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Landslide volume estimation from seismic waveform features using a global catalog of seismogenic events

Seismic waves generated by large, rapid landslides encode information about the source and can be analyzed rapidly following an event. Even remote landslides can pose hazards to downstream communities, so rapid detection and characterization using existing seismic monitoring networks could be beneficial. In this study, we expand on past regionally limited work by presenting a globally applicable method for estimating landslide volume from seismic features that could be integrated into future landslide seismic monitoring frameworks. We train the model using multivariable linear regression and five seismic features derived from recordings of 129 landslide events of a range of styles and locations with independently estimated volumes. We present two preferred models, one that combines long‐period (LP) and high‐frequency (HF) features and one for use on smaller landslides without observed long‐period signals. We find that our best‐performing model, applicable to landslides larger than 100,000 m 3 with signals containing observable long‐period energy, requires only two features: LP (20–100 s) absolute maximum amplitude and HF (1–5 Hz) rise time (time between the signal start and the maximum envelope amplitude) and has an R 2 score of 0.79. This model predicted volumes within one order of magnitude for 55 out of 58 events. We find that this combination mitigates the trade‐off between mass and acceleration and other variations of landslide style that limit methods based on amplitude alone.

Seismological Research Letters

Afterslip and creep in the rate-dependent framework: Joint inversion of borehole strain and GNSS displacements for the Mw 7.1 Ridgecrest earthquake

The elusive transition toward afterslip following an earthquake is challenging to capture with typical data resolution limits. A dense geodetic network recorded the Mw 7.1 Ridgecrest earthquake, including 16 Global Navigation Satellite System (GNSS) stations and 3 borehole strainmeters (BSM). The sub-nanostrain precision and sub-second sampling rate of BSMs bridges a gap between conventional seismologic and geodetic methods, exemplified by atypical postseismic shear strain reversals observed at nearfield (<2 km) station B921 that remain unexplained. We jointly invert GNSS displacements and BSM strains for coseismic and postseismic slip spanning hours to months over 7 independent periods. Cosiesmically, our model resolves the largest slip magnitudes of up to 6.6 m on the mainshock rupture plane, with similar patterns to other inferred slip distributions. The foreshock fault appears to slip coincidently with mainshock, revealing potential asperities activated during the preceding Mw 6.4 event. Postseismically, the best-fitting models adhere to mechanical rate-and-state expectations of logarithmically decaying slip adjacent to the coseismic rupture terminus, and where deep rheologic conditions favor creep. Most spatial variation occurs in the early postseismic timeframe (<1–2 weeks), with evidence for regional rheologic control and static stress dependence. Triggered creep on the neighboring Garlock Fault unexpectedly persists for >178 days—further highlighting the importance of fault networks in postseismic stress redistribution, critical to assessing future hazard.

Journal of Geophysics Research

Decoding the oxidative digestion mechanism for polystyrene nanoplastic detection in the Great Lakes using a customizable Raman spectral processing algorithm

Despite the concerns surging around nanoplastics (NPs) regarding their prevalence and bioavailability in freshwater systems, robust detection of NPs in complex environmental matrices is hindered by the lack of standardized sample pretreatment and a mechanistic understanding of oxidative digestion. Here, we systematically investigate the interaction between hydrogen peroxide (H 2 O 2 ) and polystyrene (PS) NPs during digestion in deionized (DI) water and four environmental matrices from in and around the Great Lakes Basin. To facilitate high-throughput analysis, we develop Pre_peak, a customizable Raman spectral processing algorithm that achieves >99% accuracy for both NP identification and interference rejection, allowing reliable NP quantification via pixel counting and systematic decoding of the oxidative digestion mechanisms. In DI water, varying H 2 O 2 doses from 0 to 30% has negligible effects on the recovery and Raman signal intensity of PS NPs over 24 hours of digestion. However, morphological changes and aggregation of PS NPs are observed when the H 2 O 2 dose exceeds 20%. Prolonged digestion further leads to progressive NP loss. In natural waters, the optimal dosage and digestion duration depend on matrix characteristics, including dissolved organic matter (DOM) and ion composition. This study provides mechanistic insights into NP–oxidant interactions and underscores the need for matrix-tailored digestion protocols to advance standardized NP detection in freshwater environments.

Great Lakes

A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps

Wildfire substantially alters aquatic ecosystems by inducing moderate to catastrophic physical and chemical changes. However, the relations of environmental and watershed variables that drive those effects are complex. We present a Driver-Factor-Stressor-Effect (DFSE) conceptual framework to assess the current state of the science related to post-wildfire water-quality. We reviewed 64 peer-reviewed papers using the DFSE framework to identify drivers, factors, stressors, and effects associated with each study. A total of five drivers were identified and ranked according to their frequency of occurrence in the literature: atmospheric processes > fire characteristics > ecologic processes and characteristics > land surface characteristics > soil characteristics. Commonly reported stressors include increased nutrients, runoff, and sediment transport. Furthermore, although several different factors have been used at least once to explain water-quality effects, relatively few factors outside of precipitation and fire characteristics are frequently studied. We identified several gaps indicating the need for long-term monitoring, multi-factor studies, consideration of organic contaminants, consideration of groundwater, and inclusion of soil characteristics. This assessment expands on other reviews and meta-analyses by exploring causal linkages between influential variables and overall effects in post-wildfire watersheds. Information gathered from our assessment and the framework itself can be used to inform future monitoring plans and as a guide for modeling efforts focused on better understanding specific processes or to mitigate potential risks of post-wildfire water quality.

Water Resources Research

Transit time modeling framework for predicting freshwater salinization in urban catchments

The salinity of inland freshwaters is rising globally, particularly in urban watersheds where winter road deicers are widely applied. Attributing stream salinity dynamics to specific sources and transport pathways remains challenging due to episodic salt inputs, engineered drainage, and strong coupling between hydrology and subsurface storage. We present a modeling framework that couples climate-driven deicer build-up and wash-off with transient transit time distribution theory to simulate salt transport through drainage, interflow, and groundwater pathways. Applied to an urban watershed in Northern Virginia (USA), the model reproduces ten years of high-frequency stream salinity measurements across daily-to-decadal timescales. The calibrated model implies an average deicer application of 206 tonnes Cl −1 yr −1 , or roughly one 20 kg bag of rock salt person −1 yr −1 when normalized by the 20,000 people living in the watershed. In winter months, higher infiltration routes a large fraction of snowmelt and deicers into shallow subsurface pathways, enhancing vadose-zone and interflow contributions to stream salinity. Limited subsurface storage capacity and seasonal hydrologic turnover flush excess chloride from the vadose zone and groundwater during subsequent summer storms. By linking climate-driven deicer inputs, hydrologic connectivity, and stream water age, the framework provides a transferable basis for diagnosing and managing freshwater salinization in urban watersheds.

Virginia

Long‐period ground motions from dynamic rupture simulations of large earthquakes on the creeping Hayward–Calaveras–Rodgers Creek fault system

he Hayward, Calaveras, and Rodgers Creek faults in the San Francisco Bay region of California have a high probability of producing a large earthquake in the next decades. Although these faults creep, the creep is insufficient to keep up with their relatively rapid slip rates on their deepest sections, so they have been storing tectonic strain since their last large earthquakes, with the Hayward’s and Rodgers Creek’s more than 150 yr ago. We do not know what the next large Hayward–Calaveras–Rodgers Creek earthquakes will look like or how strongly they will shake the San Francisco Bay region. Harris et al. (2021) used the 3D dynamic (spontaneous) rupture method to simulate large earthquakes on these creeping faults. In this article, we examine the resulting simulated long‐period ( T > 1 s) ground shaking from 0 to 50 km distance, for earthquakes nucleating on the Hayward fault and earthquakes nucleating on the Rodgers Creek fault. We compare these simulated long‐period ground motions with the Boore et al. (2014) well‐established empirically based ground‐motion model suitable for the slowest material velocity in our 3D velocity structure. We find that the simulated long‐period ground motions from the creeping‐fault earthquake scenarios produce a reasonable agreement with the empirical expectations if frictional cohesion is included only where it is appropriate.

California

Examining 22 years of ambient seismic wavefield at Mount St. Helens

An increase in seismic activity precedes most volcanic eruptions. Whereas event-based forecasting approaches have been successful, some eruptions remain unanticipated, resulting in casualties and damage. Our study leverages the recent advancements in ambient field seismology. We explore features extracted from continuous ambient fields using traditional methods, for example, peak ground velocity, peak ground acceleration, root mean square, root median square, real-time seismic amplitude measurement, and novel methods (displacement seismic amplitude ratio and spectral width). In addition, we explore unsupervised learning of higher order wavelet features using scattering networks. We find that combining all the methods was necessary to disentangle the effects of seismic sources from structural changes at Mount St. Helens. Although the ambient wavefield-based approach does not yield additional or more significant precursory signals than event-based methods at Mount St. Helens, our study demonstrates that the ambient wavefield provides supplementary information, mainly about structural changes and complements traditional methods. The ambient seismic wavefield offers additional insights into long-lasting processes. We find enhanced wave attenuation correlating with geochemical measurements. We interpret this as ongoing structural changes, such as dome growth or the evolution of the volcanic conduit system. On annual and decadal timescales, we interpret seasonal seismic attenuation in the shallow subsurface as groundwater fluctuations, corroborated by observations at the nearby Spirit Lake level. This multimethod approach at Mount St. Helens sheds light on a volcanic system’s underlying dynamics and structure.

Washington

Towards mobile wind measurements using joust configured ultrasonic anemometer for applications in gas flux quantification

Small uncrewed aerial systems (sUASs) can be used to quantify emissions of greenhouse and other gases, providing flexibility in quantifying these emissions from a multitude of sources, including oil and gas infrastructure, volcano plumes, wildfire emissions, and natural sources. However, sUAS-based emission estimates are sensitive to the accuracy of wind speed and direction measurements. In this study, we examined how filtering and correcting sUAS-based wind measurements affects data accuracy by comparing data from a miniature ultrasonic anemometer mounted on a sUAS in a joust configuration to highly accurate wind data taken from a nearby eddy covariance flux tower (aka the Tower). These corrections had a small effect on wind speed error, but reduced wind direction errors from 50° to >120° to 20–30°. A concurrent experiment examining the amount of error due to the sUAS and the Tower not being co-located showed that the impact of this separation was 0.16–0.21 ms &#x2212; 1 "> ms − 1 , a small influence on wind speed errors. Lower wind speed errors were correlated with lower turbulence intensity and higher relative wind speeds. There were also some loose trends in diminished wind direction errors at higher relative wind speeds. Therefore, to improve the quality of sUAS-based wind measurements, our study suggested that flight planning consider optimizing conditions that can lower turbulence intensity and maximize relative wind speeds as well as include post-flight corrections.

Alaska

Reference 1D seismic velocity models for volcano monitoring and imaging: Methods, models, and applications

Seismic velocity models of the crust are an integral part of earthquake monitoring systems at volcanoes. 1D models that vary only in depth are typically used for real‐time hypocenter determination and serve as critical reference models for detailed 3D imaging studies and geomechanical modeling. Such models are usually computed using seismic tomographic methods that rely on P ‐ and S ‐wave arrival‐time picks from numerous earthquakes recorded at receivers around the volcano. Traditional linearized tomographic methods that jointly invert for source locations, velocity structure, and station corrections depend critically on having reasonable starting values for the unknown parameters, are susceptible to local misfit minima and divergence, and often do not provide adequate uncertainty information. These issues are often exacerbated by sparse seismic networks, inadequate distributions of seismicity, and/or poor data quality common at volcanoes. In contrast, modern probabilistic global search methods avoid these issues only at the cost of increased computation time. In this article, we review both approaches and present example applications and comparisons at several volcanoes in the United States, including Mount Hood (Oregon), Mount St. Helens (Washington), the Island of Hawai’i, and Mount Cleveland (Alaska). We provide guidance on the proper usage of these methods as relevant to challenges specific to volcano monitoring and imaging. Finally, we survey‐published 1D P ‐wave velocity models from around the world and use them to derive a generic stratovolcano velocity model, which serves as a useful reference model for comparison and when local velocity information is sparse.

Seismological Research Letters

Limited preservation of strike-slip surface displacement in the geomorphic record

Offset geomorphic markers are commonly used to interpret slip history of strike-slip faults and have played an important role in forming earthquake recurrence models. These data sets are typically analyzed using cumulative probability methods to interpret average amounts of slip in past earthquakes. However, interpretation of the geomorphic record to infer surface slip history is complicated by slip variability, measurement uncertainty, and modification of offset features in the landscape. To investigate how well geomorphic data record surface slip, we use offset measurements from recent strike-slip surface ruptures ( n = 39), faults with geomorphic evidence of multiple strike-slip earthquakes ( n = 29), and synthetic slip distributions with added noise ( n > 10,000) to examine the constraints of the geomorphic record and the underlying assumptions of the cumulative offset probability distribution analysis method. We find that the geomorphic record is unlikely to resolve more than two paleo-slip distributions, except in specific cases with low slip variability, high slip-per-event, and semiarid climate. In cases where site-specific conditions allow for interpretation of more than two earthquakes, lateral extrapolation along a fault is not straightforward because on-fault displacement and distributed deformation may be spatially variable in each earthquake. We also find that average slip in modern earthquakes is adequately recovered by probability methods, but the reported prevalence of strike-slip faults with characteristic slip history is not supported by geomorphic data. We also propose updated methods to interpret slip history and construct uncertainty bounds for paleo-slip distributions.

Journal of Geophysical Research: Solid Earth

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

The digital archivist: Automating legacy macroseismic data processing using large language models

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor‐intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 M L 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground‐motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

Seismological Research Letters

What 25+ years of "Did You Feel It" intensities tell us about shaking in California

“When will the Big One happen?” is a question that people often have for earthquake scientists. But while waiting for the “Big One” to occur, people will usually experience frightening or damaging shaking from multiple relatively smaller‐magnitude earthquakes. Given this context, it raises the question: “Where does most of the damage come from?” Could smaller, yet more frequent, earthquakes account for the majority of reported impactful shaking? To explore this question, we consider reports of earthquake damage and felt shaking experiences from a catalog of community‐collected intensity values from the U.S. Geological Survey’s “Did You Feel It?” system. Comparing these intensities to expectations from a ground‐motion model, we find that earthquakes of magnitudes smaller than expected are responsible for most reported intensities of community decimal intensities (CDI) 4.5 and above (moderate and higher shaking intensity levels). (Here “expected value” is meant in its mathematical sense of the mean or equivalently median shaking intensity.) We also present a regional analysis of observed earthquake shaking for specific areas, detailing the maximum intensity experienced within a predetermined area. We identify several instances of M < 4.5 events that generated maximum intensities of CDI > 5 in regions in California surrounding the cities of Eureka, San Francisco, Los Angeles, and San Diego. Our results motivate the need to include smaller‐magnitude earthquakes in communications about earthquake hazard and risk reduction.

California

Modeling legacy nitrogen transport under instantaneous, steady-state, and transient groundwater flow conditions

In hydrologic settings where groundwater discharge contributes substantially to surface waters, legacy nitrogen in groundwater can confound surface water nitrogen loads estimated exclusively from current terrestrial sources. Additionally, legacy nitrogen in groundwater can contribute to lagged responses to nitrogen management efforts. Some methods of estimating groundwater contributions to surface water nitrogen loads account for legacy nitrogen, while others do not. The resulting differences are rarely quantified. We used a numerical modeling framework to compare three methods of estimating time-varying annual groundwater nitrogen loads to surface water receptors on eastern Long Island, New York. The instantaneous load method used steady-state contributing areas and includes no temporal groundwater lag. The second method used numerical simulations of nitrogen loads under steady-state flow, which captures groundwater transport lags but omits the annual variability in transient hydrologic stresses. The third method numerically simulated both transient groundwater flow and nitrogen transport to explicitly capture the effects of legacy nitrogen in groundwater. Depending on antecedent nitrogen and hydrologic conditions, historical nitrogen loads estimated from the numerical simulations were sometimes similar (<10% difference) and other times substantially different (±100%) from the instantaneous load estimates. Additionally, simulated future surface water nitrogen loads responded asymptotically over several decades following reductions in terrestrial nitrogen sources, further highlighting the effect of groundwater transport lag times. The comparison of the three methods, quantification of historical interannual variability, and prediction of lagged responses to nitrogen source reductions provide important context for decision makers using estimated groundwater nitrogen loads to help evaluate nitrogen management efficacy.

New York

Corundum discovered by SuperCam and the Perseverance rover at Jezero crater, Mars

Mars is primarily composed of mafic mineral assemblages and their alteration products, but small, scattered rocks strewn across the landscape offer clues to greater petrological diversity. While traversing the Jezero crater rim, the Perseverance rover encountered several plagioclase-rich light-toned float rocks. SuperCam identified the distinctive signature of corundum (α-Al 2 O 3 ) in these rocks using time-resolved luminescence spectroscopy. Two strong peaks (692.7 and 694.1 nm) with millisecond lifetimes, and additional supporting lines, are consistent with Cr 3+ substitution for Al 3+ in corundum. Corundum forms in Al-rich, Si-depleted environments through magmatic or metamorphic processes. Given the rocks' small size, association with plagioclase, and location on the crater rim, we interpret the most plausible formation scenario to be impact induced metamorphism at the interface of a felsic and a mafic/ultramafic member with the likely action of fluids at some stage, although other possibilities are not excluded.

Geophysical Research Letters

Moment magnitude for small earthquakes in the Delaware basin of west Texas and southeast New Mexico, USA

The Delaware Basin region of west Texas and southeast New Mexico has become one of the most prolific regions of seismic activity in the continental United States due to widespread hydraulic fracturing and wastewater disposal injection. In response to the increased number of earthquakes in this region, rapid and accurate characterization of earthquake sources is necessary to understand the evolution of seismic activity and level of seismic hazard associated with these earthquakes. This study re-evaluates earthquake magnitudes, estimating moment magnitude (MW) for small earthquakes in the Delaware Basin using 1) moment-rate spectra derived from S-wave coda envelopes, and 2) a relative magnitude method that relies exclusively on the ratio of waveform amplitudes between highly correlated waveform pairs. The coda-envelope method produces accurate M W estimates for small earthquakes ( M 1.5 – 3) that are consistent with independent, waveform modeled moment magnitudes for events with M W > 3 . Using the relative amplitudes method to extend these M W magnitudes to many other events, we successfully provide relative moment magnitude ( M W,rel ) values for 81% of the Texas Seismological Network catalog in the Delaware Basin region, and 45% of the USGS Induced Seismicity Project’s catalog of events in southeast New Mexico. The adoption and integration of the calibrated M W,rel method with current magnitude estimation methods offers valuable insights into the relationships between local and moment magnitude and will contribute to improved characterization of widespread induced seismicity.

New Mexico, Texas

Testing rate‐and‐state predictions of aftershock decay with distance

We analyze aftershocks of the 2019 M 7.1 Ridgecrest mainshock and isolated M 5–6 mainshocks in southern California to test predictions made by the rate‐and‐state friction model of Dieterich (1994) . Rate‐and‐state friction predicts that the seismicity rate after a stress step follows Omori decay, where the Omori c ‐value, which is the saturation in aftershock rate observed at small times, is larger for smaller stress steps. Put in the context of an aftershock sequence, this predicts that the Omori c ‐value will be systematically larger at greater distances from the mainshock. To our knowledge, this predicted effect has not been observed. In part this may be because the Omori c ‐value is difficult to measure because it often reflects short‐term catalog incompleteness rather than a true saturation in aftershock rate. We explore the dependence of the Omori c ‐value on the distance to the mainshock by applying the “ a ‐positive” method ( van der Elst and Page, 2023 ). This method is insensitive to short‐term aftershock incompleteness and allows resolution of the true aftershock rate deep into the mainshock coda. For aftershocks of the Ridgecrest mainshock and stacked M 5–6 mainshocks, we observe systematic differences in early aftershock rates, relative to mainshock distance, consistent with the predictions of rate‐and‐state friction. Furthermore, for the larger Ridgecrest dataset, we observe that aftershocks nearer to the mainshock start earlier, and we resolve a flattening of the Omori curve consistent with a larger Omori c ‐value for the farthest aftershocks, as predicted by Dieterich (1994) .

Seismological Research Letters

Onset of aftershocks: Constraints on the Rate-and-State model

Aftershock rates typically decay with time t after the mainshock according to the Omori–Utsu law, R (t)=K(c+t) −p ⁠ , with parameters K , c , and p . The rate‐and‐state (RS) model, which is currently the most popular physics‐based seismicity model, also predicts an Omori–Utsu decay with p = 1 and a c ‐value that depends on the size of the coseismic stress change. Because the mainshock‐induced stresses strongly vary in space, the c ‐value should vary accordingly. Short‐time aftershock incompleteness (STAI) in earthquake catalogs has prevented a detailed test of this prediction so far, but the newly developed a ‐positive method for reconstructing the true earthquake rate now allows its testing. Using previously published slip models, we calculate the coseismic stress changes for the six largest mainshocks in Southern California in recent decades and estimate the maximum shear as a scalar proxy of the coseismic stress tensor. Aftershock rates reconstructed for events in different stress ranges show that the rates follow a power law with p = 1 independent of stress with no clear sign of a c ‐value. The onset of the power‐law decay is abrupt and more delayed in areas with smaller stress changes. The observations do not necessarily contradict the RS model, as STAI limits the resolution for early aftershocks, and the RS model can reproduce the observations for specific Aσ values. However, the observations lead to strong constraints, namely Aσ <10 kPa and a power‐law decay of the background rate with distance to the fault, with exponent 2.7.

Seismological Research Letters