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1,690 records · Page 9Linked to original sources
USGS2026

Discrete element investigation of the influence of shallow soil density on the manifestations of strike-slip surface fault rupture

This study investigates the influence of soil relative density on strike-slip surface fault rupture manifestations using three-dimensional numerical simulations performed with the discrete element method (DEM). The simulations capture the formation of distinctive fault strands within complex flower structures using tens of millions of grains. The tendency for dense soils to localize shear manifests as multiple localized shear bands within wide zones of deformation in strike-slip fault rupture, whereas diffuse shear deformation develops within narrow zones in loose soils. The spatial extents of soil deformation are consistent between simulations having similar relative densities but with different quantities of grains. However, individual shears are more distinguishable in assemblages of finer grains than in assemblages of coarser grains. The simulations show the progressive development of new shears within the bounds of previously developed shears. Shear activity transitions inward as fault activity diminishes along the outermost shears and continues along newly developed shears until a vertically dipping throughgoing shear structure develops that accommodates most of the fault displacement thereon. The throughgoing fault develops at smaller fault displacements in looser soils because the first shear rupture propagates closer to the vertical direction and does not undergo as much inward translation of shear activity, as is observed in denser soils. In all simulations, ground surface uplift develops between nonintersecting active shears, and ground surface subsidence tends to develop where new shears intersect previous shears. The surface traces in these simulations are shown to be consistent with analog models and case histories of surface fault rupture occurring in different shallow subsurface materials. Although computationally costly, these modeling results are valuable for providing a strong numerical supplement to traditional analog models used to represent the mechanics of strike-slip zones in soil, and they provide quantifiable stresses and large-strain deformations throughout the model domain.

Journal of Geotechnical and Geoenvironmental Engin↗
USGS2024

Deformation by pressure solution and grain boundary sliding in a retrograde shear zone in southern New England, USA

Alleghanian phyllonites in a shear zone in southern New England were formed by the retrogression and hydration of a high-grade Acadian pelitic schist. The retrogression was locally incomplete, resulting in both heterogeneous mineralogy and mineral compositions, and in many arrested reaction textures. These features, documented by backscattered electron and element map imaging, and by 40 Ar/ 39 Ar dating, provide a record of the processes active as the schist was converted to a phyllonite. On the margins of the shear zone relic biotite and garnet grains survive but are partially replaced by chlorite. Relic high-grade muscovite flakes containing up to 35 % paragonite (pg) also persist but are entrained in swarms of pg-poor muscovite flakes producing folia with an anastomosing network of muscovite grains of variable composition. Single crystals of pg-rich muscovite are truncated by muscovite in successively younger cross-cutting folia that contain decreasing pg contents, falling to <5% pg in the youngest folia. In the core of the shear zone all high-grade minerals are destroyed, but recrystallization continues with earlier greenschist facies folia replaced by lower grade and pg-poorer muscovite in younger folia. Muscovite grains in truncated folia are commonly kinked and selective recrystallization of muscovite in kink bands to pg-poor-compositions demonstrates that strain energy helped drive recrystallization. The boundaries of these new pg-poor muscovite folia are sharp, and truncations indicate that grain boundary sliding (GBS) involved dissolution. GBS also enabled folding by flexural slip along muscovite grain boundaries. Fold amplitudes increased as chlorite dissolved from fold limbs precipitated in fold hinges producing crescent-shaped saddle-reef-like structures. Together these observations of truncation and replacement by dissolution and precipitation demonstrate that pressure solution and GBS facilitated both the formation of the phyllonitic shear zone and slip along it.

Connecticut↗
USGS2025

SURF: An automated method for building nonplanar 3D fault models from earthquake hypocenters

Accurately characterizing 3D fault geometry is vital for improving our understanding of earthquake behavior and informing the development of seismic hazard models. Despite their importance, subsurface fault structures tend to be poorly constrained because of limitations in observational data. Improvements to the seismic networks and earthquake detection algorithms have increased the precision and volume of earthquake catalogs, which help illuminate detailed subsurface fault structure and provide the most direct information available about fault geometries at depth. We present a Python package to automate generating 3D fault geometries directly from hypocentral seismicity patterns. This method begins with clustering events based on their spatial density, identifying coherent patterns. Nearby clusters are then merged based on the similarity of their orientations. We fit nonplanar surfaces using support vector regression to balance surface accuracy with minimal deviations from planarity. The fault models are output as quadrilateral meshes at user‐defined resolution. In the process of generating the 3D fault surfaces, we compute the spatial density of seismicity around the surface and the planarity as quantitative metrics of the model outputs. As a proof of concept, we apply this approach to the San Andreas–Calaveras fault junction region and the 2019 Ridgecrest earthquake sequence, both in California, which contain complex subparallel faults well defined at the Earth’s surface and abundant microseismicity. These case studies demonstrate the method’s ability to model complex fault structures, including long continuous fault surfaces, crossing faults, variably dipping segments, and subparallel faults. We test the method on both standard network catalogs and double‐difference relocated catalogs. We find that our seismicity‐based fault model results align with published 3D models that incorporate additional constraints and interpretations ( Plesch et al. , 2020 ; Aagaard and Hirakawa, 2021 ). This workflow provides a low‐user‐input solution for estimating fault geometries at depth from earthquake catalogs.

California↗
USGS2026

Special issue “The 2024 M7.6 Noto Peninsula earthquake and seismic swarm”

The 2024 Mw7.5 (M JMA 7.6) Noto Peninsula earthquake struck the Noto Peninsula, central Japan on January 1, 2024, causing widespread damage. This Mw7.5 mainshock, together with the prolonged seismic swarm that persisted in the northeastern Noto Peninsula since the end of 2020, of which the largest event was the 2023 M JMA 6.5 earthquake, constitutes one of the most significant seismic sequences in Japan in recent decades. The sequence provides a rare opportunity to investigate the complex interplay among swarm activity, fluid migration, fault geometry and distribution, and the preparatory conditions required for a large inland crustal earthquake. Motivated by this scientific context, this special issue brings together studies examining the sequence from diverse disciplinary perspectives, incorporating seismic, geodetic, and tsunami-related observations and modelling.

Noto Peninsula↗
USGS2026

Shallow differentiation of primitive arc magmas at the Jurassic Emigrant Gap mafic complex, Sierra Nevada, California

The Emigrant Gap composite pluton exposes ultramafic to silicic intrusive rocks that preserve the chemical evolution of primitive mafic arc magmas and their open-system interactions in the upper crust during mid-Jurassic growth of the Sierra Nevada batholith (California). We present field and petrographic observations and mineral and whole-rock chemistry of the ~35-km 2 ultramafic to dioritic Emigrant Gap mafic complex and an adjacent penecontemporaneous ~90-km 2 granodiorite that together make up the composite pluton. In the Emigrant Gap mafic complex, four roughly central masses of dunite, wehrlite, and olivine clinopyroxenite are surrounded by weakly layered gabbronorite and non-layered diorite. The ultramafic rocks are cumulates formed from near-liquidus minerals of primitive arc magmas that accumulated in steep feeder zones with substantial modification by melt–mush reaction as primitive liquids repeatedly transited the mush-filled conduits. The dominant gabbronoritic rocks are the variably accumulative products of more advanced crystallization–differentiation of arc tholeiitic basalts and basaltic andesites. The adjacent granodiorite intrusion originated separately and preserves field and geochemical evidence for assimilation of metasedimentary rocks. Open-system hybridization between the gabbronoritic mushes and the granodioritic magma produced an intervening body of two-pyroxene diorite. We infer that the ultramafic rocks and gabbronorite of the Emigrant Gap mafic complex crystallized from near-primitive arc basaltic to basaltic andesitic magmas at ~0.15–0.3 GPa, with estimated f O 2 of ≥FMQ +1 and dissolved H 2 O concentrations of only ~0.5–2 wt %. Notably, the Emigrant Gap composite pluton is distinct from other Mesozoic plutons in the Sierra Nevada batholith because of (1) its abundance of mafic and ultramafic rocks that crystallized from relatively primitive mafic melts and (2) the low inferred H 2 O concentrations of its parental magmas, indicated by a near absence of igneous amphibole and by the intermediate rather than calcic compositions of plagioclase. A Jurassic regional extension event probably accounts for the formation of relatively dry primitive arc magmas, as well as for their ascending to the upper crust.

California↗
USGS2025

To heal or not to heal?: 1. The effect of pore fluid pressure on the frictional healing behavior of lithologies in Oklahoma

The competition between fault healing (i.e., re-strengthening) and fault loading determines the timing and magnitude of fault failure within the seismic cycle. Repeating earthquakes can give observational estimates of fault healing rates, however, it is difficult to link laboratory studies of frictional healing and observed healing rates from repeating earthquakes in part because of uncertainty in lithology at depth. Due to well-constrained and relatively simple geology, earthquakes in Oklahoma can be linked to the granitic basement rock and to the Arbuckle Group, which is primarily composed of dolomite at earthquake depths. Here, we conduct friction experiments to measure healing rates of the two earthquake-bearing lithologies at confining pressures representative of earthquake depths and pore pressures ranging from 0% to 80% of the confining pressure. We measure frictional healing by executing slide-hold-slide tests with hold times ranging from 3 s to 3000 s. The friction experiments on the Troy Granite indicate that pore fluid pressure does not greatly affect healing rate. On the other hand, the dolomite of the Arbuckle Group exhibits decreased healing with increased pore fluid pressure, with weakening at the highest pore pressure. We hypothesize that this is due to an increase in dissolution of dolomite at high pore pressures/low effective normal stress. These healing rates are used in the companion paper to understand the moment-recurrence time behavior of repeating earthquakes in Prague, Oklahoma. This work has implications for possible enhanced dissolution and weakening behavior of the Arbuckle Group during wastewater injection activities.

Oklahoma↗
USGS2025

Statistical approaches for modeling correlated grade and tonnage distributions and applications for mineral resource assessments

Correlations between grade and tonnage exist in mineral resource data compiled from published reports, but they are not always addressed during quantitative assessment of undiscovered mineral resources. Failure to account for correlated grade and tonnage distributions can result in geologically unrealistic assessment results. Current software tools simulate univariate ore tonnage and multivariate resource grades of undiscovered deposits independently. As a result, analysts are forced to rely on ad-hoc solutions to minimize the correlation issues by: 1) creating subsets of data with restricted criteria; 2) truncating grade and tonnage distributions; and 3) testing model robustness using exploratory data analysis. While these methods represent pragmatic solutions, the statistical solutions presented here provide additional options to address real correlations in grade and tonnage data used for mineral resource assessments. We present a modified version of the MapMark4 package in R that introduces two alternatives for modeling grade and tonnage distributions, consisting of a multivariate solution that accounts for correlations between ore tonnage and metal grades and an empirical solution that utilizes simple random sampling with replacement to reproduce coupled grades and tonnages from the input data. We present simulations for contained ore and metal for three case studies representing tungsten skarn, komatiite-hosted nickel, and sediment-hosted carbonate amagmatic zinc-lead (Mississippi Valley-type) deposits. Employing the methods presented here yields quantitative mineral resource assessment results that more closely reflect the empirical distributions of grades and tonnages observed in nature and expands the applicability of these tools for ongoing critical mineral resource assessments.

Applied Computing and Geosciences↗
USGS2026

Patterns and drivers of cliff erosion in Big Sur, California, USA using repeat photogrammetry, 2017–2023

Seacliff erosion in steep terrain poses major risks to transportation and critical infrastructure. In Big Sur, California, USA, seacliff erosion threatens the sustainability of the central coast stretch of California State Route 1, a transportation corridor that is critical to the region's economy. Published cliff retreat rates for the region range from 1 to 40 cm yr −1 , highlighting that high-resolution, process-based studies could enhance understanding of the causes of spatial and temporal variability. We quantified cliff erosion and investigated its drivers along ∼13 km of the Big Sur coastline at week–month timescales during the late fall to early spring wet seasons between January 2017 and June 2023 by analyzing 3D point clouds developed from aerial imagery using four-dimensional structure-from-motion (4D SfM) photogrammetry techniques. We calculated cliff face retreat rates of 2.23 ± 3.06 cm yr −1 (mean ±1 σ ), an order of magnitude lower than long-term estimated rates for the region (which included large deep-seated landslides), but in line with short-term rates reported across California. Change detection imagery comparison, cliff profiles through time, and statistical analysis reveal a cyclical cliff evolution process in which erosion by wave action at the cliff base destabilizes the cliff and primes it for subsequent failure during precipitation events. Although more erosion by volume could be attributed to precipitation-induced increases in soil moisture (784 m 3 km −1 yr −1 ) compared with erosion attributed to wave power (282 m 3 km −1 yr −1 ), our observations underscore the coupled nature of these processes in driving cliff evolution, consistent with established theory and observations.

California↗
USGS2025

Melt generation sources and conditions in the wake of a migrating slab window: Geochemistry and petrology of the million-year history of primitive volcanism at Clear Lake volcanic field, California

Clear Lake volcanic field (CLVF) is the northernmost and youngest (~2.2 Ma to 8 ka) of the volcanic centers distributed along the San Andreas transform fault in western California. The initial phase of CLVF volcanism (interval one) occurred between ~2.2 and 1.3 Ma and extends ~35 km southeast of Clear Lake, forming a semi-continuous upland plateau capped by lava flows, with isolated volcanic remnants on the periphery. This volcanism is broadly characterized by geochemically primitive compositions that reflect three source compositions and conditions of melt generation. (1) Partial melting of upwelling asthenospheric mantle lherzolite at moderate pressures (1.2–1.4 GPa) and temperatures (1297–1329 °C) produced high-CaO (9.8–11.3 wt %) basalts with high Al 2 O 3 (16.8–17.6 wt %), Mg#s (66–70), MgO (8–10 wt %), Ni (103–262 μg/g), and Cr (284–609 μg/g). These high-CaO basalts contain olivine (Fo 87–91 ) phenocrysts with Cr-spinel inclusions ± subordinate plagioclase and crop out only in the southern part of the CLVF. (2) Partial melting of depleted sub-continental lithospheric mantle harzburgite at variable pressures (0.7–1.5 GPa) and temperatures (1097–1299 °C) produced a compositional continuum of med-K 2 O, calc-alkaline, high-MgO basalts through high-MgO andesites with high Mg#s (67–77), MgO (8–14 wt %) and high Ni and Cr abundances (154–439 and 340–1124 μg/g, respectively). Mineral assemblages are olivine (Fo 88–93 ) with Cr-spinel inclusions ± subordinate clinopyroxene, orthopyroxene and plagioclase. Small (<2.5 cm) mantle harzburgite xenoliths and mantle olivine xenocrysts are also found in several of these samples. These high-MgO basalts through andesites represent the largest volume of primitive compositions and have erupted predominantly along the main, fault-controlled northwest-southeast trending axis of volcanism with peripheral outcrops to the north, west, and east. (3) Partial melting of the Gorda eclogite slab edge produced adakitic silicic slab melts with strong depletion in the heavy rare earth elements (Yb = 0.6 μg/g). Subsequent reaction of those melts with depleted ultramafic rocks during ascent imprinted the adakitic dacites with high Mg#s (65–78) and elevated Ni (117–210 μg/g) and Cr (191–283 μg/g). Phenocrysts of orthopyroxene (En 87–94 ) with spinel inclusions (Cr# = 80–88) and extremely Ni-rich (9483 μg/g) olivine cores (Fo 84–93 ) record those reactions. Small-volume outcrops of the adakites on the eastern periphery of the CLVF track the passing slab edge. The trio of melting sources recorded by early CLVF magmatism reflect the tectonically complex environment and the hot (1097–1329 °C), shallow (0.7–1.5 GPa) melting conditions for these primitive compositions and provide estimates of the heat delivered to the crust. Over time, this flux led to maturation of the CLVF magmatic system toward the more voluminous and silicic volcanism that characterizes the balance of its subsequent volcanic history and maintains the present-day anomalously high heat flow in the region. The current interval (interval four) of volcanic activity at CLVF is characterized by low-volume, fault-controlled eruptions of basaltic andesite and andesite suggestive of mantle magma and heat delivery to the crust, similar to interval one. This analogous activity provides motivation for the current study and begs the question of whether the system is undergoing thermal priming for renewed silicic volcanism.

California↗
USGS2024

The spatially adaptable filter for error reduction (SAFER) process: Remote sensing-based LANDFIRE disturbance mapping updates

LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected by the U.S. Geological Survey Earth Resources Observation and Science (EROS)-based Remote Sensing of Landscape Change (RSLC) process. The RSLC process applies a bi-temporal change detection algorithm to Landsat satellite-based seasonal composites to generate the interim disturbances that are subsequently reviewed by analysts to reduce omission and commission errors before ingestion them into LF’s disturbance products. The latency of the disturbance product is contingent on timely data availability and analyst review. This work describes the development and integration of the Spatially Adaptable Filter for Error Reduction (SAFER) process and other error and latency reduction improvements to the RSLC process. SAFER is a random forest-based supervised classifier and uses predictor variables that are derived from multiple years of pre- and post-disturbance Landsat band observations. Predictor variables include reflectance, indices, and spatial contextual information. Spatial contextual information that is unique to each contiguous disturbance region is parameterized as Z scores using differential observations of the disturbed regions with its undisturbed neighbors. The SAFER process was prototyped for inclusion in the RSLC process over five regions within the conterminous United States (CONUS) and regional model performance, evaluated using 2016 data. Results show that the inclusion of the SAFER process increased the accuracies of the interim disturbance detections and thus has potential to reduce the time needed for analyst review. LF does not track the time taken by each analyst for each tile, and hence, the relative effort saved was parameterized as the percentage of 30 m pixels that are correctly classified in the SAFER outputs to the total number of pixels that are incorrectly classified in the interim disturbance and are presented. The SAFER prototype outputs showed that the relative analysts’ effort saved could be over 95%. The regional model performance evaluation showed that SAFER’s performance depended on the nature of disturbances and availability of cloud-free images relative to the time of disturbances. The accuracy estimates for CONUS were inferred by comparing the 2017 SAFER outputs to the 2017 analyst-reviewed data. As expected, the SAFER outputs had higher accuracies compared to the interim disturbances, and CONUS-wide relative effort saved was over 92%. The regional variation in the accuracies and effort saved are discussed in relation to the vegetation and disturbance type in each region. SAFER is now operationally integrated into the RSLC process, and LANDFIRE is well poised for annual updates, contingent on the availability of data.

Fire↗
USGS2025

Constraining landslide frequency across the United States to inform county-level risk reduction

Informative landslide hazard estimates are needed to support landslide mitigation strategies to reduce landslide risk across the United States. Whereas existing national-scale landslide susceptibility products assess where landslides are likely to occur, they do not address how often , which is a critical element of landslide hazard and risk assessments. In particular, the U.S. Federal Emergency Management Agency's National Risk Index (NRI) requires landslide frequency estimates to inform expected annual loss estimates. We present county-level landslide frequency (landslides per area per year) estimates for the 50 US states. We applied Bayesian negative binomial regression to estimate both the expected (average) reported landslide frequency and full distribution of annual landslide counts for each county. We compared a suite of models that used combinations of landslide-susceptible area, probability of potentially triggering earthquakes, frequency of potentially triggering precipitation, and ecological region as predictors. We trained our models with landslide inventory data from counties with the most comprehensive records available nationwide and used zero-inflated negative binomial distributions as an incompleteness model to correct for temporal reporting gaps. We selected a preferred frequency model to inform the NRI based on information criteria and physically plausible parameter estimates. The model showed that average annual reported landslide frequencies vary by 5 orders of magnitude across US counties, ranging from 0.002 (0.00015–0.05) landslides 1000 km −2 yr −1 in Kusilvak Census Area, Alaska, to 29 (19–46) landslides 1000 km −2 yr −1 in Lake County, California, reflecting the country's strong variations in landslide susceptibility, earthquake probability, and other factors for which ecological region serves as a proxy. Counties with estimated frequencies in the top 20 % of all counties are predominately along the West Coast of the continental United States, in mountainous regions of the Pacific Northwest and Intermountain West, in locally steep or earthquake-prone regions of the Midwest and Southeast, along the Appalachians, in southern and southeastern Alaska, and on some Hawaiian islands. By examining the number of landslides predicted in 99th percentile years for each county, we identified that 26 % of US counties likely have potential for widespread landsliding with more than 10 landslides 1000 km −2 yr −1 , even when such large events have not been reported in the training data for that county. Overall, our results better represent the range of possible landslide frequencies and spatial variations than previous national-scale estimates reported in the NRI, and our approach can inform other risk-reduction and loss-mitigation efforts across the United States and globally.

Natural Hazards and Earth System Sciences↗
USGS2026

Evolution of arsenic speciation during thermal treatment simulating wildfire heating in arsenic-rich sediments

Understanding arsenic transformations during wildfires can help better constrain the environmental impacts of increased wildfire intensity, frequency, and burned area. Previous studies have monitored the evolution of metal(loid) speciation at specific time/temperature endpoints, hampering the comprehension of the dynamic transformations of metal(loid)s during wildfires. Here, a novel approach, namely in situ time-resolved X-ray absorption near edge structure (TR-XANES) spectroscopy, was used for the first time to monitor the heat-induced redox transformations of arsenic (As) in two As-rich sediments with different characteristics. No arsenic transformations were observed in either sediment at room temperature or when the sediments were heated to a maximum temperature of 400 ºC. When heated to a maximum temperature of 600 or 700 ºC, As underwent complex, dynamic, and partially reversible redox transformations, the extent of which varied with sediment properties, initial As speciation, and heating temperature and duration. In the case of sediments initially containing As(V) and a low sulfide/sulfate ratio, the As(V) was reduced to As(III) over a short period of time, followed by immediate reoxidation of As(III) to As(V). The extent of the transient As reduction increased with increasing maximum temperature. The final As speciation at the end of the heating experiment was not substantially different from that at the beginning of the experiment. In contrast, in sediments that were best described by a more complex combination of reference compounds (As(V) coprecipitated with or adsorbed on iron oxide, arseniosiderite, arsenopyrite) with a high sulfide/sulfate ratio, As(V) phases were reduced to As(III) and As(III) was further reduced to As(-I) (at 700 ºC, only), followed by delayed reoxidation of As(-I) to As(III) (at 700 ºC, only) and reoxidation of As(III) to As(V). Approximately 9% and 26% of all As remained as As(III) ( i.e., was not reoxidized to As(V)) at the end of the experiment when heated to a maximum temperature of 600 and 700 ºC, respectively, which is higher than the relative abundance of As(III) in the native sediment. These fire-induced As transformations can potentially enhance As mobilization to surface water and groundwater, posing risks to environmental and human health.

California↗
USGS2024

Metal mobilization from thawing permafrost to aquatic ecosystems is driving rusting of Arctic streams

Climate change in the Arctic is altering watershed hydrologic processes and biogeochemistry. Here, we present an emergent threat to Arctic watersheds based on observations from 75 streams in Alaska’s Brooks Range that recently turned orange, reflecting increased loading of iron and toxic metals. Using remote sensing, we constrain the timing of stream discoloration to the last 10 years, a period of rapid warming and snowfall, suggesting impairment is likely due to permafrost thaw. Thawing permafrost can foster chemical weathering of minerals, microbial reduction of soil iron, and groundwater transport of metals to streams. Compared to clear reference streams, orange streams have lower pH, higher turbidity, and higher sulfate, iron, and trace metal concentrations, supporting sulfide mineral weathering as a primary mobilization process. Stream discoloration was associated with dramatic declines in macroinvertebrate diversity and fish abundance. These findings have considerable implications for drinking water supplies and subsistence fisheries in rural Alaska.

Alaska↗
USGS2025

Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets

Coastal marsh wetlands experience variations in vertical gains and losses through time, which have allowed them to infill relict topography and record variations in drivers. The stratigraphic unit associated with the development of the marsh also reflects the long-term importance of key ecosystem services supplied by the marsh environment, including carbon storage and storm mitigation. Mapping these coastal wetland sediments and the marsh unit thickness is challenging as traditional coastal geophysical tools are not easily deployable (acoustic methods) or are unreliable in saline-soil environments (e.g., ground-penetrating radar), leaving core-based methods the most viable mapping method. In the present study, we utilized prior information on the geologic architecture of the region to select spatial and physical metrics that likely persisted throughout evolution of the marsh during the late Holocene. We then assessed the individual and collective power of these metrics to predict marsh thickness observed from cores. Employing regressive predictive models powered by these data, we improve the quantification of marsh thickness for a coastal fringing marsh within the Grand Bay estuary in Mississippi and Alabama (USA). The information gained from this approach yields improved estimates of the carbon stocks in this environment. Additionally, the stored sediment masses reflect the past, and potential future, persistence of the Grand Bay marsh under historical and present marsh-estuarine sediment exchange fluxes. Such improvements to both the sediment budget of recent marsh stratigraphic units and the spatial extent provide new resources for comparison with large-scale landscape models, the latter of which may be used, when validated, to predict future change and ecosystem transformations.

Alabama. Mississippi↗
USGS2024

Debris-flow entrainment modelling under climate change: Considering antecedent moisture conditions along the flow path

Debris-flow volumes can increase along their flow path by entraining sediment stored in the channel bed and banks, thus also increasing hazard potential. Theoretical considerations, laboratory experiments and field investigations all indicate that the saturation conditions of the sediment along the flow path can greatly influence the amount of sediment entrained. However, this process is usually not considered for practical applications. This study aims to close this gap by combining runout and hydrological models into a predictive framework that is calibrated and tested using unique observations of sediment erosion and debris-flow properties available at a Swiss debris-flow observation station (Illgraben). To this end, hourly water input to the erodible channel is predicted using a simple, process-based hydrological model, and the resulting water saturation level in the upper sediment layer of the channel is modelled based on a Hortonian infiltration concept. Debris-flow entrainment is then predicted using the RAMMS debris-flow runout model. We find a strong correlation between the modelled saturation level of the sediment on the flow path and the channel-bed erodibility for single-surge debris-flow events with distinct fronts, indicating that the modelled water content is a good predictor for erosion simulated in RAMMS. Debris-flow properties with more complex flow behaviour (e.g., multiple surges or roll waves) are not as well predicted using this procedure, indicating that more physically complete models are necessary. Finally, we demonstrate how this modelling framework can be used for climate change impact assessment and show that earlier snowmelt may shift the peak of the debris-flow season to earlier in the year. Our novel modelling framework provides a plausible approach to reproduce saturation-dependent entrainment and thus better constrain event volumes for current and future hazard assessment.

Illgraben basin↗