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At least 199 records · Page 11Linked to original sources
USGS2012

Advances in the simulation and automated measurement of well-sorted granular material: 1. Simulation

1. In this, the first of a pair of papers which address the simulation and automated measurement of well-sorted natural granular material, a method is presented for simulation of two-phase (solid, void) assemblages of discrete non-cohesive particles. The purpose is to have a flexible, yet computationally and theoretically simple, suite of tools with well constrained and well known statistical properties, in order to simulate realistic granular material as a discrete element model with realistic size and shape distributions, for a variety of purposes. The stochastic modeling framework is based on three-dimensional tessellations with variable degrees of order in particle-packing arrangement. Examples of sediments with a variety of particle size distributions and spatial variability in grain size are presented. The relationship between particle shape and porosity conforms to published data. The immediate application is testing new algorithms for automated measurements of particle properties (mean and standard deviation of particle sizes, and apparent porosity) from images of natural sediment, as detailed in the second of this pair of papers. The model could also prove useful for simulating specific depositional structures found in natural sediments, the result of physical alterations to packing and grain fabric, using discrete particle flow models. While the principal focus here is on naturally occurring sediment and sedimentary rock, the methods presented might also be useful for simulations of similar granular or cellular material encountered in engineering, industrial and life sciences.

Journal of Geophysical Research F: Earth Surface↗
USGS2004

Rhyodacites of Kulshan caldera, North Cascades of Washington: Postcaldera lavas that span the Jaramillo

Kulshan caldera (4.5×8 km), at the northeast foot of Mount Baker, is filled with rhyodacite ignimbrite (1.15 Ma) and postcaldera lavas and is only the third Quaternary caldera identified in the Cascade arc. A gravity traverse across the caldera yields a steep-sided, symmetrical, complete Bouguer anomaly of −16 mGal centered over the caldera. Density considerations suggest that the caldera fill, which is incised to an observed thickness of 1 km, may be about 1.5 km thick and is flat-floored, overlying a cylindrical piston of subsided metamorphic rocks. Outflow sheets have been stripped by advances of the Cordilleran Ice Sheet, but the climactic fallout (Lake Tapps tephra) is as thick as 30 cm some 200 km south of the caldera. Ten precaldera units, which range in 40Ar/39Ar age from 1.29 to 1.15 Ma, are dikes and erosional scraps that probably never amounted to a large edifice. A dozen postcaldera rhyodacite lavas and dikes range in age from 1.15 to 0.99 Ma; rhyodacites have subsequently been absent, the silicic reservoir having finally crystallized. At least 60 early Pleistocene intermediate dikes next intruded the caldera fill, helping energize an acid–sulfate hydrothermal system and constituting the main surviving record of an early postcaldera andesite–dacite pile presumed to have been large. Most of the pre- and postcaldera rhyodacites were dated by 40Ar/39Ar or K–Ar methods, and 13 were drilled for remanent magnetic directions. In agreement with the radiometric ages, the paleomagnetic data indicate that eruptions took place before, during, and after the Jaramillo Normal Polarity Subchron, and that one rhyodacite with transitional polarity may represent the termination of the Jaramillo. Most of the biotite–hornblende–orthopyroxene–plagioclase rhyodacite lavas, dikes, and tuffs are in the range 68–73% SiO2, but there were large compositional fluctuations during the 300-kyr duration of the rhyodacite episode. The rhyodacitic magma reservoir was wider (11 km) than the caldera that collapsed into it (8 km).

Washington↗
USGS2010

Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

International Journal of Remote Sensing↗
USGS2002

U.S. Geological Survey spatial data access

The U.S. Geological Survey (USGS) has done a progress review on improving access to its spatial data holdings over the Web. The USGS EROS Data Center has created three major Web-based interfaces to deliver spatial data to the general public; they are Earth Explorer, the Seamless Data Distribution System (SDDS), and the USGS Web Mapping Portal. Lessons were learned in developing these systems, and various resources were needed for their implementation. The USGS serves as a fact-finding agency in the U.S. Government that collects, monitors, analyzes, and provides scientific information about natural resource conditions and issues. To carry out its mission, the USGS has created and managed spatial data since its inception. Originally relying on paper maps, the USGS now uses advanced technology to produce digital representations of the Earth’s features. The spatial products of the USGS include both source and derivative data. Derivative datasets include Digital Orthophoto Quadrangles (DOQ), Digital Elevation Models, Digital Line Graphs, land-cover Digital Raster Graphics, and the seamless National Elevation Dataset. These products, created with automated processes, use aerial photographs, satellite images, or other cartographic information such as scanned paper maps as source data. With Earth Explorer, users can search multiple inventories through metadata queries and can browse satellite and DOQ imagery. They can place orders and make payment through secure credit card transactions. Some USGS spatial data can be accessed with SDDS. The SDDS uses an ArcIMS map service interface to identify the user’s areas of interest and determine the output format; it allows the user to either download the actual spatial data directly for small areas or place orders for larger areas to be delivered on media. The USGS Web Mapping Portal provides views of national and international datasets through an ArcIMS map service interface. In addition, the map portal posts news about new map services available from the USGS, many simultaneously published on the Environmental Systems Research Institute Geography Network. These three information systems use new software tools and expanded hardware to meet the requirements of the users. The systems are designed to handle the required workload and are relatively easy to enhance and maintain. The software tools give users a high level of functionality and help the system conform to industry standards. The hardware and software architecture is designed to handle the large amounts of spatial data and Internet traffic required by the information systems. Last, customer support was needed to answer questions, monitor e-mail, and report customer problems.

Journal of Geospatial Engineering↗
USGS2023

Coproduction and modeling spatial contact networks prevent bias about infectious hematopoietic necrosis virus transmission for Snake River Basin salmonids

Much remains unknown about variation in pathogen transmission across the geographic range of a free-ranging fish or animal species and about the influence of movement (associated with husbandry practices or animal behavior) on pathogen transmission. Salmonid hatcheries are an ideal system in which to study these processes. Salmonid hatcheries are managed for endangered species recovery, supplementation of threatened or at-risk fish stocks, support of fisheries, and ecosystem stability. Infectious hematopoietic necrosis virus (IHNV) is a rhabdovirus of significant concern to salmon aquaculture. Landscape IHNV transmission dynamics previously had been estimated only for salmonid hatcheries in the Lower Columbia River Basin (LCRB). The objectives of this study were to estimate IHNV transmission dynamics in a unique geographic region, the Snake River Basin (SRB), and to quantitatively estimate the effect of model coproduction on inference because previous assessments of coproduction have been qualitative. In contrast to the LCRB, the SRB has hatchery complexes consisting of a main hatchery and ≥1 satellite facility. Knowledge about hatchery complexes was held by a subset of project researchers but would not have been available to project modelers without coproduction. Project modelers generated and tested multiple versions of Bayesian susceptible-exposedinfected models to realistically represent the SRB and estimate the effect of coproduction. Models estimated the frequency of transmission routes, route-specific infection probabilities, and infection probabilities for combinations of salmonid hosts and IHNV lineages. Model results indicated that in the SRB, avoiding exposure to IHNV-positive adult salmonids is the most important action to prevent juvenile infections. Migrating adult salmonids exposed juvenile cohort-sites most frequently, and the infection probability was greatest following exposure to migrating adults. Without coproduction, the frequency of exposure by migrating adults would have been overestimated by 70 cohort-sites, and the infection probability following exposure to migrating adults would have been underestimated by∼0.09. The coproduced model had less uncertainty in the infection probability if no transmission route could be identified (Bayesian credible interval (BCI) width = 0.12) compared to the model without coproduction (BCI width = 0.34). Evidence for virus lineage MD specialization on steelhead and rainbow trout (both Oncorhynchus mykiss) was apparent without model coproduction. In the SRB, we found a greater probability of virus lineage UC infection in Chinook salmon (Oncorhynchus tshawytscha) compared to in O. mykiss, whereas in the LCRB, UC more clearly exhibited a generalist approach. Coproduction influenced estimates that depended on transmission routes, which operated differently at main hatcheries and satellite sites within hatchery complexes. Hatchery complexes are found outside of the SRB and are not specific to salmonid hatcheries alone. There is great potential for coproduction and modeling spatial contact networks to advance understanding about infectious disease transmission in complex production systems and surrounding free-ranging animal populations.

Idaho, Oregon, Washington↗
USGS2013

Estimating instream constituent loads using replicate synoptic sampling, Peru Creek, Colorado

The synoptic mass balance approach is often used to evaluate constituent mass loading in streams affected by mine drainage. Spatial profiles of constituent mass load are used to identify sources of contamination and prioritize sites for remedial action. This paper presents a field scale study in which replicate synoptic sampling campaigns are used to quantify the aggregate uncertainty in constituent load that arises from (1) laboratory analyses of constituent and tracer concentrations, (2) field sampling error, and (3) temporal variation in concentration from diel constituent cycles and/or source variation. Consideration of these factors represents an advance in the application of the synoptic mass balance approach by placing error bars on estimates of constituent load and by allowing all sources of uncertainty to be quantified in aggregate; previous applications of the approach have provided only point estimates of constituent load and considered only a subset of the possible errors. Given estimates of aggregate uncertainty, site specific data and expert judgement may be used to qualitatively assess the contributions of individual factors to uncertainty. This assessment can be used to guide the collection of additional data to reduce uncertainty. Further, error bars provided by the replicate approach can aid the investigator in the interpretation of spatial loading profiles and the subsequent identification of constituent source areas within the watershed. The replicate sampling approach is applied to Peru Creek, a stream receiving acidic, metal-rich effluent from the Pennsylvania Mine. Other sources of acidity and metals within the study reach include a wetland area adjacent to the mine and tributary inflow from Cinnamon Gulch. Analysis of data collected under low-flow conditions indicates that concentrations of Al, Cd, Cu, Fe, Mn, Pb, and Zn in Peru Creek exceed aquatic life standards. Constituent loading within the study reach is dominated by effluent from the Pennsylvania Mine, with over 50% of the Cd, Cu, Fe, Mn, and Zn loads attributable to a collapsed adit near the top of the study reach. These estimates of mass load may underestimate the effect of the Pennsylvania Mine as leakage from underground mine workings may contribute to metal loads that are currently attributed to the wetland area. This potential leakage confounds the evaluation of remedial options and additional research is needed to determine the magnitude and location of the leakage.

Colorado↗
USGS2016

Evaluating lidar point densities for effective estimation of aboveground biomass

The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m 2 , corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m 2 . Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m 2 , and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m 2 , our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.

International Journal of Advanced Remote Sensing a↗
USGS2020

Sediment connectivity: A framework for analyzing coastal sediment transport pathways

Connectivity provides a framework for analyzing coastal sediment transport pathways, building on conceptual advances in graph theory from other scientific disciplines. Connectivity schematizes sediment pathways as a directed graph (i.e., a set of nodes and links). This study presents a novel application of graph theory and connectivity metrics like modularity and centrality to coastal sediment dynamics, exemplified here using Ameland Inlet in the Netherlands. We divide the study site into geomorphic cells (i.e., nodes) and then quantify sediment transport between these cells (i.e., links) using a numerical model. The system of cells and fluxes between them is then schematized in a network described by an adjacency matrix. Network metrics like link density, asymmetry, and modularity quantify system‐wide connectivity. The degree, strength, and centrality of individual nodes identify key locations and pathways throughout the system. For instance, these metrics indicate that under strictly tidal forcing, sand originating near shore predominantly bypasses Ameland Inlet via the inlet channels, whereas sand on the deeper foreshore mainly bypasses the inlet via the outer delta shoals. Connectivity analysis can also inform practical management decisions about where to place sand nourishments, the fate of nourishment sand, or how to monitor locations vulnerable to perturbations. There are still open challenges associated with quantifying connectivity at varying space and time scales and the development of connectivity metrics specific to coastal systems. Nonetheless, connectivity provides a promising technique for predicting the response of our coasts to climate change and the human adaptations it provokes.

Ameland Inlet↗
USGS2019

Combining numerical and statistical models to predict storm-induced dune erosion

Dune erosion is an important aspect to consider when assessing coastal flood risk, as dune elevation loss makes the protected areas more susceptible to flooding. However, most advanced dune erosion numerical models are computationally expensive, which hinders their application in early-warning systems. Based on a combination of probabilistic and process-based numerical modeling, we develop an efficient statistical tool to predict dune erosion during storms. The analysis focuses on Dauphin Island, AL in the northern Gulf of Mexico, where we combine synthetic sea storms with a calibrated and validated XBeach model to develop and test a range of different surrogate models for their ability to predict barrier-island geometric parameters under storm conditions. Surrogate models are developed by combining the oceanographic forcing from 100 optimally sampled sea-storm events covering the entire multivariate parameter space (used as XBeach input) and associated changes in the dune system (XBeach output). We test four surrogate models using a k-fold approach for validation. All models perform well in predicting changes in dune elevation, barrier-island area, and width, but are less accurate in predicting alterations in the cross-shore locations of dune morphological features. Multivariate adaptive regression splines are identified as the best surrogate model based on their fast development and good performance, attaining a modified Mielke index of 0.81 for dune crest height. As demonstrated at Dauphin Island, our approach shows potential to be used in an operational framework to predict dune response (in particular crest elevation change) when water level and wave forecasts are available.

Alabama↗
USGS2009

Inducing in situ, nonlinear soil response applying an active source

[1] It is well known that soil sites have a profound effect on ground motion during large earthquakes. The complex structure of soil deposits and the highly nonlinear constitutive behavior of soils largely control nonlinear site response at soil sites. Measurements of nonlinear soil response under natural conditions are critical to advancing our understanding of soil behavior during earthquakes. Many factors limit the use of earthquake observations to estimate nonlinear site response such that quantitative characterization of nonlinear behavior relies almost exclusively on laboratory experiments and modeling of wave propagation. Here we introduce a new method for in situ characterization of the nonlinear behavior of a natural soil formation using measurements obtained immediately adjacent to a large vibrator source. To our knowledge, we are the first group to propose and test such an approach. Employing a large, surface vibrator as a source, we measure the nonlinear behavior of the soil by incrementally increasing the source amplitude over a range of frequencies and monitoring changes in the output spectra. We apply a homodyne algorithm for measuring spectral amplitudes, which provides robust signal-to-noise ratios at the frequencies of interest. Spectral ratios are computed between the receivers and the source as well as receiver pairs located in an array adjacent to the source, providing the means to separate source and near-source nonlinearity from pervasive nonlinearity in the soil column. We find clear evidence of nonlinearity in significant decreases in the frequency of peak spectral ratios, corresponding to material softening with amplitude, observed across the array as the source amplitude is increased. The observed peak shifts are consistent with laboratory measurements of soil nonlinearity. Our results provide constraints for future numerical modeling studies of strong ground motion during earthquakes.

Journal of Geophysical Research B: Solid Earth↗
USGS2009

Rupture parameters of the 2003 Zemmouri (M w 6.8), Algeria, earthquake from joint inversion of interferometric synthetic aperture radar, coastal uplift, and GPS

We study the surface deformation associated with the 21 May 2003 (M w = 6.8) Zemmouri (Algeria) earthquake, the strongest seismic event felt in the Algiers region since 1716. The thrust earthquake mechanism and related surface deformation revealed an average 0.50 m coastal uplift along ??55-km-long coastline. We obtain coseismic interferograms using Envisat advanced synthetic aperture radar (ASAR) (IS2) and RADARSAT standard beam (ST4) data from both the ascending and descending orbits of Envisat satellite, whereas the RADARSAT data proved useful only in the descending mode. While the two RADARSAT interferograms cover the earthquake area, Envisat data cover only the western half of the rupture zone. Although the interferometric synthetic aperture radar (InSAR) coherence in the epicenter area is poor, deformation fringes are observed along the coast in different patches. In the Boumerdes area, the maximum coseismic deformation is indicated by the high gradient of fringes visible in all interferograms in agreement with field measurements (tape, differential GPS, leveling, and GPS). To constrain the earthquake rupture parameters, we model the interferograms and uplift measurements using elastic dislocations on triangular fault patches in an elastic and homogeneous half-space. We invert the coseismic slip using first, a planar surface and second, a curved fault, both constructed from triangular elements using Poly3Dinv program that uses a damped least square minimization. The best fit of InSAR, coastal uplift, and GPS data corresponds to a 65-km-long fault rupture dipping 40?? to 50?? SE, located at 8 to 13 km offshore with a change in strike west of Boumerdes from N60??-65?? to N95??-105??. The inferred rupture geometry at depth correlates well with the seismological results and may have critical implications for the seismic hazard assessment of the Algiers region. Copyright 2009 by the American Geophysical Union.

Journal of Geophysical Research F: Earth Surface↗
USGS2012

Volcanic hazards and public response

Although scientific understanding of volcanoes is advancing, eruptions continue to take a substantial toll of life and property. Some of these losses could be reduced by better advance preparation, more effective flow of information between scientists and public officials, and better understanding of volcanic behavior by all segments of the public. The greatest losses generally occur at volcanoes that erupt infrequently where people are not accustomed to dealing with them. Scientists sometimes tend to feel that the blame for poor decisions in emergency management lies chiefly with officials or journalists because of their failure to understand the threat. However, the underlying problem embraces a set of more complex issues comprising three pervasive factors. The first factor is the volcano: signals given by restless volcanoes are often ambiguous and difficult to interpret, especially at long-quiescent volcanoes. The second factor is people: people confront hazardous volcanoes in widely divergent ways, and many have difficulty in dealing with the uncertainties inherent in volcanic unrest. The third factor is the scientists: volcanologists correctly place their highest priority on monitoring and hazard assessment, but they sometimes fail to explain clearly their conclusions to responsible officials and the public, which may lead to inadequate public response. Of all groups in society, volcanologists have the clearest understanding of the hazards and vagaries of volcanic activity; they thereby assume an ethical obligation to convey effectively their knowledge to benefit all of society. If society resists, their obligation nevertheless remains. They must use the same ingenuity and creativity in dealing with information for the public that they use in solving scientific problems. When this falls short, even excellent scientific results may be nullified.

Journal of Geophysical Research Solid Earth↗
USGS2018

Evolving environmental and geometric controls on Columbia Glacier’s continued retreat

Geometry strongly controls the dynamic behavior of marine‐terminating (tidewater) glaciers, significantly influencing advance and retreat cycles independent of climate. Yet the recent, nearly ubiquitous retreat of tidewater glaciers suggests that changes in atmospheric and oceanic forcing may also drive dynamic change. To isolate the influence of geometry on tidewater glacier dynamics, we analyzed detailed observational time series from 2012 to 2016 for two tidewater glaciers with shared dynamic histories and environmental forcing: Columbia Glacier and its former tributary (Post Glacier) in southcentral Alaska. We find that although terminus retreat has driven decadal‐scale changes in dynamics of the Columbia‐Post system, environmental factors contribute to short‐term (i.e., seasonal) dynamic variability. In particular, analysis of force balance time series indicates that observed variations in speed result from seasonal changes to the subglacial hydrologic system and associated changes in basal drag. Variations in terminus position only drive noticeable speed change when the terminus retreats from regions of relatively high basal drag. In agreement with long‐term analyses of Columbia Glacier, we find that terminus geometry can perturb the timing of seasonal ice flow patterns. Specifically, our data support the idea that retreat of a glacier terminus into deeper water is accompanied by a shift in the primary control on frontal ablation. Although our analysis focuses on two Alaskan glaciers, our data suggest that changes in the relative importance of surface meltwater and buoyancy effects on submarine melting and/or calving may manifest as a shift in terminus change seasonality and offer a mechanism to identify frontal ablation controls.

Alaska↗
USGS2012

Advances in the simulation and automated measurement of well-sorted granular material: 2. Direct measures of particle properties

1. In this, the second of a pair of papers on the structure of well-sorted natural granular material (sediment), new methods are described for automated measurements from images of sediment, of: 1) particle-size standard deviation (arithmetic sorting) with and without apparent void fraction; and 2) mean particle size in material with void fraction. A variety of simulations of granular material are used for testing purposes, in addition to images of natural sediment. Simulations are also used to establish that the effects on automated particle sizing of grains visible through the interstices of the grains at the very surface of a granular material continue to a depth of approximately 4 grain diameters and that this is independent of mean particle size. Ensemble root-mean squared error between observed and estimated arithmetic sorting coefficients for 262 images of natural silts, sands and gravels (drawn from 8 populations) is 31%, which reduces to 27% if adjusted for bias (slope correction between observed and estimated values). These methods allow non-intrusive and fully automated measurements of surfaces of unconsolidated granular material. With no tunable parameters or empirically derived coefficients, they should be broadly universal in appropriate applications. However, empirical corrections may need to be applied for the most accurate results. Finally, analytical formulas are derived for the one-step pore-particle transition probability matrix, estimated from the image's autocorrelogram, from which void fraction of a section of granular material can be estimated directly. This model gives excellent predictions of bulk void fraction yet imperfect predictions of pore-particle transitions.

Journal of Geophysical Research F: Earth Surface↗
USGS2006

Acoustic bed velocity and bed load dynamics in a large sand bed river

Development of a practical technology for rapid quantification of bed load transport in large rivers would represent a revolutionary advance for sediment monitoring and the investigation of fluvial dynamics. Measurement of bed load motion with acoustic Doppler current profiles (ADCPs) has emerged as a promising approach for evaluating bed load transport. However, a better understanding of how ADCP data relate to conditions near the stream bed is necessary to make the method practical for quantitative applications. In this paper, we discuss the response of ADCP bed velocity measurements, defined as the near-bed sediment velocity detected by the instrument's bottom-tracking feature, to changing sediment-transporting conditions in the lower Missouri River. Bed velocity represents a weighted average of backscatter from moving bed load particles and spectral reflections from the immobile bed. The ratio of bed velocity to mean bed load particle velocity depends on the concentration of the particles moving in the bed load layer, the bed load layer thickness, and the backscatter strength from a unit area of moving particles relative to the echo strength from a unit area of unobstructed bed. A model based on existing bed load transport theory predicted measured bed velocities from hydraulic and grain size measurements with reasonable success. Bed velocities become more variable and increase more rapidly with shear stress when the transport stage, defined as the ratio of skin friction to the critical shear stress for particle entrainment, exceeds a threshold of about 17. This transition in bed velocity response appears to be associated with the appearance of longer, flatter bed forms at high transport stages.

Journal of Geophysical Research F: Earth Surface↗
USGS2010

Satellite observations of a surtseyan eruption: Hunga Ha'apai, Tonga

On March 17, 2009, a surtseyan eruption occurred around Hunga Ha'apai Island, Tonga. A series of observations from the high-spatial resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and the high-temporal resolution Moderate Resolution Imaging Spectroradiometer (MODIS), was used to estimate the magnitude, location, start time, and duration of the eruption, and measure the evolving characteristics of the new Hunga Ha'apai Island. The eruption start time was estimated to be between 01:50 and 11:10 local time, on March 17, 2009 (i.e., between 12:50 and 22:10 UTC, March 16). The initial explosive phase lasted 3–5 days and consisted of multiple steam and tephra explosions from two distinct vent sources, one on the northwest side, and another about 100 m off the south shore of the pre-existing island. The eruption plume reached 4.0 to 7.6 km altitude above sea level, and tephra added new land around each of the vents, initially tripling the area of the pre-existing island. The next phase of steaming from newly formed crater lakes around the vents lasted a few days. Three warm crater lakes formed initially, but disappeared with time as the shoreline eroded. After ~ 2 months, vegetation that was initially buried by tephra was recovering; after ~ 10 months, the size of the island had eroded down to ~ twice that of the pre-existing island, and the one remaining crater lake had a temperature of ~ 68 ± 17 °C. The volume of erupted material was estimated to be ~ 0.0176 km 3 and the volcanic explosivity index (VEI) was estimated to be VEI = 2.

Hunga Ha'apai Island↗
USGS2023

Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations

The hillslope and channel dynamics that govern streamflow permanence in headwater systems have important implications for ecosystem functioning and downstream water quality. Recent advancements in process-based, semi-distributed hydrologic models that build upon empirical studies of streamflow permanence in well-monitored headwater catchments show promise for characterizing the dynamics of streamflow permanence in headwater systems. However, few process-based models consider the continuum of hillslope-stream network connectivity as a control on streamflow permanence in headwater systems. The objective of this study was to expand a process-based, catchment-scale hydrologic model to better understand the spatiotemporal dynamics of headwater streamflow permanence and to identify controls of streamflow expansion and contraction in a headwater network. Further, we aimed to develop an approach that enhanced the fidelity of model simulations, yet required little additional data, with the intent that the model might be later transferred to catchments with limited long-term and spatially explicit measurements. This approach facilitated network-scale estimates of the controls of streamflow expansion and contraction, albeit with higher degrees of uncertainty in individual reaches due to data constraints. Our model simulated that streamflow permanence was highly dynamic in first-order reaches with steep slopes and variable contributing areas. The simulated stream network length ranged from nearly 98±2% of the geomorphic channel extent during wet periods to nearly 50±10% during dry periods. The model identified a discharge threshold of approximately 1 mm d −1 , above which the rate of streamflow expansion decreases by nearly an order of magnitude, indicating a lack of sensitivity of streamflow expansion to hydrologic forcing during high-flow periods. Overall, we demonstrate that process-based, catchment-scale models offer important insights on the controls of streamflow permanence, despite uncertainties and limitations of the model. We encourage researchers to increase data collection efforts and develop benchmarks to better evaluate such models.

Kentucky↗
USGS2025

Multiscale framework for assessing land cover change on barrier islands from extreme storms and restoration

Often found along the estuarine-marine interface, barrier islands and mainland coastal zones are shaped by tides, currents, extreme storms, and relative sea-level rise. These systems provide ecosystem services such as storm surge and wave attenuation, erosion protection to inland areas, habitat for fish and wildlife, recreation, and tourism. Given the importance of these ecosystems coupled with their dynamic nature, information on how these coastal systems are changing can help to inform natural resource management. Remote sensing advancements have led to an abundance of data for monitoring change in coastal settings. This study developed a multiscale framework that can provide trajectory information from screening-level analyses by using existing or custom moderate spatial resolution land cover maps. Using the north-central Gulf Coast as a case study, the trajectory of land cover area for barrier islands and mainland coastal zones was assessed using several geospatial data sets, including: (1) long-term moderate-resolution remote sensing products with an annual (or more frequent) temporal frequency; (2) a restoration database ( e.g. , beach/dune restoration, sediment placement, and dune enhancement); and (3) a tropical storm database. Due to the coarser spatial resolution of data sets used for screening-level analyses, detailed or application-specific analyses are often needed to reduce uncertainty in smaller changes that may not be captured. These may include land cover change analyses ( i.e. this study), periodic land cover maps with higher spatial resolution and more detailed land cover classes, or elevation-related analyses ( e.g. , dune change or inundation change). Using this framework, abrupt changes in land cover on Dauphin Island, Alabama, resulting from extreme storms were detected using moderate spatial resolution screening-level data, while restoration impact analyses may require higher resolution data. Further, land cover change analyses that incorporate change allocation provide robust information for understanding land cover change in dynamic coastal settings.

Alabama, Florida↗