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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↗
USGS2025

Evidence for nonlocal sediment transport on hillslopes from fault scarp morphology

Hillslope sediment transport processes such as bioturbation, rainsplash, and granular mechanics occur across the entire planet. Yet, it remains uncertain how these small-scale processes act together to shape landscapes. Longstanding hillslope diffusion theory posits that hillslope processes are spatially limited, whereas new concepts of nonlocal sediment transport argue otherwise. However, each theory produces subtly different, but distinct, predictions for the evolution of fault scarps. We use the topographic change of fault scarps to demonstrate that hillslope processes produce nonlocal sediment transport. Analysis of a global compilation of 340 dated single-earthquake scarp profiles reveals a statistically significant ( p < 0.05 ) relationship between scarp age and scarp asymmetry, here defined as the ratio of imaginary to real components of the Fourier transform of absolute slope. Numerical simulations show that nonlocal models predict this relationship, whereas hillslope diffusion models do not. To further investigate this result, we examined the depositional geometry of a well-exposed colluvial wedge along the Wasatch fault in central Utah, United States. Our quantitative comparison between the exposure and numerical simulations reveals better agreement with the nonlocal model. Nonlocal sediment transport theory appears to best capture the physics of how hillslope processes shape fault scarps, yet hillslope diffusion provides a useful approximation in many cases. As the processes that act on fault scarps are nearly identical to those acting on hillslopes, our results provide evidence supporting nonlocality as a generalized model of hillslope sediment transport.

Utah↗
USGS2025

Extremophile hotspots linked to containerized industrial waste dumping in a deep-sea basin

Decaying barrels on the seafloor linked to DDT contamination have raised concerns about the public health implications of decades old industrial waste dumped off the coast of Los Angeles. To explore their contents, we collected sediment cores perpendicular to five deep-sea barrels. The concentration of DDT and its breakdown products were highly elevated relative to control sites yet did not vary with distance from the barrels, suggesting that they were not associated with the contamination. Sediment cores collected through white halos surrounding three barrels were enriched in calcite and had elevated pH. The associated microbial communities were low diversity and dominated by alkalophilic bacteria with metagenome-assembled genomes adapted to high pH. A solid concretion sampled between a white halo and barrel was composed of brucite, a magnesium hydroxide mineral that forms at high pH. Based on these findings, we postulate that leakage of containerized alkaline waste triggered the formation of mineral concretions that are slowly dissolving and raising the pH of the surrounding sediment pore water. This selects for taxa adapted to extreme alkalinity and drives the precipitation of “anthropogenic” carbonates forming white halos, which serve as a visual identifier of barrels that contained alkaline waste. Remarkably, containerized alkaline waste discarded >50 years ago represents a persistent pollutant creating localized mineral formations and microbial communities that resemble those observed at some hydrothermal systems. These formations were observed at one-third of the visually identified barrels in the San Pedro Basin and have unforeseen, long-term consequences for benthic communities in the region.

California↗
USGS2024

Seismicity and anisotropic imaging reveal an active detachment beneath the northern Alaska Range foothills

North of the Denali Fault, the collision between the Yakutat block with North America is accommodated by a fold-thrust belt giving rise to the northern Alaska Range foothills. At the western end, the Kantishna Hills anticline hosts prominent microseismicity and surface deformation, interpreted as active folding of the Kantishna Hills anticline above a midcrustal detachment. We test for this detachment by using anisotropy-aware receiver functions to image fabric contrasts within the crust in context with seismicity. Seismic stations near the crest of the Kantishna Hills anticline and near its southern flank show a single strong contrast in dipping fabric at depths of 12–13 km near microseismicity clustering depths, consistent with a detachment plane beneath the fold. A minimum b -value at 10–13 km depth is consistent with seismicity on the detachment, compatible with the imaged anisotropic contrast, while off-fault seismicity is shallower and deeper with smaller magnitudes. South-dipping imbricate thrusts in schist characterize the northern Alaska Range foothills structure. This supports our interpretation of the observed anisotropy as reflecting SSW–SSE-dipping foliation above a detachment at ∼10–13 km depth that exploits existing crustal weaknesses along subtle fabric contrasts observed in the seismically quiescent region north of the actively deforming belt.

Alaska↗
USGS2025

Earthquake recurrence estimates for northern Caribbean faults from combinatorial optimization

We use combinatorial optimization to find the optimal spatial distribution of random samples of earthquakes (≥6.5) that minimize the misfit in target slip rates for all faults in the northeast Caribbean, and we derive magnitude-frequency relationships with uncertainties for these faults. Slip rates for many faults are derived from GPS block models, not direct measurements, because of their underwater locations. Predicted recurrence rates for eastern Hispaniola and Puerto Rico Trench faults are 220-450 yr for M7 and 3-5 kyr for M8, with maximum feasible magnitude of M8.2. The most frequent earthquakes with magnitudes ≥7.0 are predicted on the large upper plate strike-slip faults, Enriquillo (EF) and Septentrional Fault, commensurate with the historical record. Calais et al. (2023) suggested that shortening in western Hispaniola is accommodated on the offshore Jérémie and onshore Malpasse faults north and south of EF, instead of on terrestrial faults in western Hispaniola and EF. Because of our system-modeling approach, such a configuration predicts less frequent earthquakes on EF and on western Hispaniola and Muertos convergent zones. Recurrence times of a few 100s yr for M6.7 earthquakes is predicted on the submerged faults in Mona Passage, and infrequent M>7 earthquakes are predicted on the Virgin Islands faults.

Lesser Antilles↗
USGS2025

Mineralization processes at Escanaba Trough

Escanaba Trough off northern California is the southernmost and only sediment covered segment of the Gorda Ridge. Hydrothermal mineralization was first discovered in Escanaba Trough in 1985, and subsequent investigations included the delineation of the NESCA (northern Escanaba) and SESCA (southern Escanaba) sections of Escanaba Trough, as well as drilling by Ocean Drilling Program (ODP) Leg 169 in 1996. Preliminary research conducted in the 1980s distinguished two classes of sulfide mineral assemblages within the Escanaba Trough: one dominated by pyrrhotite (Fe 1-x S) and one containing ‘mixed sulfides’ including chalcopyrite (CuFeS 2 ) and sphalerite (ZnS). In 2022, we conducted a research expedition to the Escanaba Trough to more thoroughly characterize mineralization processes and consider preservation of precipitated minerals throughout hydrothermally active and inactive sections of Escanaba Trough, with the specific objective of characterizing the host minerals, and processes of enrichment for specific elements which are currently listed as critical elements and can also be toxic under certain conditions (Sb, As, Ba, Co, Ga, Ge, Te). The following will include initial results from that work.

California↗
USGS2025

Hydrogeology and groundwater quality in the Snake River alluvial aquifer at Jackson Hole Airport, Wyoming, 2011–20

The Snake River alluvial aquifer underlying the Jackson Hole Airport (JHA) in northwest Wyoming is an important source of water used for domestic, commercial, and irrigation purposes by the airport and nearby residents. The U.S. Geological Survey, in response to previously identified water-quality concerns in the area, monitored and evaluated changes in hydrogeologic characteristics and groundwater-quality conditions of the alluvial aquifer during 2011–20. During that period, the Jackson Hole Airport made several changes that potentially improved water quality at and downgradient from the airport. Well, water level, and hydrogeologic data were collected from the alluvial aquifer to identify hydrogeologic characteristic and groundwater quality changes. Additionally, results of statistical tests were applied to water-quality results to evaluate trends in selected physical properties and constituent concentrations with time. The trends of those data show that water quality did improve overall during the study period compared to previously collected data. Presumably, these trends are in response to the changes in the aircraft deicing/anti-icing fluid (ADAF) formulation used by the JHA, the many JHA infrastructure improvements made during 2011–20, the degradation of existing ADAFs in subsurface soils and groundwater, or some combination of these possibilities.

Wyoming↗
USGS2025

The Long Island Sound and Watershed Metadata map application

The Long Island Sound and its watershed encompass an area of about 17,000 square miles and include the Connecticut, Housatonic, and Thames Rivers, which all drain to the sound. Dozens of organizations from government agencies, nonprofits, and Tribal Nations have developed projects and monitoring programs to analyze and protect the water resources of the watershed and sound. The abundance of data and lack of an existing searchable index require a centralized metadata repository to allow users to find water resources data more efficiently. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency and the Long Island Sound Study, has created an interactive map application to visualize and search for metadata information across organizations working to monitor and protect the Long Island Sound.

Connecticut, Massachusetts, New Hampshire, New Yor↗
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↗
USGS2025

Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration

Model criticism, discrimination, and selection methods often rely on calibrated model outputs. Because calibration can be computationally expensive, model criticism can first be undertaken by assessing model outputs obtained from limited prior parameter ensembles. However, such prior-based methods are often heuristic and do not formalize the notion of balancing model consistency with data and model complexity (i.e., model adequacy). We present a new framework to discriminate among candidate models prior to calibration that formalizes prior-to-calibration model adequacy into a metric to implicitly balance prior model output data coverage with model complexity represented by prior output (co)variance. The prior model adequacy metric “Mahalanobis distance deviation” quantifies the deviation of (a) the set of squared Mahalanobis distances of data from a prior model output distribution from (b) the set of squared Mahalanobis distances of data from their own distribution. A new data worth metric “discernment value” is also presented which quantifies the value of data for screening less-adequate models prior to calibration. Discernment value is calculated from the change in variance of a weighted average of prior model outputs from all candidate models due to less-adequate model outputs receiving lower weight. The framework is demonstrated using a one-dimensional groundwater flow model with eight possible configurations. A synthetic data network is used to test the framework. Results show the framework identifies the candidate models most similar to the true model used to create the synthetic data. Discernment values show variation in the value of different data types and locations for screening less-adequate models.

Water Resources Research↗
USGS2024

Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance

The Uniform California Earthquake Rupture Forecast version 3-Time Dependent depicts California’s seismic faults and their activity. Its logic tree has 5760 leaves. Considering 30 more model combinations related to ground motion produces 172,800 distinct models representing so-called epistemic uncertainties. To calculate risk to a portfolio of buildings, one also considers millions of earthquakes and spatially correlated ground-motion variability. We offer a tree-trimming technique that retains the probability distribution of portfolio loss and identifies the leading sources of uncertainty for further study. We applied it to a California statewide building portfolio and various levels of nonexceedance probability between one in 100 and one in 2500. We trimmed the logic tree from 172,800 leaves to as few as 15. The result: a supercomputer that would otherwise run 24 h to estimate the distribution of one-in-250-year loss can calculate it in moments with the reduced-order model. Others can use the reduced-order model to calculate risk to different California portfolios, and scientists can prioritize study to reduce the remaining epistemic uncertainty.

Earthquake Spectra↗
USGS2024

Self-guided decision support groundwater modelling with Python

The GMDSI tutorial notebooks repository provides learners with a comprehensive set of tutorials for self-guided training on decision-support groundwater modelling using Python-based tools. Although targeted at groundwater modelling, they are based around model-agnostic tools and readily transferable to other environmental modelling workflows. The tutorials are divided into three parts. The first covers fundamental theoretical concepts. These are intended as background reading for reference on an as-needed basis. Tutorials in the second part introduce learners to some of the core concepts parameter estimation in a groundwater modelling context, as well as providing a gentle introduction to the PEST, PEST++ and pyEMU software. Lastly, the third part demonstrates how to implement highly-parameterized applied decision-support modelling workflows. The tutorials aim to provide examples of both “how to use” the software as well as “how to think” about using the software. A key advantage to using notebooks in this context is that the workflows described run the same code as practitioners would run on a large-scale real- world application. Using a small synthetic model facilitates rapid progression through the workflow.

Journal of Open Source Education↗
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↗
USGS2025

Three-dimensional seismic velocity models for the San Francisco Bay region, California from joint body-wave and surface-wave tomography validated by waveform simulation

A high-resolution seismic velocity model for both P and S waves is essential for the San Francisco Bay (SFB) region to accurately simulate earthquake ground motions and assess seismic hazards in this high-risk region. We present new three-dimensional P-wave and S-wave velocity (Vp and Vs) models of the SFB region developed using joint tomographic inversion with a rich set of earthquake and active-source body-wave data and ambient-noise surface-wave data. We designed a dynamic balance strategy to effectively balance the contributions of body-wave and surface-wave data during each iteration of the inversion. Owing to the complementary resolution of body-wave and surface-wave data, our new models are significantly improved compared to previous tomographic models. Major geologic features in the SFB region, including low-velocity basins, high-velocity Franciscan Complex, granite, and gabbro rocks, and across-fault velocity contrasts, are imaged in our Vp and Vs models. Compared to the geology-based U.S. Geological Survey velocity model, our new model has better defined structures for some important areas that are of great concern for seismic hazard assessment, such as the Sacramento-San Joaquin Delta, and the 2014 magnitude 6.0 South Napa earthquake area. We validated our model by simulating waveforms for a set of moderate-magnitude earthquakes. The good performance of our model in waveform simulation indicates its potential for improving ground motion simulation and seismic hazard assessment in the SFB region.

California↗
USGS2025

Modeling byproduct and coproduct mine production and mineral substitution using multidimensional supply curves: Application to the Cu-Co-Ni system and beyond

Rapid demand growth is expected for many metals used in the energy transition. Many of these metals are byproducts of other commodities. Byproduct production’s price response is tied to host mineral economics, complicating its supply dynamics. Moreover, many of these metals are used in applications where the material properties desired are difficult to substitute; effectively, limiting how quickly demand can adapt to changes in commodity price. Previous work has demonstrated the interconnectivity of jointly produced mineral commodities from the supply side, where the copper–cobalt–nickel system was used and demand was assumed independent across commodities. Studies to understand byproduct-coproduct market interconnectivity on the demand side are limited, while studies on the interconnectivity of supply and demand simultaneously are even more so. We propose a modification to the multicommodity supply curve method to enable inter-commodity effects on demand simultaneous with supply. In batteries, high cobaltprices may push consumers to transition to high-nickel chemistries, causing the nickel demand surface to decrease with nickel price but increase with cobaltprice, creating a two-dimensional demand surface. Below cross-price elasticities of 0.05, inter-commodity effects were found to be negligible, potentially permitting exclusion of these effects for many commodities. This additional demand curve complexity introduces potential computation challenges alongside the capacity to model many interrelated commodity systems such as rare earth elements, ferroalloys, country-oriented subsidies or restrictions, and bifurcated sustainable metals markets. By presenting the work done on multicommodity supply surfaces to date and potential new directions, this work aims to catalyze the next round of innovative approaches to modeling jointly produced commodities.

Conference Paper↗
USGS2025

Persistent deep long-period seismicity near the Lassen Volcanic Center

Deep long-period (DLP) earthquakes have been observed at many volcanic settings around the world and linked to the magmatic processes that drive volcanic unrest. At the Lassen Volcanic Center (LVC) of the Cascade arc, limited detection of DLP activity hinders classification of anomalous seismic behavior and its relationship to the LVC magmatic system. This study uses a template matching approach with seismic data from temporary nodal and permanent stations to detect and locate DLP earthquakes near the LVC between 2017 and 2024. Within the DLP catalog of 611 events, a transition occurs from scattered (2017–2020) to oscillatory (2021–2024) occurrence rates. During the oscillatory period, regional earthquakes with large amplitude velocity waveforms observed near the LVC are associated with abrupt changes in DLP occurrence rates. Continued monitoring of DLP activity has the potential to better define the processes that drive volcanic unrest at the LVC in the future.

California↗
USGS2024

Updated three-dimensional temperature maps for the Great Basin, USA

As part of the periodic update of the geothermal energy assessments for the USA (e.g., last update by Williams and others, 2008), a new three-dimensional temperature map has been constructed for the Great Basin, USA. Williams and DeAngelo (2011) identified uncertainty in estimates of conductive heat flow near land surface as the largest contributor to uncertainty in previously published temperature maps. The new temperature maps incorporate new conductive heat flow estimates developed by DeAngelo and others (2023). Predicted temperatures at depth are compared with representative measurements (for conductively dominated conditions), showing good agreement under relatively simple uniform conditions. Inputs included radiogenic heat production for all layers of 1.89 μW/m 3 , effective bulk thermal conductivity of 2.7 W/m/°C for all rocks underlying sedimentary basins, and a previously published (Williams and DeAngelo, 2011) empirically driven estimate of increasing thermal conductivity with depth in sedimentary sequences. The resulting three-dimensional temperature model is published in a USGS data release associated with this manuscript (Burns and others, 2023).

Arizona, California, Idaho, Nevada, Oregon, Utah↗
USGS2026

Cultural benefits knowledge and social learning in Elwha River dam removal and ecosystem decision-making

In a retrospective case study of the seminal Elwha River dam removal in Washington State, USA, we explore pathways through which ecosystem services (ES) knowledge can inform environmental decision-making. We specifically investigate how knowledge of cultural benefits linked to the Elwha River ecosystem was made available. Through interviews and historical document review we identify diverse forms of cultural benefits knowledge (i.e., how individuals or groups know the contributions of an ecosystem to their identities, experiences, and capabilities), including both knowledge in the form of practices – embodied or enacted forms of knowledge, and knowledge in the form of products – quantitative or written documentation. Recognizing and learning from the diverse forms in which benefits knowledges are conveyed can support more accurate and equitable consideration of the diverse values, well-beings, and human-nature relationships linked to ecosystems. With this case study, we illuminate pathways for meaningful consideration of multiple knowledge forms, and the plural ecosystem values they convey, with relevance for environmental decision processes in the Puget Sound and beyond.

Washington↗