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Preferential groundwater discharges along stream corridors are disregarded sources of greenhouse gases

Groundwater delivery of greenhouse gases (GHGs) to stream banks and riparian areas, before mixing with surface waters, has not been well quantified. We measured preferential groundwater delivery of GHGs to stream banks within three stream reaches, and found that stream banks with discharging groundwater emitted more CO 2 and were sources of N 2 O compared to stream banks without actively discharging groundwater, which emitted less CO 2 and were N 2 O sinks. At one of our stream reaches, groundwater CO 2 and N 2 O concentrations were 1.4–19.2 and 1.1–40.6 times higher than those in surface water, respectively, and groundwater delivery rates of CO 2 and N 2 O were 1.5 and 1.6 times higher than surface water emissions per unit area. On average, 21% (range 0%–100%) of CO 2 and N 2 O were emitted at the stream bank before mixing with surface waters. Preferential groundwater GHG emissions may contribute substantially to stream corridor emissions and may be underestimated when using a channel-centric approach to estimate riverine GHG budgets.

JGR Biogeosciences

Seamless Geologic Map Database for the Intermountain West, United States: A foundational dataset for mineral systems analysis

The Intermountain West has a complex geologic history, resulting in the formation of a diverse array of mineral deposits. Effective mineral exploration requires understanding the spatial and temporal relationships among geologic processes and events, a key focus of the mineral systems approach to exploration. This paper presents the Intermountain West Seamless Geologic Map Database, a unified dataset designed to support mineral exploration. Integrating geologic provinces, structural settings, and hydrothermal alteration, the database leverages the Seamless Integrated Geologic Mapping (SIGMa) extension to the USGS Geologic Map Schema (GeMS) to standardize geologic data from varied sources. SIGMa's hierarchical stratigraphic organization and feature-level metadata enhance data interoperability and reusability, enabling seamless query, analysis, and visualization of lithology, structural features, mineral deposits, geochronology, hydrothermal alteration. volcanic activity, and By providing a regionally consistent and dynamically evolving geologic map, this database provides a foundational framework for mineral exploration and geologic research. It also allows for an efficient workflow that expedites the publication of integrated geologic map databases.

Conference Paper

Reconnaissance basement geology and tectonics of North Zealandia

New rock dredge samples supply key information to establish the tectonic and geological framework of the northern two-thirds of the 95% submerged Zealandia continent. The R/V Investigator voyage IN2016T01 to the Fairway Ridge, Coral Sea, obtained poorly sorted poly-lithologic pebbly to cobbly sandstones, well sorted fine grained sandstones, mudstones, bioclastic limestones, and basaltic lavas. Post-cruise analytical work comprised petrography, whole rock geochemical and Sr and Nd isotopic analyses, and U-Pb zircon, Rb-Sr, and Ar-Ar geochronology. A Fairway Ridge cobbly sandstone has a ∼95 Ma (early Late Cretaceous) depositional age; two biotite granite cobbles are 111 ± 1 and 128 ± 1 Ma in age, and some volcanic pebbles are also likely Early Cretaceous. Fairway Ridge basalts have intraplate alkaline chemistry and are of Late Eocene age (∼40–36 Ma). By analogy with South Zealandia, we interpret strong positive continental magnetic anomalies of North Zealandia to mainly result from Late Cretaceous to Cenozoic intraplate basalts, many of them rift-related lavas. A new basement geological map of North Zealandia shows the position of the Mesozoic Gondwana magmatic arc axis (Median Batholith) and other major geological units. This study completes onland and offshore reconnaissance geological mapping of the entire 5 Mkm 2 Zealandia continent.

Tectonics

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation

3D Dynamic rupture modeling of the 6 February 2023, Kahramanmaraş, Turkey Mw 7.8 and 7.7 earthquake doublet using early observations

The 2023 Turkey earthquake sequence involved unexpected ruptures across numerous fault segments. We present 3D dynamic rupture simulations to illuminate the complex dynamics of the earthquake doublet. Our models are constrained by observations available within days of the sequence and deliver timely, mechanically consistent explanations of the unforeseen rupture paths, diverse rupture speeds, multiple slip episodes, heterogeneous fault offsets, locally strong shaking, and fault system interactions. Our simulations link both earthquakes, matching geodetic and seismic observations and reconciling regional seismotectonics, rupture dynamics, and ground motions of a fault system represented by 10 curved dipping segments and embedded in a heterogeneous stress field. The M w 7.8 earthquake features delayed backward branching from a steeply branching splay fault, not requiring supershear speeds. The asymmetrical dynamics of the distinct, bilateral M w 7.7 earthquake are explained by heterogeneous fault strength, prestress orientation, fracture energy, and static stress changes from the previous earthquake. Our models explain the northward deviation of its eastern rupture and the minimal slip observed on the Sürgü fault. 3D dynamic rupture scenarios can elucidate unexpected observations shortly after major earthquakes, providing timely insights for data‐driven analysis and hazard assessment toward a comprehensive, physically consistent understanding of the mechanics of multifault systems.

The Seismic Record

USGS Geochron Database

Introduction Geochronology helps us understand Earth’s history by determining when important events, like volcanic eruptions, the rise of mountains, the formation of mineral resources, and changes in the landscape, happened. Geochronological data directly support geologic mapping and can inform decisions about geologic hazard mitigation, natural resource management, and infrastructure resilience. The U.S. Geological Survey (USGS) Geochron database provides access to more than 300,000 published, publicly available age measurements from more than 40,000 geological samples. This database is the result of a collaborative effort with State geological surveys and geoscientists from across the globe. The USGS Geochron database is the most comprehensive collection of geochronological data available for the United States. Users can view data through an interactive map explorer, download datasets, and integrate data into geospatial software or other analysis tools.

Fact Sheet

Geologic map of Scoggins Dam, Henry Hagg Lake, and Scoggins Valley, Washington County, Oregon

New geologic mapping (Wells and others, 2020b) and geophysical mapping (Blakely and others, 2000; McPhee and others, 2014; Wells and others, 2020a) document kilometers of Cenozoic right-lateral offset along the Gales Creek Fault Zone, a major, northwest-striking fault zone forming the boundary between the Tualatin Valley and the Coast Range. The Bureau of Reclamation’s (Reclamation) Scoggins Dam (fig. 1), in the Coast Range foothills west of Forest Grove, Oregon, lies within the Gales Creek Fault Zone as mapped by Wells and others (2020a, 2020b; fig. 2). Active faults of the Gales Creek Fault Zone defined by paleoseismic trenching (Redwine and others, 2017, 2019b, Horst and others, 2018, 2019, 2021, and Wells and others, 2020a) are presently mapped as projecting through the existing dam. The Pacific Northwest Region of Reclamation requested assistance with geologic studies around Scoggins Dam to provide better understanding of fault locations and their activity, which are needed to design a modification of the dam (Maguire, 2019a, b). The scope of this project includes detailed geology of the existing Scoggins Dam site, Henry Hagg Lake, the reservoir behind the dam, and Scoggins Valley downstream of the existing dam, particularly around a potential new dam site, where Scoggins Creek cuts through a narrow gap formed by a resistant felsic tuff bed that crosses the valley.

Oregon

New constraints on northeast Seattle basin structure from converted seismic waves

The Seattle basin is a deep sedimentary basin in the Seattle–Bellevue, Washington metropolitan area within the Puget Lowland of Washington State. We determine the structure of a portion of the basin and the underlying basement using analysis of P waves converted from direct S incident from below. A deep local crustal event beneath Monroe, about 35 km northeast of Seattle, was recorded by a 100‐station nodal array deployed in 2019. The event produced a variety of coherent seismic phases, including converted waves from the sediment—basement boundary, internal structure within the basin, and additional crustal discontinuities. Using observed Sp converted waves, we apply an adjoint‐based full waveform inversion (FWI) method to determine the amplitude and extent of seismic discontinuities at depth. We find the strongest source of converted waves for this event lies ∼6 to 7 km depth below northern Lake Washington, interpreted to be the local depth to basement rock. The newly imaged shallow basement structure may be part of a deformation zone associated with the Siletzia eastern boundary. Our results highlight the utility of converted seismic waves recorded by a dense array, combined with an FWI method, to illuminate crustal structure.

Washington

A process-based model for forecasting wave runup along the coast of Georgia

Wave runup is an important nearshore process that impacts total water level, sediment transport, and coastal design. Current methods for forecasting wave runup implement an empirical model that considers offshore wave height, wave period, and generalized beach slope. In this study, the authors generated wave runup forecasts from offshore wave conditions and a system of polynomial equations derived from numerical simulations at three different still water datums for each beach profile. They developed a process-based methodology that incorporated site-specific cross-shore topobathy into the phase-resolving numerical model. A comparison between the system of equations, deterministic hydrodynamic simulations, and observed high-water marks was made using Hurricanes Matthew (2016) and Irma (2017) for 12 cases, and it showed that the polynomials were capable of being consistent with the results from full simulation runs, while not requiring hours of runtime when a forecast was needed—the differences between the polynomial and the observed high water marks ranged from 3 to 32 cm for the Irma hindcast and 9–70 cm for Matthew. Then, using forcings from Hurricanes Ian and Nicole (2022), the model predicted the occurrence of dune collision, overwash, and inundation for the coast of Georgia and suggested that wave runup was impacted by the still water level and local topobathy.

Georgia

The projected exposure and response of a natural barrier island system to climate-driven coastal hazards

Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.

North Carolina

Multi-lithofacies alluvial characterization via airborne electromagnetic-borehole fusion using ordinary interval kriging and geologic constraints

Airborne electromagnetic (AEM) survey provides extensive spatial coverage and detailed resolution at the near surface and can be used to develop hydrogeological models. However, utilization of AEM data is not straightforward because AEM resistivity is an indirect measurement for inferring sediment types. This study develops an ordinary interval kriging (OIK) algorithm and a resistivity-to-multi-lithofacies (R2ML) data fusion workflow for multi-lithofacies alluvial characterization. OIK utilizes irregular interval data to construct three-dimensional (3D) resistivity fields from one-dimensional inverted AEM resistivity models. The R2ML workflow maps the resistivity field generated from OIK into a multi-facies lithological model, incorporating geologic constraints derived from well logs and geological observations. The numerical and real-world cases demonstrate that OIK is computationally efficient, accounts for 3D anisotropy, and minimizes the smoothing effect, thereby preserving resistivity contrasts and reducing interpolation uncertainty. The methodology is applied to lithologic characterization of the Mississippi River Valley alluvial aquifer (MRVA) in the Shellmound area, Mississippi, U.S. A frequency-domain AEM survey was conducted to support groundwater studies for the managed aquifer recharge (MAR) to the MRVA. The resulting lithological model, including four types of lithofacies—clay, very fine sand, fine-medium sands, and graveliferous sands, illustrates the geomorphological processes of the MRVA and implies potential MAR. The alignment between the lithological model and existing geological and hydrogeological investigations demonstrates that OIK and R2ML workflow effectively capture the subsurface architecture of the MRVA. The methods have broad applicability for characterizing alluvial aquifers through AEM-borehole data fusion, supporting sustainable groundwater management.

Mississippi

Fully contained laboratory earthquakes: The effect of asperity aspect ratio and free surfaces

Corner frequency ( f c ) and seismic moment ( M 0 ) are key parameters derived from seismic signals that are used to characterize earthquake stress drop, rupture area, and slip. These parameters are also affected by fault geometry and boundary conditions. However, the systematic study of these effects in laboratory settings has been challenging. This study presents laboratory earthquake experiments that examine how rupture dynamics are influenced by (a) the aspect ratio of rectangular PMMA velocity-weakening (VW) asperities surrounded by the Teflon velocity-strengthening (VS) patches, and (b) whether the sides of a VW asperity are confined with VS patches or are free surfaces. We found that increasing confinement by reducing free surfaces or increasing the VW asperity aspect ratio stabilizes fault slip, so that higher normal stress is required to transition from aseismic to seismic slip. Increased confinement and high aspect ratios also reduced M 0 and increased f c , both of which were determined from the radiated seismic waves. M 0 and f c were primarily controlled by the shorter dimension of the VW asperity. Analysis of high-frequency acoustic emission signals revealed that ruptures on high-aspect-ratio VW asperities propagated more unidirectionally, whereas ruptures on square VW asperities were more complex. Further, the high-aspect-ratio asperities were more likely to be eroded by surrounding VS regions while low-aspect-ratio asperities were more likely to rupture into the VS surroundings. These results demonstrate that both the confinement from surrounding stable areas and the geometry of the seismogenic patch can affect rupture nucleation, propagation, and seismic source characteristics.

JGR Solid Earth

An entropic explanation for Gutenberg-Richter scaling

We develop a simple explanation for Gutenberg-Richter (G-R) size scaling of earthquakes on a single fault. We discretize the fault and consider all possible contiguous ruptures at that level of discretization. In this static model, we assume that slip scales with rupture length, and that the rupture rates at each point along the fault are consistent with an a priori long-term slip rate. These simple assumptions define an (under-determined) non-negative least-squares inverse problem. Each solution to this inverse problem is a set of earthquake rates that matches the slip-rate constraint. We use a Markov Chain Monte Carlo (MCMC) algorithm to uniformly sample the solution space assuming constant slip rates along the fault. At finer discretizations, deviations from G-R behavior decrease, which is consistent with an entropic pressure towards G-R solutions. When the fault is discretized into 10 or more segments, random solutions found by the MCMC algorithm have G-R size scaling, even though there are trivial solutions that, for example, have earthquakes of only one size. This is because there are simply far more solutions that have G-R scaling; as the problem size increases, the strong degeneracy of GR solutions results in other solutions becoming improbably rare. Also, the entropically favored G-R distribution has a b -value of approximately 1, which agrees with measured b -values in real earthquake catalogs.

JGR Solid Earth

A northeast-dipping zone of low frequency earthquakes at the southern edge of Cascadia subduction

Tectonic tremor monitoring occasionally detects events in an anomalous zone in southern Cascadia, 50–100 km west of the main tremor band, near the expected southern edge of the subducting Gorda slab at the Mendocino triple junction. To investigate the geometry and temporal behavior of this tremor, we examine its constituent low-frequency earthquakes (LFEs) by developing 27 stacked LFE waveform templates that we use to detect events from 2018 to 2024. We then relocate LFE sources together with regional seismicity. We find that LFE hypocenters form a northeast-dipping alignment at 22–29 km depth, extending eastward from a zone of micro-earthquakes, ∼15 km south of the southern edge of Gorda slab seismicity. These LFE families exhibit small bursts of activity every few days. Considering the strong world-wide association of tremor and LFEs with high slip-rate, plate-bounding faults, we hypothesize these LFEs may demark the southern edge of Cascadia subduction.

California

Diamond drilling at the Ma'milah Mine, Kingdom of Saudi Arabia

The Ma'millah gold mine is about 90 km southeast of At Ta'if at lat 21°03'N., long 41°18'E., in southwestern Saudi Arabia. The deposit, which was worked extensively by ancient miners, consists of several veins and massive lenses of quartz along a regional fault. The extensive ancient mine workings, large size of some quartz outcrops, and significant gold content of several samples indicated that subsurface exploration was warranted. Accordingly, two holes were drilled into the deposit during the interval December 1972 to February 1973. The drill findings were disappointing; the grade of vein material was found to be too low to be of economic interest and the quartz bodies were found to pinch out both along strike and downdip. The drilling program therefore was terminated. The deposit is not worth further exploration

Ma'milah Mine

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

Methodology for quantitative spatial sensitivity analysis of volcanic geodetic networks

Introduction This report introduces a methodology for assessing the state of the U.S. Geological Survey Volcano Observatories’ geodetic monitoring networks that measure how volcanoes deform or change shape. This new method uses a model-based approach that considers the uniqueness of the instrument environments at each volcano. This report focuses on simplified volcanic sources, is independent of the shape or size of the volcano, or the network geometry, and thus highlights the strengths and potential vulnerabilities of each volcano’s geodetic network in an actionable visual format. This analysis can help observatories to make informed decisions about whether volcanoes have an adequate level of geodetic monitoring and indicate where improvements are needed.

Lassen Peak, Mount Shasta

pySATSI: A Python package for computing focal mechanism stress inversions

We introduce pySATSI, a Python package for computing earthquake focal mechanism stress inversions. This algorithm can handle a wide variety of types of stress inversion problems with a single script and can duplicate many capabilities of preceding methodologies. We also add new capabilities that include spatiotemporally variable inversion grids, damped stress estimates for clusters with few or no focal mechanisms, and variable fault‐plane ambiguities that the user can assign to individual events. In addition, we added the ability to use damped stress inversions with fault‐plane ambiguity probabilities that are weighted by fault instabilities. Our algorithm is computationally efficient with faster runtimes than previous algorithms, scales well for large datasets, and can be easily parallelized.

Seismological Research Letters