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USGS2026

Black rails in Baja California

Summarizing records from 1905 to 2025, we document the presence and distribution of the California black rail ( Laterallus jamaicensis coturniculus ) in northwestern México, particularly Baja California and the Colorado River Delta. This subspecies has a restricted distribution in the western U.S. and northwestern México. We found few records over the past century: sparse detections in the early 1900s and an increase in reported records after 2000. Over 120 years, we compiled 35 documented records of California black rail occurrence in Baja California with a minimum reported count of 56 rails. Our call-broadcast survey methods reconfirmed previously occupied sites and documented the species at a previously unreported site. Surveys in the Baja California portion of the Colorado River Delta yielded 20 detections across nine survey events between 2000 and 2022. In April 2003, standardized surveys detected 12 California black rails: 7 in Bahía de San Quintín, 3 in Arroyo San Telmo, and 2 in Arroyo El Rosario. Our recent survey work (2022–2025) recorded maximum monthly counts of 31 detections at Bahía de San Quintín and 15 detections at Estero de Punta Banda, the latter representing a previously undocumented location for the subspecies. These surveys also yielded the first photographic and acoustic documentation of California black rail in México. The contribution of spatial and temporal data provided by citizen science platforms increased our understanding of the subspecies’ distribution. Enforceable protection of this subspecies’ habitat is needed to safeguard its persistence.

Baja California↗

USGS2026

Repeated coral bleaching events have eroded reef accretion potential in the Florida Keys

Coral bleaching is now the primary driver of coral-reef degradation globally, threatening the persistence of coral-reef functions and the invaluable ecosystem services they support. The Florida Keys have been impacted by four severe, regional-scale coral-bleaching events, which occurred in 1997–1998, 2005, 2014–2015, and 2023. Our aim in this study was to quantify the effects of those thermal-stress events on the persistence of coral-reef structures. We leveraged long-term coral-reef monitoring data to quantify the impacts of coral bleaching on coral cover, carbonate production, and reef-accretion potential throughout the Florida Keys from 1996–2024. Our study indicates that coral bleaching drove significant declines of reef-building corals, which successively diminished regional-scale reef-accretion potential (from 1.65 ± 0.33 mm y -1 in 1996) and culminated with a regional-scale transition to net reef erosion (-0.12 ± 0.08 mm y -1 ) following the 2023 event. Coral bleaching was the primary driver of declining reef-building capacity, with the cumulative impacts of the four coral-bleaching events accounting for >75% of total declines since 1996. The 1997–1998 event alone drove ~50% of overall declines, largely due to losses of the shallow-water ecosystem engineer, Acropora palmata . More moderate impacts of thermal stress on regional reef-accretion potential in 2005 (6%) and 2014–2015 (9%) could lend some support to the hypothesis that the remaining corals were more thermally tolerant; however, the unprecedented thermal stress event in 2023 caused widespread coral-bleaching and bleaching-related mortality, and caused an additional 12% of the total decline in reef-accretion potential. Stony-coral tissue loss disease accounted for an additional 6% of the decline, with the remaining 19% unexplained. Coral bleaching has already dramatically reshaped the structure and function of coral reefs in the Florida Keys over the last three decades. With the high likelihood that thermal stress will accelerate moving forward, the persistence of Florida’s essential coral-reef functions and services is uncertain.

Florida↗

USGS2026

Rapid characterization of the 2025 Mw 8.8 Kamchatka, Russia earthquake

The 29 July 2025 M w 8.8 Kamchatka, Russia, earthquake was the sixth largest instrumentally recorded earthquake. This event was seismically well observed at regional and teleseismic distances, but publicly available near‐source data were sparse at the time of the event, presenting unique challenges for rapid source and impact characterization. The U.S. Geological Survey (USGS) National Earthquake Information Center provides global real‐time monitoring for earthquakes, including rapid response information products that estimate source characteristics, shaking, and the resulting impacts. We describe the USGS rapid response earthquake information products following the Kamchatka event and discuss their implications for ongoing hazards in the region. We describe potential improvements to our response workflows motivated by this event, including more rapid constraints on source geometries and the automated selection of fault geometries for finite‐fault inversions. The rapid response products together support the interpretation of a unilateral southwestward rupture with significant slip on the southwestern end of the rupture extent. The M w 8.8–9.0 event in 1952, which ruptured a comparable extent of the Kuril–Kamchatka subduction interface, has many similarities to the 2025 rupture. This illustrates that slip deficits may remain following great earthquakes and highlights the usefulness of comparative studies between historic and modern events.

Kuril-Kamchatka subduction zone↗

USGS1976

Diamond drilling at the Ma'milah Mine, Kingdom of Saudi Arabia

The Ma'millah gold mine is about 90 km southeast of At Ta'if at lat 21°03'N., long 41°18'E., in southwestern Saudi Arabia. The deposit, which was worked extensively by ancient miners, consists of several veins and massive lenses of quartz along a regional fault. The extensive ancient mine workings, large size of some quartz outcrops, and significant gold content of several samples indicated that subsurface exploration was warranted. Accordingly, two holes were drilled into the deposit during the interval December 1972 to February 1973. The drill findings were disappointing; the grade of vein material was found to be too low to be of economic interest and the quartz bodies were found to pinch out both along strike and downdip. The drilling program therefore was terminated. The deposit is not worth further exploration

Ma'milah Mine↗

USGS2026

A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping

Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD. LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics. Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved 72.1 ± 1.60% overall agreement, compared to 71.1 ± 1.7% agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved 83.4 ± 1.22% agreement, compared to 84.6 ± 1.11% agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.

Remote Sensing of Environment↗

USGS2023

Advancing subsurface investigations beyond the borehole with passive seismic horizontal-to-vertical spectral ratio and electromagnetic geophysical methods at transportation infrastructure sites in New Hampshire

The U.S. Geological Survey (USGS), in cooperation with the New Hampshire Department of Transportation (NHDOT), surveyed transportation infrastructure sites using rapidly deployable geophysical methods to assess benefits added to a comprehensive site characterization with traditional geotechnical techniques. Horizontal-to-vertical spectral-ratio (HVSR) passive-seismic and electromagnetic-induction (EMI) methods were applied at 4 sites including a roadway-stream crossing, roadway-bridge rail-trail crossing, commuter-parking expansion, and a railroad-adjacent river-cutbank slope-failure site. Additionally, ground-penetrating-radar (GPR) was used at the slope-failure site. Typically, subsurface geotechnical properties are determined from boring data; however, borings are often spaced hundreds of feet apart, potentially missing important spatial variability between boreholes. Geotechnical site characterization including geophysical surveys helped provide a more accurate characterization by using continuous or near continuous profiling. Three-component ambient noise measured with HVSR methods were used to determine resonance frequency and estimate sediment thickness. The method works when there is a strong shear-wave acoustic impedance contrast (> 2:1) between sediment and bedrock. Sediment thickness estimates from HVSR measurements were combined with boring data to make detailed maps of the bedrock surface altitude. The bulk electrical conductivity of the subsurface was indirectly measured with EMI methods and was used to identify lithologic variations, shallow bedrock, and conductive groundwater. Ground penetrating radar, which transmits pulses of electromagnetic energy into the subsurface and records the amplitude and timing of reflected signals, was used to identify bedding and changes in lithology or water content. By combining geophysical and boring data analyses, transportation projects produced more spatially comprehensive representations of geotechnical subsurface conditions than would be determined using conventional borings alone.

New Hampshire↗

USGS2026

3D semantic mapping of surface geological features

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

Computers & Geosciences↗

USGS2025

Accurate simulation of flow through dipping aquifers with MODFLOW 6 using enhanced cell connectivity

In simulations of groundwater flow through dipping aquifers, layers of model cells are often “deformed” to follow the top and bottom elevations of the aquifers. When this approach is used in MODFLOW, adjacent cells within the same model layer are vertically offset from one another, and the standard conductance-based (two-point) formulation for flow between cells does not rigorously account for these offsets. The XT3D multi-point flow formulation in MODFLOW 6 is designed to account for geometric irregularities in the grid, including vertical offsets, and to provide accurate results for both isotropic and anisotropic groundwater flow. A recent study evaluated the performance of the standard formulation and XT3D using a simple, synthetic benchmark model of a steeply dipping aquifer. Although XT3D generally improved the accuracy of flow simulations relative to the standard formulation as expected, neither formulation produced accurate flows in cases that involved large vertical offsets. In this paper, we explain that the inability of XT3D to produce accurate flows in the steeply dipping aquifer benchmark was not due to an inherent limitation of the flow formulation, but rather to the limited cell connectivity inherent in the most commonly used discretization packages in MODFLOW 6. Furthermore, we demonstrate that XT3D is able to produce the expected accuracy when adequate cell connectivity is introduced using MODFLOW's unstructured grid type and the aquifer is discretized vertically using at least two model layers.

Groundwater↗

USGS2026

Cotton farming pesticides affect ileal microbiota activity expressions of virulome but not resistome or metabolic pathways in a sedentary wild passerine

The increased use of agrochemicals to enhance crop production has had detrimental environmental effects including implication in the sharp decline of North American farmland-breeding birds. Here, using a combination of deep shotgun metatranscriptomics and pesticide exposure data, we sought to assess whether exposure to cotton ( Gossypium spp.) production had a differential effect on ileum multi-kingdom microbial activity, metabolism, anti-microbial resistance, and virulence factors of sedentary northern mockingbirds ( Mimus polyglottos ) sampled from two cotton-producing areas (16 birds in total) and one uncultivated area (7 birds) in Texas, USA. Both Shannon Index values (Adj. r 2 = 0.174, F (1,21) = 5.633, p = 0.027) and a Mantel test (Spearman ρ = 0.184, p = 0.013) supported a relationship between metabolically active microbiota Bray–Curtis dissimilarities and differences in pesticide mixtures among study areas. Virulence factor richness (Adj. r 2 = 0.182, F (1,21) = 5.890, p = 0.024), Shannon Index (Adj. r 2 = 0.231, F (1,21) = 7.612, p = 0.012), and load (sum of virulence factor abundances; Adj. r 2 = 0.160, F (1,21) = 5.194, p = 0.033) were related to total pesticide load (total quantity of pesticides). We found no pesticide effects on expression of either antimicrobial resistance genes or metabolic pathways.

Texas↗

USGS2024

Estimating domestic self-supplied water use in Rhode Island, 2014–21

Water withdrawal from private groundwater wells is often unaccounted for in water planning studies, and water from private wells can be a source of exposure to environmental contaminants. The sizes of populations that depend on private wells for domestic water use and the amounts of water that are withdrawn from these wells are generally poorly represented in data collection efforts because of the challenges of locating, metering, or gathering withdrawal information from individual property owners. To address this problem, the U.S. Geological Survey, in cooperation with the Rhode Island Water Resources Board, estimated the volume of water withdrawn from domestic self-supply wells and the populations who use them for the State of Rhode Island at a 30-meter pixel spatial resolution and one-month temporal resolution between July 2014 and June 2021. The number of people reliant on domestic self-supply wells has increased in Rhode Island over the study period; however, the statewide estimate of total water withdrawal has not statistically increased. Withdrawals from private wells are largest in the inland areas of the western part of the State, and the towns of Scituate and Charlestown have the highest estimated withdrawals. Statewide monthly withdrawals ranged from 3.987 million gallons per day in March 2018 to 7.767 million gallons per day in September 2016. The median per capita domestic water use rate was 46.0 gallons per capita per day.

Rhode Island↗

USGS2026

Bottom-up characterization of geologic methane emissions in the San Juan Basin in the southwestern USA

Methane is a potent greenhouse gas that plays an important role in atmospheric chemistry and global warming. The current global methane budget has large uncertainties, and a better understanding of the budget would help to guide strategies for reducing anthropogenic emissions to fight climate change. Natural geologic methane emissions are a particularly poorly constrained source, with top-down estimates from 14 C in ice cores suggesting much lower geologic emissions than bottom-up scaling of direct flux measurements. Our study aims to contribute to resolving this discrepancy through improved bottom-up characterization of geologic methane seepage in the San Juan Basin in southwestern Colorado and northwestern New Mexico, USA. We performed 983 new flux chamber measurements in this basin during summer 2022 and winter 2023 field campaigns. Our results, in combination with prior measurements, suggest that natural seepage in the San Juan Basin only occurs on or near the Fruitland coal outcrop. Specifically, our new measurements confirm previous measurements of seepage along the northwestern exposure of the Fruitland outcrop in Colorado (a known hydrodynamic overpressure region) and for the first time, identified seepage locations along the southernmost Fruitland outcrop exposure in New Mexico, in association with a coal cleat and a fault. Overall, seepage along the Fruitland coal outcrop is heterogeneously distributed, with both positive and negative (interpreted as microbial soil sink) methane fluxes. Features that are hypothesized to be predictive of seepage (e.g., faults) were not associated with positive methane fluxes in areas outside of the Fruitland outcrop. Our best estimate for total geologic methane seepage in the San Juan Basin from spatial interpolation and statistical upscaling is approximately 0.14 Tg CH 4 /yr, with a range from 0.029 to 0.48 Tg CH 4 /yr. This best-estimate value is lower than a previous bottom-up estimate from a gridded seepage inventory, but higher than a previous top-down estimate.

Colorado, New Mexico↗

USGS2025

Reply to, “Comment on ‘The 1886 Charleston, South Carolina, earthquake: Relic railroad offset reveals rupture,’ by Roger Bilham and Susan E. Hough”

We welcome this opportunity to respond to Pratt et al. (2024) (hereinafter P24). Bilham and Hough (2023) proposed a “first-cut” elastic deformation model for the 1886 earthquake, a quantitative source model constrained by identified coseismic constraints. A key observation was the measurement of a lateral offset of a railroad line south of Summerville, leading to a model with predominately dextral slip and minor convergence, from which we concluded that active faulting had raised the Penholoway Marine Terrace >6 m since ∼770 ka. P24 questioned these constraints and proposed an alternative rupture model with predominantly reverse slip. This alternative model is neither consistent with coseismic constraints nor with other geophysical data. In a revised model presented here, we recognize that uplift of the Penholoway Terrace is confined to the eastern edge of the terrace, which we conclude results from active folding and tectonic transpression centered on the dextral fault that offset the railroad in 1886.

South Carolina↗

USGS2022

South Carolina and Landsat

South Carolina, the eighth State admitted to the union, transcends its size with its deep, rich history; striking beauty; vast natural resources; and extensive cultural diversity. Home to part of the Blue Ridge Mountains of the Central Appalachians, the Upstate is graced with more than 100 waterfalls, while the Lowcountry borders the Atlantic Ocean with 187 miles of coastline and 35 barrier islands. Forests cover two-thirds of the State, and forestry and agriculture together, as agribusiness, make up South Carolina’s leading industry. Two historic crops—cotton and tobacco—still rank in the top 10 commodities, though corn and soybeans now rank higher. Poultry, cattle, peanuts, and flowers also make the list. South Carolina’s population totals more than five million. Other residents include a variety of wildlife, bird, reptile, and fish species, including Ursus americanus (black bears), Alligator mississippiensis (American alligators), and Tursiops truncatus (bottlenose dolphins). More than 100 tree species also reside in South Carolina, which pays homage to one with its “The Palmetto State” nickname. South Carolina’s subtropical climate, long coastline, and lower elevations make it highly susceptible to tornado and hurricane activity and coastal flooding. Projected sea-level rise is a growing concern. A view from space can help monitor and manage natural resources on the land and in rivers, marshes, and the coast. Landsat reveals not just what an area looks like now, but also insights from decades ago.

South Carolina↗

USGS2026

Groundwater source water assessment area delineation of public supply wells in the Treasure Valley, western Idaho

The Idaho Department of Environmental Quality (IDEQ) is responsible for assessing the source water for public water supply systems including the delineation of source water assessment areas for wells, which are defined as the subsurface areas contributing water to a well during a period of time. Part of the IDEQ assessment plan is to update source water assessments over time. The U.S. Geological Survey (USGS) developed a new groundwater-flow model for part of the western Snake River Plain aquifer in southwestern Idaho. This groundwater- flow model provided a new opportunity for IDEQ to update source water assessment for public water supply wells within the model boundary. The USGS, in cooperation with IDEQ, used the USGS Treasure Valley Groundwater Flow Model along with a MODPATH particle tracking post-processing program to reassess public-water supply source water assessment areas. The USGS created an automated script that requests a well location, depth, and pumpage rate, and then incorporates that information into the Treasure Valley Groundwater Flow Model combined with the MODPATH model to create 3-, 6-, and 10-year time of travel zones that are output to a geographic information system shapefile. The TVSWA_Delineator script provides a fast, transparent tool for IDEQ to reassess or create new public-water supply source water assessment area delineations based on new and updated information and is available as a Python script and a Windows executable with the compiled script and all necessary components. TVSWA_Delineator utilizes a quadtree approach to rediscretize the Treasure Valley Groundwater Flow Model grid around the pumping well location from 1-mile cell lengths telescoped down to 1/16 mile. This rediscretization increases the source water assessment area delineation resolution near the pumping well and minimizes the effect of weak sinks in the MODPATH model. The stress inputs for each month of the final 10 years (2006 to 2015) of the Treasure Valley Groundwater Flow model historical simulation were averaged for the particle tracking analysis. The MODPATH model used backwards tracking of particles released at each stress period to create the source water assessment area delineations. This report documents the creation of the TVSWA_Delineator Python script, including adaptations made to the Treasure Valley Groundwater Flow Model, creation of a companion MODPATH model, and post-processing results to provide source water assessment areas.

Idaho↗

USGS2024

Analysis of factors affecting plume remediation in a sole-source aquifer system, southeastern Nassau County, New York

Several plumes of dissolved, chlorinated solvents, including trichloroethylene, have been identified in a sole-source aquifer near the former Northrop Grumman Bethpage Facility and Naval Weapons Industrial Reserve Plant sites in southeastern Nassau County, New York. Past investigations have documented that the groundwater contamination originated from this industrial area and now extends to the south, in the direction of groundwater flow. The intermixed plumes are commonly referred to as the “Navy Grumman groundwater plume.” Detailed groundwater-flow modeling was needed for the New York State Department of Environmental Conservation (NYSDEC) to evaluate design options necessary for the construction, operation, optimization, maintenance, and monitoring of a groundwater extraction and treatment cleanup plan selected in a December 2019 Amended Record of Decision by the NYSDEC to comprehensively address these plumes. Consequently, the NYSDEC began a cooperative study with the U.S. Geological Survey in 2020 to better understand the local hydrogeologic framework using two independent approaches to characterize aquifer heterogeneity and update an existing regional groundwater-flow model to provide transient boundary conditions for new inset groundwater-flow models of the plume area. We developed these detailed inset models for the two independent aquifer characterizations using history-matching techniques coupled with a novel approach to risk-based management optimization of the remedial design. We also used the updated regional model to assess this optimized groundwater extraction and treatment design for potential saltwater intrusion. The ensembles of parameters resulting from history matching provided a platform with which to evaluate capture by water-supply and remedial wells using particle-tracking techniques. Using the ensemble to select a risk stance, we performed multiobjective optimization to identify various configurations of remedial pumping that are consistent with external constraints and that favor potentially competing objectives. Multiple solutions provide tradeoffs that NYSDEC can consider. In general, pumping redistribution may help to prevent further contamination migration downgradient. These and other study results are intended to support decisions for the remedial design focused on the local area encompassing the full extent of the Navy Grumman groundwater plume.

New York↗

USGS2024

Forecasting storm-induced coastal flooding for 21st century sea-level rise scenarios in the Hawaiian, Mariana, and American Samoan Islands

Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Hawaiian, Mariana, and American Samoan Islands as a result of climate change and sea-level rise. We followed a hybrid (dynamical and statistical) downscaling approach to map flooding due to waves and storm surge at 10-square meter resolution along all 1,870 kilometers of these islands’ coastlines for annual (1-year), 20-year, and 100-year return-interval storm events and +0.00 meter (m), +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios. We quantified the coastal flood depths and extents using the latest climate forcing from Intergovernmental Panel for Climate Change’s Sixth Assessment Report Coupled Model Intercomparison Project. The data generated using these methods provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when climate change and sea-level rise increase coastal storm-induced flooding to help identify areas where management and (or) restoration could potentially help reduce the risk to, and increase the resiliency of, the coastal communities in the populated Hawaiian, Mariana, and American Samoan Islands.

Hawaii↗

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↗

USGS2025

Groundwater-storage change in the north Phoenix aquifer, Arizona, 2020–23

The city of Phoenix, Arizona, relies primarily on surface water for municipal water supply. The city also maintains wells to withdraw groundwater, particularly in times of drought and reduced surface-water supply, and to recharge groundwater when excess surface water is available. As of 2023, withdrawals from the aquifer in the northeastern part of the city are a small volume of water, less than 3,000 acre-feet in most years. Each year a similar volume of water is recharged through injection wells. The withdrawal wells are permitted to produce in total more than 20,000 acre-feet per year; increased pumping could lead to future groundwater-storage declines. To better understand groundwater-storage change in the north Phoenix aquifer, a repeat microgravity monitoring network was established in 2020. Measurements of changes in Earth’s gravity provide a direct, non-invasive measurement of subsurface mass change. Groundwater-storage changes were small during the 2020–23 study period, consistent with the relatively small volumes of pumping and recharge. Groundwater levels measured in monitoring wells were stable or increased slightly during this period, although the number of monitoring wells within the area of the gravity monitoring network is sparse. In total, about 15,000 acre-feet of water were pumped and 31,000 acre-feet recharged through injection in the north Phoenix aquifer during the 2020–22 period. Within the monitored area, groundwater storage increased by a small amount, about 1,000 acre-feet, in 2020, and decreased by a larger amount, about 6,000 acre-feet, each year in 2021 and 2022. Storage decreased at 89 of 102 stations from 2020 to 2023. Groundwater-storage decreases greater than the volume of net pumping indicate down-gradient subflow from the aquifer is greater than recharge plus incoming subflow, drying of the unsaturated zone resulting from decreased land-surface recharge, or both. At present (2023), the aquifer appears able to store and supply the relatively small amounts of water needed without excessive drawdown or harmful effects, such as land subsidence and surface inundation. If pumping or recharge increases in the future, the established repeat microgravity network is well suited to capture the spatial extent and magnitude of groundwater-storage changes in the aquifer.

Arizona↗