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1,661 records · Page 20Linked to original sources
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↗
USGS2025

Invasion of perennial sagebrush steppe by shallow-rooted exotic cheatgrass reduces stable forms of soil carbon in a warmer but not cooler ecoregion

Soil organic carbon ('SOC') in drylands comprises nearly a third of the global SOC pool and has relatively rapid turnover and thus is a key driver of variability in the global carbon cycle. SOC is also a sensitive indicator of longer-term directional change and disturbance-responses of ecosystem C storage. Biome-scale disruption of the dryland carbon cycle by exotic annual grass invasions (mainly Bromus tectorum, 'Cheatgrass') threatens carbon storage and corresponding benefits to soil hydrology and nutrient retention. Past studies on cheatgrass impacts mainly focused on total C, and of the few that evaluated SOC, none compared the very different fractions of SOC, such as relatively unstable particulate organic carbon (POC) or relatively stable, mineral-associated organic carbon (MAOC). We measured SOC and its POC and MAOC constituents in the surface soils of sites that had sagebrush canopies but differed in whether their understories had been invaded by cheatgrass or not, in both warm and relatively colder ecoregions of the western USA. MAOC stocks were 36.1% less in the 0–10 cm depth and 46.1% less in the 10–20 cm depth in the cheatgrass-invaded stands compared to the uninvaded stands of the warmer Colorado Plateau, but not in the cooler and more carbon-rich Wyoming Basin ecoregion. In plots where cheatgrass increased SOC, it was via unstable POC. These findings indicate that cheatgrass effects on the distribution of soil carbon among POC and MAOC fractions may vary among ecoregions, and that cheatgrass can reduce forms of carbon that are otherwise considered stable and 'secure', i.e. sequestered.

Environmental Research Communications↗
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↗
USGS2026

A roadmap for identifying and interpreting physical processes and national water model prediction bias associated with baseflow index regimes across the contiguous United States

Understanding how groundwater–surface water interactions shape streamflow variability is critical for diagnosing low flow behavior and prediction bias in continental scale hydrologic models. We present a process informed framework that links observed baseflow (BF) dynamics, watershed attributes, and National Water Model (NWM) performance across the contiguous United States. Using daily observed streamflow from 797 reference quality streamgages, we developed monthly baseflow index (BFI) signatures using a streamgage specific, calibrated digital filter. Hierarchical clustering of these signatures identified seven distinct BFI regimes capturing regional and seasonal variability. We evaluated NWM v3.0 retrospective streamflow performance within each regime using multiple hydrograph and flow duration curve-based metrics. Model skill varied systematically across regimes: mixed flow systems were simulated most accurately, while predominantly BF dominated and quickflow dominated regimes exhibited substantially poorer performance. Across nearly all regimes, the NWM underestimated observed BFI magnitude and frequently failed to reproduce seasonal BF patterns, indicating systematic biases in simulated low flow contributions. To relate these regimes to potential process controls, we trained a Random Forest classifier using static watershed attributes and applied Shapley Additive Explanations to identify features most strongly associated with each regime. Results highlight regionally varying influences, including the dominant role of snow fraction and seasonal runoff timing in snow dominated basins and the importance of evapotranspiration and aridity in quickflow dominated systems. Collectively, these findings demonstrate how hydrologic signatures combined with interpretable machine learning can diagnose regime specific model biases and generate process-based hypotheses about limitations in large scale hydrologic prediction systems.

contiguous United States↗
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↗
USGS2025

An unexplained tsunami: Was there megathrust slip during the 2020 Mw7.6 Sand Point, Alaska, earthquake?

On October 19, 2020, the M w 7.6 Sand Point earthquake struck south of the Shumagin Islands in Alaska. Moment tensors indicate the earthquake was primarily strike-slip, yet the event produced an enigmatic tsunami that was larger and more widespread than expected for an earthquake of that magnitude and mechanism. Using a suite of hydrodynamic, seismic, and geodetic modeling techniques, we explore plausible causes of the tsunami. We find that strike-slip models consistent with the moment tensor orientation cannot produce the observed tsunami. Hydrodynamic inversion of sea surface deformation from deep ocean and tide gauge data suggest seafloor deformation more closely matches a megathrust, rather than a strike-slip, source. Static slip inversions, using sea level and Global Navigation Satellite System data, allow for a portion of co-seismic megathrust slip that can explain tsunamigenesis. Combining all available geophysical datasets to model the kinematic rupture, we show that considerable, relatively slow, megathrust slip is allowable in the Shumagin segment, concurrent with strike-slip faulting. We hypothesize that the slow megathrust rupture does not contribute much seismic radiation allowing it to previously go unnoticed with traditional seismic monitoring.

Alaska↗
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↗
USGS2026

Global performance of remote sensing-based and reanalysis-driven models to estimate open water evaporation

Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, we analyze the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. We compare 3 remote sensing-based models, 1 reanalysis-driven model and 1 ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. Our results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm day −1 , respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.

Water Resources Research↗
USGS2026

Reassessing water availability in the Nile River Basin using satellite-based irrigation water use accounting

Existing estimates of irrigation areas and water use in the Nile River Basin vary widely and are based on inconsistent data and methodologies. This study leverages advances in remote sensing to provide an up-to-date and consistent basin-wide reassessment of water use in the Nile River Basin. Land cover and actual evapotranspiration data from 2013 to 2022 were used to quantify irrigated areas, irrigation water use, and the average naturalized water yield. Across the basin, 7.1 million hectares of irrigated land consume an average of 72.5 ± 2.6 billion cubic meters (BCM) of blue water annually. Egypt and Sudan together account for 92% of the irrigated area and 97% of the irrigation water use. The basin’s average naturalized yield, evaluated at Dongola station, is determined to be between 108 and 114.4 ± 3.2 BCM. Although conservative, this updated analysis indicates the basin’s average naturalized yield is 14%–20% higher than the previous naturalized yield estimate (95 BCM) and 29%–36% higher than the commonly cited observed flow of 84 BCM, which is frequently treated as the total basin-wide available water. Importantly, the study underscores that the 84 BCM represents flow at the Aswan gauging station after upstream consumptive uses, not the total water available in the basin under naturalized conditions. This distinction is critical for accurate water accounting, planning, and governance in this water-scarce basin. This study demonstrates the value of open-source remote sensing resources in data-scarce regions while emphasizing the need for region specific validation and bias correction for improved accuracy.

Nile River Basin↗
USGS2025

Seismic intensities, ground motions and basin amplification from the 2022 Mw 6.4 Ferndale, California intraslab earthquake

On December 20, 2022, a Mw 6.4 earthquake occurred at a depth of 18 km within the subducting Gorda plate in the Mendocino Triple Junction (MTJ), one of the most seismically active regions of the contiguous United States, causing widespread damage to local communities. Here we document the seismic intensities, ground motions, and basin amplification effects recorded by this earthquake across Humboldt County as part of an ongoing scientific effort to understand subduction zone earthquake hazards. Modified Mercalli Intensity (MMI) values from our post-earthquake field survey report shaking intensities as high as VIII (Severe). Strong ground motion data from 54 seismic stations were processed to calculate amplitude and frequency content parameters across Northern California. The maximum calculated geometric mean PGA and PGV are 1053 cm/s 2 and 52 cm/s (respectively), both recorded within the 3 km deep Eel River sedimentary basin. Comparisons with four published Ground Motion Prediction Equations indicate that PGA and PGV measurements align with expected attenuation-distance patterns for intraslab earthquakes of this nature. Within the Eel River Basin, ground motions for frequencies above 1 Hz are amplified, with respect to reference stations, by factors greater than 2. Our findings suggest that peak ground motions were mainly caused by sedimentary basin site-effects within the Eel River basin, although rupture directivity may have also increased ground motion amplitudes locally. While the Ferndale area is primarily impacted by shallow intraslab earthquakes, our results also raise questions about site-response and basin amplification hazards from a potential megathrust earthquake. The high seismicity rates of the southernmost Cascades call for stronger regional preparedness and improved strategies to mitigate the effects of such a large-scale disaster.

California↗
USGS2026

Baseflow and snowmelt sustained streamflow in the Upper Colorado River Basin, 1986-2020

The Upper Colorado River Basin (UCRB) faces substantial water availability limitations. Although most streamflow originates as snowmelt, the partitioning of snowmelt between surface runoff and groundwater recharge and subsequent groundwater discharge to streams is highly uncertain. On average, over half of the streamflow in the UCRB is estimated to originate from groundwater discharge to streams, highlighting the importance of baseflow in sustaining surface water. However, the historical patterns of baseflow and streamflow, along with their variability over space and time and their specific sources, remain unknown at the basin scale. This study addresses those gaps by characterizing the sources and transport pathways of both baseflow and streamflow in the UCRB at a seasonal timestep from 1986 to 2020, including the lagged delivery of subsurface water to streams beyond the current season, using coupled models of baseflow and streamflow. Between 1986 and 2020, on average 63% of UCRB streamflow originated from baseflow. About half of this baseflow took longer than one season to reach streams, and outside the snowmelt season, baseflow was the dominant source of streamflow. Snowmelt was a key source of both baseflow and streamflow. Current season snowmelt contributed 33% of streamflow via runoff, and 22% of the 29% of streamflow that originated as current season baseflow via subsurface flow to streams. Over the study period, baseflow index (BFI) declined in headwaters and increased at mid-elevations. Springtime increases in BFI demonstrate the increasingly important role baseflow plays in water supply. Identifying the sources, locations, and timing of water that contributed to the UCRB outlet can inform management of water resources in the basin.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2025

Nodal seismic deployment on Mauna Loa volcano, Hawaii: Dataset and preliminary insights

Mauna Loa is the largest active volcano on Earth, comprising ∼51% of the Island of Hawai‘i’s landmass and posing significant risks to the island’s communities, infrastructure, and natural environment. Historical eruptions have produced lava flows that have reached the ocean in as little as 3 hr. The timing and location of such lava flows in the past 200 yr underscore how critical determination of the location and geometry of magma storage and structure is for volcanic hazard assessment and eruption forecasting. Now, after nearly 38 yr of volcanic quiescence, Mauna Loa has erupted again. On 27 November 2022, fissures initiated within the summit caldera and then migrated to the northeast rift zone, where they generated a large lava flow that threatened a major highway. To improve our understanding of the geometry of this magma system, we deployed a temporary nodal array on Mauna Loa in the summer of 2024. This increased our seismic coverage sufficiently to image this magmatic system. This nodal array consists of 33 seismometers distributed on and around the volcano and was deployed for over three months to record seismic signals. The primary objective of this project is to resolve the high‐resolution seismic velocity structure and characterize seismic features associated with magma storage and ascent pathways. In this article, we present an overview of the deployment, evaluate the quality of the data, and show example recordings to evaluate the suitability of the data set for future seismic investigations, including earthquake relocation, seismic tomography, and receiver function analysis. Comparisons with nearby permanent broadband and short‐period seismic stations demonstrate that the nodal array recorded high‐quality waveforms, making it a valuable resource for constraining the magmatic system beneath Mauna Loa at multiple scales.

Hawaii↗
USGS2025

RioM-1: A new calcite reference material for U-Pb LA-ICP-MS geochronology

Determining absolute ages of carbonate diagenesis, faulting, fossil formation, speleothem growth, carbonate-hosted hydrocarbon deposits, vein mineralisation and hydrothermal alteration has become increasingly accessible through LA-ICP-MS U-Pb dating of calcite, complementing traditional isotope dilution methods still applicable to certain materials (e.g., speleothems via micro-drilling). However, well-calibrated reference materials for LA-ICP-MS calcite geochronology remain scarce. Here, we characterise the Rio Maior calcite, designated ‘RioM-1’, as a potential reference material for U-Pb dating by LA-ICP-MS. Fragments (0.1 to 1 cm 3 ) from a single scalenohedral crystal were analysed by ID-TIMS (U-Pb), LA-ICP-MS (U-Pb and 87 Sr/ 86 Sr), and SIMS (O isotopes). RioM-1 displays high U mass fraction and low, though variable, proportions of common Pb. Combined ID-TIMS analyses from two independent laboratories yielded a Tera-Wasserburg lower intercept date of 63.93 ± 0.11 Ma (2 s , MSWD = 1.3, n = 16). LA-ICP-MS U-Pb data from three independent laboratories are concordant with the TIMS age, producing a pooled date of 64.10 ± 0.12/1.2 Ma (2 s , MSWD = 7.7, n = 708) and an initial 207 Pb/ 206 Pb ratio of 0.85 ± 0.01. Other calcite reference materials, when normalised to RioM-1, yielded dates within uncertainty of their published values. SIMS measurements returned a mean 18 O/ 16 O of 0.002044450 ± 181 (1 s ) and δ 18 O SMOW of 19.57 ± 0.92‰ (1 s ), while LA-ICP-MS strontium isotope measurement yielded a mean 87 Sr/ 86 Sr of 0.708177 ± 9 (2 s ).

Geostandards and Geoanalytical Research↗
USGS2024

On algorithmically determined versus traditional macroseismic intensity assignments

The utility of macroseismic data, defined as the effects of earthquakes on humans and the built environment, has been increasingly recognized following the advent of online systems that now produce unprecedented volumes of macroseismic intensity information. Contributed reports from the U.S. Geological Survey “Did You Feel It?” (DYFI) system ( Wald et al ., 1999 ) are used to generate intensity values with an algorithm based on seminal work by Dengler and Dewey (1998) . The algorithm was developed initially to reproduce intensity values assigned by expert opinion using questionnaire results collected by telephone survey. In this article, I discuss reasons why intensity values from (self‐selected) DYFI responses can differ from values that would be assigned by expert opinion given more complete data from randomly selected participants. For example, with the data used by Dengler and Dewey (1998) , intensities near 4 could be determined from the percentage of people who felt shaking in each town. With less spatially rich data from self‐selected participants, this percentage often cannot be determined reliably. Audible noises are key additional diagnostic criteria for modified Mercalli intensity (MMI) 4, but, although the DYFI system includes a question about noise, following Dengler and Dewey (1998) , the DYFI algorithm does not include a noise indicator. At the upper end of the scale, as defined the DYFI algorithm yields a maximum intensity value of 9.05, nominally corresponding to peak ground acceleration of 75% g . These and other factors can result in DYFI values that are low compared to traditional MMI values assigned using expert opinion, even absent factors that can bias traditional MMI assignments. Modern ground‐motion intensity conversion equations determined using DYFI intensities are expected to be appropriate for DYFI intensities, but the results of this study suggest that biases may be introduced if DYFI and traditional intensities are assumed to be interchangeable.

Seismological Research Letters↗
USGS2025

Estimating earthquake source depth using teleseismic broadband waveform modeling at the USGS National Earthquake Information Center

The U.S. Geologic Survey National Earthquake Information Center (NEIC) monitors global seismicity, producing a catalog of earthquake source parameters in near-real-time to provide information that can help mitigate the societal impact of earthquakes. The NEIC commonly relies on teleseismic observations to constrain earthquake source parameters (e.g., location, depth, magnitude, and mechanism) due to a lack of local and regional observations. For these ‘teleseismic’ events, depth phase (i.e., pP , sP ) arrival time observations provide the best estimate on source depth. However, depth phases are often difficult to accurately identify and/or pick. Therefore, NEIC relies on waveform modeling, such as those determined from W-phase ( M ww ), body wave ( M wb ), and regional ( M wr ) moment tensor estimations, to provide constraints on source depth. While depth estimates from these approaches are informative, higher frequency observations provide more precise estimates because depth phases are more prominently observed at higher frequencies. Here, we present NEIC’s relatively high-frequency (~0.04 to 1 Hz) teleseismic waveform modeling approach, termed Synthetic Depth Phase Modeling (SynDepth), for determining source depth. SynDepth was developed to provide NEIC with a tool that enables rapid, accurate, and quantifiable estimates of earthquake source depth in cases where locator depths are not reliable. This relatively simple and fast procedure searches over 1 km-incremented source depths and an expanding triangular source-time function to find the best-fitting solution. We compare automatic SynDepth solutions for a dataset of 1,216 earthquakes (M5.5-M7.6) between 2017 and 2021 to NEIC-derived depth estimates from other methods. Our approach provides a robust depth estimate for earthquakes lacking local arrival time data, and it minimizes the need for analyst review of depth-phase picks ( pP , sP ) or using predefined ‘fixed’ depths.

Seismological Research Letters↗
USGS2024

A seismic nodal deployment to understand magmatic structure in the vicinity of the Pahala earthquake swarm

In summer-fall 2022, 80 three-component SmartSolo IGU-BD3C-5 nodal seismometers were deployed surrounding the Pāhala seismic swarm on the Island of Hawaiʻi, with the goal of improving seismicity catalogs, and seismic velocity images of the crust and upper mantle in this region. The Pāhala swarm, located south of Mauna Loa and Kīlauea, has been the site of a multiyear sustained swarm of seismicity at depths of ~ 25 – 40 km, with order of magnitude increases in rate in 2015, and then again in 2019. This seismicity is possibly related to the input of magma from the mantle plume below, which may then be subsequently transported to volcanic edifices. However, these processes remain enigmatic, in part due to a lack of precise earthquake locations and seismic velocity models in this region. Here we provide an overview of the deployment, an assessment of the quality of the collected data, and discuss the viability of the dataset for local earthquake relocation, tomography, and teleseismic receiver functions. Through comparisons with proximal permanent broadband and short period instruments, we find that the nodes produce high quality data, particularly at periods shorter than 5 s, although we find, document, and correct discrepancies with the gain and polarities of the instruments. We successfully record signals from teleseismic earthquakes, even at periods longer than 5 s (the corner of the flat response of the nodes). We also record local earthquakes, including details related to source characteristics. This indicates that the data is likely to prove useful for investigations using both local and teleseismic earthquake signals to better understand the connections between the deep and shallow magmatic systems of Hawaiʻi. While this deployment provides a snapshot in time, its success may provide a useful benchmark for future studies as the volcanic systems of Hawaiʻi continue to evolve in the future.

Hawaii↗