low‐quality data that enters an algorithm like GFAST. To preserve our limited real earthquake data for model inference, we generated a training dataset composed of >700,000 synthetic displacement waveforms. We combined the synthetic waveforms with real‐time GNSS noise to produce realistically noisy training waveforms and then tested our model on additional synthetic data and performed inference using the real data that were held back. We discuss the performance of our trained model on both the unseen synthetic data and real inference data. Our model can be used to selectively filter only high‐quality data where an earthquake signal is observed for input into an algorithm like GFAST (outperforming a simple signal‐to‐noise ratio–based filter) to reduce the error in GFAST’s real‐time earthquake magnitude estimations.

California↗
USGS1992

Description and effects of 1988 drought on ground-water levels, streamflow, and reservoir levels in Indiana

Documentation of the 1988 drought in Indiana was undertaken to aid water-management agencies and planners concerned with periods of below-normal precipitation and their effect on commercial, agricultural, and residential water use. Precipitation, temperature, Palmer Drought Severity Indices, and ground- and surface-water levels from water years 1988 and 1989 were compared to the historical record to evaluate severity, extent, and duration of the 1988 drought in Indiana. Three types of drought-climatological, hydrologic, and agricultural--occurred in most of Indiana during water years 1988 and 1989. The drought began toward the end of calendar year 1987 as annual precipitation decreased to 4.6 inches below the long term mean. By the end of September 1988, statewide precipitation deficits had increased to almost 8 inches below normal. High temperatures during the summer months increased the stress on crops, livestock, and people. Northwest Indiana experienced the second warmest June-August on record. Palmer Drought Severity Indices indicated that a moderate-to-severe drought had occurred in Indiana during most of 1988. Ground-water levels were affected substantially in many areas of the State. Record low-water levels were observed at 12 of the 20 monitoring wells included in this report. A go-day ground-water emergency was declared in parts of northwestern Indiana. Streamflow throughout the State was affected to varying degrees by the drought. Annual mean discharge in some rivers was only slightly less than the mean annual discharge, while others flowed at less than half that value. The effects of low streamflows were felt by many as electric power plants reduced or ceased production and public-water utilities requested conservation measures by their customers. Major reservoirs in the State approached or reached record low levels, causing water supplies as well as recreational activities to be diminished. Most major crops produced in Indiana were affected by the dry conditions. Average yields in 1988 ranged from 50 to 86 percent of 1987 yields.

Indiana↗
USGS2025

Characterizing Meteor Crater impact melts through geochemistry and textural analysis

The U.S. Geological Survey Astrogeology Science Center houses the Meteor Crater sample collection, an assemblage of over 2,500 meters of cuttings from 161 drill holes into Meteor Crater’s rim, flanks, and ejecta blanket. We have utilized this unique collection to study the composition and spatial distribution of impact-generated materials from within the ejecta blanket. Meteor Crater has historically been known to have generated only a relatively small amount of impact melt compared to other terrestrial craters of similar size. A detailed compositional and textural dataset of impact-derived melts from this impact can therefore be a useful asset in improving our understanding of crater formation, and in particular impact melt formation. We have characterized 42 impact-melt particles from Meteor Crater using a scanning electron microscope and an electron microprobe for textural and compositional analysis. We analyzed samples from six drill holes in the ejecta blanket, situated to the northwest, southeast, south, and southwest of the crater (ejecta northeast of the crater is devoid of impact melts). Impact melts were collected from drill cuttings at various depths within the ejecta blanket, ranging from a few centimeters below the surface down to ~6.5 meters. Backscattered electron (BSE) images were acquired for each analyzed impact-melt particle. To characterize the various textures and phases present in each impact melt, we also took many detailed BSE images. Our geochemical analyses include full spectral profiles using energy dispersive X-ray spectrometry and well-calibrated wavelength dispersive spectrometry for a number of phases, including minerals (olivine, pyroxene, and so on), pristine glass, and metallic inclusions. The full dataset is available in ScienceBase as a data release (Gullikson and others, 2024), accessible at https://doi.org/10.5066/P9OGAJ8P . Our goal for this Open-File Report is to provide a summary of this immense dataset, details on data collection, descriptions of the different phases observed within impact-melt particles (both geochemically and texturally), and observable trends.

Arizona↗
USGS2026

Ground-motion simulations for the 2024 Mw 4.8 Tewksbury, New Jersey, earthquake

Ground-motion simulations of notable earthquakes in the central and eastern United States are limited and typically assume one-dimensional (1D) Earth structure. In this study, we use a three-dimensional (3D) seismic velocity model to better constrain the depth and focal mechanism of the April 5th, 2024, moment magnitude 4.8 Tewksbury earthquake and investigate the spatial variability of earthquake ground motions and the effects of nearby sedimentary basins. We perform earthquake ground-motion simulations up to 0.5 Hz using the 3D spectral-element wave-propagation solver SPECFEM3D over a region 280-km wide by 260-km long by 77-km deep. Topography and subsurface geophysical structure are assigned using the U.S. Geological Survey National Crustal Model with a minimum shear-wave velocity of 200 m/s. We use earthquake time series from 13 broadband seismic stations in the region that have a uniform azimuthal distribution and epicentral distances ranging from 76 to 131 km to compare with synthetics and explore the effects of 1D versus 3D seismic structure on focal mechanism and depth solutions. Ground-motion intensity metrics are also presented relative to the NGA-East ground-motion models (GMMs) currently used in seismic hazard assessments for the region. We find that the 3D model, which reveals a wide spatial variability of period-dependent ground motions, yields better predictions of earthquake ground motions relative to the 1D model and the NGA-East ergodic ground-motion model, with 76 percent reduction of residual variance in observed ground motions averaged over 3-, 5-, 7-, and 10-second periods. Use of the 3D model to solve for a focal mechanism yields a shallower focal depth at 4 km and a shallower east-dipping focal plane relative to the U.S. Geological Survey regional moment tensor and Global Centroid Moment Tensor. Our study demonstrates that use of 3D seismic velocity models can improve estimates of earthquake focal mechanisms, ground motions, and seismic hazard.

New Jersey↗
USGS2025

Magnitude, depth and methodological variations of spectral stress drop within the SCEC/USGS Community Stress Drop Validation Study using the 2019 Ridgecrest Earthquake Sequence

We present the first ensemble analysis of the 56 different sets of results submitted to the ongoing Community Stress Drop Validation Study using the 2019 Ridgecrest, California, earthquake sequence. Different assumptions and methods result in different estimation of the source contribution to recorded seismograms, and hence to the source parameters (principally corner frequency, f c ⁠ , spectral stress drop, Δσ, and seismic moment, M 0 ⁠ ) obtained from modeling calculated source spectra. For earthquakes smaller than magnitude (M) 2.5 there is negligible correlation between the f c values obtained by different studies, implying that no present method is reliable using available data. For larger magnitude events, correlation between f c measurements of different studies, within even a small M range is always higher than spectral ⁠Δσ , because the f c measurements simply reflect the underlying physical decrease in f c with increasing M. We model the observed trends of submitted f c with both magnitude and depth. Most methods report an increase in spectral Δσ with M, although a magnitude‐invariant spectral Δσ is within the confidence limits. The depth dependence is smaller and depends on whether a study allows attenuation to vary with source depth; a combination of depth‐dependent attenuation correction, and depth‐dependent shear‐wave velocity can compensate for reported depth trends. We model the submitted values to remove differing M and depth variation to investigate the relative interevent variability. We find consistent relative variation between individual events, and also lower relative spectral Δσ in the northwest of the aftershock sequence, and higher on the cross fault and in the region of main fault intersection. This large‐scale comparison implies that absolute spectral Δσ estimates are dependent on the methods used; studies of different regions or using different methods should not be directly compared and improved constraints on path and site corrections are needed to resolve these absolute spectral Δσ differences.

California↗
USGS2026

The 2025 Puerto Rico and Virgin Islands U.S. National Seismic Hazard Model Update: Ground motion model selection and comparison

We evaluate, select, and describe the ground-motion models (GMMs) used in the 2025 update of the U.S. National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). We identify the most appropriate models that align with GMM selection criteria for use in the PRVI region to improve the accuracy of seismic hazard assessments. The update incorporates globally applicable GMMs suited for the active crustal and subduction earthquakes in the region. We include region-specific adjustments to these GMMs derived from local site response analyses derived from ground motion records. The unadjusted and regionally-corrected GMMs are combined to create a robust model for predicting median ground motion. The model integrates epistemic uncertainty through a median ground motion logic tree that accounts for variations in magnitude and distance. This study compares the GMMs selected for the 2025 PRVI NSHM, including both as-provided and regionally adjusted NGA-West2 and NGA-Subduction models, with those used in the 2003 PRVI NSHM. We evaluate how changes in model selection, weighting, aleatory variability, and epistemic uncertainty influence seismic hazard estimates. Trends with distance, magnitude, and spectral period are analyzed to evaluate how the scaling behavior of the newer GMMs differs from that of earlier models. Relative to the GMMs used in the 2003 NSHM for this region, the 2025 models generally predict lower ground motions. Comparisons with additional GMMs indicate that the adjustments applied for PRVI are consistent with regional-specific modifications developed elsewhere globally. The increase in aleatory variability and epistemic uncertainty in the 2025 update results in a notable increase in hazard levels from these wider uncertainty bounds. These changes can result in as much as a 10%–20% variation in probabilistic ground motion at the 2% in 50 years exceedance level for hazard maps computed across the region for representative site classes and periods.

Puerto Rico, Virgin Islands↗
USGS2025

Estimating agricultural irrigation water consumption for the High Plains aquifer region with integrated energy- and water-balance evapotranspiration modeling approaches

Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. Conventionally, water use data are created based on reports and surveys from water users, whereas manual records may not be complete due to lacking flow meters, measurement gaps, inconsistent methods across regions, and time- and cost-consuming data processing. Alternatively, spatially explicit estimation of irrigation water use can be conducted efficiently using remote sensing evapotranspiration (ET) modeling approaches. In this study, we created a gridded blue water evapotranspiration (BWET) dataset to estimate historical irrigation water consumption (1986 – 2020) in the croplands across the United States High Plains aquifer region. The BWET data were generated by integrating an energy-balance ET model [Operational Simplified Surface Energy Balance model (SSEBop)] and a water-balance ET model [Vegetation ET model (VegET)]. BWET in croplands indicates crop consumptive use of irrigation water extracted from surface water and groundwater resources. The BWET estimates were compared with reported irrigation water use data for all counties within the aquifer region. The results revealed high agreement between growing season (May – September) BWET and annual water withdrawal at county level. Specifically, correlation coefficients of volumetric BWET and water withdrawal were 0.90 and 0.96, respectively, for the entire aquifer region and western Kansas. The timeseries of BWET and water withdrawal showed similar temporal trends and high covariations. The BWET estimates were systematically lower than the water withdrawal measurements, which was primarily attributed to blue water losses in the irrigation system. The irrigation efficiency, calculated as the ratio of BWET to water withdrawal depth, was 0.57 and 0.74 for the entire aquifer region and western Kansas, respectively. This study demonstrates the capability of using satellite-based ET models (e.g., SSEBop and VegET) to efficiently estimate crop water consumption and evaluate irrigation efficiency at landscape, county, and regional scales.

Colorado, Kansas, Nebraska, New Mexico, Oklahoma, ↗
USGS2024

Evidence for low effective stress within the crust of the subducted Gorda plate from the 2022 December Mw 6.4 Ferndale earthquake sequence

Stress levels on and adjacent to megathrust faults at seismogenic depths remain a key but difficult to constrain parameter for assessing seismic hazard in subduction zones. Although strong ground motions have been observed to be generated from distinct, high-stress regions on the downdip end of the megathrust rupture areas in many great earthquakes, we lack direct constraints on the stress level in the lower seismogenic portion of the Cascadia megathrust. On 2022 December 20, a M w 6.4 strike-slip earthquake occurred near Ferndale, California in southern Cascadia and likely ruptured the Gorda slab crust in the lower seismogenic portion, providing an opportunity to assess the stress level in this region. Here, we relocate the Ferndale mainshock and the first two weeks of aftershocks using a high-resolution 3-D velocity model and estimate rupture dimensions, directivity, and stress drop for several M w 4-5 aftershocks and recent earthquakes. The aftershocks define a strike-slip fault in the slab crust striking ENE, consistent with the mainshock focal mechanism. The orientation of this fault is about 45 ° off the ideally oriented fault plane given the stress state in the slab. The aftershock zone is extensive and broad in the forward direction of the mainshock rupture but still constrained within the volume of high Vp/Vs within the slab crust. Our stress drop estimates are generally lower for M w 4-5 earthquakes located within the slab crust compared to those a few km deeper in the slab mantle. Combined, our results support a relatively low effective stress level in the vicinity of the megathrust in the lower portion of the seismogenic zone in southern Cascadia, likely due to elevated fluid pressures. Consequently, the ground motion in the onshore region above this low-stress seismogenic portion in southern Cascadia may not be as intense as that observed during great earthquakes in other subduction zones.

California↗
USGS2023

Sediment thickness map of United States Atlantic and Gulf Coastal Plain Strata, and their influence on earthquake ground motions

With the recent successful accounting of basin depth ground-motion adjustments in seismic hazard analyses for select areas of the western United States, we move toward implementing similar adjustments in the Atlantic and Gulf Coastal Plains by constructing a sediment thickness model and evaluating multiple relevant site amplification models for central and eastern United States seismic hazard analyses. We digitize and combine existing sediment thickness data sets into a composite surface that delineates the base of Cretaceous sediments under the Atlantic Coastal Plain and the base of Mesozoic sediments under the Gulf Coastal Plain. Amplification models dependent on sediment thickness, site natural period, and source-to-site path length are compared with data sets of observed ground motions to evaluate the ability of the new models to improve ground motion estimates. We find that the amplification models can account for observed trends in sediment-thickness and period-dependent residuals, but some tuning is required. For example, the model of Chapman and Guo requires a reference V S 30 , the time-averaged shear-wave velocity within 30 m of the Earth’s surface, for non-Coastal Plain sites, which we estimate to be between about 1 and 2 km/s. Along with our sediment thickness model, we estimate a velocity profile for application to the Harmon et al. site-natural-period-based model in order to best match the Chapman and Guo period dependence for a broad range of sediment thicknesses. The Next Generation of Attenuation models for the eastern United States Gulf Coast path-based adjustment models can also account for seismic attenuation in the Coastal Plain sediments and reduce the standard deviation of total residuals. If enacted in the U.S. Geological Survey National Seismic Hazard Model, these amplification models will reduce predicted short-period (<1 s) and increase predicted long-period (>1 s) ground motions in the Coastal Plains appreciably.

Earthquake Spectra↗
USGS2024

Exploring landscape and geologic controls on spatial patterning of streambank groundwater discharge in a mixed land use watershed

Preferential groundwater discharge features along stream corridors are ecologically important at local and stream network scales, yet we lack quantification of the multiscale controls on the spatial patterning of groundwater discharge. Here we identify physical attributes that best explain variation in the presence and lateral extent of preferential groundwater discharges along two 5th order streams, the Housatonic and Farmington Rivers, and 32 1st to 4th order reaches across the Farmington River network. We mapped locations of preferential groundwater discharge exposed along streambanks using handheld thermal infrared cameras paired with high-resolution topographic and land use land cover datasets, surficial soil characteristic maps, and depth-to-bedrock geophysical measurements. The unconfined Housatonic River, MA, USA (12 km) had fewer discharge locations and less lateral extent (41 discharge locations with 38 m of active discharge/km of river) compared to the partially confined Farmington River, CT, USA (26 km; 169 discharge locations with 129 m of active discharge/km of river). Using a moving window analysis, we found along both rivers that discharge was more likely to occur where bank slopes were steeper, floodplain extent was narrower, and degree of confinement was higher. Along the Farmington River, groundwater discharge was more likely to occur where saturated hydraulic conductivity was higher and depth-to-bedrock was shallower. Among the 32 stream reaches surveyed (33.2 km of total stream length) within the Farmington River watershed, preferential discharge was observed in all but two stream reaches, varied from 0 to 25% of lateral extent along stream banks (mean = 6%), and was more likely to occur where stream reach slopes were steep, saturated hydraulic conductivity was high, and watershed urbanization was low. Our results show that, though both surface (e.g., topographic, land use land cover) and subsurface (e.g., soil characteristics, bedrock depth) factors control the prevalence of streambank preferential groundwater discharge, the dominant controls vary across valley settings and stream sizes.

Connecticut, Massachusetts↗