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At least 91 records · Page 5Linked to original sources
USGS2024

Sensitivity analysis of a dynamic vegetation-sediment transport model using equadratures: Exploring inorganic accretion on a marsh platform

Salt marsh systems require a net import of inorganic sediment to maintain their structure in response to sea‐level rise. Marshes are affected by physical processes including tides, waves, sediment transport, and the influence of vegetation, and these processes interact in complex ways leading to sediment accretion or erosion. We implement a 3‐D hydrodynamic sediment transport model in an idealized marsh‐bay complex with a gently sloping edge, and use it as a laboratory to explore the processes leading to bed elevation change through the bay‐marsh continuum. We use the novel equadratures method for efficient sensitivity analysis to test the roles of wave, vegetation, and sediment parameters on wave dissipation, bed shear stress, sediment fluxes, and deposition and erosion across a transect spanning bay shallows to the marsh. Within the explored bounds of parameter uncertainty, significant wave height ( H sig ), settling velocity ( w s ), and critical shear stress (τ crit ) most strongly affect accretion on the marsh platform. Deposition is affected more by parameter‐parameter interactions, that is, both τ crit and w s or both H sig and w s , than by a single parameter varying alone. The sediment that accretes on the marsh platform originates beyond the marsh edge, indicating that the dynamics of the adjacent mudflat are important for predicting the fate of the marsh. Applying efficient sensitivity analysis techniques can empower process‐based models to test more parameters, larger ranges, and longer timeframes, enabling future predictions of marsh response to sea‐level rise based on physical processes

California↗
USGS2025

Outwash events inhibit vegetation recovery and prolong coastal vulnerability

Overwash, when high ocean water levels and waves flood a coastline, is a common phenomenon that can lead to washover deposits and barrier rollover. Outwash, by contrast, involves seaward flow, often driven by high back-barrier water levels, and can produce washout channels and nearshore deposition. Our observations show that washout channels were quickly (days to weeks) filled and reshaped into beaches, berms, and washover deposits and ponds often formed at the landward ends. However, there was a significant delay in revegetation of former washout areas compared with washover areas. North Core Banks, North Carolina, was affected by repeat hurricanes in different ways: Hurricane Florence (2018) deposited large washover fans 0.5–1 m thick, and Hurricane Dorian (2019) removed 1–4 m of sediment from washout channels. Aerial surveys captured vegetation recolonization on the Florence washover fans within a year but, after Dorian, surveys showed that although the washout channels and ponds quickly filled with marine sand, the channel throats and new washover platforms remained mostly unvegetated for five years. New vegetation growth was associated with the washout ponds and was characteristic of low-elevation hydrophilic environments. We observed comparable outcomes at washout and washover locations on the coasts of Texas and New York and suggest that outwash interrupts the normal cycle of vegetation and dune growth that is key to rebuilding barrier islands after storms. The lack of vegetation in the former washout channels prolongs vulnerability to overwash, further delaying recovery. Our findings have implications for best-management practices and modeling of coastal geomorphic evolution.

JGR Earth Surface↗
USGS2025

Dynamic feedbacks between river meandering and landsliding in northwestern Washington glacial terraces

Landsliding in river valleys poses unique risks for cascading hazards and can damage infrastructure and cause fatalities. In postglacial valleys, many landslides are posited to occur in relation to lateral river erosion, but the dynamics of fluvial-hillslope interactions are not well understood. Here, we investigate a section of the Nooksack River in western Washington State where the channel is flanked by landslide-prone glacial terraces similar to those that failed in the 2014 State Route 530 “Oso” landslide. We map 216 landslides through time across 17 aerial imagery data sets (1933–2022) and analyze them in relation to river meandering and curvature. We observe dynamic feedbacks between lateral river meandering and valley-adjacent landsliding. Terrace lateral retreat rates of up to 25 m/year owing to combined fluvial erosion and slope failure occur on pinned, outer meander bends immediately downstream from peaks in river curvature (>0.0075 1/m); these locations are predisposed to both shallow and deep-seated landslides. Deep-seated landslides extending 17%–32% of the active valley width into the floodplain can displace the river away from the floodplain margin and change the channel planform. River-displacing landslides relocate meanders up- or downstream, thereby conditioning the location of subsequent landslides. This conceptual model of coupled landslide-driven meander displacement and valley-adjacent landsliding is exemplified across western Washington river systems. The distance between up- and downstream valley-adjacent landsliding scales with valley width, meander wavelength, and terrace height. Our results can advance our understanding of the river-hillslope interface in landscape evolution and can be used to inform hazard management in river corridors.

Washington↗
USGS2024

Controls on lake pelagic primary productivity: Formalizing the nutrient-color paradigm

Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. Lake primary production is strongly controlled by inputs of nutrients and colored dissolved organic matter. While past studies have developed mathematical models of this nutrient-color paradigm, broad empirical tests of these models are scarce. We used data from 58 diverse and globally distributed temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. These lakes varied widely in size (0.02-2300 km2), pelagic gross primary production (20-8000 mg C m-2 d-1), and other characteristics. Across these diverse systems, and given relatively limited inputs, model predictions of primary production were highly correlated with observed values derived from high-frequency sensor data. Our analysis provides a model structure, including calibrated parameter estimates, that may be broadly useful for understanding current and future patterns in lake primary production.

JGR Biogeosciences↗
USGS2024

Classifying plant communities in the North American Coastal Plain with PRISMA spaceborne hyperspectral imagery and the spectral mixture residual

The effort to map terrestrial biodiversity, in recent years limited mostly to the use of broadband multispectral remote sensing at decameter scales, can be greatly enhanced by harnessing hyperspectral imagery. Interpretation of hyperspectral imagery may be aided by the Mixture Residual (MR) spectral preprocessing transformation. MR integrates the benefits of spectral mixture analysis with the absorption peak-enhancing characteristics of continuum removal. MR characterizes each pixel as a linear combination of generic end-members estimating the spectral continuum, from which the residual of each wavelength is computed and treated as a source of additional information. Using Hyperspectral Precursor of the Application Mission (PRISMA) imagery, we tested the ability of MR-transformed reflectance as compared to untransformed surface reflectance (SR) to map plant associations and land cover using ground truthing and random forest classifications across four landscapes within the North American Coastal Plain. We used a forward stepwise selection algorithm to choose bands for each classification and subsequently compared these between SR and MR. Our MR classifications distinguished land cover with 5% greater balanced accuracy on average than the SR-based classifications across all four landscapes. The MR-based classification that integrated data from all landscapes into a unified model encompassing all 21 land cover types achieved a 76% average balanced accuracy over three iterations. Generally, MR utilized the near-infrared region to a greater degree than SR while deemphasizing the green peak. Based on our results, MR improves the accuracy of mapping terrestrial biodiversity, likely extending to other current and planned satellite hyperspectral missions.

JGR Biogeosciences↗
USGS2025

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↗
USGS2025

Organic matter composition versus microbial source: Controls on carbon loss from fen wetland and permafrost soils

Wetland and permafrost soils contain some of Earth's largest reservoirs of organic carbon, and these stores are threatened by rapid warming across the Arctic. Nearly half of northern wetlands are affected by permafrost. As these ecosystems warm, the cycling of dissolved organic matter (DOM) and the opportunities for microbial degradation are changing. This is particularly evident as the relationship between wetland and permafrost DOM dynamics evolves, especially with the introduction of permafrost-derived DOM into wetland environments. Thus, understanding the interplay of DOM composition and microbial communities from wetlands and permafrost is critical to predicting the impact of released carbon on global carbon cycling. As little is understood about the interactions between wetland active layer and permafrost-derived sources as they intermingle, we conducted experimental bioincubations of mixtures of DOM and microbial communities from two fen wetland depths (shallow: 0–15 cm, and deep: 15–30 cm) and two ages of permafrost soil (Holocene and Pleistocene). We found that the source of microbial inoculum was not a significant driver of dissolved organic carbon (DOC) degradation across treatments; rather, DOM source and specifically, DOM molecular composition, controlled the rate of DOC loss over 100 days of bioincubations. DOC loss across all treatments was negatively correlated with modified aromaticity index, O/C, and the relative abundance of condensed aromatic and polyphenolic formula, and positively correlated with H/C and the relative abundance of aliphatic and peptide-like formula. Pleistocene permafrost-derived DOC exhibited ∼70% loss during the bioincubation driven by its initial molecular-level composition, highlighting its high bioavailability irrespective of microbial source.

Alaska↗
USGS2025

Nitrate loads and concentrations from forested watersheds and implications for Long Island Sound

Reduction in point sources of nitrogen has led to improvement in water quality of the Long Island Sound (LIS) since 2000, but changes in nonpoint sources are less clear. A significant yet poorly quantified nonpoint nitrogen source is the forested landscape. Because a large proportion of the LIS basin is forested, even small areal inputs from the forested landscape have a large cumulative effect on nitrogen loading to LIS. Atmospheric nitrogen deposition, the primary source of nitrogen to forested landscapes in LIS basin, has been declining for several decades. However, nitrogen export in streams does not necessarily mirror nitrogen deposition. To assess forest nitrogen export to LIS, we estimated annual average concentrations and fluxes of nitrate in 17 forested watersheds in and near the LIS basin. Average flow-normalized nitrate-nitrogen concentrations ranged from less than 0.05–0.43 mg per liter among all sites; annual flow-normalized yields ranged from 0.45 to 4.3 kg per hectare. Flow-normalized annual average concentrations and yields of nitrate between water years 1991–2021 did not monotonically increase or decrease at most watersheds. Where determined, the other major N species generally had comparable magnitude and trends. Based on the watersheds analyzed in this study, forested areas are not responding uniformly to the continued decline of atmospheric nitrogen deposition. The variability among sites may indicate that local-scale factors exert substantial influence over the magnitude and trends in nitrogen exports. One watershed that had increasing development showed an increasing trend in nitrate, but not in dissolved organic nitrogen.

Connecticut, Massachusetts, New Hampshire, New Yor↗
USGS2025

Multi-scale spectroscopy to map intertidal microbial biofilm community and trait diversity

Intertidal microbial biofilms, or microphytobenthos, support estuarine biogeochemical cycling, the physical stability of mudflats, and food webs, particularly those of migratory shorebirds. Photosynthetic biofilms dominated by diatoms, cyanobacteria, and chlorophytes represent a significant fraction of biofilm biomass and contain pigments that can be detected with remote sensing. These diverse biofilm community types vary in indicator pigments and functional traits related to biogeochemical cycling and nutritional quality. We modeled and mapped spatial variation in intertidal biofilm distribution, quantity, diversity, and functional traits using multi-scale spectroscopic data collected within southern San Francisco Bay, California, USA (South SFB). We developed a new biofilm index (B-index) from 5 mm HySpex spectra to detect biofilm presence. We developed single and multiple response partial least squares regression (PLS) models of chlorophyll -a (chl -a ; biomass indicator), indicator pigments: fucoxanthin and diadinoxanthin (diatoms), zeaxanthin (cyanobacteria), and chl -b (chlorophytes), and functional traits: carbohydrates, lipids, and total organic carbon from paired in situ biofilm data and field spectra. The B-index and PLS models were scaled to South SFB with a 3.7 m AVIRIS-NG hyperspectral image. The model %RMSE calculated from AVIRIS-NG test samples ranged from 12.7% for chl -a to 49% for chl -b ; for six of the eight models, %RMSE was 23% or below. Mapped community types differed in mapped traits, with average lipid concentrations three times higher in areas indicated as diatoms compared to other groups. Available maps depict for the first time the spatial variation of an important shorebird food resource and inform the contribution of intertidal biofilm in carbon and nutrient cycling.

California↗
USGS2025

Effects of total suspended solids on photomineralization of dissolved organic matter in the Peace-Athabasca Delta, Canada

Northern deltas receive chromophoric dissolved organic matter (CDOM) from their watersheds, which can be oxidized to carbon dioxide upon absorption of sunlight (i.e., photomineralized). These deltas also receive total suspended solids (TSS), which may shade sunlight absorption by CDOM, thus limiting photomineralization. To quantify this interaction for the first time, we measured photomineralization rates at 11sites in the Peace‐Athabasca Delta (PAD), Canada. We sampled waters during a July 2022 field campaign for TSS concentration, CDOM concentration ( α CDOM ,λ), total downwelling sunlight attenuation coefficients ( K d , tot , λ ), and light attenuation coefficients due to CDOM ( K d , CDOM,λ ). TSS ranged from <1 to 112 mg/L with an average of 19 ± 34 mg/L (mean ± one standard deviation), an order of magnitude lower than TSS reported in rivers entering the PAD earlier in the open water season. α CDOM ,λ at 305 nm ( α CDOM , 305 ) ranged from 23.3 to 65.2 m -1 , K d , CDOM,305 ranged from 26.3 to 74.1 m −1 , and K d , tot,305 ranged from 19.0 to 63.7 m −1 . The ratio of sunlight absorbed by CDOM relative to total sunlight attenuation K d , CDOM,λ/ K d ,tot,λ was inversely correlated with TSS concentration across all wavelengths measured (305–412 nm). TSS thus limited photomineralization rates by shading CDOM from ultraviolet A and visible wavelengths of sunlight, reducing photomineralization rates by up to 56% compared to rates in the absence of TSS or other non-CDOM particles that attenuate sunlight. Results suggest that shifts in delta hydrology that affect TSS concentration likely influence photomineralization rates within TSS-rich northern deltas.

Peace‐Athabasca Delta↗
USGS2024

Computationally efficient emulation of spheroidal elastic deformation sources using machine learning models: a Gaussian-process-based approach

Elastic continuum mechanical models are widely used to compute deformations due to pressure changes in buried cavities, such as magma reservoirs. In general, analytical models are fast but can be inaccurate as they do not correctly satisfy boundary conditions for many geometries, while numerical models are slow and may require specialized expertise and software. To overcome these limitations, we trained supervised machine learning emulators (model surrogates) based on parallel partial Gaussian processes which predict the output of a finite element numerical model with high fidelity but >1,000× greater computational efficiency. The emulators are based on generalized nondimensional forms of governing equations for finite non‐dipping spheroidal cavities in elastic halfspaces. Either cavity volume change or uniform pressure change boundary conditions can be specified, and the models predict both surface displacements and cavity (pore) compressibility. Because of their computational efficiency, using the emulators as numerical model surrogates can greatly accelerate data inversion algorithms such as those employing Bayesian Markov chain Monte Carlo sampling. The emulators also permit a comprehensive evaluation of how displacements and cavity compressibility vary with geometry and material properties, revealing the limitations of analytical models. Our open‐source emulator code can be utilized without finite element software, is suitable for a wide range of cavity geometries and depths, includes an estimate of uncertainties associated with emulation, and can be used to train new emulators for different source geometries.

JGR Machine Learning and Computation↗
USGS2025

Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data

Borehole nuclear magnetic resonance (bNMR) data are typically used to infer in situ hydrologic properties. Partial water content as a function of pore size is estimated by fitting the measured NMR response to a multi-exponential T 2 distribution, and the sum of estimated T 2 amplitudes equals the total volumetric water content. From these estimated parameters, several empirical relationships are commonly used to infer hydraulic conductivity from the NMR-estimated water content and T 2 distribution. Often, parameters are estimated through deterministic inversion methods that produce a single best-fit estimate, but do not reflect uncertainties in model parameters. Here, a Bayesian Markov chain Monte Carlo (McMC) approach for analyzing bNMR data is developed that allows for comprehensive uncertainty quantification of NMR parameters and derived hydrologic properties. The underlying model that describes the T 2 distribution is defined by a set of spline interpolation points. The number of interpolation points is allowed to vary in a trans-dimensional algorithm that naturally favors simple models with fewer interpolation points, allowing the data to inform the necessary level of model complexity. Additionally, data error is estimated as an unknown parameter. Analysis of the ensemble of models output from the McMC algorithm provides useful details on the range of plausible T 2 distributions that can fit a measured bNMR decay curve, as well as uncertainty estimates of total water content. The ensemble of NMR parameters can also be propagated through commonly used relationships to produce uncertainty estimates on derived parameters such as bound/capillary/mobile water content or hydraulic conductivity.

JGR Machine Learning and Computation↗
USGS2025

Three-dimensional seismic velocity models for the San Francisco Bay region, California from joint body-wave and surface-wave tomography validated by waveform simulation

A high-resolution seismic velocity model for both P and S waves is essential for the San Francisco Bay (SFB) region to accurately simulate earthquake ground motions and assess seismic hazards in this high-risk region. We present new three-dimensional P-wave and S-wave velocity (Vp and Vs) models of the SFB region developed using joint tomographic inversion with a rich set of earthquake and active-source body-wave data and ambient-noise surface-wave data. We designed a dynamic balance strategy to effectively balance the contributions of body-wave and surface-wave data during each iteration of the inversion. Owing to the complementary resolution of body-wave and surface-wave data, our new models are significantly improved compared to previous tomographic models. Major geologic features in the SFB region, including low-velocity basins, high-velocity Franciscan Complex, granite, and gabbro rocks, and across-fault velocity contrasts, are imaged in our Vp and Vs models. Compared to the geology-based U.S. Geological Survey velocity model, our new model has better defined structures for some important areas that are of great concern for seismic hazard assessment, such as the Sacramento-San Joaquin Delta, and the 2014 magnitude 6.0 South Napa earthquake area. We validated our model by simulating waveforms for a set of moderate-magnitude earthquakes. The good performance of our model in waveform simulation indicates its potential for improving ground motion simulation and seismic hazard assessment in the SFB region.

California↗
USGS2025

False positives in the identification of dynamic earthquake triggering

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

JGR Solid Earth↗
USGS2026

The magmatic-hydrothermal system of the Three Sisters volcanic cluster, Oregon, imaged from field gravity measurements

From 2019 to 2024, gravity surveys were conducted at the Three Sisters volcanic cluster (TSVC), measuring 246 gravity sites using a spring relative gravimeter. We calculated the residual Bouguer anomaly and identified three main zones with negative anomalies, ranging from −4 to −8 mGal, located southwest and west of South Sister, within an area that has been uplifting for the past two decades. After inversion, we obtain a 3D density model of the subsurface and identify low-density bodies extending from the surface down to 3 km. We estimate a total of 15 km 3 of crustal bodies with density close to 2 g/cm 3 that could store up to ~5 km 3 of water, forming an extensive hydrothermal system beneath the TSVC. We explore the possible combinations of melt compositions and temperatures that could create a bulk density close to our reference crustal density (2.5 g/cm 3 ) using MELTS thermodynamic simulations. Our results indicate that a magmatic mush with as little as 15% partial melt of bulk rhyolitic composition or as much as 52%–57% partial melt of a bulk dacitic composition could be stored in a magmatic system under TSVC without generating a detectable gravity anomaly. Episodic magma injections at the base of the magmatic system, such as the 1998–2000 intrusion at ~6 km depth, would bring heat and gas to the hydrothermal system while maintaining a low melt fraction in the magmatic mush, as imaged at other Cascade volcanoes.

Oregon↗
USGS2026

Interplay between tectonics and submarine mass transport deposits in Cortes Basin: New high-resolution geophysics in the Outer California Borderland

The Outer California Borderland (OCB) is an active transform plate boundary offshore Southern California, where the relationship between faulting and submarine mass transport deposits (MTDs) remains poorly understood. Onshore paleoseismic data provide high-resolution earthquake records, whereas marine geophysical data capture longer-term histories. Offshore fault systems pose hazards to infrastructure and dense coastal populations, particularly when linked to submarine landslides. We present new high-resolution geophysical data set (cruise SR2303), including bathymetric and CHIRP sub-bottom data integrated with legacy seismic reflection data and chronostratigraphic constraints from ODP Site 1012 to examine Quaternary MTD recurrence and tectonic controls in the Cortes Basin, OCB. Bathymetry shows deformational features, including slide scarps and previously unmapped fault segments with evidence of Holocene activity. CHIRP profiles reveal 10 stacked MTDs in the East Cortes Basin and 8 in the West Cortes Basin, spanning ∼752 ka with an average recurrence of ∼83.6 ± 1 ka. Acoustic imaging shows 7 MTD intervals coinciding with fault offset increments and fault growth suggesting earthquake-triggered mass wasting. A strong association between MTD occurrences and sea-level extremes also supports glacio-eustatic contribution to slope failure. Stratigraphic correlations suggest quasi-synchronous MTDs across the eastern and western areas, likely triggered by larger eathquakes in the Quaternary. Although the identified MTDs occur relatively far from the Southern California coast, they still pose a potential tsunamigenic hazard requiring further assessment. Moreover, if linked to earthquakes along major strike-slip faults, for example, the Ferrelo fault, the MTDs may provide valuable proxies to constrain rupture scenarios and fault connectivity within the understudied OCB.

California↗
USGS2026

From collision to subduction: Thermal-kinematic inversions constrain plate boundary structure and dip-slip activity in southwestern New Zealand

Constraints on three-dimensional fault system geometry and kinematics are required to understand both long-term tectonics and contemporary seismic hazard. In many cases, these parameters must be inferred from a combination of different data or analyses. Here, we invert low-temperature thermochronological data to quantitatively parameterize both the crustal-scale geometry and late Cenozoic dip-slip activity of the plate boundary system in southwest New Zealand. We find that the modern transpressive plate boundary system has accommodated the bulk of Australian-Pacific Plate convergence since establishment in the middle Miocene-early Pliocene. Shortening has occurred via (a) dextral-reverse slip on the moderate angle, listric central Alpine Fault décollement, and (b) reverse-slip on either the sharply curved, anti-listric northern Puysegur subduction interface or low-angle offshore thrust fault system that splays from the high-angle southern Alpine Fault at depth. We resolve late Cenozoic shortening rates on these structures that are indistinguishable, and interpret these to reflect the transfer of convergent deformation outboard of the predominantly strike-slip southern Alpine Fault. Our work helps elucidate the transition from strain localized oblique continental collision to strain partitioned subduction. We also provide an estimate of the across-strike width of the central-southern Alpine Fault section boundary at seismogenic depths. This is the first quantitative constraint on the geometry of a structural feature inferred to have arrested several major prehistoric earthquakes. This study furthers understanding of fault structure and dip-slip kinematics along the greatest sources of seismic hazard in and offshore of southwest New Zealand.

South Island↗
USGS2026

Structural evolution and slip rate variations through time of the Puente-Hills blind-thrust fault beneath Los Angeles: Implications for seismic hazard and folding kinematics

Using seismic reflection profiles, historical well logging data, and luminescence and radiocarbon ages, we determine a Pleistocene-Holocene slip history for the central, Santa Fe Springs segment of the Puente Hills blind-thrust fault (PHT), a major seismogenic fault situated beneath the urbanized Los Angeles metropolitan region. We analyze the geometry of correlative stratigraphic units in the forelimb and backlimb of the overlying growth-fold, the Santa Fe Springs anticline, and determine the uplift of seven age-correlative markers. Uplift measurements are converted to thrust displacements on the underlying PHT using a structural method laid out by Don et al. (2022, https://doi.org/10.1785/0120220048 ) that accounts for the geometry of the fault. These data indicate that deep thrust displacement on the PHT is partially consumed updip in the creation of a hanging-wall fault-bend fold, with forelimb growth strata recording <80% of the slip documented within the backlimb. Chronological data from growth strata yield age constraints for folding and faulting on the underlying PHT, providing a detailed incremental slip history derived from both the forelimb and backlimb folding for seven discrete growth horizons, spanning the past 1.4 million years. The resulting six incremental slip rates demonstrate that fault slip has varied through time from the middle Pleistocene to the Holocene. Moreover, these results reveal synchronous acceleration of both the central, Santa Fe Springs and western, Los Angeles segments of the fault system since late Pleistocene time (after 200 ka) and slip rates of greater than 2 mm/yr on the downdip, backlimb, fault-ramp below the anticline.

California↗