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At least 865 records · Page 48Linked to original sources
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↗
USGS2024

Deep structure of Siletzia in the Puget Lowland: Imaging an obducted plateau and accretionary thrust belt with potential fields

Detailed understanding of crustal components and tectonic history of forearcs is important due to their geological complexity and high seismic hazard. The principal component of the Cascadia forearc is Siletzia, a composite basaltic terrane of oceanic origin. Much is known about the lithology and age of the province. However, glacial sediments blanketing the Puget Lowland obscure its lateral extent and internal structure, hindering our ability to fully understand its tectonic history and its influence on modern deformation. In this study, we apply map-view interpretation and two-dimensional modeling of aeromagnetic and gravity data to the magnetically stratified Siletzia terrane revealing its internal structure and characterizing its eastern boundary. These analyses suggest the contact between Siletzia (Crescent Formation) and the Eocene accretionary prism trends northward under Lake Washington. North of Seattle, this boundary dips east where it crosses the Kingston arch, whereas south of Seattle the contact dips west where it crosses the Seattle uplift (SU). This westward dip is opposite the dip of the Eocene subduction interface, implying obduction of Siletzia upper crust at this southern location. Elongate pairs of high and low magnetic anomalies over the SU suggest imbrication of steeply-dipping, deeply rooted slices of Crescent Formation within Siletzia. We hypothesize these features result from duplication of Crescent Formation in an accretionary fold-thrust belt during the Eocene. The active Seattle fault divides this Eocene fold-thrust belt into two zones with different structural trends and opposite frontal ramp dips, suggesting the Seattle fault may have originated as a tear fault during accretion.

Washington↗
USGS2024

Paleoseismology of the Sawtooth fault and implications for fault behavior in the epicentral region of the 2020 Mw 6.5 Stanley, Idaho, earthquake

The 2020 moment magnitude ( M w ⁠⁠ ) 6.5 Stanley, Idaho, earthquake raised questions about the history and extent of complex faulting in the northwestern Centennial Tectonic Belt (CTB) and its relation to the Sawtooth normal fault and Eocene Trans‐Challis fault system (TCFS). To explore faulting in this area, we excavated a paleoseismic trench across the Sawtooth fault along the western margin of the CTB, and compared an early Holocene (9.1 ± 2.1 ka, 1δ ⁠ ) rupture at the site with lacustrine paleoseismic data and fault mapping in the 2020 epicentral region. We find: (1) a history of partial to full rupture of the Sawtooth fault ( M w ⁠ 6.8–7.4), (2) that shorter ruptures ( M w ≤ ⁠⁠6.9 ) are likely along distributed and discontinuous faults in the epicentral region, (3) that this complex system that hosted the 2020 earthquake is not directly linked to the Sawtooth fault, (4) that the northeast‐trending TCFS likely plays a role in controlling fault length and rupture continuity for adjacent faults, and (5) that parts of the TCFS may facilitate displacement transfer between normal faults that accommodate crustal extension and rotation. Our results help unravel complex faulting in the CTB and imply that relict structures can help inform regional seismic hazard assessments.

Idaho↗
USGS2024

Short-term sediment dispersal on a large retreating coastal river delta via 234Th and 7Be sediment geochronology: The Mississippi River Delta Front

Many Mississippi River Delta studies have shown recent declines in fluvial sediment load from the river and associated land loss. In contrast, recent sedimentary processes on the subaqueous delta are less documented. To help address this knowledge gap, multicores were collected offshore from the three main river outlets at water depths of 25–280 m in June 2017 just after the peak river discharge period, with locations selected based on 2017 U.S. Geological Survey seabed mapping. The coring locations included the undisturbed upper foreset, mudflow lobes, gullies, and the undisturbed prodelta. Nine multicores were analyzed for Beryllium-7 activity, and four cores were analyzed for excess Thorium-234 activity via gamma spectrometry, granulometry and X-radiography. Our results indicate a general trend of declining 7 Be and 234 Th activities and inventories with increasing distance from sources and in deeper water. The core X-radiographs are graded from the predominantly physically stratified nearshore to the more bioturbated offshore, consistent with the sedimentation patterns. Sediment focusing assessed via the 7 Be and 234 Th sediment inventories shows preferential sedimentation in gully and lobe environments, whereas the upper foreset and prodelta focusing factors are relatively depleted. Overall, short-term sediment deposition from the main fluvial source remains active offshore from all three major river outlets, despite the overall declining river load.

Louisiana↗
USGS2024

Upper crustal seismic velocity structure of the Hayward fault zone, San Francisco Bay, California, USA: Results from the 2016 East Bay Seismic Experiment (EBSI-16)

We developed Vp, Vs, Vp / Vs ratio, and Poisson’s ratio models of the uppermost crust (<4 km depth) from the eastern San Francisco (SF) Bay (California, USA) to near the Calaveras fault along a 15-km-long, linear profile. Upper crustal velocities are highly variable beneath, west, and well east of the Hayward fault. We observe eight notable features, from west to east: (1) Near San Francisco Bay, there is an ~2-km-wide structure with high Vp / Vs ratios (up to 5) and Poisson’s ratios (up to 0.48) extending from the surface to the base of our model, which we suggest the structure is a near-vertical fault that lies along a straight-line projection between the Silver Creek fault to the south and the Point Richmond fault to the north. The structure may be part of an ~90-km-long fault along the eastern SF Bay. (2) The western East Bay Plain, the lower lying area between the bay and the hills, includes up to 800 m of low-velocity sediments ( Vp ~1600–3000 m/s, Vs ~500 m/s to ~1000 m/s), underlain by higher velocity basement rocks ( Vp ~3000–5800 m/s; Vs ~1000–1500 m/s). (3) Between ~1 km and 3 km east of the Bay shoreline, sediments thin in a series of steps (likely faults) toward the Hayward fault. (4) Between ~3 km west and ~1 km east of the Hayward fault (at the East Chabot fault) at depths greater than 1 km, basement Vp (up to 6000 m/s) and Vs (up to 2800 m/s) are high, and Vp / Vs ratios (<2) and Poisson’s ratios (<0.3) are low, suggesting crystalline rocks. Furthermore, a near-vertical zone of low Vp / Vs ratios and Poisson’s ratios is between near-surface traces of the Hayward and East Chabot faults, likely corresponding to the San Leandro Gabbro of Ponce et al. (2003) . (5) Eastward of the East Chabot fault in the upper 1.5 km, basement Vp (~3000 m/s to ~4200 m/s) and Vs (~1200–2000 m/s) are lower than those west of the fault. (6) In the eastern Hayward/Oakland Hills, there are zones of laterally varying, high- and low-velocity ( Vp ~2500–3000 m/s) Jurassic–Cretaceous and Tertiary sediments in the shallow subsurface that likely extend much deeper than imaged. (7) Seismic energy that propagates westward from sources east of the Hayward fault (HF) appear weaker than energy that propagates eastward from sources west of the HF, suggesting that the HF acts as a partial barrier to shallow seismic energy propagation into the more populated eastern SF Bay area. (8) Unlike many fault zones, it appears that the active trace of the Hayward fault (in our study area) is not cored by a prominent, low-velocity zone relative to rocks to the east and west of the active trace. However, the active trace does mark a prominent change from relatively higher velocities to the west and lower velocities to the east.

California↗
USGS2024

Mafic alkaline magmatism and rare earth element mineralization in the Mojave Desert, California: The Bobcat Hills connection to Mountain Pass

Occurrences of alkaline and carbonatite rocks with high concentrations of rare earth elements (REE) are a defining feature of Precambrian geology in the Mojave Desert of southeastern California. The most economically important occurrence is the carbonatite stock at Mountain Pass, which constitutes the largest REE deposit in the United States. A central scientific goal is to understand the genesis of the carbonatite ore body in the context of widespread REE-rich igneous activity. A swarm of mafic alkaline (shonkinite) dikes has been mapped and sampled at Bobcat Hills, 65 km southeast of the Mountain Pass mine. Whole-rock geochemistry and zircon geochronology demonstrate a clear affinity to the ca. 1.4 Ga Mountain Pass intrusive system. Bobcat Hills dikes have comparably high REE concentrations (La ∼1,000× chondritic) and an error-weighted mean 207 Pb/ 206 Pb zircon crystallization age of 1,426 ± 2 Ma (2 σ ). Unlike the alkaline intrusions at Mountain Pass, which have abundant inherited zircon from Paleoproterozoic basement rocks and crustally influenced oxygen isotope compositions (δ 18 O zircon = 6.5–7.5‰), the Bobcat Hills dikes lack any evidence of crustal assimilation and have oxygen isotope values that overlap a mantle range (Bobcat Hills average δ 18 O zircon = 5.6 ± 0.3‰). The dikes were a high-temperature, early center of mafic alkaline magmatism in the Mojave Desert that serve as a snapshot of melt generation from a spatially extensive, metasomatized mantle source. We propose that modification of the crust over many tens of Myr at Mountain Pass created an environment that favored crustal assimilation and enabled ascent of late-stage, REE-rich carbonatite magmas.

California↗
USGS2024

The importance of nodal plane orientation diversity for earthquake focal mechanism stress inversions

Inversions of earthquake focal mechanisms are among the most accessible and reliable methods for determining crustal stress. However, the use of this method varies widely, and assumptions that underpin it are often violated, potentially compromising stress estimates. We investigate the consequences of violating the little-studied assumption that the focal mechanisms have diverse orientations. Our approach is to employ data-informed synthetic mechanisms, with nodal plane orientations defined by recent earthquake lineaments in the Midland Basin, western Texas, and rakes consistent with slip in the mapped stress field. Using both the traditional stress inversion method that assumes constant shear stress magnitudes on the causative faults as well as a recently published variable shear stress method, we show that low fault plane diversity can cause maximum horizontal stress ( S Hmax ) orientation and relative principal stress magnitude (faulting regime) estimates to differ markedly from the true values. This problem is compounded for catalogs with even modest amounts of noise (≤15°) or few (e.g., 20) mechanisms. Significantly, traditional approaches for quantifying uncertainty such as the bootstrap can severely underestimate the true uncertainty under these circumstances. To remedy this, we provide simple tools to quantify nodal plane orientation diversity and stress inversion reliability.

Geological Society of London Special Publications↗
USGS2024

Slope Unit Maker (SUMak): An efficient and parameter-free algorithm for delineating slope units to improve landslide modeling

Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), and better accommodating the varying data accuracy and precision in landslide inventories. However, the use of slope units in regional ( > 100 km 2 ) landslide studies remains limited due, in part, to the large computational costs and/or poor reproducibility with current delineation methods. We introduce a computationally efficient algorithm for the parameter-free delineation of slope units that leverages tools from within TauDEM and GRASS, using an R interface. The algorithm uses geomorphic laws to define the appropriate scaling of the slope units representative of hillslope processes, avoiding the often ambiguous determination of slope unit size. We then demonstrate how slope units enable more robust regional-scale landslide susceptibility and event-specific landslide occurrence maps.

Natural Hazards and Earth Systems Sciences (NHESS)↗
USGS2024

Land-use interactions, Oil-Field infrastructure, and natural processes control hydrocarbon and arsenic concentrations in groundwater, Poso Creek Oil Field, California, USA

Like many hydrocarbon production areas in the U.S., the Poso Creek Oil Field in California includes and is adjacent to other land uses (agricultural and other developed lands) that affect the hydrology and geochemistry of the aquifer overlying and adjacent to oil development. We hypothesize that the distributions of hydrocarbons and arsenic in groundwater in such areas will be controlled by complex interactions between mixed land uses, oil-field infrastructure, and natural processes. In 2020–2021, samples of groundwater and surface water were collected and analyzed for a large suite of inorganic and organic chemicals and isotope and gas tracers to test this hypothesis. Those data are supplemented with ancillary data on historical geochemistry, hydrology, geology, and oil-field infrastructure. Hydrocarbons in groundwater (e.g., methane through pentane gases and benzene) are associated with natural processes (e.g., fault offsets or transition in sediment depositional environment) and oil-field infrastructure (e.g., fluid-migration pathways associated with uncemented annulus in oil wells or unlined pits). Arsenic concentrations >10 μg per liter (μg/L; maximum concentration 12.9 μg/L) are associated with natural processes in old, high-pH groundwater, and more recent recharge of water from natural and/or engineered recharge processes. Along the southwest margin of the oil field, pumping for drinking-water and irrigation supplies in combination with engineered groundwater recharge produce a depression in groundwater elevations where groundwater with elevated sulfate concentrations from agricultural areas and groundwater with hydrocarbons from the oil field mix to produce a zone of sulfate reduction that removes hydrocarbons and arsenic from groundwater but produces elevated sulfide (S 2- ) concentrations (maximum concentration 29 mg per liter, mg/L). In this study, multiple approaches were required to resolve the overlapping effects of land uses, oil-field infrastructure, and natural processes on the distributions of hydrocarbons and arsenic in groundwater. The combined use of geographic, historical, physical, chemical, isotopic, and other information to constrain processes could be a useful approach for studies in other hydrocarbon-production areas. This is particularly important where land uses affect aquifer hydrology to an extent that causes mixing of groundwaters with different chemical compositions.

California↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2024

Mitigating climate change by abating coal mine methane: A critical review of status and opportunities

Methane has a short atmospheric lifetime compared to carbon dioxide (CO 2 ), ∼decade versus ∼centuries, but it has a much higher global warming potential (GWP), highlighting how reducing methane emissions can slow the rate of climate change. When considering the contribution of greenhouse gas (GHG) emissions to current global warming (2010–2019) relative to the industrial revolution (1850–1900) levels, methane contributes 0.5 °C or ∼ a third of the total. The most recent post-2023 global estimates of methane emissions by bottom-up (BU) and top-down (TD) approaches for the coal mining sector are in the range of ∼41 ± 3 Tg yr −1 and 33 ± 5 Tg yr −1 , respectively. This divergence, notwithstanding overlapping confidence intervals, is a result of differences between applied TD global inversion models and BU emission inventories. Further research can help to better refine emissions from the various contributing coal mine methane (CMM) emissions sources. The coal mining sector accounts for over 10 % of global anthropogenic methane emissions. The contribution of CMM emissions to the global budget have increased since 2000, although upward and downward regional trends have been observed.

International Journal of Coal Geology↗
USGS2024

Deep syntectonic burial of the Anthracite belt, Eastern Pennsylvania

Fluid inclusion microthermometry and Raman spectroscopy of fluid inclusions in quartz veins from the Pennsylvanian rocks of the Anthracite belt, eastern Pennsylvania support a deep burial model of coalification in favor of focused orogenic hot fluid flow. High-temperature (250 to 255 °C) trapping of CH 4 ± CO 2 saturated aqueous fluids and CH 4 ± CO 2 inclusions indicate fluid trapping at depths of 11.5 to 13.4 km under a cover of Pennsylvanian to Permian(?) syntectonic load. In the folded rocks to the south of the Anthracite belt, CH 4 ± CO 2 fluid inclusions indicate a sediment load that was up to 16.3 km thick. Re -equilibrated aqueous fluid inclusions from veins in Silurian through Devonian rocks give the same range of trapping conditions but a wide range of fluid salinities suggesting that folding, fracturing, and meteoric recharge resulted in the intermixing of fluids from throughout the stratigraphic succession.

Pennsylvania↗
USGS2024

Influence of inherited structure on flexural extension in foreland basin systems: Evidence from the northern Arkoma basin and southern Ozark dome, USA

Extensional faults are key components of foreland basin systems. They form within the upper crust in response to flexure of the lithosphere and accommodate subsidence within the foredeep and forebulge depozones. Such faults are excellent proxies for orogenic system evolution and control the distribution of natural resources and hazards. However, the spatiotemporal evolution of flexural extension has not been documented previously at a regional scale, thereby limiting our understanding of underlying geodynamic controls. Here, we resolve late Paleozoic flexural extension in the northern Arkoma basin and southern Ozark dome, USA. We synthesize a large database of previous mapping, existing research, subsurface data, and geophysical data into 3D geologic and 2D kinematic models. Mesh surfaces representing several key horizons from the Carboniferous Period (ca. 335-306 Ma) were constructed. These surfaces were built from oil and gas well tops (n = ∼10,000) and surface geologic map contacts using an advanced kriging method. The mesh surfaces are offset by a complex 3D fault network, allowing detailed analysis of along-strike and down-dip variations in fault displacement. Analysis of the 3D model reveals a regular and repeated fault segmentation pattern wherein E -W striking, left- and foreland-stepping en échelon normal faults are segmented by inherited NE striking basement faults. Maximum vertical separation along the E -W normal faults is generally focused between the inherited NE-trending faults. This suggests that the inherited basement faults delocalized extensional strain during late Paleozoic normal faulting. Maximum vertical separation and fault localization may correlate to areas with high-amplitude positive magnetic anomalies interpreted as Mesoproterozoic granitic rocks. Speculative covariance of magnetic anomalies and fault displacements implies that the relatively strong basement granite concentrated stress, leading to localized faulting within the relatively thin sedimentary cover. Lastly, we show that flexural extension migrated southeast to northwest from the Chesterian-Morrowan (ca. 335-319 Ma) to the Desmoinesian (ca. 306 Ma). The migratory flexural extension may be explained by diachronous loading during Pangean assembly, or by synchronous loading but variable load compensation due to inherent factors.

Arkansas, Oklahoma↗
USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗
USGS2024

Improving crop-specific groundwater use estimation in the Mississippi Alluvial Plain: Implications for integrated remote sensing and machine learning approaches in data-scarce regions

Study region The Mississippi Alluvial Plain (MAP) in the United States (US). Study focus Understanding local-scale groundwater use, a critical component of the water budget, is necessary for implementing sustainable water management practices. The MAP is one of the most productive agricultural regions in the US and extracts more than 11 km 3 /year for irrigation activities. Consequently, groundwater-level declines in the MAP region pose a substantial challenge to water sustainability, and hence, we need reliable groundwater pumping monitoring solutions to manage this resource appropriately. New hydrological insights for the region We incorporate remote sensing datasets and machine learning to improve an existing lookup table-based model of groundwater use previously developed by the U.S. Geological Survey (USGS). Here, we employ Distributed Random Forests, an ensemble machine learning algorithm to predict annual and monthly groundwater use (2014–2020) throughout this region at 1-km resolution, using pumping data from existing flowmeters in the Mississippi Delta. Our model compares favorably with the existing USGS model, with higher R 2 (0.51 compared to 0.42 in the previous model), and lower root mean square error (RMSE) and mean absolute error (MAE)— 0.14 m and 0.09 m, respectively in our model, compared to 0.15 m and 0.1 m in the previous model. Therefore, this work advances our ability to predict groundwater use in regions with scarce or limited in-situ groundwater withdrawal data availability.

Journal of Hydrology Regional Studies↗
USGS2024

Complex landslide patterns explained by local intra-unit variability of stratigraphy and structure: Case study in the Tyee Formation, Oregon, USA

Lithology and geologic structure are important controls on landslide susceptibility and are incorporated into many regional landslide hazard models. Typically, metrics for mapped geologic units are used as model input variables and a single set of values for material strength are assumed, regardless of spatial heterogeneities that may exist within a map unit. Here we describe how differences in bedding thickness, grain size, inferred uniaxial compressive strength, and bedding dip control the inherent susceptibility of slopes to deep-seated failure within a single mapped geologic unit - the Tyee Formation of Oregon, USA. The Tyee, which covers over 15,000 km2 and underlies much of the Oregon Coast Range, comprises gently folded alternating beds of sandstone and siltstone deposited as turbidites, forming a 2-km thick Eocene submarine fan which has been uplifted and exhumed through the Cenozoic. Deep-seated landslides are widespread in the Tyee, but form a complex spatial pattern such that landslide density ranges from 0 to 24% of the total landscape area. These slides are often extensive and sufficiently deep to reduce local hillslope gradients, resulting in a strong negative correlation between landslide density and mean local slope. Mean annual precipitation and predicted strong ground motions from Cascadia earthquake scenarios also fail to explain the spatial distribution of deep-seated landslides. Consequently, landslide stability models, which are strongly influenced by landscape slope, pore-water pressure, and seismic acceleration, yield landslide susceptibility maps which are broadly anti-correlated with mapped deep-seated landslide density. Through a multivariable linear regression model, we show that much of the variance in deep-seated landslide density can be explained by variability of intra-unit stratigraphic and structural characteristics, which we measure at 128 sites across two study areas totaling ∼3000 km2. Our results suggest bedding dip is only weakly correlated to landslide density, but strongly influences landslide failure style. Subtle increases in bedding dip, even in the gently folded Tyee Formation, result in a substantially higher likelihood of a landslide being cataclinal, or parallel to bedding. Overall, we find a slight majority of landslides fail within these cataclinal slopes, and that these landslides tend to be larger than non-cataclinal landslides. We also show that the lithological and structural properties that influence landslide susceptibility are distinct for these two populations of landslides. Our results demonstrate how localized, intra-unit, geologic variability can exert strong control on landslide susceptibility and failure style. This suggests that in some locations, landslide hazard models could be significantly improved by incorporating detailed, spatially variable, geologic properties rather than relying solely on generalized geologic map units.

Oregon↗
USGS2024

Field evidence and indicators of rockfall fragmentation and implications for mobility

Rockfall fragmentation can play an important role in hazard studies and the design of protective measures. However, the current lack of modeling tools that incorporate rock fragmentation mechanics is a limitation to enhancing studies and design. This research investigates the fragmentation patterns of rockfalls and analyzes the resulting distribution of fragment sizes within corresponding rockfall deposits. We focus on small rock fragments, which provide insights into the dynamics of the rockfall event and can be used as input for numerical modeling. We analyzed multiple rockfall events from locations worldwide, each exhibiting different degrees of fragmentation. Using image analysis techniques, we mapped all visible blocks, determined their volumes, and measured the distances they travelled from the initial point of impact. A key finding is the identification of three indicators of fragmentation. First, in cases where fragmentation was largely absent, we observed a trend of increasing block size with distance from the impact point or source area, which aligns with previously published findings. However, for energetic rockfall events characterized by intense fragmentation, we observed that small fragments exhibited longer travel distances compared to larger fragments. This distinction allowed us to differentiate blocks primarily resulting from the disaggregation process from those primarily resulting from dynamic fragmentation, with implications for rockfall mobility. Second, although the size distribution of rockfall deposits exhibits a power-law scaling for volumes larger than a minimum size threshold corresponding to a rollover of the distribution, in some case studies a deviation from power-law scaling is observed, indicating a process of larger block comminution due to fragmentation. Third, we found that rockfalls with fragmentation experience reduced mobility, indicated by higher reach angles, and higher lateral dispersion showing a wider distribution of trajectories. We interpret these findings as being directly related to the energy-consuming nature of fragmentation, which prevents farther deposition of fragmented rock blocks.

Albacete province, Lombardy and Aosta Valley, Yose↗
USGS2024

A great tsunami earthquake component of the 1957 Aleutian Islands earthquake

The great 1957 Aleutian Islands earthquake ruptured ∼1200 km of the plate boundary along the Aleutian subduction zone and produced a destructive tsunami across Hawaiʻi. Early seismic and tsunami analyses indicated that large megathrust fault slip was concentrated in the western Aleutian Islands, but tsunami waves generated by slip in the west cannot explain the large observed runup in Hawaiʻi far to the southeast. Recently mapped 1957 geologic deposits on eastern Aleutian Islands suggest occurrence of very large nearby slip. Jointly modeling tsunami runup along the eastern Aleutian and Hawaiian Islands together with tide gauge recordings across the Pacific resolves 12-26 m shallow slip along 600 km of the eastern Aleutian Islands in addition to modest, deeper western slip inferred from seismic records. The eastern near-trench slip results in an M W 8.3-8.6 tsunami earthquake component of the M W 8.6-8.8 rupture, comparable in size to the adjacent 1946 Aleutian tsunami earthquake to the east. The reexamination of the 1957 rupture confirms the tsunami hazards posed by the eastern Aleutian subduction zone to Hawaiʻi and lays the groundwork for investigation of large prehistoric earthquakes through modeling tsunami runup inferred from stratigraphic observations to constrain their rupture processes.

Alaska↗