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1,225 records · Page 5Linked to original sources
USGS2025

Groundwater dominates snowmelt runoff and controls streamflow efficiency in the western United States

Climate change in seasonally snow-covered mountain catchments is reducing water supply and decreasing streamflow predictability. Here, we use tritium age dating to show that contrary to the common assumption that snowmelt quickly contributes to runoff, streamflow during snowmelt in western US catchments is dominated by older groundwater. The average age of streamwater during snowmelt runoff (5.7 ± 4.3 years) was intermediate to the average age of groundwater (10.4 ± 4.5 years) and recent precipitation, indicating that 58% (±34%) of snowmelt runoff was derived from groundwater. Water ages, streamflow, and groundwater storage were mediated by bedrock geology: low-permeability hard rock/shale catchments exhibited younger ages, less storage, and more efficient streamflow generation than high-permeability sandstone/clastic catchments. Our results demonstrate that snowmelt runoff is the result of multiple prior years of climate mediated by groundwater storage. Including these interactions will be crucial for predicting water resources as climate and landscape changes accelerate.

western united States↗
USGS2026

High-resolution landscape-scale maps of nutrients, phytoplankton, and related water-quality constituents in Suisun Bay and the Sacramento–San Joaquin Delta, California, during 2018—Results from high-resolution underway surveys

We examined the abundance and distribution of nutrients and phytoplankton in the tidal aquatic environments of the Sacramento–San Joaquin Delta (Delta) and Suisun, Grizzly, and Honker Bays in California by completing three spatial surveys that used continuous underway high frequency (1 hertz) measurements and sampling onboard a high-speed boat. Surveys were conducted in May, July, and October 2018. Water was sampled continuously during surveys to simultaneously collect information about the concentration and spatial distribution of all major nutrient forms together with information about the major classes of phytoplankton and associated standard field measurements of water quality, such as dissolved oxygen, dissolved organic matter, pH, salinity, specific conductance, turbidity, and water temperature. The results show a greater than 50-fold variation in nutrient and phytoplankton concentrations across space and time, providing evidence of the dynamic environmental processes that shape the ways nutrients interact with and affect Delta aquatic habitats.

Data Report↗
USGS2026

Estimating paleotemperature using stable isotopes of soil-formed phyllosilicates from paleosols: A review

Fossilized soils, or paleosols, contain soil-formed phyllosilicates whose stable isotopic compositions may be used to calculate paleotemperature and thus reconstruct ancient terrestrial environments. Though paleosols are common in the geologic record, the use of phyllosilicates as paleotemperature proxies is limited in the literature owing to difficulties with selecting optimal paleosols, isolation from non-clay minerals and organic materials, mixtures of phyllosilicates in natural samples, wide variations of chemical compositions for phyllosilicates, and limited to undefined equilibrium fractionation factors between phyllosilicates-water. Here, we address these challenges by examining and comparing methods used for sample selection, mineral isolation, pretreatments, mineral identification, conventional and developing methods for oxygen and hydrogen isotopic analyses, and determination of phyllosilicate-water equilibrium fractionation factors, concluding with recommendations for best approaches for paleotemperature estimation. Additionally, we discuss how to identify and avoid detrital phyllosilicates, the impacts of diagenesis, comparison of stable isotope and non-isotope paleosol paleotemperature proxies, and challenges and opportunities for broadly using paleosols as paleoclimate archives. With ongoing efforts to refine this multi-faceted paleotemperature approach, the stable isotope geochemistry of soil-formed phyllosilicates continues to be an invaluable proxy system, enhancing our understanding of terrestrial paleoenvironments and paleoclimate.

Kansas↗
USGS2026

Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)

Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.

Alaska↗
USGS2025

Earthquake stress-drop values delineate spatial variations in maximum shear stress in the Japanese forearc lithosphere

Earthquake stress drop (Δσ) may increase with depth and stress in the brittle lithosphere. However, the range of uncertainty in Δσ and the lack of constraints on absolute stress make it difficult to establish whether they are correlated. Here, we investigate Δσ dependence on depth and maximum shear stress ( τ max ) based on ~11 years of seismicity in the northeastern Japanese forearc following the 2011 Tohoku-Oki megathrust earthquake. We interpret Δσ estimates computed using both individual spectra and spectral-ratio methods and find that Δσ exhibits a clear depth dependence within the seismically active upper ~60 km of the forearc lithosphere ( ~ 0.8 MPa per 10 km). We further compare Δσ values with quantitative τ max estimates from finite-element models of force balance. We find that median Δσ values increase with τ max in the brittle forearc lithosphere and that earthquake stress release is proportional to τ max . The dependence of Δσ on τ max explains the apparent depth dependence of Δσ and suggests that average Δσ values provide a relative measure of the stress at failure. In the northeastern Japanese forearc, Δσ values remained roughly constant in the decade following the Tohoku-Oki earthquake, suggesting negligible changes in failure stress in the forearc since the mainshock.

Communications Earth and Environment↗
USGS2026

The damability function: A probabilistic approach to regional landslide dam susceptibility analysis applied to the Oregon Coast Range, USA

Landslides can dam rivers and require rapid response to mitigate catastrophic outburst floods. Here, we present a workflow to map landslide dam formation susceptibility at a regional scale. We define a probabilistic function that combines river valley width and landslide volume to efficiently determine the likelihood of a landslide dam or “damability”. We combine damability values with landslide susceptibility to estimate landslide dam susceptibility. The valley width measurements are automated using a new elevation threshold-based algorithm. Landslide volume is represented as a statistical distribution from mapped landslides. We validate and apply our approach to the Oregon Coast Range, USA and find that 36 % of river stretches exceed a dam potential threshold; these are in river headwaters and steeper terrain, which in this case correlate with more resistant lithologies. We also estimate volumes of the potential dammed lakes and find that most rivers with high dam susceptibility are less likely to impound large lakes because they have low drainage areas. However, widespread susceptibility, and the potential impacts from exceptionally large landslides, suggest that this hazard should be considered in the Pacific Northwest. The damability function workflow can ingest new data and be applied more broadly to assess future landslide dam hazards.

Oregon↗
USGS2025

3D viscoelastic models of slip-deficit rate along the Cascadia subduction zone

Interseismic deformation in the Pacific Northwest is constrained by the horizontal crustal velocity field derived from the Global Positioning System (GPS) in addition to vertical rates derived from GPS, leveling, and tide gauge measurements. Such measurements were folded in to deformation models of fault slip rates as part of the 2023 National Seismic Hazard Model (NSHM) update. Here I build upon one of the contributing models, the viscoelastic earthquake-cycle model of Pollitz [2022]. This model permits inclusion of effects of time-dependent viscoelastic relaxation within earthquake cycles (i.e., ‘ghost transients’) and laterally variable elastic and/or ductile material properties. I lever-age these capabilities to incorporate the Cascadia megathrust into Western U.S.-wide deformation models in which crustal fault slip rates are estimated simultaneously with slip deficit rates along the interplate boundary between the descending Juan de Fuca plate and North American plate. This effort includes construction of a margin-wide model of viscoelastic structure founded on the Slab 2.0 model and probes different models of the ductile properties of the surrounding oceanic asthenosphere, continental lower crust, and mantle asthenosphere. This results in new estimates of the distribution of slip deficit rate along the ∼ 1000 km long margin, highlights the importance of correcting for glacial-isostatic adjustment effects, and permits assessment of sensitivity of results to assumed ductile properties.

California, Oregon, Washington↗
USGS2025

Metaproteomics and metagenomics reveal microbial pathways of organic matter degradation and methanogenesis in a marginally producing natural gas well

The expansion of natural gas production and utilization worldwide has led to the decline of many once-productive wells, eventually resulting in costly well-plugging and unused infrastructure. However, in areas like the Michigan basin, MI, where the majority of natural gas is biogenically produced, microbial communities could potentially be stimulated to generate additional methane, increasing gas supply and reducing the need to drill new wells. In this study, we performed metaproteomic, metagenomic, and geochemical analyses of Antrim Shale formation water from a marginally producing natural gas well to evaluate resident microbial community functions in the context of potential bioenergy production. Functional proteins involved in methanogenesis, degradation/catabolism (including organic matter degradation), biosynthesis, energy utilization, transmembrane transport, and stress response were among the most commonly identified groups. Three metagenome-assembled genomes (MAGs) were characterized, including Methanomicrobiaceae, Methanothrix , and Smithella . For each, the identified proteins involved in methanogenesis and the degradation of diverse organic compounds, strongly suggest their role in utilizing shale-derived organic matter. These findings provide an increased understanding of the microorganisms and their metabolisms generating natural gas in the Antrim Shale and establish a foundation for future stimulation efforts aimed at enhancing biogenic methane production in marginal gas wells.

Michigan↗
USGS2026

Continental-scale prediction of hydrologic signatures and processes

Understanding how dominant hydrologic processes and their drivers vary across diverse continental-scale landscapes is critical for hydrologic modeling and water management applications. Our research addresses this question by synthesizing large-sample watershed datasets, Caravan and GAGES-II, and developing random forest models to identify patterns in hydrologic function. We assessed dominant processes by examining hydrologic signatures – summary indicators of watershed function derived from hydroclimatic time series and random forest models across 14 146 gauged United States watersheds. The results reveal clear continental-scale gradients in hydrologic processes, including baseflow, overland flow, storage, and water balance losses. Our map of dominant processes highlights, for example, the transition from baseflow to fast responses and back to baseflow along the elevation gradient from the Appalachian spine, through the Piedmont, to the Eastern Coastal Plain; a distinct outer ring around the Great Lakes region; and sharp contrasts between coastal and inland processes in the West. Variable importance analysis from random forest models show that processes in the western U.S. are primarily controlled by climate, whereas in the eastern U.S., soil, geology, and topography play larger roles, with distinct human influences apparent in urban areas. Our approach of estimating dominant processes and their drivers facilitates extending process knowledge from research watersheds to the continental scale, assessing current hydrological understanding, and evaluating hydrological model structures.

conterminous United States↗
USGS2026

A temporal look at the influence of topographic amplification on earthquake-triggered landslides in 3D seismic simulations

Earthquakes are a primary trigger for landslides, often leading to catastrophic consequences. While numerous studies have explored the spatial distribution of earthquake-triggered landslides, understanding the interaction between seismic waves and topography remains a critical challenge. Topographic irregularities can cause seismic wave amplification, altering ground shaking, and can trigger landslides that are challenging for predictive models to anticipate. This study investigates the spatial and temporal evolution of topographically amplified landslides, focusing on coseismic landslides triggered by the Mw 7.5 mainshock of the 2018 Papua New Guinea earthquake and post-seismic landslides associated with its four aftershocks, each exceeding Mw 6.0. We employ low-frequency, three-dimensional numerical ground shaking simulations and data-driven multivariate analyses to examine how landslides evolved from the coseismic to post-seismic periods. Our findings reveal a spatial shift in landslide distribution, in which the mainshock triggered slope failures predominantly on steep hillslopes, and the aftershocks triggered landslides on gentler slopes, often near geologic boundaries. We attribute this transition partly to the earthquake legacy effect of the mainshock, where the mainshock caused weakening of these hillslopes, making them more prone to failure when aftershocks occur. Additionally, the concentration of failures along geologic contacts in the post-seismic phase suggests that site amplification, stemming from contrasts in subsurface materials, exerts a key influence on landslide occurrence. Although not explicitly captured in our current numerical simulations, this mechanism warrants further investigation for more accurate hazard modeling.

JGR Solid Earth↗
USGS2026

An improved empirical model for predicting postfire debris-flow volume in the western United States

Reliable estimates of debris-flow volume can be used to help predict the magnitude of debris-flow hazards following wildfire in the western United States. In this study, we compiled and used a database of 227 postfire debris-flow volumes that were collected across the western United States to develop a multiple linear regression model for predicting postfire debris-flow volume. We explored 36 predictor variables related to rainfall, terrain, and fire characteristics, and selected the model with the combination of variables that yielded the most accurate predictions of debris-flow volume. We evaluated model performance against the entire volume database, as well as against four subsets of volume data from southern California, the Intermountain West, the Southwest, and regions with limited volume data, such as northern California and Washington. We also compared model performance against 3 existing postfire debris-flow volume models that were developed for use in southern California, the Intermountain West, and the Southwest. We demonstrate that the new volume model performs as well as the regional models in the regions for which they were developed and outperforms existing models when applied to volumes from data-limited regions in the western United States. These results indicate that the debris-flow volume model introduced in this study can be used to improve postfire hazard assessments across the western United States, especially outside of southern California.

Arizona, California, Colorado, New Mexico, Utah, W↗
USGS2025

An exploration of the relative influence of physical models for Omori’s law

Omori’s law states that the rate of aftershocks decays as a function of inverse time. There are multiple physical explanations that we reduce into a nonlinear mixed effects relation of three terms: (1) a Rate/State expression that can account for static/dynamic and viscoelastic triggering caused directly by the mainshock, (2) a fluid diffusion triggering term, and (3) a randomized secondary triggering (cascade) term. We fit free physical-model parameters to an observed aftershock sequence through two nonlinear regression methods to find the relative contributions of physics-based models in an observed aftershock sequence. Results from both methods show that Rate/State models overpredict aftershock rates by ∼0–30%. Secondary aftershocks cause a net negative contribution (seismicity rate reduction that corrects overprediction by other terms) ranging between ∼0 and 30%. All regression solutions yield negative secondary triggering contributions without being guided to do so. A physical explanation for this is that aftershock occurrence relieves stress from the crust, ultimately causing the sequence to extinguish itself. Fluid diffusion triggering contributions range from ∼0 to 20%. Diffusion processes are observed to be shorter in time than the full duration of an aftershock sequence and they are also spatially limited, diminishing their influence. Our results apply to an aftershock decay curve from the 2016 Central Apennines earthquake sequence, meaning that our specific results may not be general. Our primary conclusion is that any one physical model cannot alone fit the observed sequence as well as the combination of three we investigated.

Frontiers in Earth Science↗
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↗
USGS2026

Dynamic drainage reorganization in Eastern Tibet: Insights from the Yangtze River first bend

The modern drainage network of eastern Tibet is widely believed to have developed through a series of river capture and flow reversal events; however, the timing and mechanisms driving this reorganization remain contentious. Among these events, the river capture that formed the First Bend of the Yangtze River (YFB) stands out as both iconic and particularly debated. Here we present sedimentary provenance data from the Late Miocene–Quaternary Dali Basin, located south of the YFB, which indicate that a southward-flowing Jinsha River (i.e., the present-day upper Yangtze River) sourced sediment to the Dali basin at ∼7.4–6.4 Ma in a drainage configuration different from that of today. Because this interval postdates the initial establishment of a near-modern Jinsha River system prior to the Miocene, our results imply at least two discrete fluvial reorganizations occurred at the YFB—one preceding ∼7.4 Ma and another following ∼6.4 Ma. By integrating these findings with landscape evolution modeling, we infer that the initiation of rapid uplift of the Yulong-Haba Mountains and the Diancang Shan may have been responsible for these drainage reorganizations. These results underscore that Cenozoic drainage systems on the eastern Tibetan Plateau have evolved dynamically on a short timescale of ∼10 5 –10 6 -year, rather than remaining in a long-term stationary configuration on ∼10 7 -year timescales.

eastern Tibetan Plateau, first bend of the Yangtze↗
USGS2025

A high-resolution 3-D P-wave velocity structure of the south-central Cascadia subduction zone from wide-angle shore-crossing seismic refraction data

This study addresses a significant gap in understanding the features of the south-central Cascadia subduction zone, a region characterized by complex geologic, tectonic, and seismic transitions both offshore and onshore. Unlike other segments along this margin, this area lacks a 3-D velocity model to delineate its structural and geological features on a fine scale. To address this void, we developed a high-resolution 3-D P-wave velocity model using active source seismic data from ship-borne seismic shots recorded on temporary and permanent onshore seismic stations and ocean-bottom seismometers. Our model shows velocity variations across the region with distinct velocity-depth profiles for the Siletz, Franciscan, and Klamath terranes in the overlying plate. We identified seaward dipping high-velocity static backstops associated with the Siletz and Klamath terranes, situated near the shoreline and further inland, respectively. Regions of reduced crustal velocity are associated with crustal faults. Moreover, there is significant along-strike depth variation in the subducting slab, which is about 4 km deeper near the thick, dense Siletz terrane and becomes shallower near the predominantly less-dense Franciscan terrane. This highlights a sudden tectonic and geologic transition at the southern boundary of the Siletz terrane. Our velocity model also indicates slightly increased hydration, though still minimal, in both the oceanic crust and the upper mantle of the subducting plate compared to other parts of the margin.

British Columbia, California, Oregon, Washington↗
USGS2025

Characterizing the scale of regional landslide triggering from storm hydrometeorology

Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a dimensionless index for landslide-inducing rainfall, A * , based on extremes of modeled soil water relative to its local climatology. We calibrate A * using four landslide inventories, comprising over 11 000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow-landslide-triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A * , along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past 20 years, and we test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.

California↗
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↗
USGS2025

False positives in the identification of dynamic earthquake triggering

Dynamic earthquake triggering is commonly identified through the temporal correlation between increased seismicity rates and global earthquakes that are possible triggering events. However, correlation does not imply causation. False positives may occur when unrelated seismicity rate changes coincidently occur at around the time of candidate triggers. We investigate the expected false positive rate in Southern California with global M ≥ 6 earthquakes as candidate triggers. We compute the false positive rate by applying the statistical tests used by DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 to synthetic earthquake catalogs with no real dynamic triggering. We find a false positive rate of ∼3.5%–8.5% when realistic earthquake clustering is present, consistent with the 95% confidence typically used in seismology. However, when this false positive rate is applied to the tens of thousands of spatial-temporal windows in Southern California tested in DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 , thousands of false positives are expected. The expected false positive occurrence is large enough to explain the observed apparent triggering following 70% of large global earthquakes (DeSalvio & Fan, 2023, https://doi.org/10.1029/2023jb026487 ), without requiring any true dynamic triggering. Aside from the known triggering from the nearby El Mayor-Cucapah, Mexico, earthquake, the spatial and temporal characteristics of the reported triggering are indistinguishable from random false positives. This implies that best practice for dynamic triggering studies that depend on temporal correlation is to estimate the false positive rate and investigate whether the observed apparent triggering is distinguishable from the correlations that may occur by chance.

JGR Solid Earth↗