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USGS2026

Estimation of parental abundance using hierarchical Bayesian modeling with data augmentation

Pedigree-based estimation methods leverage the fact that each offspring in a cohort is genotypically “marked” by its parents and represent a recent and promising toolset for estimating population dynamics. This includes pedigree accumulation estimators that model the “accumulation” of inferred unique parents within a given cohort to estimate parental abundance. Unlike close-kin mark-recapture approaches, which rely on intercohort comparisons, pedigree accumulation modeling can be completed solely using intracohort samples. This is particularly advantageous for semelparous species, where intercohort pairs are impossible and adult life stages can be difficult to sample without affecting their likelihood of successfully reproducing. Previous work has evaluated a range of estimators for such datasets, concluding that the non-parametric Chao estimator provides the most accurate and precise estimates for feasible levels of sampling effort. We used simulated data to evaluate an alternative estimator based on hierarchical modeling and data augmentation in a Bayesian framework. Results indicate that estimates from the hierarchical Bayesian estimator had comparable accuracy and better precision than both the previously tested Chao1 estimator and the improved iChao formulation across a range of sample sizes and sex ratios. Furthermore, the Bayesian estimator was far more robust to simulated errors in pedigree reconstruction, especially the presence of false negatives. Hierarchical Bayesian pedigree accumulation models can also provide additional insight into underlying reproductive ecology through their use of an explicit observation process, allowing for the incorporation or estimation of species- and population-specific reproductive dynamics. More broadly, the parametric nature of these models offers opportunities to efficiently pool information among datasets as well as to propagate uncertainty within more complex models.

Ecology and Evolution↗
USGS2025

Estimation of the accessible and useful resource base for electric-grade enhanced geothermal systems (EGS) resources of the Great Basin, USA

Scientists with the U.S. Geological Survey (USGS) recently completed a provisional assessment of the electric-grade geothermal resources associated with the low-permeability geologic formations of the Great Basin, USA, where resources are assumed to be accessible using enhanced geothermal systems (EGS) technologies (i.e., the engineering of sufficient permeability to facilitate efficient heat extraction). This assessment required estimation of the accessible resource base (electric-grade heat [>90ºC] at depths where drilling and stimulation are deemed achievable using current technology) and useful resource (heat that can be extracted from the accessible region). Electric-grade heat can be estimated from existing temperature models. The accessible resource base can be estimated as the electric-grade heat that exists at depths shallower than 6 km based on the limitations of current drilling and stimulation technologies, along with evidence for sustained natural fracture conductivity at depth. The useful part of the accessible heat can be estimated as the product of three efficiencies and factors: the heat extraction efficiency, the viable geology factor, and the reservoir spacing efficiency. The accessible and useful parts of the resource can be estimated in units of heat, or in units of electric power using an electrical conversion efficiency, which is a function of resource temperature. We also estimate the ranges for each of the efficiencies and describe the motivations behind the choice of best estimates used for the recent assessment. An analytic solution is provided for the useful resource above any depth (in units of electric power), where efficiency estimation assumes nearly steady heat extraction rates that cool reservoirs to 90ºC over 30 years of power generation.

Great Basin↗
USGS2026

Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas

In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1 km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10 μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km 2 as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.

Minnesota↗
USGS1999

Comparison of two approaches for determining ground-water discharge and pumpage in the lower Arkansas River Basin, Colorado, 1997-98

In March 1994, the Colorado Division of Water Resources (CDWR) adopted “Rules Governing the Measurement of Tributary Ground Water Diversions Located in the Arkansas River Basin” (Office of the State Engineer, 1994); these initial rules were amended in February 1996 (Office of the State Engineer, 1996). The amended rules require users of wells that divert tributary ground water to annually report the water pumped monthly by each well. The rules allow a well owner to report the pumpage measured by a totalizing flowmeter (TFM) or pumpage determined from electrical power data and a power conversion coefficient (PCC) (Hurr and Litke, 1989). Opinions by representatives of the State of Kansas, presented before the Special Master hearing a court case [State of Kansas v. State of Colorado, No. 105 Original (1996)] concerning post-Compact well pumping, stated that the PCC approach does not provide the same level of accuracy and reliability as a TFM when used to determine pumpage. In 1997, the U.S. Geological Survey (USGS), in cooperation with the CDWR, began a 2-year study to compare ground-water pumpage estimates made using the TFM and the PCC approaches. The study area was along the Arkansas River between Pueblo, Colorado, and the Colorado-Kansas State line (fig. 1). The two approaches for estimating ground-water discharge and pumpage were compared for more than 100 wells completed in the alluvial aquifer of the Arkansas River Basin. The TFM approach uses an inline flowmeter to directly measure instantaneous discharge and the total volume of water pumped at a well. The PCC approach uses electrical power consumption records and a power conversion coefficient to estimate the pumpage at ground-water wells. This executive summary describes the results of the comparison of the two approaches. Specifically, (1) the differences in instantaneous discharge measured with three portable flowmeters and measured with an inline TFM are evaluated, and the statistical differences in paired instantaneous discharge between the two approaches are determined; (2) short- and long-term variations in the PCC’s are presented; (3) differences in pumpage between the two approaches are evaluated, and the statistical differences in pumpage between the two approaches are determined; (4) potential sources of discrepancy between pumpage estimates are discussed; and (5) differences in total network pumpage using the two approaches are presented. During the irrigation seasons of 1997 and 1998, instantaneous discharge and electrical power demand were measured at randomly selected wells to determine PCC’s. At more than 100 wells, the PCC’s determined during the 1998 season were applied to total electrical power consumption data that was recorded between the initial and final readings at each network well site in 1998 to estimate total ground-water pumpage. At each site, an inline TFM was installed in a full-flowing, acceptable test section of pipe on the discharge side of the pump where the measurement of discharge was made. Measurements of instantaneous ground-water discharge also were made using three different types of portable flowmeters. The average velocity multiplied by the cross-sectional area of the discharge pipe was used to compute the discharge in gallons per minute. Whenever possible, discharge measurements were made at each network site using all three types of portable flowmeters.

Colorado↗
USGS2026

Cajon Pass and the southern San Andreas Fault System: Earthquake cycle stress accumulation and present-day loading

With over a century since the last major rupture affecting the wider Los Angeles region, tectonic stress has steadily built along the southern San Andreas and San Jacinto fault systems, raising concerns of an imminent large earthquake. Cajon Pass, located at the junction of these faults, represents a critical site for potential through-going ruptures in Southern California. We constructed new 4D earthquake cycle simulations using a 1000-year paleoseismic rupture history of the San Andreas Fault System (SAFS) to assess spatial and temporal variations in stress. A semi-analytic Fourier transform model was used to compute stress from 3D dislocations in an elastic plate overlying a Maxwell viscoelastic half-space, assuming a complete coseismic reset of resolved shear stress on ruptured elements. Results show highest stress accumulation north of Cajon Pass (∼1.8 MPa/100 years) due to greater slip rates, and lower rates south of Cajon Pass (∼1.0–1.5 MPa/100 years). By 2025, Coulomb stress is estimated at 2.8 MPa on the Mojave South (MOS) segment, 1.8 MPa on the North San Bernardino (NSB1) segment and 3.6 MPa on the San Jacinto Bernardino (SJB) segment. Segments accumulate stresses with characteristic ranges of pre-event stress interpreted as failure thresholds: 1.2–2.7 MPa for MOS, 0.4–1.6 MPa for NSB1, and 1.2–2.9 MPa for SJB. When the stress disparity between segments SJB and MOS narrows, the faults appear to rupture jointly, suggesting that stress levels may control how Cajon Pass acts as an earthquake gate. These results may inform seismic hazard assessments by linking stress evolution to fault interactions.

California↗
USGS2026

Numerical modeling of Late Pleistocene to Holocene earthquake-induced progressive rock slope damage in the paraglacial Serpentine valley, Prince William Sound, Alaska

Landslides in deglaciating fjords pose a potential tsunami threat to nearby communities; however, processes contributing to long-term progressive rock damage and landslide conditioning remain poorly constrained in paraglacial settings. Here, we analyse the role of earthquake-induced rock mass damage over late Pleistocene to Holocene time scales, as a conditioning factor for modern landslides, using distinct element numerical modelling to assess spatial and temporal patterns of fracture propagation influenced by varying glacier thickness. Conceptualised numerical models were parameterised by in situ rock mass, glacial and topographic conditions in Serpentine valley, located in Prince William Sound, Alaska, where several large landslides are actively developing along the western valley wall. Results show that although rigid glacier buttressing reduces co-seismic rock mass damage, it does not suppress it completely, and damage occurs both above and below the glacier surface elevation. We demonstrate that topography, and especially steep slopes with topographic convexity, as well as preexisting damage of joint networks and faults inherited from tectonic and exhumation induced stresses, exert primary control on the location of new co-seismic damage. Simulations representing a simplified deglaciation sequence over the past 25 ka, with a series of 10 evenly spaced earthquakes, generated rock mass damage patterns that qualitatively match in situ landslide structural and kinematic observations at one instability in Serpentine valley. Our conceptual study helps clarify the role of repeated seismicity over glacial timescales as a long-term conditioning process for paraglacial rock slope failure, highlighting spatial and temporal patterns of progressive damage accumulation, with outcomes relevant for modern landslide hazard assessment.

Alaska↗
USGS2025

International data gaps at the Center for Engineering Strong Motion Data

The Center for Engineering Strong Motion Data (CESMD) is utilized by seismologists, engineers, and disaster management professionals in the US and has historically achieved and distributed waveforms from across the globe for significant earthquakes. The increased access to the waveforms via Web API (Application Programming Interface) offers a unique opportunity to provide the community complete datasets, sampling a variety of tectonic environments and geologic conditions, increasing the number of available ground motion records for use in ground motion models (GMMs) and improving the accuracy of earthquake engineering evaluations. The objective of this study is to programmatically identify gaps in global event data from the past decade and backfill missing data gaps at CESMD. We first compare the CESMD catalog with the Advanced National Seismic System (ANSS) Comprehensive Earthquake Catalog identifying regions and time periods where strong-motion data is limited or inadequate. To backfill datasets at CESMD for significant events, we pinpoint regions and time intervals that lack information, creating a list of events for which we’d like to obtain data. An important facet of this work is identifying the source of data and metadata across earthquake repositories around the world and integrating these data repositories into our current strong-motion data processing workflow. In parallel with these newly processed datasets, we are developing a script to produce data origination citations to include provenance and attribution information to associate with respective datasets at CESMD. We showcase our methodology for identifying and filling data gaps at CESMD using three case studies (the 2018 Anchorage Alaska earthquake sequence, seismicity associated with the 2018 Hawaiian Kilauea volcano eruption, and several earthquakes in Turkey) and then outline our strategy to apply our data gap backfilling methods on an international scale.

Conference Paper↗
USGS2025

Exploring the science and data foundation for Federal public lands decisions

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

Colorado↗
USGS2025

Fiber-optic sensing for earthquake hazards research, monitoring and early warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

California, Oregon, Washington↗
USGS2026

Stress states on the eve of past earthquakes inform earthquake rupture through fault complexity along the San Andreas and San Jacinto faults

Estimating the evolving state of stress along active fault systems can provide insight into the conditions that generated past ground‐rupturing earthquakes and influenced their ability to propagate through areas of geometric complexity, such as fault branches and stepovers. We use quasi‐static forward numerical models that incorporate the 3D complex configuration of active faults in southern California to estimate shear tractions on the geometrically complex southern San Andreas and San Jacinto faults from 1000 to 1900 C.E. These tractions include interseismic accumulation of traction due to tectonic loading, viscoelastic relaxation of shear stress within the upper crust between earthquakes, and effects of other earthquakes on the fault network. We simulate ground‐rupturing earthquakes based on the along‐strike earthquake extents modeled by Scharer and Yule (2020) , assuming that stress drop is complete in each earthquake. We use Monte Carlo simulations to estimate uncertainty in evolving shear tractions due to uncertainties in earthquake timing and in upper‐crustal viscosity. Pre‐earthquake shear tractions typically do not exceed ∼2 MPa. Although ruptures with length <200 km have pre‐earthquake shear tractions that range from near zero to ∼1.75 MPa, these tractions are not less than ∼0.4 MPa for earthquakes with rupture length >200 km. Earthquakes with long (>200 km) ruptures occur only in the single‐stranded part of the system, whereas those with short (<125 km) rupture length and high pre‐earthquake shear traction occur near fault stepovers and branches. This suggests that high accumulated shear traction encourages longer rupture propagation, but may not be sufficient to overcome geometric complexities. This modeling approach informs our understanding of rupture propagation and provides estimates of fault shear tractions that are unavailable from direct measurements.

Callifornia↗
USGS2025

Using gridded seismicity to forecast the long-term spatial distribution of earthquakes for the 2025 Puerto Rico and U.S. Virgin Islands National Seismic Hazard Model

Gridded (or background) seismicity models are a critical component of probabilistic seismic hazard assessments, accounting for off‐fault and smaller‐magnitude earthquakes. They are typically developed by declustering and spatially smoothing an earthquake catalog to estimate a long‐term seismicity rate that can be used to forecast future earthquakes. Here, we present new gridded seismicity models for use in the 2025 National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). The previous PRVI NSHM was released in 2003, and our new models incorporate updates to both data and methodology. We utilize an updated earthquake catalog based on improved Puerto Rico Seismic Network data with newly characterized completeness epochs. The catalog is divided into crustal, subduction interface, and intraslab seismicity using new methods and Slab2 subduction zone geometries. To forecast the long‐term spatial distribution of earthquakes, we use an updated methodology developed for the 2023 U.S. 50‐state NSHM, considering three declustering methods and two spatial smoothing methods based on 2D Gaussian kernels. To adapt it for the complex seismotectonics of the region, we also adopt probabilistic methods to account for events with unknown depths and uncertainties in tectonic classification, and develop a new method for spatial scaling to counteract the effects of spatial variability in network coverage while maintaining the use of smaller events. Finally, we test the performance of these spatial models in forecasting the location of M w ≥ 5earthquakes in the region. Our updated methodology improves the representation of epistemic uncertainty relative to the 2003 model, and our results demonstrate the effectiveness of the new measures we have introduced to address heterogeneities in network detection and systematically evaluate forecast performance.

Puerto Rico, U.S. Virgin Islands↗
USGS2024

Debris-flow entrainment modelling under climate change: Considering antecedent moisture conditions along the flow path

Debris-flow volumes can increase along their flow path by entraining sediment stored in the channel bed and banks, thus also increasing hazard potential. Theoretical considerations, laboratory experiments and field investigations all indicate that the saturation conditions of the sediment along the flow path can greatly influence the amount of sediment entrained. However, this process is usually not considered for practical applications. This study aims to close this gap by combining runout and hydrological models into a predictive framework that is calibrated and tested using unique observations of sediment erosion and debris-flow properties available at a Swiss debris-flow observation station (Illgraben). To this end, hourly water input to the erodible channel is predicted using a simple, process-based hydrological model, and the resulting water saturation level in the upper sediment layer of the channel is modelled based on a Hortonian infiltration concept. Debris-flow entrainment is then predicted using the RAMMS debris-flow runout model. We find a strong correlation between the modelled saturation level of the sediment on the flow path and the channel-bed erodibility for single-surge debris-flow events with distinct fronts, indicating that the modelled water content is a good predictor for erosion simulated in RAMMS. Debris-flow properties with more complex flow behaviour (e.g., multiple surges or roll waves) are not as well predicted using this procedure, indicating that more physically complete models are necessary. Finally, we demonstrate how this modelling framework can be used for climate change impact assessment and show that earlier snowmelt may shift the peak of the debris-flow season to earlier in the year. Our novel modelling framework provides a plausible approach to reproduce saturation-dependent entrainment and thus better constrain event volumes for current and future hazard assessment.

Illgraben basin↗
USGS2025

Capturing the uncertainty of seismicity observations in earthquake rate estimates: Implications for probabilistic seismic hazard analysis and the USGS National Seismic Hazard Model

The rate of earthquakes in a region is a fundamental input to Probabilistic Seismic Hazard Analysis. We present a Monte Carlo method for computing that rate from seismicity catalogs while including a range of data and analysis uncertainties. This method is applied to regions for which the b value is assumed to be spatially invariant. Each region is broken down into epochs for which each epoch is estimated to have a uniform magnitude of completeness ( ⁠⁠ M c ). The distribution of earthquake rates for M ≥ M c is determined for each epoch by considering the Poisson likelihood of rates given the number of observed earthquakes with M ≥ M c ⁠ . We use a Monte Carlo process to include the uncertainty in b , ⁠ M c , and individual event magnitudes. The result for each epoch is the joint distribution of the Poisson rate of earthquakes with magnitudes larger than the minimum value used to calculate hazard ( ⁠⁠ M 1 ) and the Gutenberg–Richter b values, which control the extrapolation to other magnitudes. The rate for each region is either the duration‐weighted average over the epochs or, to better capture temporal variations, we also consider mixture models. The mixture models also provide an avenue to allow temporal variations in b values. To implement this joint distribution in a logic tree, we use the mean and 95% confidence branches, each of which is parameterized with an M ≥ M 1 rate and b value. We explore different ways of defining those branches, as well as non‐Gutenberg–Richter branches, and their impact on hazard estimates. The mean hazard, but not the fractiles, is robust with respect to these choices. To illustrate these new methods, we use synthetic data and catalogs from recent U.S. Geological Survey National Seismic Hazard Models for the Central and Eastern United States and for Puerto Rico and the U.S. Virgin Islands.

central and eastern United States, Puerto Rico, U.↗
USGS2025

Fluid inclusion constraints on the geometry of the magmatic plumbing system beneath Mauna Loa – Part 2: Xenoliths

Mauna Loa volcano erupts crystal-poor material at its summit and more crystal-rich material on its rift zones. Some of the more olivine-rich lava flows contain xenoliths with diverse mineralogy, including cumulate harzburgites with high-Mg# orthopyroxenes and high-Fo olivines (both > 84). Previous experimental work and thermodynamic modelling has proposed that high-Mg# orthopyroxenes only crystallize from Mauna Loa melts at high pressures (> 6 kbar, > 20 km), leading to suggestions that there is a region of sub-Moho magma storage at Mauna Loa in addition to the geophysically imaged magma reservoir at 2–5 km depth below the summit. We use melt and fluid inclusion barometry combined with thermodynamic models to further investigate this suggestion. Fluid inclusion data from harzburgites and dunitic xenoliths yield storage depths remarkably similar to those found in non-xenolithic crystals from lavas and tephras, with a clear peak at ~ 2–3 km (below the summit). Depths from melt inclusions in these xenoliths overlap with fluid inclusion pressures, ruling out the possibility of fluid inclusion re-equilibration during a period of stalling in a shallower reservoir. We examine five different thermodynamic models and find that the minimum pressure of olivine-orthopyroxene co-saturation varies by ~ 4 kbar (~ 12 km). These models also fail to predict that orthopyroxene is stable in ~ 15–80% of compositionally relevant experimental charges which grew orthopyroxene. Overall, this shows that phase stability modelling is an unreliable method of determining magma storage depth at Mauna Loa. We suggest that model discrepancies reflect a lack of experimental constraints on orthopyroxene stability at > 1200 ℃ and 0.01–5 kbar. Based on the presence of large oikocrystic orthopyroxenes completely enclosing rounded olivine chadacrysts, we suggest that these harzburgitic xenoliths formed through the reaction of intruding melts with olivine mush piles within the Mauna Loa edifice at ~ 3 km depth below the summit, with no need for a deeper storage reservoir. The predominance of pre-eruptive shallow storage means that there is more chance of detecting reservoir destabilization with geophysical monitoring techniques compared to a scenario where melts are supplied from sub-Moho reservoirs.

Hawaii↗
USGS2025

Factors affecting the distribution of water-bearing fractures in the bedrock aquifers of West Virginia

Bedrock aquifers cover 23,601 square miles within the State of West Virginia and comprise 97.4 percent of the surficial area within the State; the remaining 2.6 percent (621 square miles) consists of alluvial sand-and-gravel and glacial outwash aquifers bordering the State’s major rivers. While West Virginia’s alluvial aquifers have been studied extensively, bedrock aquifers have only been characterized for studies completed in a few areas in Jefferson, McDowell, and Monroe Counties. Bedrock aquifers are water supplies for public supply, agriculture, industry, and residential homeowner use. In this study, the U.S. Geological Survey, in cooperation with the West Virginia Department of Environmental Protection Division of Water and Waste Management, provides a statewide assessment of the occurrence and distribution of fractures within bedrock aquifers of the State and the various topographic, physiographic, and lithologic influences controlling the occurrence and distribution of bedrock fractures. The results of this study provide an increased understanding of the distribution of fractures in bedrock aquifers in West Virginia and help to verify trends that have been suspected for many years but were never well documented or verified by data. The results confirmed that the density of fractures and those that were determined to be water bearing decrease significantly with depth. A statistically significant difference in the density of fractures was observed at a depth of 215 feet for wells in the Appalachian Plateaus Physiographic Province’s and in the Valley and Ridge Physiographic Province’s aquifers; a higher density of fractures and water-bearing fractures were above a depth of 215 feet than below that depth. This is an important consideration when drilling wells for residential, commercial, industrial, or agricultural water supply. Abandoned underground coal mines are commonly believed to form large pools of water in the interconnected mine entries in abandoned room and pillar coal mines. Such pools of water can and do exist in abandoned underground coal mines, but many mines lack open entries and are held up by overburden strata and pillars that can collapse and form aquifers comprised of vast interconnected rubble zones (gob), especially in older mines. Data assessed for this study showed that shale-corrected values of effective porosity for limestone aquifers in West Virginia had a median value of 2 percent and an average value of 4 percent and generally are mineralized with low effective porosity. Argillaceous or sandy limestone has a median shale-corrected porosity of 4 percent and an average shale-corrected porosity of 5 percent. The median and average shale-corrected porosity of sandstone aquifers was estimated to be 14 percent, but the median shale-corrected porosity for argillaceous or calcareous sandstone was 5 percent and the average shale-corrected porosity for argillaceous or calcareous sandstone was 6 percent. Even though shale has a relatively high total sonic porosity compared to other lithologies, shale and siltstone had relatively low shale-corrected porosity, ranging from 0 to 2 percent. Well yields were previously documented to be highest in valley settings, lowest on hilltops, and intermediate on hillsides. Transmissivity data provided by this study confirm this general pattern within the Appalachian Plateaus Province; however, the Valley and Ridge Province does not follow this pattern. While still lowest on hilltop settings, the highest well yields were in hillside settings. The trend for the Valley and Ridge Province was likely skewed because of 9 high-yield wells specifically targeting deeper thin limestone units, such as the Tonoloway and Helderberg Limestones, at depths with transmissivity in excess of 2,000 feet squared per day in Mineral County, West Virginia, or targeting karst aquifers in Berkeley, Jefferson, or Greenbrier Counties, West Virginia. Finally, water-bearing fractures have been hypothesized to comprise a small number of all fractures within a typical bedrock well in West Virginia. Data collected for this study support this theory. A total of 3,403 fractures were identified during this study; 3,151 (92.6 percent) of those fractures are low-transmissive, and only 252 (7.4 percent) fractures are water-bearing. Even though a well may contain many fractures, less than 8 percent are considered water-bearing fractures.

West Virginia↗
USGS2026

Quantitative mineral resource assessment of lithium pegmatite deposits in the northern Appalachian orogen, USA

Lithium demand is projected to increase more than 48 times by 2040 due to electric vehicle production and other energy storage needs. Most lithium production is outside of the USA, thereby increasing supply chain vulnerability. The combined end use importance and heightened supply risk of lithium make this lightest metallic element a critical commodity to the USA. To mitigate this supply risk, the US Geological Survey is actively assessing lithium deposits in the USA. Herein, we detail an assessment for lithium-mineralized pegmatites in the US northern Appalachian Mountains. Permissive tracts were generated by cross-referencing tectonic and geologic maps and mineral occurrence data with mappable criteria derived from generalized and region-specific lithium pegmatite ore deposit models; tracts were then ranked as having high, medium, or low permissibility. Available geophysical and geochemical data were found to be of minimal utility for this deposit type at the scale of the assessment. The number of undiscovered deposits were estimated and integrated into probabilistic simulations, which included an expanded and updated global grade and tonnage model of pegmatite-hosted lithium ore. The estimated total amount of undiscovered resources for the northern Appalachian Orogen has a median value of 1,410,000 metric tons of Li 2 O when considering moderate correlation across sub-regions. At a confidence level of 90%, a resource of at least 90,000 metric tons of Li 2 O remains undiscovered, and at a 10% confidence level, a resource of as much as 7,380,000 metric tons Li 2 O remains undiscovered. After applying an up-to-date economic filter to convert median contained lithium to recoverable material, a correlated total of 900,000 metric tons of Li 2 O may be economically extractable, equating to enough Li 2 O to provide the current annual US lithium supply deficit (presently obtained through net imports) for 127 years at 2025 rates of apparent consumption. This period of provision will inevitably shorten with projected increasing consumption rates, emphasizing that further research could be completed to better delineate regions of high lithium resource potential and support exploration and domestic production.

Connecticut, Delaware, Maine, Massachusetts, New H↗
USGS2024

Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2019–2021

The Navajo (N) aquifer is an extensive aquifer and the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Water availability is an important issue in the Black Mesa area because of the arid climate, past industrial water use, and continued water requirements for municipal use by a growing population. Precipitation in the area typically ranges from less than 6 to more than 16 inches per year, depending on location. The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents the results of data collected as part of the monitoring program in the Black Mesa area from calendar years 2020–2021 and, additionally, uses streamflow statistics from November and December 2019. The monitoring program includes measurements of (1) groundwater withdrawals (pumping), (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater chemistry. In calendar year 2020, total groundwater withdrawals were estimated to be 2,680 acre-feet (acre-ft), and, in 2021, total withdrawals were estimated to be 2,570 acre-ft. Total withdrawals during 2021 were about 65 percent less than total withdrawals in 2005 because the Peabody Western Coal Company discontinued its use of water to transport coal in a coal slurry pipeline after 2005 and ceased mining operations in 2019. Owing to Navajo Nation and Hopi Reservation access restrictions during the Coronavirus pandemic, water levels were not collected from municipal wells in 2020 or 2021. Water levels measured in 2021 from wells completed in the unconfined areas of the N aquifer within the Black Mesa area showed a decline in 7 of 13 wells when compared with water levels from the prestress period (prior to 1965). The changes in water levels across all 13 wells ranged from +8.4 feet (ft) to −42.4 ft, and the median change was −0.4 ft. Water levels also showed decline in 11 of 12 wells measured in the confined area of the aquifer when compared to the prestress period. The median change for the confined area of the aquifer was −25.9 ft, with changes across all 12 wells ranging from +17.3 ft to −133.7 ft. Spring flow was measured at four springs between 2020 and 2021. Flow fluctuated during the period of record for Burro Spring and Pasture Canyon Spring, but a decreasing trend was statistically significant (p<0.05) at Moenkopi School Spring and Unnamed Spring near Dennehotso, Arizona. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s, and discharge at Pasture Canyon Spring has fluctuated for the period of record. Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976–2021), Dinnebito Wash near Sand Springs 09401110 (1993–2020), Polacca Wash near Second Mesa 09400568 (1994–2020), and Pasture Canyon Springs 09401265 (2004–2021). Median winter flows (November through February) of each winter were used as an estimate of the amount of groundwater discharge at the above-named sites. For the period of record, the median winter flows have generally remained constant at Polacca Wash and Pasture Canyon Springs, whereas a decreasing trend was observed at Moenkopi Wash and Dinnebito Wash. In 2020 and 2021, water samples were collected from a total of four springs in the Black Mesa area and analyzed for selected chemical constituents. Results from the four springs were compared with previous analyses from the same springs. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 30 years of record at that site. Concentrations of dissolved solids and sulfate at Pasture Canyon Spring have not varied significantly (p>0.05) since the early 1980s, and there is no increasing or decreasing trend in those data. However, concentrations of chloride from Pasture Canyon Spring show a diminishing trend. Concentrations of dissolved solids, chloride, and sulfate at Unnamed Spring near Dennehotso have varied for the period of record, but there is no statistical trend in the data. Concentrations of dissolved solids at Burro Spring have varied for the period of record, but there is no statistical trend in the data. However, concentrations of chloride and sulfate from Burro Spring show a trend towards lower concentrations.

Arizona↗
USGS2025

A spatial analysis of the groundwater emergence flood hazard in Long Island, New York and near coastal areas surrounding Long Island Sound in New York, Connecticut, and Rhode Island

Long Island, New York and near coastal areas surrounding Long Island Sound are densely populated and, like other coastal areas, are susceptible to flooding from several potential sources, including stormwater from precipitation events, tidal flooding and storm surge, and groundwater inundation or groundwater emergence flooding. The latter refers to the intersection of a rising water table with land surface or critical infrastructure. Many studies of flood drivers either neglect or only briefly discuss how shallow groundwater conditions may contribute to or exacerbate flood conditions. As part of a comprehensive study of compound flood hazards in the near coastal areas surrounding Long Island and Long Island Sound, a spatial analysis was completed, in cooperation with the Environmental Protection Agency’s Long Island Sound Study, using available regional datasets to characterize the potential hazard for groundwater emergence flooding. The approximately 3,100 square mile study area was subdivided into 11,407 900-meter by 900-meter (approximately 3,000-feet by 3,000-feet) grid cells, for the purposes of integrating the spatial datasets to calculate and map the groundwater emergence flood hazard. The depth to the water table, hydrologic soil groups, and National Land Cover Database were harmonized to the common grid. A groundwater emergence flood hazard rank was calculated for each grid cell for current average conditions following a set of rules accounting for the depth to the water table and the percent of area within each cell with slow infiltrating soils. A higher sea level position scenario was also calculated for the Long Island part of the study area. The calculated groundwater emergence flood hazard rank was reviewed in concert with the National Land Cover Data Base to identify developed areas and associated infrastructure that may be at risk to groundwater emergence flooding. Study results indicate that the groundwater emergence flood hazard is highest in coastal areas and near surface water where the water table is close to ground surface. Inland areas away from surface water bodies are not likely to be exposed to groundwater emergence flooding. For Long Island, under a scenario with higher sea level position, a greater groundwater emergence flood hazard is calculated in some locations closer to the coast and where land is submerged. Away from the coast and surface-water drainage, the groundwater emergence flood hazard is similar between the current average sea level condition and a higher sea level position scenario.

EarthArXiv↗