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USGS2025

Understanding market sensitivity: Estimation of supply and demand elasticities for non-fuel minerals

In today’s rapidly changing economic landscape, understanding market responsiveness to price changes and the factors influencing commodity prices has become increasingly relevant. Price elasticities serve as indicators of how variations in market conditions affect supply and demand, providing insights into the sensitivity of commodity markets to price fluctuations. This paper presents a comprehensive analysis of price elasticities of supply and demand for 74 non-fuel mineral commodities including precious metals, base metals, minor metals, and industrial minerals that are utilized across various industries. We employ various econometric techniques, including fixed effects models for panel data and two-stage dynamic ordinary least squares (2S-DOLS) alongside autoregressive distributed lag (ARDL) models for time series analysis, to derive robust estimates of price elasticities. Our findings reveal variability in elasticities among different commodities and indicate that all studied mineral commodities exhibit price inelastic supply and demand in the short run, which we define as one year for the purposes of our analysis, given that the data is all annual. This research provides original estimates of price responsiveness for a wide range of commodities that have not been previously addressed in the literature, thereby enhancing the understanding of market dynamics in the mineral sector. Given that price elasticities can be influenced by factors such as market structure, technological advancements, mining costs, and industry-specific demand drivers, we use variables that serve as proxies for these factors.

Mineral Economics↗
USGS2026

Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems

In intermittent stream systems, including those occurring in Texas, USA, the severity of low-flow conditions, duration of seasonal disconnection, and frequency of no-flow events have been amplified by drought. Documentation of these no-flow events is necessary to evaluate ecosystem health. However, many intermittent reaches remain un-gauged given that perennial river sec-tions are often prioritized for gauge placement. Our objectives were to 1) document stream flow using Stream Temperature, Intermittency, and Conductivity (STIC) loggers to determine the frequency and duration of no-flow events in intermittent tributaries of the Colorado River, Texas and 2) compare logger data to publicly available data from streamflow discharge and precipitation gauge networks to understand differences among these data types for drying event characterization. We use these comparisons to summarize benefits and limitations of the application of in-stream data loggers. STIC loggers were deployed at 19 sites, one in each pool and riffle habitat of a stream reach. STIC loggers recorded a measurement of relative conductance every six hours from June 2022 to March 2024, which was used to determine the presence or absence of flow connectivity in a reach. No-flow duration among intermittent reaches varied between 37 and 270 days across tributaries during an ongoing drought in the study area. Overall, logger data was more precise than discharge data for characterizing no-flow events or precipitation data when documenting presence of water in the stream channel due to runoff. Lack of discharge gauges in intermittent tributaries left large sections of stream reaches undocumented and resulted in mischaracterization of flow patterns. Drought severity across the tributaries did not follow longitudinal patterns that would be expected by the climatic precipitation gradient of the study area. More research is needed to determine if factors such as population size affect severity. Likewise, precipitation data did not correlate well with logger water presence data, lacking consideration for groundwater recharge, soil hydrophobicity, and surface compaction. This study shows that to monitor no-flow events, detailed spatial datasets are necessary and that STIC loggers are useful tools that provide data to fill spatial information gaps and facilitate more accurate flow characterization and water presence data in intermittent systems.

Texas↗
USGS2023

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

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

Geothermal Resources Council Transactions↗
USGS2025

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↗
USGS1976

Guidelines for collection and field analysis of ground-water samples for selected unstable constituents

The unstable nature of many chemical and physical constituents in ground water requires special collection procedures and field analysis immediately after collection. This report describes the techniques and equipment commonly used in the collection and field analysis of samples for pH, temperature, carbonate, bicarbonate, specific conductance, Eh, and dissolved oxygen.

Open-File Report↗
USGS2026

Mid-Cretaceous porphyritic magmatism in the Beartooth Mountains of the northern Laramide foreland and its connection to Frontier Formation sediment dispersal in Bighorn basin, Montana-Wyoming (USA), and Cordilleran tectonism

Porphyritic intrusions in the southeast Beartooth Mountains and porphyritic cobbles from the Torchlight conglomerate of the Cenomanian Frontier Formation in Bighorn basin (Montana-Wyoming, USA) bear striking resemblance. We utilize geologic mapping, petrography, geochemistry, and geochronology to characterize rocks from both locations and test whether the Beartooth Mountains area was the provenance for Bighorn basin cobbles. Mapping on Line Creek Plateau in the Beartooth Mountains shows three units with porphyritic phenocrysts consisting dominantly of plagioclase, plagioclase + potassium feldspar, and plagioclase + quartz. Petrography shows embayed quartz, opacitic rims, and zoned plagioclase. Geochemistry characterizes the intrusions as trachydacite to trachyte and trace elements exhibit enrichment in light rare earth elements and slight depletion in heavy rare earth elements relative to primitive mantle. Zircon U-Pb dating shows substantial Archean inheritance and ca. 104−92 Ma dates; some samples display multiple mid-Cretaceous date populations. Bighorn basin porphyritic cobbles exhibit similar modal mineralogy, near-identical geochemistry, and Archean inheritance and mid-Cretaceous geochronology. We suggest the porphyritic cobbles were sourced from basement-hosted porphyritic intrusions now exposed in the Beartooth Mountains, given that geochemistry does not agree with coeval volcanic sources along the Frontier Formation depositional fairway (Idaho batholith) or sedimentary-hosted Beartooth Mountains porphyritic sills intruded into Cambrian shale. Stratigraphic evidence does not support kilometer-scale mid-Cretaceous Beartooth Mountains exhumation to expose basement-hosted porphyritic intrusions, and we therefore present a volcanic hypothesis to bring rocks to the surface. This mid-Cretaceous multimillion-year magmatism is unexplained by tectonic models for the north-central Laramide foreland, and thus we further explore the emplacement processes, spatiotemporal significance, and tectonic implications of these rocks.

Montana, Wyoming↗
USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗
USGS2026

Multi-site evaluation of a postfire debris-flow runout forecast method

Postfire debris flows pose a hazard to human life, property, and infrastructure when they travel from steep source areas to urbanized alluvial fans or other developed areas. Existing methods for rapid (<1 week) postfire debris-flow hazard assessment document the increase in the likelihood and size of debris flows as the magnitude of high-intensity rain necessary to initiate debris flows increases but do not indicate the extent of downstream debris-flow runout. Although many models for the simulation of debris-flow motion are available, there is no established approach for using these models to delineate locations susceptible to postfire debris-flow runout that (a) is feasible to use at the spatial scale of an entire fire; (b) is appropriate for runout onto unconfined areas; (c) reproduces observed relations between runout and rainfall intensity; and (d) characterizes inherent uncertainty in runout, even without spatiotemporally variable rainfall. We propose and evaluate a method for generating postfire debris-flow runout hazard maps that has all the above qualities. Selection of case studies prioritized events triggered by a range of rainfall intensities, locations within and outside of southern California, and observed runout onto unconfined topography. Qualitative and quantitative assessment of performance for four events indicate that simulation results broadly match observations albeit with some discrepancies at a scale larger than structure or land parcel level (approximately 20-m by 20-m). The method may be used to identify potentially hazardous areas immediately following a fire and to provide approximate runout forecasts when a storm is imminent.

Arizona, California↗
USGS2024

RegionGrow3D: A deterministic analysis for characterizing discrete three-dimensional landslide source areas on a regional scale

Regional-scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics-based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three-dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad-scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km 2 ) using 3D, limit-equilibrium (LE)-based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back-calculated from inventoried landslides using 3D LE-based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.

Journal of Geophysical Research: Earth Surface↗
USGS2024

A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA

We develop a partially nonergodic ground-motion model (GMM) for Fourier amplitude spectra for the San Francisco Bay Area, California, USA, using the Bayless and Abrahamson (2019) GMM as a reference ergodic GMM and developing location-dependent adjustments to the predicted median and variance. We compile regional ground-motion data from moment magnitude (𝑀 w ) >3 earthquakes occurring during 2000–2022 for which magnitude information is available in the U.S. Geological Survey Comprehensive Catalog (Guy et al., 2015). The data set predominantly consists of records from 𝑀 w 3.5–4.5 earthquakes but includes three well-recorded 𝑀 w > 5 events. Ground-motion residuals are evaluated using the time-averaged shear-wave velocity in the top 30 m (𝑉 S30 ) from the California-specific map of Thompson et al. (2018) and basin-depth site parameters from the seismic velocity model of Aagaard and Hirakawa (2021). The 𝑉 S30 dependence and basin-depth scaling of the reference ergodic GMM of Bayless and Abrahamson (2019) are evaluated and modified with the updated data set. We compute maps of site adjustments using a varying-coefficient model that considers the spatial correlation structure and uncertainties at each observation location. The spatial covariance model is developed using ground-motion residuals that are standardized by the uncertainty model, which allows for consideration of the aleatory variability in developing the site adjustments. The covariance model is fit considering the means and standard deviations of the site terms at all locations. The use of partially nonergodic median adjustments results in modified variance components of the within-event variability. Due to the low number of large-magnitude earthquakes that control seismic hazard in the data set, we do not modify between-event variance; however, we present adjustments to site-to-site variability for use in partially nonergodic hazard assessments.

California↗
USGS2025

Remote single-station seismic monitoring of the July–October 2022 earthquake swarm at Tau volcano, American Samoa

From July to October 2022, a non-eruptive volcanic earthquake swarm occurred within ~15 km of Taʻū Island, located in eastern American Samoa. Felt reports from local residents were the only available information about the swarm when it started, as American Samoa lacked a seismic monitoring network. We developed a consistent single-station catalog for the entire swarm, using seismic data from the nearest station IU.AFI, ~250 km away. We applied the EQTransformer deep-learning model (Mousavi et al., 2020), automatically picking Pn and Sn arrivals on IU.AFI continuous data. We retained only events with Sn-Pn times of 22.5–25 seconds, consistent with the expected locations based on felt reports, then detected smaller swarm events with subsequent template-matching. This single-station catalog characterized the swarm’s onset and escalation to peak activity before a multi-agency field response team installed a local seismic network in mid-August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S-P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Taʻū Island. Modern seismological processing methods, combined with basic observations such as felt reports, can quickly contribute useful information during an earthquake response in a poorly monitored region.

American Somoa↗
USGS2026

Satellite tracking of Galapagos Petrel Pterodroma phaeopygia reveals distribution and movements during chick rearing

We tracked 19 adult Galapagos Petrels Pterodroma phaeopygia during the chick-rearing seasons in 2009 and 2010 (Santa Cruz Island [ n = 16] and Floreana Island [ n = 3]) in the Galápagos Islands, Ecuador. Eight petrels performed 27 complete foraging trips lasting 0.6 to 18.8 days. Short trips (3.2 ± 2.1 days; 785 km; max displacement 671 km) and long trips (10.8 ± 3.9 days; 2,856 km; max displacement 1,034 km) resulted in concentrated use of waters off southern and western Isabela Island and within the Galápagos Marine Reserve (GMR). Less concentrated time extended farther southwest and eastward, in that case toward mainland Ecuador. Total distance covered among all completed trips, independent of duration, was strongly correlated with trip duration ( R ² = 0.92), indicating a strategy favoring active searching and foraging over commuting. Petrels ranged across Ecuador's exclusive economic zone (EEZ), as well as other countries' (Colombia, Costa Rica, Perú), and waters beyond; they spent 46%, 27%, and 34% of their time in the GMR during short, long, and apparent (incomplete) trips, respectively. However, overlap with EEZs or marine protected areas (MPAs) does not necessarily confer protection, because commercial tuna fishing, including legal fishing historically permitted inside the GMR, occurs within these waters. Including all complete and incomplete trips, petrels spent 37% of their time in high-seas waters without formal protection, outside both MPAs and EEZs. While some hot spots overlapped Galápagos MPAs, the far-ranging nature of chick-provisioning petrels underscores the importance for this species of also having coordinated, multinational protection of the high seas.

Floreana Island, Galápagos Islands, Santa Cruz Isl↗
USGS2025

Time-varying rates of organic and inorganic mass accumulation in southeast Louisiana marshes: Relationships to sea-level anomalies and tropical storms

Louisiana's coastal wetlands are complex systems that require a continuous input of organic and inorganic material to keep pace with relative sea-level rise. Coastal restoration projects such as sediment diversions are being implemented to mitigate land loss and increase availability of inorganic sediment to coastal wetlands, and marshes specifically rely on organic material to build soil volume and maintain surface elevation. Interannual-to-decadal sea-level anomalies such as hurricanes can affect marsh accretion, mineral deposition, and plant productivity. In this light, complex ecogeomorphic feedback controls whether a marsh surface is sustainable or eroded/drowns. This study performs some of the first differential vertical accretion rates (VARs) and organic and inorganic mass accumulation rates (MARs) over time in SE Louisiana marshes determined from the 210 Pb Constant Rate of Supply model, coupled with standard 137 Cs VARs. These accumulation rates over the past ∼100 years were measured from a total of six brackish and salt marsh locations in Barataria Basin near the proposed Mid-Barataria Sediment Diversion. They were then related to interannual sea-surface elevations at Grand Isle, Louisiana, over the last ∼60 years and recorded hurricane activity in the delta. Results show VARs range from 0.63 cm/y to 1.69 cm/y and total MARs range from 0.11 to 0.43 g/cm 2 /y. Temporally, VARs and MARs (total, inorganic, and organic) are characterized by gradual increases in rates with decreasing age along with episodic peaks in VARs and MARs. The findings of this study indicate that no relationship occurs between sea-level anomalies and VARs or organic and inorganic MARs; however, a strong relationship appears to occur between major hurricanes to VAR and MAR contributions. Furthermore, high water content (81 ± 8%) and organic-rich soils in the sediment cores highlight the significance of belowground biomass and associated pore volume in maintaining marsh elevation in the study area.

Louisiana↗
USGS2024

Mapping karst groundwater flow paths and delineating recharge areas for springs in the Little Sequatchie and Pryor Cove watersheds, Tennessee

The Little Sequatchie River and Pryor Cove Branch, in southern Tennessee, drain the eastern escarpment of the Cumberland Plateau to the Sequatchie River near the southern end of the Sequatchie Valley. The Little Sequatchie River is the largest tributary to the Sequatchie River by drainage area, covering over 120 square miles. The hydrology of the two drainage areas has been largely altered by karst processes, which has caused the majority of the streams to sink at the contact between the Mississippian Pennington Formation and the underlying Mississippian Bangor Limestone. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service and Tennessee Department of Environment and Conservation, initiated a study in 2021 to map the karst groundwater pathways in both watersheds in order to delineate recharge areas for several springs. One of these springs, Sequatchie Cave, represents a significant habitat for two Species of Greatest Conservation Need, the Glyphopsyche sequatchie (Sequatchie caddisfly) and the federally endangered Marstonia ogmorhaphe (royal marstonia). Springs and springflow-dominated streams in the Little Sequatchie River valley and Pryor Cove also provide water for agricultural practices and serve as a drinking water source for nearby communities. During the study, a total of 25 dye injections were conducted over eight rounds from January 2022 through March 2023. Dye traces from these injections helped to delineate recharge areas for six major springs, ranging from 7.3 to 65.2 square miles in area. The majority of the dye traces remained subsurface (from sinkpoint to recovery site) for long distances, with karst groundwater travelling nearly 8 miles before resurfacing. The dye traces also had rapid traveltimes, often travelling hundreds to thousands of feet per hour. The goal of this project was to provide scientific data related to karst groundwater pathways and spring recharge areas to aid State and Federal agencies in making informed decisions to protect and preserve this unique and vulnerable karst system.

Tennessee↗
USGS2025

Enhanced geothermal systems electric-resource assessment for the Great Basin, southwestern United States

The U.S. Geological Survey recently (2025) completed a provisional assessment of the geothermal-electric resources associated with high-temperature, low-permeability rock formations of the Great Basin, Southwestern United States. If sufficient technological advances to commercialize enhanced geothermal systems occur, then a current best provisional estimate for electric-power generation capacity of 135 gigawatts electric are available from the upper 6 kilometers of the Earth’s crust. This estimate is a potential substantial increase of the installed geothermal electricity-generating capacity from <1 to 10 percent of current total U.S. power production capacity.

California, Idaho, Nevada, Oregon, Utah↗
USGS2025

Colored shaded-relief bathymetry and acoustic backscatter of Lake Sammamish, Washington

Evidence of strong earthquakes (such as underwater landslides and associated deposits) may be recorded within the lacustrine sediments of Pacific Northwest lakes. The floor of Lake Sammamish, Wash., an approximately 11 kilometer (6.8 mile) long, 2 kilometer (1.2 mile) wide, and 35 meter (114.8 feet) deep lake located in a populated region just east of Seattle, was mapped by the U.S. Geological Survey in November of 2021 to search for evidence of past earthquakes. Mapping was conducted using a SWATHplus-M 234-kHz interferometric side-scan sonar system was pole-mounted on the U.S. Geological Survey research vessel Parke Snavely, and the system collected full-coverage bathymetric and acoustic backscatter data, which were processed to 2-meter spatial resolution. Two maps were created, a colored shaded-relief bathymetric map showing lake floor morphology (sheet 1), and an acoustic-backscatter map showing backscatter intensities (sheet 2). The results may then be utilized together to investigate past earthquake activity.

Washington↗
USGS2025

Identification of representative earthquakes for probabilistic tsunami hazard analysis (PTHA) using earthquake rupture forecasts and machine learning

As probabilistic tsunami hazard analysis (PTHA) focuses more on assessments for localized, populous regions, techniques are needed to identify a subsample of representative earthquake ruptures to make the computational requirements for producing high-resolution hazard maps tractable. Moreover, the greatest epistemic uncertainty in seismic PTHA is related to source characterization, which is often poorly defined and subjective. We address these two salient issues by applying streamlined earthquake rupture forecasts (ERFs), based on combinatorial optimization methods, to an unsupervised machine learning workflow for identifying representative ruptures. ERFs determine the optimal distribution of a millennia-scale sample of earthquakes by inverting the observed slip rate on major faults. We use two previously developed combinatorial optimization ERFs, integer programming and greedy sequential, to produce the optimal location of ruptures with seismic moments sampled from a regional Gutenberg–Richter magnitude–frequency distribution. These ruptures in turn are used to calculate peak nearshore tsunami amplitude, using computationally efficient tsunami Green's functions. An unsupervised machine learning workflow is then used to identify a small subsample of the earthquakes input to ERFs for onshore PTHA analysis. We eliminate epistemic uncertainty related to source distribution under traditional PTHA analysis; in its place, a quantifiable, less subjective and generally smaller uncertainty related to the input to ERFs is included. The Nankai subduction zone is used as a test case, where previous ERFs have been conducted. Results indicate that the locations of representative earthquakes are sensitive to choice of magnitude–area relation and to whether a minimum cumulative stress objective is imposed on the fault. In general, incorporating ERFs into PTHA provide a physically self-consistent method to incorporate fault slip information in determining representative earthquakes for onshore PTHA, eliminating a major source of epistemic uncertainty.

Nankai subduction zone↗
USGS2026

Evaluation of stream capture related to groundwater pumping, middle Humboldt River Basin, Nevada

Historical, future, and potential stream capture from groundwater pumping in the middle Humboldt River Basin (MHRB), Nevada, is estimated using a calibrated numerical groundwater flow model. The model was developed to estimate (1) stream capture, which is the change in flux between the groundwater system and the Humboldt River and tributaries, and (2) change in streamflow, which is the change in streamflow estimated for the Imlay gage on the Humboldt River (U.S. Geological Survey streamgage 10333000). Historical stream capture for water years (WYs) 1961–2015 is estimated using recorded and estimated groundwater pumping during that period. Future (predictive) stream capture was based on historical stresses (WYs 1961–2015) using a scenario that simulated non-mine pumping from WY 2015 at a uniform rate for 100 years into the future. Potential stream capture throughout the middle Humboldt River Basin from groundwater pumping during varying durations of time are presented in a series of capture maps. Maps also are presented that show the potential to capture from groundwater evapotranspiration, as well as the storage changes for pumping duration of 100 years. Estimates of historical stream capture from the mainstem Humboldt River during the early 1960s are less than 400 acre-feet per year (acre-ft/yr) when groundwater withdrawals and pumping rates were relatively small compared to more recent times. In the late 1980s and early 1990s, groundwater withdrawals increased and estimated historical stream capture also increased from about 4,000 acre-ft/yr in the late 1980s and early 1990s to as much as 18,800 acre-feet (acre-ft) in WY 1998. In WY 2015, estimated historical stream capture declined to about 13,000 acre-ft because of decreasing groundwater withdrawals and lower streamflow during the drought of WYs 2012–15, resulting in less stream water available for capture. Stream capture was estimated for 100 years into the future based on WY 2015 non-mine pumping rates and mine-dewatering activity through WY 2015. Stream capture is forecast to increase to about 23,000 acre-ft/yr, and streamflow in the Humboldt River could decrease by as much as 19,000 acre-ft/yr. Pumping for mine-dewatering and the associated discharge of that water affects streamflow in the Humboldt River at Imlay, Nevada (U.S. Geological Survey streamgage 10333000). Historically, from WYs 1991 to 2015, streamflow was greater at Imlay gage during active mine-dewatering from mine-water discharge operations and increased by as much as 105,000 acre-ft in WY 1998. The increase was attributed mostly to the discharge of groundwater from mine-related dewatering operations directly into the mainstem Humboldt River or its tributaries, with some of this increase associated with return flows from discharge to rapid infiltration basins. Results indicate that streamflow at Imlay gage is expected to decrease by as much as 1,600 acre-ft/yr 30 years after mine-related pumping and discharge are discontinued. The streamflow reductions at the Imlay gage are expected to then decrease to around 500 acre-ft/yr, 100 years after mine-related pumping and discharge are discontinued. Potential capture maps were produced for pumping durations of 10, 25, 50, and 100 years. Capture map results indicate that areas of greater potential stream capture occur adjacent to the Humboldt River and for upstream tributaries areas north of the Humboldt River.

Nevada↗