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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

Broadband stochastic simulation of earthquake ground motions with multiple strong phases with an application to the 2023 Kahramanmaraş, Turkey (Türkiye), earthquake

Stochastic ground motion simulation models are often less accurate at lower frequencies than at higher frequencies when fitting recorded data unless supplemented by a deterministic forward directivity velocity pulse model. Moreover, time-modulated stochastic models, which adjust ground motion amplitudes over time, typically use functions that fail to capture multiple strong-motion phases. The February 2023 Turkey (Türkiye) earthquake exhibited diverse recordings, including near-fault and far-field motions with pulse-like and non-pulse-like characteristics, along with single and multiple strong-motion phases. To better represent such a diverse set of recordings, this study enhances a fully non-stationary site-based stochastic model without combining it with a deterministic model. Improvements include a new band-pass filter with upper- and lower-frequency limits, which refines the representation of the low-frequency content. Moreover, a time-modulating function that can represent energy arrival in multiple strong phases is introduced. The reference model’s parameters are identified by fitting to the energy content, zero-level crossings, and cumulative counts of positive-minima and negative-maxima of a target accelerogram. This fitting procedure is modified to address the increased number of parameters. These improvements broaden the reference model’s applicability while preserving its simplicity, a key aspect appealing to engineering practitioners. The improved model’s applicability is demonstrated by simulating a dataset from the February 2023 Türkiye earthquake, and the accuracy is tested using a pulse-like Next Generation Attenuation Relationships for Western United States dataset. Validations are performed based on total energy, zero-level crossings, Fourier amplitude spectrum, elastic response spectra, and peak ground motion parameters. Validations are performed schematically in the time and frequency domains and quantitatively using goodness-of-fit scores, various validation-metrics errors, and inter-period correlations. Overall, the improved stochastic model can effectively simulate a set of diverse ground motion recordings, including near-fault pulse-like records, records with multiple strong phases, and far-field motions across a broad frequency range.

Kahramanmaraş↗
USGS2026

Distributed faulting of the northern West Napa Fault Zone in Napa Valley, California

Mapped surface ruptures from the 24 August 2014 M w 6.0 South Napa earthquake in the Napa Valley, California, show a 2‐km‐wide zone of distributed faulting in the southern and central West Napa fault zone (WNFZ). In the northern WNFZ at Hendry Winery (HW), however, the mapped 2014 surface ruptures encompass an ∼100‐m‐wide zone, implying significant narrowing of the near‐surface fault zone to the north. We present a tomographic shear‐wave velocity ( ⁠⁠ V S ) model and guided‐wave data that indicate the northern WNFZ is at least 400‐m wide, with multiple near‐surface fault traces. Our V S model shows that the 2014 surface ruptures are underlain by discrete low‐velocity zones (LVZs), and coincident guided‐wave data show that the LVZs carry fault‐zone guided waves. If nearby (<500 m) mapped faults to the east of HW are part of the WNFZ, the entire WNFZ is more than 1 km wide in the northern Napa Valley. WNFZ guided waves travel up to 38% slower than S body waves, and low‐strain guided‐wave shaking is up to five times stronger than the associated body‐wave shaking. Our data suggest that guided waves, traveling along distributed faults, may result in an increased shaking hazard over a 1‐km‐wide area of the northern Napa Valley during future significant earthquakes. In places, the 2014 surface ruptures were difficult to find one year after the earthquake, and paleoseismic trenching showed only weak evidence for faulting, which may not have been identified in trenches if the locations of the 2014 surface ruptures had not been previously mapped ( Prentice et al. , 2015 ). Guided‐wave and V S tomography data, however, show strong evidence for faulting beneath the 2014 surface ruptures and at locations to the east. Although paleoseismic trenching is the gold standard for identifying near‐surface faulting, methods such as peak ground velocities of guided waves may better identify immature near‐surface fault traces.

California↗
USGS2025

Scientific opportunities in the National Landscape Conservation System

The National Landscape Conservation System consists of unique and beautiful places across America’s landscapes where identified resources and values are protected and science is highlighted. The mission of the National Landscape Conservation System (NLCS), which is managed by the Bureau of Land Management and is often referred to as the agency’s National Conservation Lands, is to conserve, protect, and restore nationally significant landscapes for their cultural, ecological, and scientific values. This clear inclusion of science in the NLCS mission sets the stage for individual units to serve as places of learning, teaching, discovery, and innovation. Science is an integral part of managing the National Conservation Lands, and science conducted within and across the more than 900 units that make up the NLCS can inform and influence conservation and public land management well beyond its boundaries. Here, we highlight seven core aspects of National Conservation Lands that present valuable science opportunities: (1) the scientific values for which individual units are designated; (2) the many other resources, objects, and values within units; (3) the value of units as “control” sites for understanding the effects of activities such as mineral extraction that commonly occur elsewhere on multiple-use public lands but are often prohibited within National Conservation Lands; (4) the value of units for studying the effects of activities such as recreation that regularly occur and may be intensified on National Conservation Lands; (5) the high visibility of units, which draws strong interest and engagement from scientists, partners, and the public; (6) the functioning of the units as a network managed for a common purpose, which provides an opportunity to explore cross-cutting science questions across widely varying contexts and geographies; and (7) the opportunities units provide to promote and apply Indigenous Knowledge to scientific research to manage natural and cultural resources. Because of all of these characteristics, National Conservation Lands can serve as hubs for basic and applied science that can inform management of all public lands and resources into the future. We highlight these science opportunities through examples from existing units and suggest two actions that could help further science activities and impact on National Conservation Lands.

Parks Stewardship Forum↗
USGS2025

ShakeAlert® version 3: Expected performance in large earthquakes

The ShakeAlert earthquake early warning (EEW) system partners along with U.S. Geological Survey (USGS) licensed operators deliver EEW alerts to the public and trigger automated systems when a significant earthquake is expected to impact California, Oregon, or Washington. ShakeAlert’s primary goal is to provide usable warning times before the arrival of damaging shaking. EEW is most likely to achieve this goal in large‐magnitude earthquakes. In recent years, ShakeAlert has gone through a series of upgrades to its underlying scientific algorithms aimed at improved performance during large earthquakes. Version 3 of this software recently went live in the production system and includes improvements to all algorithms. The main seismic algorithms that detect an earthquake and characterize its location, magnitude, and fault rupture orientation are faster than older versions. Other key changes include: using real‐time geodetic data to characterize the magnitude growth in large earthquakes; the introduction of an alert pause procedure to compromise between speed near the epicenter and improved accuracy at larger distances; and the inclusion of a nonergodic site‐response model in the ground‐motion predictions. ShakeAlert has achieved its primary goal of usable warning times before strong shaking at some locations in real‐time operations in recent M 6 earthquakes. Using offline tests, we demonstrate usable warning times are possible for many sites with peak shaking values of modified Mercalli intensity (MMI) 7–8 in M 7+ earthquakes and also for many MMI 8–9 sites in M 8+ earthquakes. ShakeAlert partners use a variety of MMI and magnitude thresholds in deciding when to alert their users within bounds set by the USGS. Our study shows that there is room to raise the magnitude thresholds up to about M 5.5 without adversely affecting performance in large earthquakes. The ground‐motion criteria are more complex owing to a significant drop‐off in warning times between the MMI 4 and 5 levels of predicted shaking. However, widely used ShakeAlert products, such as the MMI 3 and 4 contour products, can provide sufficiently long warning times before strong shaking in moderate‐to‐great earthquakes to enable a range of protective actions.

Bulletin of the Seismological Society of America↗
USGS2025

Simulated effects of future water availability and protected species habitat in a perennial wetland, Santa Barbara County, California

This study evaluates the potential water availability in Barka Slough and the effects of changing hydrological conditions on the aquatic habitat of five protected species. Barka Slough is a historically perennial wetland at the downstream western end of the San Antonio Creek Valley watershed (SACVW). A previously published hydrologic model of the SACVW for 1948–2018 was extended to include 2019–2021 and then modified to simulate the future years of 2022–2051. Two models simulating the future years of 2022–2051 were constructed, each with different climate inputs: (1) a repeated historical climate and (2) a 2070-centered Drier Extreme Warming climate (2070 DEW). The model with the 2070 DEW climate had warmer temperatures and an increase in average annual precipitation driven by larger, albeit more infrequent, precipitation events than the model with the historical climate. Simulated groundwater pumpage resulted in cumulative groundwater storage depletion and groundwater-level decline in Barka Slough in both future models. The simulations indicate that Barka Slough may transition from a perennial to an ephemeral wetland. Streamflow, stream disconnection, and depth to groundwater are key habitat metrics for federally listed species in Barka Slough. Future seasonal conditions for each metric are more likely to affect federally listed species’ habitats under 2070 DEW climatic conditions. Future seasonal streamflow volume may negatively impact unarmored threespine stickleback ( Gasterosteus aculeatus williamsoni ) and tidewater goby ( Eucyclogobis newberryi) habitats. Future seasonal stream disconnection may negatively impact the unarmored threespine stickleback habitat. Future groundwater-level decline may negatively impact Gambel’s watercress ( Nasturtium gambelii ) and La Graciosa thistle ( Cirsium scariosum var. loncholepis ) habitats and could influence the ability to use Barka Slough as a restoration or reintroduction site for these species. Results from this study can be used to inform water management decisions to sustain future groundwater availability in the SACVW.

California↗
USGS2025

Risk implications of Poisson assumptions and declustering inferred from a fully time-dependent earthquake forecast

We use the Third Uniform California Earthquake Rupture Forecast Epidemic Type Aftershock Sequence model, which is fully time-dependent in terms of including spatiotemporal clustering, to evaluate the effects of the Poisson assumption and declustering algorithms on statewide loss exceedance curves. The model is simulation based, meaning it produces synthetic catalogs that exhibit realistic behavior with respect to aftershocks and multi-fault earthquakes. A Poisson version of the model was constructed by randomizing event times, and the influence of two declustering algorithms was examined as well. We demonstrate that the probability of one-or-more loss exceedances (occurrence exceedance probability) is greater for the Poisson model because it has fewer seismically quiet time windows. The discrepancy between dollar loss estimates with a given exceedance probability is up to a factor of 32% but varies depending on the loss threshold (the x-axis value) and the forecast duration (we examined a range between 24 h and 50 years, with the discrepancy for the latter being negligible). We discuss how the one-or-more loss exceedance metric is questionable because it ignores all but the maximum loss experienced in each timeframe. An alternative metric based on total aggregate loss in each time window (aggregate exceedance probability) was therefore also examined, for which the Poisson model again implies higher risk at intermediate losses but lower risk at higher losses (because large, triggered events now contribute to total aggregate losses for the fully time-dependent model). We also argue that declustering is not a scientifically justifiable way to deal with full time dependence, in agreement with a chorus from other recent studies. It is difficult to draw generally applicable conclusions from our study, in part because application specific details will likely be important, but our results highlight how full time dependence can be reckoned with once authoritative forecast models are made available.

California↗
USGS2025

Probing lower-crustal fault properties with frequency-dependent tidal tremor triggering

The way seismicity responds to periodic stress perturbations offers crucial insights into the processes that can trigger an earthquake. Laboratory and theoretical analyses have shown that the period of imposed forcing and source properties affect the sensitivity to triggering, but frequency-dependent triggering of tectonic faults is poorly understood. The rate of low-frequency earthquakes (LFEs) near Parkfield, California has been found to be strongly correlated with solid earth tides. Tidal forcing acts over multiple frequencies, and the sensitivity to tidal triggering of LFEs therefore provides a unique opportunity to probe the physics of earthquake triggering and underlying fault properties. Here, we find that the response of LFEs to solid earth tides at diurnal and semi-diurnal frequencies is highly variable but spatially coherent along the San Andreas Fault. Using rate-state friction modeling, we find that the variation of the amplitude of tidal modulation is mainly affected by the spatial variation of the background effective normal stress, whereas the spatially varied tidal modulation at diurnal and semi-diurnal frequencies is mainly affected by the fault frictional property. The spatial variations of the LFE response reveal a heterogeneous lower-crustal geologic structure and complex physical faulting processes below the rupture zone of eventual great earthquakes.

California↗
USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗
USGS2026

Wavelet Inversion for SliP (WISP): Open-source earthquake slip modeling software

Models of the spatiotemporal evolution of earthquake slip, termed finite-fault models, are a critical component of rapid earthquake and tsunami response, earthquake forecasting, seismic ground-motion estimates, and studies of earthquake kinematics. Here, we detail a newly released finite-fault modeling software, Wavelet Inversion for SliP (WISP), in use at the U.S. Geological Survey’s National Earthquake Information Center (NEIC) and available to the public. WISP version 1.1.0 allows inversion of teleseismic body and surface waves, as well as local strong-motion, static and dynamic Global Navigation Satellite System, and satellite imagery (e.g., Interferometric Synthetic Aperture Radar) observations on single or multiple planar fault segments. The software is used in NEIC rapid response of earthquakes M w ≥ 7, generally resulting in a published model within the first few hours after the event origin time. The rupture location and dimensions are then used as inputs to downstream products to estimate earthquake shaking, predict loss, and model the likelihood of secondary hazards, namely landslides and liquefaction. WISP is also used in research studies to evaluate the characteristics of complex ruptures including multifault ruptures and earthquake doublets, among others. The WISP version 1.1.0 software release is composed of Python-wrapped FORTRAN code to accomplish the inversion procedure. A simple command line interface facilitates ease of use even for those with only a cursory knowledge of Python scripting. WISP version 1.1.0 includes a Jupyter Notebook tutorial demonstrating use of the software for modeling the 2015 M w 8.3 Illapel, Chile, earthquake. In parallel with the tutorial, we demonstrate the typical usage of the WISP software using the M w 8.3 Illapel earthquake example here.

Seismological Research Letters↗
USGS2025

Mineral commodity summaries 2025

Introduction Each mineral commodity chapter of the 2025 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production, reserves, and resources. The MCS is the earliest comprehensive source of 2024 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses. Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D. The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2025 are welcomed.

Mineral Commodity Summaries↗
USGS2026

Mineral commodity summaries 2026

Introduction Each mineral commodity chapter of the 2026 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production, reserves, and resources. The MCS is the earliest comprehensive source of 2025 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses. Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D. The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the 2026 MCS are welcomed.

Mineral Commodity Summaries↗
USGS2025

A new groundwater energy transport model for the MODFLOW hydrologic simulator

Heat transport in the subsurface is an important aspect of research related to the effects of a warming climate on ecological services (i.e., cold-water refugia); the development of geothermal resources for energy banking schemes (i.e., aquifer thermal energy storage [ATES]); and the effects of temperature on other aspects of groundwater quality, such as nutrient cycling. Historically, simulation of heat transport using the MODFLOW groundwater simulator and related codes was performed by scaling the input parameters of a solute-transport model to emulate heat transport. However, that approach required additional pre- and post-processing of input and output and could not account for the variation in effective thermal storage and transport properties during transient, unsaturated flow, for example. True heat-transport capabilities in the context of MODFLOW were first introduced in a variant called USG-Transport. More recently, a new groundwater energy-transport (GWE) model type has been added to MODFLOW 6, the core version of the MODFLOW hydrologic simulator. GWE supports the simulation of heat transport on structured or unstructured grids as well as within and between features of advanced packages that represent streams, lakes, multi-aquifer wells, and the unsaturated zone. GWE is integrated within MODFLOW 6 and is accessible through the FloPy Python package and the MODFLOW 6 application programming interface (API). An example simulation demonstrates conduction between grid cells through both the water and the solid aquifer material, including thermal bleeding from saturated overburden cells into a groundwater flow field.

Groundwater↗
USGS2025

U.S. Geological Survey science strategy to address white-nose syndrome and bat health in 2025–2029

Since its discovery in 2006, the fungal disease known as white-nose syndrome (WNS) has killed millions of bats. Of the 47 bat species native to the conterminous United States, Alaska, Hawaii, and Canada, 12 have been affected by WNS, including 3 endangered species and 1 proposed endangered species. WNS has also been detected in 40 States and 9 Canadian Provinces. U.S. Geological Survey (USGS) scientists have been critical in identifying the causal fungus for WNS ( Pseudogymnoascus destructans [Pd]), characterizing the effects of WNS, and tracking the spread of Pd in many bat populations in North America. The mission of the USGS WNS and Bat Health Science Team is to deliver integrated science in order to build resiliency into free-ranging bat populations through more effective WNS management, build capacity for bat health science, and enhance bat health information sharing across USGS science centers and cooperative research units as well as with stakeholders. The USGS can play an important role in supporting regional and national capacity building by providing resources and guidance to local, State, and Tribal management entities and by providing tools to enhance disease management. The USGS Ecosystems Mission Area’s Biological Threats and Invasive Species Research Program is the lead Federal program for free-ranging wildlife disease research and surveillance. As of 2024, guided by the science priorities set by the WNS Steering Committee, USGS scientists are engaged in a nationwide response to WNS. This work is done in close coordination with our partners at the U.S. Fish and Wildlife Service, National Park Service, Bureau of Land Management, U.S. Forest Service of the U.S. Department of Agriculture, U.S. Department of Defense, as well as State and Tribal agencies. In addition to conducting WNS research, the USGS is mapping the spread of WNS and coordinating the North American Bat Monitoring Program (NABat) to understand how WNS and other stressors affect the status and trends of native bats across their range. The USGS is supporting the national WNS response through four science goals: (1) provide situational awareness on the health of bat populations; (2) conduct ecological studies of bats along the gradient of disease vulnerability; (3) contribute actionable science to enhance the resiliency of bat populations; and (4) implement an adaptive, holistic approach to bat health.

Circular↗
USGS2025

Lithium from magma to mine in an early Yellowstone hotspot caldera

Renewable energy technologies rely on the extraction of metals not historically in high demand, such as lithium (Li), for which ore deposit models are incompletely understood. One of the world’s largest Li deposits is hosted in lake sediments of the 16.4 Ma McDermitt caldera, which formed during the early stages of Yellowstone hotspot volcanism in the western United States. Eruptive and posteruptive mobility of Li are major challenges in elucidating deposit formation. Melt inclusions preserved in quartz crystals provide a means to assess pre-eruptive magmatic Li contents. Concentrations of Li determined by ion microprobe for melt inclusions in a McDermitt rhyolite lava are 400−1350 ppm, compared to 20−70 ppm Li in matrix rhyolite glasses. Synthesis with melt inclusion data for eight additional calderas demonstrates a recurrence of Li-rich rhyolitic magmas (200−2000 ppm Li) in the western part of the Yellowstone hotspot track. However, unlike the multicyclic caldera complexes with overlapping fault networks that may have compromised Li retention, the McDermitt caldera remained a closed hydrologic system throughout its evolution. Modeling indicates 100 km 3 of resurgent magma could yield 25−150 Mt Li in a magmatic fluid and supports accumulation of Li-rich magmatic fluid in a closed intracaldera lake, followed by evaporative concentration and sequestration of Li within clay minerals to generate the McDermitt deposit.

Idaho, Nevada, Oregon, Wyoming↗
USGS2025

Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin

Future water availability depends on understanding the responses of constituent concentrations to hydrologic change. Projecting future water quality remains a methodological challenge, particularly when using discrete observations with limited temporal resolution. This study introduces Weighted Regression on Time, Discharge, and Season for Projection (WRTDS-P), a novel, computationally efficient method that enables the projection of daily stream water quality under varying hydrologic conditions using commonly available discrete monitoring data. WRTDS-P model performance was validated using 39 sites in the Delaware River Basin (DRB) and four key constituents: specific conductance (SC), nitrate (NO 3 − ), magnesium (Mg 2+ ) and calcium (Ca 2+ ). Projections were tested against holdout data from the final 1 to 5 years of each time series, demonstrating robust predictive capability, with median Nash-Sutcliffe efficiencies of 0.67 for SC, 0.56 for NO 3 − , 0.65 for Ca 2+ , and 0.79 for Mg 2+ . Model uncertainty was correlated with indicators of hydrologic or geochemical mass-sinks, such as groundwater storage and adsorption in wetland soils. Drought scenario analyses for SC used ranges of reduced discharge including flows from the 1965 drought of record. Scenarios predicted widespread increases of SC, especially in southern DRB streams where baseline SC levels are already elevated. Fractional increases of SC were more uniformly distributed, indicating potential risk to sensitive ecosystems. Notably, drought-induced SC increases were positively correlated with interannual SC trends, indicating that hydrologic extremes could exacerbate ongoing salinization. This work provides a transferable and interpretable framework for projecting future water quality and assessing hydrologic risk to water resources and aquatic ecosystems.

Delaware, New Jersey, New York, Pennsylvania↗
USGS2026

Reassessing water availability in the Nile River Basin using satellite-based irrigation water use accounting

Existing estimates of irrigation areas and water use in the Nile River Basin vary widely and are based on inconsistent data and methodologies. This study leverages advances in remote sensing to provide an up-to-date and consistent basin-wide reassessment of water use in the Nile River Basin. Land cover and actual evapotranspiration data from 2013 to 2022 were used to quantify irrigated areas, irrigation water use, and the average naturalized water yield. Across the basin, 7.1 million hectares of irrigated land consume an average of 72.5 ± 2.6 billion cubic meters (BCM) of blue water annually. Egypt and Sudan together account for 92% of the irrigated area and 97% of the irrigation water use. The basin’s average naturalized yield, evaluated at Dongola station, is determined to be between 108 and 114.4 ± 3.2 BCM. Although conservative, this updated analysis indicates the basin’s average naturalized yield is 14%–20% higher than the previous naturalized yield estimate (95 BCM) and 29%–36% higher than the commonly cited observed flow of 84 BCM, which is frequently treated as the total basin-wide available water. Importantly, the study underscores that the 84 BCM represents flow at the Aswan gauging station after upstream consumptive uses, not the total water available in the basin under naturalized conditions. This distinction is critical for accurate water accounting, planning, and governance in this water-scarce basin. This study demonstrates the value of open-source remote sensing resources in data-scarce regions while emphasizing the need for region specific validation and bias correction for improved accuracy.

Nile River Basin↗
USGS2025

Phase 1 technical implementation plan for the expansion of the ShakeAlert earthquake early warning system to Alaska

Executive Summary The conference report accompanying the fiscal year (FY) 2022 Consolidated Appropriations Act (Public Law 117–103) for the U.S. Department of the Interior and related agencies directed the U.S. Geological Survey (USGS) to “work with the State of Alaska to develop an implementation plan to be completed within two years in order to put ShakeAlert/Earthquake Early Warning in Alaska” (p. 29). Congress included $1 million in the FY 2022 appropriation to conduct this effort. The USGS Earthquake Hazards Program, along with partner organizations, has developed the ShakeAlert earthquake early warning (EEW) system for the West Coast, which currently operates in California, Oregon, and Washington. The purpose of the system and its alert delivery partners is to reduce the impact of earthquakes and save lives and property by delivering ShakeAlert-powered alerts that are transmitted to the public via mass notification technologies, and by providing more detailed data streams to institutional users and commercial service providers to trigger automated, user-specific, protective actions. ShakeAlert was designed in such a way that it could be expanded to other U.S. regions with high earthquake risk, after the build-out of seismic and geodetic networks to support ShakeAlert in a specified region is completed and the necessary funding is secured for long-term operation and maintenance. When an earthquake occurs, seismic waves radiate from the rupturing fault like waves on a pond. It is these waves that people feel as earthquake shaking and that can cause damage to structures. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Early warnings of impending shaking are then sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. There will almost always be a region near the earthquake epicenter where alerts arrive after damaging shaking has begun. The ShakeAlert system updates its ground-motion estimates as an earthquake grows larger. In response to the FY 2022 congressional direction, the USGS worked with the State of Alaska to devise this implementation plan for ShakeAlert expansion to Alaska. The USGS engaged with the Alaska Division of Homeland Security and Emergency Management (DHS&EM) and the Alaska Division of Geological and Geophysical Surveys (DGGS). A cooperative agreement was awarded to the Alaska Earthquake Center (AEC) at the University of Alaska Fairbanks (UAF) for their contributions to the plan and their work coordinating with other networks in Alaska. The USGS engaged with the Alaska Seismic Hazards Safety Commission (ASHSC) throughout the process. The USGS also held a series of Alaska stakeholder engagements. The process of developing the implementation plan was facilitated by contracted staff from Corner Alliance, which is a government consulting firm. This implementation plan describes the details and estimates the costs for a Phase 1 expansion of the ShakeAlert system to Alaska. A geographically limited Phase 1 goal was chosen that covers the highest risk and most populated areas of Alaska. The areas proposed encompass the State’s main population centers and 90 percent of the State’s population. This Phase 1 design is considered very challenging and ambitious from the viewpoint of network operators. The lessons learned if this plan is implemented could be used to consider subsequent phases to expand EEW beyond Phase 1 in Alaska in the future. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System (ANSS). This implementation plan calls for a total of 450 high-quality, real-time EEW-capable ANSS seismic stations in Alaska: 270 new stations, 160 upgraded stations, and 20 existing stations. These seismic station numbers are based on a station spacing of 10 kilometers (km) in urban areas, 20 km in seismic source areas that endanger population centers, and 40 km in other areas. The associated costs also include support for some EEW-capable global navigation satellite system (GNSS) stations, with a focus on improving warnings for large subduction zone earthquakes. For effective EEW, ShakeAlert requires low-latency, high-availability, robust telemetry links to deliver continuous, real-time data from field stations to the data centers. The Alaska data processing hardware infrastructure would follow the general design for fail-safe operation that is used for the ShakeAlert system on the West Coast. The ShakeAlert architecture uses two independent layers: the production layer for earthquake processing and the alert layer to make alerting decisions and serve alerts to users. This implementation plan includes two geographically separated data centers in Alaska, each with two fully independent production and alert layers using the same system design developed for the West Coast. As of March 2024, the ShakeAlert system is at version 3.0.1, with more advanced versions in the development and testing pipeline. ShakeAlert originally used two algorithms to determine the location and magnitude of earthquakes using seismic data. A third algorithm that can calculate very large magnitudes of very large earthquakes with geodetic data was added in March 2024. ShakeAlert publishes several data and alert products to meet the needs of different users. All messages include the location of the earthquake, either as a point or a line, and its magnitude. Ground-shaking estimates are published in two forms, as ground-motion contours and a map grid. Providing adequate warning time for strong shaking (the “target threshold”) requires sending alerts at a threshold lower than that strong shaking level (the “alert threshold”). The thresholds for public alerting in Alaska would be a joint USGS and State decision. To have the greatest benefit, ShakeAlert-powered alerts would be delivered to institutional users and individuals by all practical pathways. The USGS alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission nor the infrastructure and expertise to perform mass notifications to the public or implement automatic actions for end users of the alerts. To meet this need, ShakeAlert recruits private sector “technology enablers” that have the necessary expertise to develop end-user implementations using EEW alerts with the goal of stimulating an EEW industry. Earthquake early warning alerts are useless if people do not know how to respond to them. Although the alert messages include instructions about what to do (drop, cover, and hold on), alerts are more effective if people have been trained in advance. Messages about ShakeAlert’s capabilities, limitations, and benefits could be integrated with existing earthquake education programs, including State-run programs. Therefore, ShakeAlert would coordinate with both public and private partners and stakeholders through various partnerships and agreements to accomplish consistent and ongoing public earthquake hazard education. The estimated capital cost of completing the computing infrastructure and sensor networks for the Phase 1 ShakeAlert expansion to Alaska is approximately $66 million in 2024 dollars. The annual operation and maintenance cost of the completed system is estimated to be $12 million per year in 2024 dollars when fully built out.

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