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RegionGrow3D: A deterministic analysis for characterizing discrete three-dimensional landslide source areas on a regional scale

Regional-scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics-based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three-dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad-scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km 2 ) using 3D, limit-equilibrium (LE)-based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back-calculated from inventoried landslides using 3D LE-based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.

Journal of Geophysical Research: Earth Surface

Remote single-station seismic monitoring of the July–October 2022 earthquake swarm at Tau volcano, American Samoa

From July to October 2022, a non-eruptive volcanic earthquake swarm occurred within ~15 km of Taʻū Island, located in eastern American Samoa. Felt reports from local residents were the only available information about the swarm when it started, as American Samoa lacked a seismic monitoring network. We developed a consistent single-station catalog for the entire swarm, using seismic data from the nearest station IU.AFI, ~250 km away. We applied the EQTransformer deep-learning model (Mousavi et al., 2020), automatically picking Pn and Sn arrivals on IU.AFI continuous data. We retained only events with Sn-Pn times of 22.5–25 seconds, consistent with the expected locations based on felt reports, then detected smaller swarm events with subsequent template-matching. This single-station catalog characterized the swarm’s onset and escalation to peak activity before a multi-agency field response team installed a local seismic network in mid-August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S-P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Taʻū Island. Modern seismological processing methods, combined with basic observations such as felt reports, can quickly contribute useful information during an earthquake response in a poorly monitored region.

American Somoa

Linking stream-reach nitrogen loads and groundwater “reachsheds” to inform wastewater-nitrogen management actions, Cape Cod, Massachusetts

Study Region Cape Cod, Massachusetts, U.S.A. Study Focus Anthropogenic nitrogen (N) is a key factor in degrading groundwater and surface-water quality, particularly in coastal New England where onsite wastewater systems are prevalent. This study evaluated whether direct N-load measurements in streams on Cape Cod, Massachusetts, coupled with flow-path information from groundwater-flow models, can effectively identify potential land areas where nitrogen mitigation could substantially reduce loads to receiving waters. Nitrogen fluxes were measured along 63 stream reaches during winter and summer and paired with simulated groundwater recharge areas to identify and rank potential areas for reduction of nonpoint-source N inputs. New Hydrologic Insights for the Region Reach-scale nitrate-N loads ranged from −39.1–1182 kg-N/yr per 100 m of stream, indicating spatially variable groundwater inputs across seasons. “Reachsheds” — areas contributing groundwater recharge to specific stream reaches — were delineated using a regional groundwater-flow model. Strong correlations were found between observed N loads and land-use characteristics, especially the number of septic systems and total N inputs from the sum of considered sources. Observed N loads were moderately correlated with recharge area size and wastewater flow estimates. Correlating reach-specific groundwater N loads with land use and parcel-scale nitrogen-yield data identified reachsheds with the highest potential for N load reduction. This approach enables targeted implementation of restoration efforts to optimize nutrient management and support regional load reduction.

Massachusetts

Petrogenesis and mineralization potential of the Bradley Peak komatiitic basalts, Wyoming Province

The ca. 2.72 Ga Bradley Peak greenstone terrane in the Wyoming Province contains spinifex- and cumulate-textured komatiitic volcanic rocks that may host Ni-Cu-PGE sulfide mineralization. New whole rock geochemistry classifies these rocks as Al-undepleted komatiitic basalts derived from a parental melt with ~17 wt. % MgO. Isotopic data (Sm-Nd, Re-Os) and REE profiles suggest a plume source and possible assimilation of juvenile footwall volcanic rocks. Calculated sulfur concentrations at sulfide saturation and low-detection PGE geochemistry indicate these magmas did not saturate a sulfide liquid resulting in sulfide mineralization. Although the Bradley Peak komatiitic basalt flows are unlikely to host magmatic sulfide mineralization, they are likely the source of Au for regional orogenic gold deposits.

Wyoming

Paleoseismology and paleogeodesy using coral microatolls

Establishing the rupture extent and slip distribution of individual paleo-earthquakes is vital for assessing fault behavior including the persistence of rupture segmentation, recurrence patterns, and similarity of successive events, key issues in both fault mechanics and hazard assessment. Techniques with high temporal and geodetic precision as well as a wide distribution of study sites are necessary to investigate past earthquakes in such detail. Coral microatoll growth is one of the best types of geologic record for paleoseismology and paleogeodesy given these needs, as it provides long, continuous, widely distributed records of centimeter-scale vertical tectonic motion with potentially annual-level temporal precision. This chapter describes the process of interpreting microatoll growth records to obtain time series of relative sea level, tectonic vertical deformation fields, and finally slip and coupling parameters on an underlying fault interface.

Book chapter

Corundum discovered by SuperCam and the Perseverance rover at Jezero crater, Mars

Mars is primarily composed of mafic mineral assemblages and their alteration products, but small, scattered rocks strewn across the landscape offer clues to greater petrological diversity. While traversing the Jezero crater rim, the Perseverance rover encountered several plagioclase-rich light-toned float rocks. SuperCam identified the distinctive signature of corundum (α-Al 2 O 3 ) in these rocks using time-resolved luminescence spectroscopy. Two strong peaks (692.7 and 694.1 nm) with millisecond lifetimes, and additional supporting lines, are consistent with Cr 3+ substitution for Al 3+ in corundum. Corundum forms in Al-rich, Si-depleted environments through magmatic or metamorphic processes. Given the rocks' small size, association with plagioclase, and location on the crater rim, we interpret the most plausible formation scenario to be impact induced metamorphism at the interface of a felsic and a mafic/ultramafic member with the likely action of fluids at some stage, although other possibilities are not excluded.

Geophysical Research Letters

Geospatial PDF map of the compilation of GIS data for the mineral industries and related infrastructure of Africa

Introduction In 2021, the U.S. Geological Survey's (USGS) National Minerals Information Center (NMIC) completed the project titled "Compilation of geospatial data for the mineral industries and related infrastructure of Africa." This project aimed to leverage the expertise and capabilities of the NMIC to collect, synthesize, and interpret geospatial data to inform on the extractive resources of the African region and expand the NMIC's understanding on the impact of mineral industry of African nations in the global economy. The African region, which comprises the independent nations that make up the African continent and its associated islands and dependencies, consists of a total of 58 mineral producing countries. The primary objective of this effort was to create a fully attributed Geographic Information System (GIS) portraying existing mining infrastructure, resources, and development capacity across Africa along with the related infrastructure capable of supporting current (for the reference year 2018) and future extractive industry operations in the region. The compiled GIS geodatabase with supporting documentation including comprehensive metadata was published as a USGS data release titled "Compilation of Geospatial Data (GIS) for the Mineral Industries and Related Infrastructure of Africa." This georeferenced portable document format (GeoPDF) map sheet presents a new geographic information product containing a partial representation of the GIS data. This GeoPDF map provides a visual comparison of the distribution of mineral industry and related infrastructure GIS data, which contributes to a deeper understanding of the intersections and complexities of the extractive industries within Africa.

Open-File Report

Earthquake stress drop, source spectra from laboratory experiments, and the apparent unsteadiness of frictional slip

Over a range of co-seismic total energy release, high sample rate slip, stress, and slip velocity measurements were made during frictional failure to determine seismic source properties. The near-field measurements were used to estimate stress drops using spectral approaches that are analogous to the standard seismological moment-corner determined Δσ and acceleration amplitude Δσ arms stress drops. Rapid frictional sliding produces slip velocity amplitude spectra that vary with frequency -1 so long as the energy dissipated by friction approaches the total energy release. Under these conditions Δσ and Δσ arms are similar in size. Since these are nearly direct measurements of fault slip velocity and because they produce flat acceleration spectra between the corner and an apparent fmax, friction in these experiments seems to produce dynamic acceleration and deceleration at all resolved frequencies. The physical origin of this unsteady motion is not known exactly but likely reflects rapid dynamic variations in fault strength or applied stress. On the other hand, when the total energy stored prior to failure is artificially made somewhat larger relative to that which can be dissipated by friction the velocity spectra vary with frequency -2 immediately below the corner. At these conditions Δσ and Δσ arms diverge. The excess stored energy is preferentially partitioned into radiated energy upon failure. Collectively the experiments imply that to produce unsteady, white noise accelerations that are observed for natural earthquakes, requires that at least 95% of the energy released does not escape the source region to be radiated to the far-field.

Bulletin of the Seismological Society of America

Where will the cat cross the road? Comparing camera and GPS-based models for identifying wildlife corridors

Designing effective wildlife corridors is a critical conservation challenge in fragmented landscapes. GPS-based step selection functions strongly predict dispersal corridors and connectivity, but GPS collaring can be expensive and invasive. Camera-based occupancy models are widely used for connectivity analyses but may involve trade-offs in data resolution. Despite widespread use of both approaches, few studies have directly compared them using concurrent datasets. We developed a stacked single-species, single-season occupancy model and a Circuitscape connectivity surface for mountain lions (Puma concolor) on Washington’s Olympic Peninsula, USA, and compared them with a connectivity surface from an existing integrated step selection function. Both models predicted mountain lion GPS locations well, with binned Spearman rank correlations of 1 for Circuitscape and 0.96 for the step selection function, though step selection better identified habitat use by dispersers. Connectivity predictions were moderately correlated across the landscape ( r = 0.26), but agreement was strongest in human-dominated areas most critical for corridor planning. We conclude that GPS-based approaches are advantageous when data collection is feasible and the focus is on dispersal or fine-scale movement. However, camera-based approaches may be preferable for multi-species monitoring, large spatial and temporal scales, noninvasive sampling, when resources are limited, or when fine-scale or dispersal-specific inference is not required.

Washington

Water, ice, meteorological, and speed measurements at South Cascade Glacier, Washington, 1999 balance year

Winter snow accumulation and summer snow, firn, and ice melt were measured at South Cascade Glacier, Washington, to determine the winter and net balances for the 1999 balance year. The 1999 winter snow balance, averaged over the glacier, was 3.59 meters, and the net balance was 1.02 meters. Since the winter balance record began in 1959, only three winters have had a higher winter balance. Since the net balance record began in 1953, only 2 years have had a greater positive net balance than 1999. Runoff was measured from the glacier and an adjacent non-glacierized basin. Air temperature, precipitation, and humidity were measured nearby, and ice speed was measured. This report makes these data available to the glaciological and climatological community.

Washington

Substrate Enhancement Pilot Project—Monitoring summary and evaluation, Kootenai River, Idaho, 2012–22

To assess changes in substrate conditions and the efficacy of artificially placed substrates at select sites on the Kootenai River near Bonners Ferry, Idaho, the U.S. Geological Survey, in cooperation with the Kootenai Tribe of Idaho, completed repeat bathymetric, velocimetric, and underwater videography surveys. Collectively, three project sites throughout the Kootenai River make up the Substrate Enhancement Pilot Project (SEPP), an effort intended to improve spawning and egg incubation viability at locations identified to be aquatic habitat limited for the endangered Kootenai River white sturgeon (Acipenser transmontanus). Following the placement of coarse substrates at each site, bathymetric, velocimetric, and underwater videography data were collected from 2012 to 2022 to assess the role of deposition and erosion on maintaining suitable white sturgeon spawning and incubation substrates. Minimal erosion and deposition occurred at all Substrate Enhancement Pilot Project sites, according to interannual and intra-annual net volumetric changes between bathymetric surveys. Depending on the timing of bathymetric surveys relative to the annual peak streamflow conditions, isolated locations of deposition or erosion were observed at each site and the potential for deposition or erosion was supported by measured mean depth-averaged velocities. This study concluded that variability of deposition and scour were common at each site throughout the monitoring period and may be attributed to fluctuations in streamflow. Repeat bathymetric, underwater videography, and velocity mapping surveys were used to verify the interstitial spaces and surfaces of substrates at each SEPP site remained free of fine sediments for intervals longer than a year but were susceptible to deposition between high streamflow events.

Idaho

Parsimonious high-resolution landslide susceptibility modeling at continental scales

Landslide susceptibility maps are fundamental tools for risk reduction, but the coarse resolution of current continental-scale models is insufficient for local application. Complex relations between topographic and environmental attributes characterizing landslide susceptibility at local scales are not transferrable across areas without landslide data. Existing maps with multiple susceptibility classifications under-represent landslide potential in moderate and gently sloping terrain. We leverage an extensive landslide database ( N = 613,724), a high-resolution digital elevation model (10-m), and high-performance computing resources, to develop a new nationwide susceptibility map for the contiguous United States, Hawaii, Alaska, and Puerto Rico. We calculate four alternative linear and nonlinear thresholds of topographic slope and relief using an objective split-sample calibration. We down-sample our results to a 90-m grid to account for uncertainty in the digital elevation model and landslide position, and evaluate these thresholds' ability to differentiate areas of greater susceptibility. The less conservative nonlinear model optimally balances our priorities of capturing observed landslides (99%) while minimizing area covered by susceptible terrain (43%). Independent evaluation with four statewide landslide inventories ( N = 172,367) reinforces our model selection but highlights spatially variable performance. Therefore, we propose a novel approach to susceptibility classification using the concentration of landslide-prone terrain within each down-sampled grid. While landslides are possible within any cells containing susceptible terrain, those with the highest concentration capture the majority of observed landslides. Our new map characterizes landside susceptibility more consistently than prior models; our transparent classification approach also provides flexibility for accommodating different tolerances in risk reduction measures.

AGU Advances

Beyond the mangroves: A global synthesis of tidal forested wetland types, drivers and future information opportunities

There is increasing awareness of the global diversity of tidal forested wetlands (TFWs) and their significance in the provision of ecosystem services. These ecosystems, including mangrove forests, tidal freshwater forested wetlands, supratidal forests and transitional forests together span multiple climatic zones, geomorphic settings, and inundation and salinity regimes. We utilise case studies across five continents to demonstrate the state of knowledge among TFWs. Intertidal mangroves are the best-defined of the TFWs thanks to decades of research on their geomorphology, hydrology and ecology across their broad distribution. Non-mangrove forest settings, however, demonstrate more diverse hydrological, biochemical and vegetation conditions. In many cases, non-mangrove forests are situated at upper intertidal or supratidal elevations, where surface waters and groundwater are subject to interactions between tides freshwater inputs. Salinity datasets show variations ranging from tidal freshwater forested wetlands and ‘low-salinity mangroves’ to mesohaline or marine salinities, often with high temporal variability. While the floristic composition of non-mangrove forests vary among biogeographic regions, locally dominant TFW species are commonly distributed beyond the tidal niche into non-tidal wetland and upland forests. This presents challenges for traditional remote sensing approaches to ecosystem mapping, which are mostly lacking for non-mangrove forests. Geomorphic approaches and developments in machine learning offer opportunities to address this.

Preprint

Software to support remote sensing of river discharge based on critical flow theory

Water resource management requires accurate observations of streamflow but standard field methods for measuring river discharge ( Q ) are costly and can be hazardous for equipment and personnel. Remote sensing has become a viable alternative, but many image-based techniques require field data for calibration and depth and velocity can seldom be mapped with a single sensor. A new approach based on critical flow theory, in contrast, allows both of these attributes to be inferred from readily available image data. This technique only pertains to sites with standing waves, called undular hydraulic jumps (UHJs), but a recent investigation demonstrated its potential to provide accurate discharge estimates. This paper introduces software designed to facilitate Inferring Q from UHJs Identified in River Images (InQUIRI). The package includes modules for retrieving data from image servers, making the measurements of wavelength and width required to calculate discharge, inferring a representative wavelength from a profile digitized along a wave train, combining multiple estimates to obtain an ensemble median discharge, and assessing accuracy via comparison to gage records from the U.S. Geological Survey. By making these steps easier to implement, InQUIRI enables users to apply the workflow to a variety of UHJ-containing images. Accumulating more case studies, some successful and others less so, would help constrain the range of applicability of the critical flow approach and foster development of refined guidelines for selecting and measuring waves. The software described herein could play an important role in promoting informed use of this new technique for non-contact streamflow measurement.

Arizona, Colorado, New Mexico, Utah

Geothermal district energy systems coupled with seasonal underground thermal energy storage: A U.S. techno-economic screening by climate and geology

In the United States, cooling-dominated commercial building loads can cause geothermal heat pump-based district energy systems to accumulate a long-term subsurface thermal imbalance, motivating the incorporation of seasonal underground thermal energy storage. We developed a transferable workflow to evaluate geothermal district systems that pair ground heat exchangers with seasonal underground thermal energy storage. Using standardized hourly loads for seven commercial buildings and a uniform cost framework, we simulated ten U.S. cities with a physics-based ground heat exchanger model, subsurface storage simulations, and economic assessment to isolate the roles of climate and hydrogeology. In cooling-dominated cities, underground thermal energy storage supplied the majority of annual cooling, cutting electricity use and summer peaks substantially while achieving levelized costs comparable to or below conventional chiller-boiler plants. In cooler climates, the storage share shrunk, required borefield size and costs rose, and levelized cost of energy increased nearly linearly with declining underground thermal energy storage fraction, indicating storage fraction as the primary economic lever. Sensitivity analysis showed capital risk dominated by borefield drilling and surface heating, ventilation, and air-conditioning and piping, with underground thermal energy storage costs secondary. This workflow provides a transparent foundation for site-specific design and screening of next-generation geothermal district energy systems.

Arizona, Illinois, Maryland, Michigan, Mississippi

Ground motions from finite faults with unknown geometry

Earthquake emergency response and loss modeling require accurate models of ground‐motion intensity metrics (IMs), such as those produced by ShakeMap. In the critical minutes and hours after an earthquake, however, knowledge of the earthquake source geometry limits the accuracy of these models, especially in areas where seismic instrumentation is insufficient to constrain the shaking intensity pattern. Previous attempts to overcome this limitation have centered on computing the mean distance metrics from a suite of assumed source geometries. That approach is inadequate with modern ground‐motion models (GMMs) because they typically include terms for the hanging wall effect, depth to top of rupture, and other nonlinear terms. Such approaches also propagate the distance uncertainty through the GMMs and may not properly allocate the additional uncertainty into the between‐ and within‐event components. Here we present Finite‐Fault SIMulation with Mixed Effects Regression (FFSIMMER), a method to address these limitations by computing IM distributions from a suite of rupture realizations that fully accounts for all geometry‐related GMM terms and allows for the separation of the between‐ and within‐event components of the total uncertainty. The accuracy of this method is limited by the available constraints on the source parameters. To address this, FFSIMMER can incorporate constraints based on knowledge of the source, such as the approximate strike and dip based on knowledge of the plate tectonics and focal mechanism of the earthquake. We demonstrate the improvement in accuracy that can be achieved with the 2025 M 7.7 Mandalay, Burma (Myanmar), earthquake by incorporating constraints on the range of plausible source parameters.

Bulletin of the Seismological Society of America

Fault displacement model for surface principal rupture of strike-slip faults

The probability distribution model for principal displacement accommodated on the surface main trace is a critical input to the fault displacement hazard analysis. This article presents a new model for strike-slip ruptures in the moment magnitude ( M ) range of 6 to 8.3. The new model is the outcome of a multi-year research effort to update the widely used model developed by Petersen and others in 2011. Updates include the adoption of the Fault Displacement Hazard Initiative database and enhancements to rupture and displacement data preparation. Statistical formulation and estimation have also been updated substantially. A three-parameter modified normal distribution that we refer to as the negative Exponentially Modified Gaussian distribution is adopted to model the probability distribution of the natural logarithm of principal displacement. Formulation for the mean parameter of the modified normal includes a random earthquake term, a nonlinear scaling relation with M , and an ellipse function for along-main-trace variation. The aleatory variability of the updated model now depends on M as well as site’s along-main-trace position. These updates not only significantly improve the fit to the distribution of the observed displacements but also yield reasonable 95th percentile predictions for M > 7.5 events. Alternative models representing the estimation uncertainty of the M -scaling relation are also developed. These new models are compared to the previous model in terms of percentile predictions and the calculated hazard curves. The steeper hazard curves from the new models yield a lower exceedance rate than the normal-distribution based model developed previously by Petersen and others.

Earthquake Spectra

Estimation of parental abundance using hierarchical Bayesian modeling with data augmentation

Pedigree-based estimation methods leverage the fact that each offspring in a cohort is genotypically “marked” by its parents and represent a recent and promising toolset for estimating population dynamics. This includes pedigree accumulation estimators that model the “accumulation” of inferred unique parents within a given cohort to estimate parental abundance. Unlike close-kin mark-recapture approaches, which rely on intercohort comparisons, pedigree accumulation modeling can be completed solely using intracohort samples. This is particularly advantageous for semelparous species, where intercohort pairs are impossible and adult life stages can be difficult to sample without affecting their likelihood of successfully reproducing. Previous work has evaluated a range of estimators for such datasets, concluding that the non-parametric Chao estimator provides the most accurate and precise estimates for feasible levels of sampling effort. We used simulated data to evaluate an alternative estimator based on hierarchical modeling and data augmentation in a Bayesian framework. Results indicate that estimates from the hierarchical Bayesian estimator had comparable accuracy and better precision than both the previously tested Chao1 estimator and the improved iChao formulation across a range of sample sizes and sex ratios. Furthermore, the Bayesian estimator was far more robust to simulated errors in pedigree reconstruction, especially the presence of false negatives. Hierarchical Bayesian pedigree accumulation models can also provide additional insight into underlying reproductive ecology through their use of an explicit observation process, allowing for the incorporation or estimation of species- and population-specific reproductive dynamics. More broadly, the parametric nature of these models offers opportunities to efficiently pool information among datasets as well as to propagate uncertainty within more complex models.

Ecology and Evolution