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1,666 records · Page 29Linked to original sources
USGS2023

Oligocene–Miocene northward growth of the Tibetan Plateau: Insights from intermontane basins in the West Qinling Belt, NW China

Growth of the Tibetan Plateau, Earth’s broadest and highest elevation collisional system, shapes orographic barriers, reorganizes drainage networks, and influences surface erosion and sediment delivery, whose changes in space and provenance feed back to intracontinental tectonic processes. Studies of interior basins within the northern Tibetan Plateau provide new sediment accumulation, provenance, paleodrainage, and deformation timing data that enable a reconstruction of the far-field tectono-geomorphic evolution of the rising Tibetan Plateau. Along the northern plateau margin, topographic growth in the West Qinling Belt is inferred to have initiated in the Eocene, nearly coeval with the India-Asia collision, as well as in the late Miocene. However, geological knowledge about the intervening period remains at present enigmatic, and the kinematics and dynamics are uncertain. This study presents a multidisciplinary data set from the intermontane Anhua-Huicheng Basin (AHB; Gansu Province, China) to fill this gap. Magnetostratigraphic dating, regional mapping, and sedimentological analysis imply that contractional deformation and thrust-top basin systems formed within the West Qinling Belt in the Oligocene (not later than ca. 24 Ma). A combination of observations including paleocurrent changes, detrital zircon U-Pb age variations, and appearance of growth strata along the Anhua-Huicheng Basin reveal the rapid uplift of the West Qinling Belt at ca. 15 Ma. Sedimentation in the intermontane basins ended after the late Miocene (ca. 8 Ma), when the region experienced intrabasinal deformation, uplift, and erosion with the establishment of an external drainage system. Since the late Miocene, the growth of the West Qinling Belt reached a climax with the lack of substantial contractional deformation in Cenozoic sequences heralding the onset of the modern kinematic regime and attainment of high elevation. Observed transitions in the tectonostratigraphy and paleodrainage define different phases of deformation and plateau-wide shifts in stress reorganization, which led to the northward growth and later lateral expansion of the Tibetan Plateau.

GSA Bulletin↗
USGS2026

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↗
USGS2024

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↗
USGS2024

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↗
USGS2026

A three-dimensional geologic framework model of the northern Great Plains region of Montana, North Dakota, South Dakota, and Wyoming, USA

This report presents a new three-dimensional geologic framework model (GFM) of the northern Great Plains region, encompassing parts of Montana, North Dakota, South Dakota, and Wyoming. The model provides a regionally consistent, geographic information system (GIS)-ready representation of Phanerozoic sedimentary strata, major fault systems, and Precambrian basement geometry across two sedimentary basins and adjacent uplifts. More than 300,000 geologic and geophysical data inputs were synthesized to model 41 stratigraphic horizons and 47 faults, yielding an internally coherent, sealed-volume interpretation of the subsurface. The modeling workflow developed for this study demonstrates an efficient and scalable approach for constructing basin-to regional-scale GFMs in geologically complex and data-variable settings. Although model fidelity varies with data density and quality, the resulting geometry is broadly consistent with 1:500,000-scale geologic mapping and highlights areas where additional geologic study is most needed. The three-dimensional GFM provides a foundational framework to support groundwater, energy, and mineral resource assessments, and offers a transferable methodology for potential future U.S. Geological Survey efforts to build large-area subsurface models in underexplored regions of the United States.

Montana, North Dakota, South Dakota, Wyoming↗
USGS2026

Software to support remote sensing of river discharge based on critical flow theory

Water resource management requires accurate observations of streamflow but standard field methods for measuring river discharge ( Q ) are costly and can be hazardous for equipment and personnel. Remote sensing has become a viable alternative, but many image-based techniques require field data for calibration and depth and velocity can seldom be mapped with a single sensor. A new approach based on critical flow theory, in contrast, allows both of these attributes to be inferred from readily available image data. This technique only pertains to sites with standing waves, called undular hydraulic jumps (UHJs), but a recent investigation demonstrated its potential to provide accurate discharge estimates. This paper introduces software designed to facilitate Inferring Q from UHJs Identified in River Images (InQUIRI). The package includes modules for retrieving data from image servers, making the measurements of wavelength and width required to calculate discharge, inferring a representative wavelength from a profile digitized along a wave train, combining multiple estimates to obtain an ensemble median discharge, and assessing accuracy via comparison to gage records from the U.S. Geological Survey. By making these steps easier to implement, InQUIRI enables users to apply the workflow to a variety of UHJ-containing images. Accumulating more case studies, some successful and others less so, would help constrain the range of applicability of the critical flow approach and foster development of refined guidelines for selecting and measuring waves. The software described herein could play an important role in promoting informed use of this new technique for non-contact streamflow measurement.

Arizona, Colorado, New Mexico, Utah↗
USGS2024

Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites: Insights from deep learning

We developed a suite of models using deep learning to make hindcast predictions of the 7‐day average backward‐looking nitrate concentration at 46 predominantly agricultural sites across the midwestern and eastern United States. The models used daily observations of discharge and meteorological variables and watershed attributes describing anthropogenic modification to hydrology, nitrogen application, climate, groundwater, land use, watershed physiographic attributes, and soils. Across all sites, discharge and watershed soil and physiographic attributes showed a strong influence on model performance. Analysis of drivers across sites revealed considerable regional differences related to controlling processes such as groundwater contributions. We tested several ways to pool data across sites to develop accurate models and make the most effective use of available data. Single‐site models, in which models are trained and tested at a single location, showed generally strong predictive performance (median Kling‐Gupta Efficiency = 0.66), and accuracy at poorly performing sites could be improved by grouping sites with similar characteristics. Developing a single model for all sites reduced performance at several locations with distinct characteristics, suggesting that there is a threshold of dissimilarity beyond which more data does not improve the model. While many deep learning studies have shown that national or even global models can outperform local models, it is not clear that this is true for water quality constituents. This study demonstrates how data can be combined effectively, using deep learning to develop accurate and interpretable models of instream nitrate at sites where varying processes are responsible for changes in nitrate concentration.

Water Resources Research↗
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↗
USGS2025

Using peak geometry and shifts in the x-ray spectrum of carbon from electron probe microanalysis to determine thermal maturity of organic matter

During the burial of mudstones, the associated organic matter undergoes gradual thermal maturation, a key process that can influence the reactivity of organic matter during catagenesis, the formation of hydrocarbon deposits and the chemical weathering of mudstones. Conventional methods for assessing the thermal maturity of organic matter often fail to reflect the geochemical heterogeneity between individual organic phases in mudstone samples. Here, we report an alternative, non-destructive, surficial and micro-scale (analytical spot size of ~ 300 nm with about 4 μm diffusion depth for micrometre-size organic grains) method to evaluate the thermal maturity of organic matter in mudstones using the carbon K α X-ray spectrum measured by field emission-electron probe microanalyser (FE-EPMA). Using this method, we observed correlations between parameter values derived from FE-EPMA spectra, including the peak position, the peak area and the intra-sample heterogeneity of these measurements, and independently measured vitrinite/solid bitumen reflectance for a suite of mudstones, representing different age, geological context and burial depth. With the increased values in peak area and position, we identified an increase in the carbon mass fraction of organic matter and the mean nominal oxidation state of carbon approaching zero. These trends, which are consistent with aromatisation and graphitisation, provide the rationale for using FE-EPMA to estimate the thermal maturity of organic matter. To explore some of these trends in more detail, we employed time-of-flight secondary ionisation mass spectrometry, X-ray photoelectron spectroscopy and optical reflectance measurements on a subset of samples.

Geostandards and Geoanalytical Research↗
USGS2026

Magnitude conversion relations create substantial differences in seismic hazard models

Earthquake catalogs are essential data inputs for seismic hazard modeling. Because earthquake magnitudes are reported in a variety of types (e.g., local magnitudes and moment magnitudes), magnitude conversion relationships must be used to convert the different magnitude types present in a catalog to a uniform magnitude type to avoid biases in the hazard computation. However, these conversion relationships are often uncertain and have been shown to sometimes perform poorly. Here, we investigate the sensitivity of the gridded seismicity component of the National Seismic Hazard Model (NSHM) to the catalog conversion equations in the Eastern United States. In the 2023 NSHM, magnitudes of various types were converted to moment magnitudes using equations developed by the Central and Eastern United States Seismic Source Characterization for Nuclear Facilities (CEUS‐SSCn), based on least‐squares (LS) regressions made using data from a catalog containing events up through 2008. We recompute these equations using events in the Advanced National Seismic System Comprehensive Earthquake Catalog with multiple magnitudes from 2000 to 2023. Although we prefer the use of orthogonal regressions for our datasets, LS regressions produce broadly similar results, with both approaches exhibiting large deviations from the CEUS‐SSCn conversions, especially at smaller magnitudes. We compare the spatial distribution of annual rates using three different models: (1) the 2023 NSHM conversions, (2) our updated conversions, and (3) no conversions. We find that the choice of conversions leads to substantial differences in the rate forecasts, which can greatly impact the seismic hazard model, particularly in regions with low‐seismicity rates such as the Eastern United States, where the hazard is dominated by gridded seismicity rather than a fault model.

Seismological Research Letters↗
USGS2025

Searching for seismic precursors - The Barry Landslide hazard clean up

The Barry Landslide, located in Barry Arm of Prince William Sound, Alaska, poses a major hazard due to its steep, unstable slopes and the potential for a massive landslide-generated tsunami. With an estimated volume of 500–700 million cubic meters, the Barry Landslide could trigger highly destructive waves. In this study, we focus on seismic signals from the Barry Landslide, which are critical for providing timely tsunami warnings. Since the summer of 2020, the region has been instrumented to monitor the landslide, but the seismic record is complicated by the presence of nearby glaciers and frequent regional earthquakes. Among these signals, we analyze a specific class of short-duration, high-frequency seismic events that exhibit strong seasonal variability, increasing in rate from late summer to mid-winter before ceasing abruptly in late winter or early spring. Our analysis suggests that the source of these signals is likely near or beneath Cascade Glacier, adjacent to the landslide, rather than within the landslide mass itself. We apply detection algorithms to construct a time history for this signal type, which we then compare with environmental factors like precipitation, temperature, and slope displacement data from ground-based radar and remote sensing. Correlations indicate that these seismic events may be driven by seasonal hydrological changes, particularly the freeze-up of subglacial water pathways. While these events are not directly linked to landslide motion, they serve as indirect markers of subsurface hydrological conditions that influence slope stability. Our findings highlight the complex interplay between glaciers, groundwater, and landslide dynamics, emphasizing the need for multi-parameter monitoring to assess evolving geohazards in the region.

Alaska↗
USGS2026

Making many out of one: Synthetic geologic deformation model distributions for use in USGS NSHM25‐PRVI Puerto Rico-U.S. Virgin Island update

A key use‐case of geologic slip rates is within deformation models used in probabilistic seismic hazard analyses. Field‐derived geologic slip rates have formed the cornerstone of deformation models in such applications for decades. Recent advancements in seismic hazard analyses have expanded the use of faults for which geologic slip rates are not well constrained using categorical slip rate estimates. Because of these advancements, application of a geologic deformation model for use in 2025 U.S. Geological Survey National Seismic Hazard Model Puerto Rico‐U.S. Virgin Islands (NSHM25‐PRVI) proved challenging due to: (1) a lack of field‐based geologic slip rates, and (2) a lack of epistemic uncertainty distributions within a broad range of estimated slip rates. Preliminary versions of the NSHM25‐PRVI model sampled these slip rate bins in a coincident manner along preferred and extreme value branches, which yielded untenable correlations in mean hazard results. To minimize the influence of correlated uncertainties amid these challenges, we develop a synthetic epistemic uncertainty distribution for deformation rate on each crustal fault. Each fault has a weighting schema across four possible distribution shapes: uniform, normal, triangular favoring local minima, and triangular favoring local maxima. The synthetic distributions are then sampled several times for each logic tree branch. The results provide a more realistic distribution of rates across the study region as compared with using correlated extrema sampling. This exploration of our method in a small region like PRVI can pave the way for larger‐scale, more complicated applications (e.g., western United States).

Puerto Rico, US Virgin Islands↗
USGS2026

Modeling future groundwater depletion to evaluate sustainability goals set under the Sustainable Groundwater Management Act in the critically overdrafted basins of the Central Valley, California, USA (2020–2070)

In 2014, California's Sustainable Groundwater Management Act (SGMA) mandated local agencies to devise and implement groundwater sustainability plans to address critically overdrafted conditions throughout the state's aquifers. However, the feasibility of these agencies' sustainability goals has not previously been assessed through a regional-scale, integrative lens. Here, we develop and analyze a novel, basin-wide database of 936 sustainability indicator wells located within Central Valley subbasins designated as critically overdrafted, most of which lie in the San Joaquin Valley. Our database shows 2040 groundwater elevation goals vary widely from 60 m above to 80 m below 2020 levels, with variability within and between adjacent subbasins. To evaluate the feasibility of achieving these goals, we coupled the database with a regional hydrologic model (Central Valley Hydrologic Model version 2) and simulated multiple future pumping scenarios. Results show that under increased groundwater demand, 60%–70% of indicator wells may fail to meet their 2040 goals. Even a 50% reduction from 2020 demand levels leaves nearly 40% of wells failing to meet their sustainability thresholds by 2040. Baseline models show that by 2070, up to 70% of wells could fail to meet their goals due to large-scale, spatially connected regions of groundwater depletion. This integrated framework, linking the first region-wide compilation of SGMA indicator wells with a regional groundwater model, demonstrates that many local sustainability goals may be unattainable with substantial (up to 50%) reductions in pumping. Additional management interventions, such as expanded recharge or coordinated demand reductions, may help achieve sustainability goals.

California↗
USGS2025

Summary of results from monitoring the Geysers with continuous passive seismic and repeat magnetotelluric measurements (2021-2023)

Understanding temporal variations in a geothermal field can support operators in decision making that pertains to optimizing production and mitigating hazards. Between 2021 and 2023, The Geysers geothermal field in northern California was monitored with an array of continuous passive seismic sensors and annual repeat magnetotelluric (MT) measurements. Each of these data sets were analyzed and modelled separately to understand the data, sensitivity, and any observable changes. Then, the data were inverted jointly using a crossgradient method to further constrain temporal changes in geophysical properties within the geothermal field. Multiple permutations of annual datasets were used as inputs to the joint inversion. Results demonstrate seismic data constrain smooth inversion of the MT data, and the MT data provide supplementary information about the location of temporal fluid changes. Estimating relative changes in steam saturation for various time intervals of the joint models shows compartmentalized changes in the field, and good spatial correlation with the location of injection wells. These results demonstrate that collecting both passive seismic and MT measurements then modeling them jointly provide complementary information and a relatively inexpensive method for monitoring temporal changes in an active geothermal field that provides results to support operators.

California↗
USGS2026

Earthquake ground-motion model adjustments for the San Francisco Bay area

We develop adjustments to ergodic ground‐motion models (GMMs) to improve their performance in the San Francisco Bay Area (SFBA). GMMs are widely used in hazard assessments to estimate characteristics of ground shaking based on known properties of the source, path, and site. Such models are often developed using datasets containing records from various regions, resulting in models that represent median ground‐motion behavior, which may not adequately represent ground motions within subregions. This is true for the SFBA, where ground motions attenuate more rapidly with distance than in many other parts of California that dominate GMM databases. To support improved seismic hazard estimates in the SFBA, we calculate regional constants and anelastic attenuation coefficient adjustments relative to two commonly used ergodic GMMs: BSSA14 ( Boore et al. , 2014 ) and ASK14 ( Abrahamson et al. , 2014 ). These adjustments are obtained for a suite of ground‐motion intensity measures (peak ground acceleration, peak ground velocity, and 5%‐damped pseudospectral acceleration at oscillator periods ranging from 0.075 to 10 s) using mixed‐effects regression. Use of the regionally adjusted models reduces the overall bias by up to 0.5 natural log units for BSSA14 and up to 0.6 natural log units for ASK14. We demonstrate one application of our attenuation adjustments and their implications in an earthquake early warning case study of the 2014 M 6.0 South Napa earthquake. The predicted extent of shaking using the adjusted models better matches observed shaking at large source‐to‐site distances, especially for lower shaking intensities, thus potentially reducing overalerting. We encourage the use of our model adjustments when ergodic models are considered for seismic hazard studies in the SFBA.

California↗
USGS2025

Megafaunal community structure on ferromanganese and phosphorite hardgrounds in the Southern California Borderland

The Southern California Borderland (SCB) is a topographically complex region on the active continental margin that hosts varied hardground habitats, including ferromanganese (FeMn) crusts and phosphorites, marine minerals being considered for resource extraction. The SCB is influenced by seasonal upwelling and terrestrial inputs, and has a well-defined oxygen-minimum zone (OMZ). We analyzed megafaunal community composition, density, and diversity across 41 ROV video transects at 10 SCB hard substrate sites spanning depth (378–2765 m), temperature (1.79–7.96 °C), and oxygen (3.91–105.67 μM) gradients, with varying rock types (FeMn crusts, phosphorites, other rocks). We counted 32,426 individuals representing 146 unique taxa over a total area of 21,935 m 2 . Echinodermata contributed 48 % of the total abundance; Cnidaria 24 %; Porifera 13 %; Annelida 6 %; Arthropoda 6 %; Chordata 2 %; Mollusca, Foraminifera, and Hemichordata <1 %. Megafauna communities showed clear heterogeneity, with density, diversity, and community composition varying among transects within sites and across sites. Rock type recorded no influence on megafaunal density, but habitats that included FeMn crusts had higher diversity and distinct taxonomic composition. Location, depth, and oxygen were the most important variables explaining variance among megafaunal communities, with distinct communities formed at deeper depths and within the OMZ. This study provides baseline information about the megafauna inhabiting SCB hardgrounds, particularly those associated with minerals considered for their resource potential. It extends existing documentation of such communities to greater depths, reveals increased representation of sponges and corals below 1000 m, and highlights the variability within and among deep-sea megafaunal communities, offering context for informed policy decisions.

Southern California borderland↗
USGS2024

Agricultural tile drains increase the susceptibility of streams to longer and more intense streamflow droughts

Streamflow droughts are receiving increased attention worldwide due to their impact on the environment and economy. One region of concern is the Midwestern United States, whose agricultural productivity depends on subsurface pipes known as tile drains to improve trafficability and soil conditions for crop growth. Tile drains accomplish this by rapidly transporting surplus soil moisture and shallow groundwater from fields, resulting in reduced watershed storage. However, no work has previously examined the connection between tile drainage and streamflow drought. Here, we pose the question: does the extent of watershed-level tile drainage lead to an increased susceptibly and magnitude of streamflow droughts? To answer this, we use daily streamflow data for 122 watersheds throughout the Midwestern United States to quantify streamflow drought duration, frequency, and intensity. Using spatial multiple regression models, we find that agricultural tile drainage generates statistically significant ( p < 0.05) increases in streamflow drought duration and intensity while significantly reducing drought frequency. The magnitude of the effect of tile drainage on streamflow drought characteristics is similar to that of water table depth and precipitation seasonality, both of which are known to influence streamflow droughts. Furthermore, projected changes in regional precipitation characteristics will likely drive the installation of additional tile drainage. We find that for each 10% increase in tile-drained watershed area, streamflow drought duration and intensity increase by 0.03 d and 12%, respectively, while frequency decreases by 0.10 events/year. Such increases in tile drainage may lead to more severe streamflow droughts and have a detrimental effect on the socio-environmental usage of streams throughout the Midwest.

Illinois, Indiana, Iowa, Michigan, Minnesota, Ohio↗
USGS2025

Reflections on a trio of North American earthquakes in 1925

In 1925, three moderately large damaging earthquakes occurred in North America over four months: the 28 February (local time; LT) M 6.2 Charlevoix, 27 June (LT) M 6.6 Montana, and 29 June M 6.5 Santa Barbara earthquakes. The centennial anniversaries of these events motivated this retrospective consideration focused on the ground motions generated by the three events, including a reconsideration of early intensity assignments for the Montana earthquake. At the time, these three earthquakes appeared to support the arguments of some geologists who downplayed the severity of seismic hazard in southern California relative to other parts of the country. Some of the arguments advanced at that time, for example that Los Angeles “has the least to fear from ‘Acts of God’ of any city under the American flag,” ( Hill, 1928 ) sound naïve if not laughable now, but a comparison of well‐constrained shaking distributions for the three earthquakes reveals the dramatic difference in wave propagation efficiency in western versus eastern North America (ENAM), which leads to moderate ENAM events being felt to much larger distances. At M 6.2, the 1925 Charlevoix earthquake was a notably large event in ENAM. This earthquake was the largest event in eastern Canada since 1870 and caused damage in the epicentral region in addition to towns as far away as 200 km, with felt shaking extending over 1000 km. In contrast, felt shaking from the Santa Barbara earthquake barely extended beyond ∼200 km. Compiling published intensity distributions for larger ENAM earthquakes, we show that perceptible earthquake shaking is not uncommon in ENAM over century time scales, but experience with weakly felt shaking may incline people to downplay potential earthquake risk.

California, Montana, Quebec↗