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USGS2024

Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand

On 14 February 2016, a magnitude (M)5.7 earthquake struck in Christchurch New Zealand (Aotearoa in the Maori language). The shaking caused damage to historic facades, power outages, cliff collapses, rock falls, and liquefaction but no reported injuries or fatalities. This Valentine’s Day earthquake was an aftershock in the Canterbury earthquake sequence (CES), which began on 4 September 2010 with the M7.1 Darfield Earthquake and included the destructive and fatal M6.2 Christchurch aftershock on 22 February 2011. This study, eight months after the Valentine’s Day earthquake and six years after the initiation of the CES, is the first to explore long-term aftershock forecast information and communication needs. The exploratory study also aimed to gather feedback on aftershock scenarios, an alternative form for communicating the forecast. The qualitative study involved workshops with emergency managers, public health officials, and members of the public in Christchurch. Key findings for long-term communication throughout an earthquake sequence include: 1. divergent earthquake experiences affect aftershock communication response and information needs; 2. understanding aftershock sequence behavior is foundational to sense-making when large aftershocks occur; 3. strategic earthquake sequence updates from the trusted science agency and local agencies could serve as important reminders for earthquake preparedness; 4. communication of aftershock forecast uncertainty could aid with both the credibility of the information and living with uncertainty, and 5. inclusion of impact information and preparedness advice into aftershock forecast scenarios could provide links to actionable information. The paper derives implications for research and practice of long-term communications during an aftershock sequence.

Christchurch↗

USGS1976

An environmental assessment of impacts of coal development on the water resources of the Yampa River basin, Colorado and Wyoming; Phase I work plan

Coal resources of the western United States are being developed at ever-increasing rates, causing concerns of the effects of mining and associated activities on the environment. The Yampa River basin in northwestern Colorado and south-central Wyoming is undergoing economic development of its coal, oil and gas, and uranium resources. The Yampa River basin assessment is a 21-year program of the U.S. Geological Survey. It is designed primarily to assess the availability and quality of the basin's water resources. The basin assessment also will evaluate potential environmental and selected socioeconomic impacts of energy-resource development plans proposed by mining and power companies. This report serves as a project work plan for the basin assessment's first-phase work activities. Economic development in the Yampa River basin will result in higher levels of residuals (noneconomic byproducts) being discharged into the environment. Residuals-management encompasses the technological and economic interrelationships that should be considered in order to comply with Federal and State environmental-control regulations regarding air quality, water quality, and disposal of solid wastes. The basin assessment, the first phase that is described by this report, is designed to provide Federal, State, and local decision-makers with the basic environmental information needed to formulate and to evaluate policies for the development of energy resources. The techniques applied and conclusions reached in the Yampa River basin assessment should aid similar studies of other energy-rich basins in the western United States.

Colorado, Wyoming↗

USGS2026

Evaluation of best management practices at an edge-of-field site in the Eagle Creek watershed, Ohio, 2012–20

In 2010, the U.S. Geological Survey worked in partnership with the Great Lakes Restoration Initiative and the Natural Resources Conservation Service to identify farm fields in priority watersheds—watersheds critically important to Great Lake health. Intensive best management practices were implemented in five States to test the efficacy of best management practices, also referred to as agricultural conservation practices, to reduce sediment and nutrient runoff on agricultural fields. These fields were chosen as representatives of the priority watersheds because their farming practices and geographical conditions were common among farms in those watersheds. A farm site located near Findlay, Ohio, in the Eagle Creek watershed used two conservation practices, cover crop (Natural Resources Conservation Service practice standard 340) and variable rate technology (VRT; Natural Resources Conservation Service practice standard 590), which represent common practices in the Maumee priority watershed. This study monitored surface runoff and subsurface tile runoff at the Eagle Creek watershed site. The effects of cover crop and VRT nutrient application on sediment and nutrient runoff were assessed from October 2012 to September 2020. Cover crops were applied in fall of 2016, 2017, and 2018, coinciding with VRT applications. The following parameters were analyzed as part of the study: runoff discharge; peak discharge; and concentrations and loads of total phosphorus, particulate phosphorus, dissolved reactive phosphorus, and suspended sediment. High peak runoff events disproportionally affected nutrient concentrations and loads in runoff. A threshold of the 85th percentile of the peak discharge was chosen to assess the effect of cover crop and VRT nutrient application on nutrient mitigation at each gage. Runoff events below the 85th percentile were considered small, and runoff events over the 85th percentile were considered large. Concentrations from collected water-quality samples were used for the analysis; estimated concentrations were excluded from the statistical evaluation. All surface runoff parameters during small runoff events, except surface runoff volume, were significantly lower in the period with cover crops and VRT implementation. Contrarily, subsurface runoff parameters during small events were not statistically different between the periods with and without cover crops and VRT implementation. Surface and subsurface parameters during large events were also not statistically different between the periods with and without cover crops and VRT implementation. These results indicate cover crops and VRT may improve water quality during small runoff events, but additional best management practices that mitigate large runoff events may lead to greater water-quality improvement given the contribution of large events to overall losses.

Ohio↗

USGS2026

Quantifying methane emissions from a rich fen with uncrewed aircraft systems in boreal Alaska

Thawing of permafrost in northern latitudes is accelerating, potentially releasing substantial amounts of methane (CH 4 ) as forested permafrost plateaus transition into wetlands. This ecosystem shift alters the carbon exchange between the soil and atmosphere, influencing the permafrost-carbon feedback. Monitoring these changes may require measurement platforms operating across varied spatial and temporal scales. Recent advancements in small uncrewed aircraft systems (sUAS) enable high resolution CH 4 flux quantification in remote, complex terrains; however, comparisons with established methods such as eddy covariance flux towers remain limited. We used a hexacopter sUAS to quantify CH 4 emissions from the Alaska Peatland Experiment, a wetland within the Bonanza Creek Experimental Forest. Using an ensemble of methods to define the background CH 4 concentration, along with near surface emissions from soil chambers, helped constrain our flux estimates. The sUAS method yielded an average flux of 0.0077 ± 0.0019 mol s −1 CH 4 , within a factor of two concurrent tower-derived total source flux estimates (0.0036 ± 0.00042 mol s −1 CH 4 ). To assess spatial drivers of observed fluxes, we conducted a 2D footprint analysis and overlaid the results with high-resolution hyperspectral land cover classification, quantifying vegetative contributions within each footprint. This revealed higher fen representation in sUAS measurements (73.8%) than in tower footprints (58.8%), and lower tussock meadow representation (15.6% and 30.3%, respectively). These differences were consistent with known variation in vegetation-specific CH 4 emissions. Our results highlight that combining footprint modeling with land cover characterization can enhance interpretations of CH 4 fluxes and guide cross-platform comparisons.

JGR Atmospheres↗

USGS2024

topoBuilder quick start guide

TopoBuilder is a public web application from the National Geospatial Program that enables anyone to create customized digital U.S. Geological Survey (USGS) topographic maps, called OnDemand Topos, with the best available, most up-to-date data from The National Map (nationalmap.gov). OnDemand Topos can be made at different scales or quadrangles and can cover anywhere within the United States and its territories.

Fact Sheet↗

USGS2025

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

Lithium is classified as a U.S. critical mineral commodity, and its demand is projected to drastically increase through 2040, driven by electric vehicle production and energy storage applications (IEA 2021).Most global lithium production is not in the United States increasing vulnerability to a supply disruption. The U.S. Geological Survey is actively assessing domestic lithium deposits including lithium-bearing pegmatites in the Appalachian orogen. Permissive tracts for lithium pegmatite deposits were delineated by integrating lithological, tectonic, geochemical, geophysical, and mineral occurrence data. The geospatial data and permissive tracts were used to estimate the number of undiscovered lithium pegmatite deposits. Estimates were then integrated into probabilistic simulations along with a new global lithium pegmatite grade and tonnage dataset to quantify potential contained undiscovered lithium resources. An economic filter was used to estimate the amount of potentially recoverable undiscovered resources. Preliminary computations for the northern Appalachians, including application of the economic filter to the median recoverable contained resource, yields 900,000 metric tons of Li 2 O that correspond to enough Li 2 O to replace 127 years of import reliance at the current rate (7,100 t Li 2 O/yr; USGS, 2025). For the southern Appalachians, preliminary computations yielded 1,430,000 metric tons of Li 2 O, which corresponds to 201 years of import reliance.

Alabama, Connecticut, Delaware, Georgia, Maine, Ma↗

USGS2025

Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs

Oil and gas reservoirs represent suitable containers to sequester carbon dioxide (CO 2 ) in a supercritical state because they are accessible, reservoir properties are known, and they previously contained stored buoyant fluids. However, planners must quantify the relative magnitude of the CO 2 storage resource in these reservoirs to formulate a comprehensive strategy for CO 2 mitigation. Even reconnaissance-type estimates of CO 2 storage resources of known oil and gas reservoirs may require complicated calculations involving 1) estimates of recoverable oil and gas, 2) reservoir properties (depth, temperature, pressure, etc.), and 3) the physical qualities of the retained fluids. We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO 2 storage resources in reservoirs capable of hosting CO 2 in a supercritical state. ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. The proposed methods and models provide an effective and novel way to more rapidly and directly determine the subsurface CO 2 storage capacity of oil and gas reservoirs around the world, information that operators, researchers, and policymakers alike require to meet energy transition and decarbonization goals.

Frontiers in Enviornmental Science↗

USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗

USGS2025

Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management

The San Joaquin Valley (SJV) of California is one of the world’s most productive agricultural regions. Reliance on groundwater has led to some of the greatest rates of human-induced land subsidence in the world in the 20th century, as well as more recently. The United States Geological Survey (USGS) has recently developed an integrated surface–subsurface hydrologic model, the Central Valley Hydrologic Model 2 (CVHM2), that represents the major components of the hydrologic system of California’s Central Valley. In this study, CVHM2 was applied as a decision support tool while simulating various management strategies to mitigate the land subsidence caused by the extraction of groundwater. CVHM2 was extended through to 2073 and applied to simulate management scenarios in terms of three primary drivers and their impact on subsidence along the Delta–Mendota Canal (DMC), a critical piece of infrastructure in the western SJV. The drivers considered were agricultural water demands, managed aquifer recharge (MAR), and changes in future climate. The results show that future subsidence is most sensitive to water demands, second most sensitive to future changes in climate, and relatively insensitive to MAR when it is applied as a surface application in the western SJV. However, we demonstrate via proof-of-concept scenarios that the MAR is capable of arresting subsidence when implemented via injection below the Corcoran Clay Member of the Tulare Formation instead of as a surface application. We also examine the uncertainty that is the result of climate variability and how to use the tool to identify the most appropriate strategies to constrain future subsidence to acceptable levels.

California↗

USGS2023

Evaluation of models for estimating hydraulic conductivity in glacial aquifers from NMR logging

Nuclear magnetic resonance (NMR) logging is a promising method for estimating hydraulic conductivity ( K ). During the past ∼60 years, NMR logging has been used for petroleum applications, and different models have been developed for deriving estimates of permeability. These models involve calibration parameters whose values were determined through decades of research on sandstones and carbonates. We assessed the use of five models to derive estimates of K in glacial aquifers from NMR logging data acquired in two wells at each of two field sites in central Wisconsin, USA. Measurements of K , obtained with a direct push permeameter (DPP), K DPP , were used to obtain the calibration parameters in the Schlumberger-Doll Research, Seevers, Timur-Coates, Kozeny-Godefroy, and sum-of-echoes (SOE) models so as to predict K from the NMR data; and were also used to assess the ability of the models to predict K DPP . We obtained four well-scale calibration parameter values for each model using the NMR and DPP measurements in each well; and one study-scale parameter value for each model by using all data. The SOE model achieved an agreement with K DPP that matched or exceeded that of the other models. The Timur-Coates estimates of K were found to be substantially different from K DPP . Although the well-scale parameter values for the Schlumberger-Doll, Seevers, and SOE models were found to vary by less than a factor of 2, more research is needed to confirm their general applicability so that site-specific calibration is not required to obtain accurate estimates of K from NMR logging data.

Wisconsin↗

USGS2024

Seismic techniques and suggested instrumentation to monitor volcanoes

Introduction Changes in the pressure or location of magma can stress or break surrounding rocks and trigger flow of nearby waters and gases, causing seismic signals, such as discrete earthquakes and tremor. These phenomena are types of seismic unrest that commonly precede eruption and can be used to forecast volcanic activity. Mass movements at the surface, including avalanches, debris flows, and lahars, may also generate seismic signals that are specifically addressed in chapter H , this volume (Thelen and others, 2024). Our focus in this chapter is to determine the levels of instrumentation recommended to produce high-quality, well-constrained seismic observations important for early warning of impending eruptions, detecting changes in ongoing eruptions, and characterizing other hazardous volcanic events. There are emerging techniques and new types of instrumentation, such as distributed acoustic sensing or rotational seismometers, that we do not consider here. These types of instrumentation show promise for monitoring but still require maturation before being considered more generally in volcano monitoring. Most of the capabilities mentioned below are universal for all types of volcanic systems, although some are best applied to stratovolcanoes with an apical single vent. In some settings, such as calderas or shield volcanoes, we must broaden coverage to include multiple possible storage regions or vent locations. As an example, Thelen (2014) discretized the long rift zones of shield volcanoes in Hawaiʻi as a set of evenly spaced “vents.” In this construct, each vent comes with recommendations, and several thousand network configurations were simulated to assess the effect on network quality levels and to determine the most efficient network design. The same process could be applied in a caldera setting or a volcanic field, where an evenly spaced grid of potential vents is considered. Localized recommendations for each unique system are beyond the scope of this report and left up to local experts to assess based on the conditions, restrictions, and requirements of each volcano.

Scientific Investigations Report↗

USGS1999

Characterization and simulation of the quantity and quality of water in the Highland Lakes, Texas, 1983-92

The Highland Lakes, located in central Texas, are a series of seven reservoirs on the Colorado River (Lake Buchanan, Inks Lake, Lake Lyndon B. Johnson, Lake Marble Falls, Lake Travis, Lake Austin, and Town Lake). The reservoirs provide hydroelectric power for the area. In addition, Lake Austin and Town Lake also provide the public water supply for the Austin metropolitan area. Saline water released from Natural Dam Salt Lake during 1987–89 caused increased concern among water managers that high-salinity water entering the Highland Lakes could result in waterquality problems, necessitating additional treatment of the water. The maximum dissolved solids concentrations for the reservoirs after the saline inflow were about two to three times the average concentrations before the inflow. The maximum concentrations of chloride and sulfate after the inflow were about three to five times the average concentrations before the inflow. The concentrations of dissolved solids, chloride, and sulfate in Lake Buchanan, Inks Lake, Lake Lyndon B. Johnson, and Lake Marble Falls were less than the concentrations of the applicable water-quality standards by the end of 1990. Concentrations of these constituents in Lake Travis, Lake Austin, and Town Lake did not decrease to previous levels, which were less than the concentrations of the applicable waterquality standards, until the end of 1991. Constituent concentrations for Lake Buchanan and Inks Lake; for Lake Lyndon B. Johnson and Lake Marble Falls; and for Lake Travis, Lake Austin, and Town Lake were similar because of the relative storage capacities and location of tributary inflows. From the initial increase in constituent concentrations in Lake Buchanan (summer 1987) in response to the saline inflow, the high-salinity water passed through the entire Highland Lakes in about 3.5 years. A mathematical mass-balance model was used to simulate the input and movement of highsalinity water through the Highland Lakes and to estimate monthly mean concentrations of dissolved solids, chloride, and sulfate for wet, average, and dry hydrologic conditions. The simulated median monthly concentrations during the 10-year simulation period for each reservoir generally are larger for the average condition than for the wet condition and generally are larger for the dry condition than for the average condition. The simulated concentrations of dissolved solids, chloride, and sulfate decreased to levels less than the concentrations of the applicable water-quality standards in about 2 to 5 years after the saline water inflow of 1987–89 was simulated for the three hydrologic conditions. Results from the simulations indicate that saline inflows to the Highland Lakes similar to those of the releases from Natural Dam Salt Lake during 1987–89 are unlikely to cause large increases in future concentrations of dissolved solids, chloride, and sulfate in the Highland Lakes. The results also indicate that high-salinity water will continue to be diluted as it is transported downstream through the Highland Lakes, even during extended dry periods.

Texas↗

USGS2024

Developing international standards and guidelines for disseminating and validating simulated ground motions

We are leading an effort to develop international standards and guidelines for curating, disseminating, and validating simulated ground-motion data. This effort is organized as a working group within the Consortium of Organizations for Strong Motion Observation Systems (COSMOS). In 2022 we held online workshops on 7 and 8 June and 20 October. The first workshop focused on curating and disseminating simulated ground-motion data. The second workshop focused on validating simulated ground-motions for engineering applications. About 100 people participated in each of the workshops with strong representation from North America, Europe, and western Asia. In the coming year, we intend to form a technical committee to draft the international guidelines and standards while continuing to engage stakeholders from across the globe through online and in-person meetings. The key points from the workshops include: (1) Numerous groups are generating simulated earthquake ground motions and making them openly available; however there is very little coordination among groups to provide consistent interfaces for searching and retrieving data; (2) Standardizing interfaces for metadata and data access should consider agile approaches that can adapt to changing capabilities and user needs while building upon existing efforts; (3) A distributed architecture is preferred by most participants to allow institutions to host and manage their own data while broadcasting their holdings to a combined catalog; (4) Validation of ground-motion simulations applies to the entire workflow for simulating earthquake ground-motions, including the rupture model, seismic velocity model, and seismic wave propagation software; (5) Metrics to evaluate the validation are application dependent; more research is needed to tie structural response characteristics to ground-motion characteristics; and (6) Validation results should provide a clear, transparent, and quantitative assessment of the simulated ground motions.

Conference Paper↗

USGS2025

Four-band image mosaic of the Colorado River Corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2021 airborne image acquisition

In May 2021, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center acquired airborne multispectral high-resolution data for the Colorado River in the Grand Canyon, Arizona. The image data, which consist of four spectral bands (red, band 1; green, band 2; blue, band 3; and near infrared, band 4) with a ground resolution of 20 centimeters, are available as 16-bit unsigned-integer GeoTIFF files in Sankey and others (2024) (available online at https://doi.org/10.5066/P9BBGN6G ). The image files are projected in the State Plane Coordinate System, using the central Arizona zone (202) with the North American Datum of 1983 National Adjustment of 2011. The assessed spatial accuracy for these data is based on 47 ground-control points that were independent from the ground-control points used by the contractor for aerotriangulation and is reported at the 95-percent confidence level as 0.514 meter (m) and a root mean square error of 0.297 m. The intended uses of this dataset are primarily in support of scientific research and monitoring applications. Examples of these applications include high-resolution spatial and temporal change detection of the river channel, geomorphic landforms, riparian vegetation, and backwater and nearshore habitat, as well as other ecosystem-wide mapping. These imagery data also serve as reference material for field science mission planning, as base data for field data collection including community science activities, and as a highly detailed guide for technical boat operation during science activities such as reconnaissance for nighttime missions and navigating rapids during low flows.

Arizona, Nevada, Utah↗

USGS2025

The 3D Elevation Program—Supporting Rhode Island’s economy

Introduction High-resolution elevation data are critical to applications of landscape modeling and planning, both of which have a significant effect on Rhode Island’s economy. In these and other enterprises, program managers, while aiming to strike a balance between accuracy and cost, strive to obtain the best available elevation data to help them address a range of issues. Programs focused on climate change, environmental management, transportation design and asset management, aviation navigation and safety, riverine ecosystem management, wildlife habitat characterization and management, shellfish aquaculture, and the management and mapping of forests, parks and recreation areas, soils, wetlands, and impervious surfaces are also among the critical applications that meet the State’s management needs and depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Rhode Island. The status of available and in-progress 3DEP baseline lidar data in Rhode Island is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $178,560 in new benefits annually to the State. The top 10 Rhode Island business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Rhode Island↗

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↗

USGS2024

Distinguishing natural sources from anthropogenic events in seismic data

As seismic data are increasingly used to investigate a diverse range of subsurface phenomena beyond regular fast-rupturing earthquakes (Peng and Gomberg, 2010; Beroza and Ide, 2011), it is important to acknowledge that human-generated ground vibrations may be mistaken for naturally generated subsurface processes (Larose et al., 2015; Li et al., 2018). Correct discrimination of natural processes from anthropogenic noise is especially pressing given the trend in seismic detection research toward automated algorithms and machine learning methods (Yoon et al., 2015; Kong et al., 2019;Mousavi and Beroza, 2022) and the growth in seismic data collection in new environments such as urban and industry settings (e.g., Díaz et al.,2017).

Seismological Research Letters↗

USGS2026

Methodology for quantitative spatial sensitivity analysis of volcanic geodetic networks

Introduction This report introduces a methodology for assessing the state of the U.S. Geological Survey Volcano Observatories’ geodetic monitoring networks that measure how volcanoes deform or change shape. This new method uses a model-based approach that considers the uniqueness of the instrument environments at each volcano. This report focuses on simplified volcanic sources, is independent of the shape or size of the volcano, or the network geometry, and thus highlights the strengths and potential vulnerabilities of each volcano’s geodetic network in an actionable visual format. This analysis can help observatories to make informed decisions about whether volcanoes have an adequate level of geodetic monitoring and indicate where improvements are needed.

Lassen Peak, Mount Shasta↗