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At least 865 records · Page 48Linked to original sources
USGS2004

Application of near real-time radial semblance to locate the shallow magmatic conduit at Kilauea Volcano, Hawaii

Radial Semblance is applied to broadband seismic network data to provide source locations of Very-Long-Period (VLP) seismic energy in near real time. With an efficient algorithm and adequate network coverage, accurate source locations of VLP energy are derived to quickly locate the shallow magmatic conduit system at Kilauea Volcano, Hawaii. During a restart in magma flow following a brief pause in the current eruption, the shallow magmatic conduit is pressurized, resulting in elastic radiation from various parts of the conduit system. A steeply dipping distribution of VLP hypocenters outlines a region extending from sea level to about 550 m elevation below and just east of the Halemaumau Pit Crater. The distinct hypocenters suggest the shallow plumbing system beneath Halemaumau consists of a complex plexus of sills and dikes. An unconstrained location for a section of the conduit is also observed beneath the region between Kilauea Caldera and Kilauea Iki Crater.

Hawaii↗
USGS2005

Forecasting the evolution of seismicity in southern California: Animations built on earthquake stress transfer

We develop a forecast model to reproduce the distibution of main shocks, aftershocks and surrounding seismicity observed during 1986-200 in a 300 ?? 310 km area centered on the 1992 M = 7.3 Landers earthquake. To parse the catalog into frames with equal numbers of aftershocks, we animate seismicity in log time increments that lengthen after each main shock; this reveals aftershock zone migration, expansion, and densification. We implement a rate/state algorithm that incorporates the static stress transferred by each M ??? 6 shock and then evolves. Coulomb stress changes amplify the background seismicity, so small stress changes produce large changes in seismicity rate in areas of high background seismicity. Similarly, seismicity rate declines in the stress shadows are evident only in areas with previously high seismicity rates. Thus a key constituent of the model is the background seismicity rate, which we smooth from 1981 to 1986 seismicity. The mean correlation coefficient between observed and predicted M ??? 1.4 shocks (the minimum magnitude of completeness) is 0.52 for 1986-2003 and 0.63 for 1992-2003; a control standard aftershock model yields 0.54 and 0.52 for the same periods. Four M ??? 6.0 shocks struck during the test period; three are located at sites where the expected seismicity rate falls above the 92 percentile, and one is located above the 75 percentile. The model thus reproduces much, but certainly not all, of the observed spatial and temporal seismicity, from which we infer that the decaying effect of stress transferred by successive main shocks influences seismicity for decades. Finally, we offer a M ??? 5 earthquake forecast for 2005-2015, assigning probabilities to 324 10 ?? 10 km cells.

Journal of Geophysical Research B: Solid Earth↗
USGS2005

Spatial and temporal variations in the age structure of Arctic sea ice

Spatial and temporal variations in the age structure of Arctic sea ice are investigated using a new reverse chronology algorithm that tracks ice-covered pixels to their location and date of origin based on ice motion and concentration data. The Beaufort Gyre tends to harbor the oldest (>10 years old) sea ice in the western Arctic while direct ice advection pathways toward the Transpolar Drift Stream maintain relatively young (10 years old (10+ year age class) were observed during 1989-2003. Since the mid-1990s, losses to the 10+ year age class lacked compensation by recruitment due to a prior depletion of all mature (6-10 year) age classes. Survival of the 1994 and 1996-1998 sea ice generations reestablished most mature age classes, and thereby the potential to increase extent of the 10+ year age class during the mid-2000s.

Geophysical Research Letters↗
USGS2007

Reach‐averaged sediment routing model of a canyon river

Spatial complexity in channel geometry indicates that accurate prediction of sediment transport requires modeling in at least two dimensions. However, a one‐dimensional model may be the only practical or possible alternative, especially for longer river reaches of practical concern in river management or landscape modeling. We have developed a one‐dimensional model of the Colorado River through upper Grand Canyon that addresses this problem by reach averaging the channel properties and predicting changes in sand storage using separate source and sink functions coupled to the sand routing model. The model incorporates results from the application of a two‐dimensional model of flow, sand transport, and bed evolution, and a new algorithm for setting the near‐bed sand boundary condition for sand transported over an exposed bouldery bed. Model predictions were compared to measurements of sand discharge during intermittent tributary inputs and varying discharges controlled by dam releases. The model predictions generally agree well with the timing and magnitude of measured sand discharges but tend to overpredict sand discharge during the early stages of a high release designed to redistribute sand to higher‐elevation deposits.

Water Resources Research↗
USGS2008

Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

Journal of Geophysical Research D: Atmospheres↗
USGS2008

An autocorrelation method to detect low frequency earthquakes within tremor

Recent studies have shown that deep tremor in the Nankai Trough under western Shikoku consists of a swarm of low frequency earthquakes (LFEs) that occur as slow shear slip on the down-dip extension of the primary seismogenic zone of the plate interface. The similarity of tremor in other locations suggests a similar mechanism, but the absence of cataloged low frequency earthquakes prevents a similar analysis. In this study, we develop a method for identifying LFEs within tremor. The method employs a matched-filter algorithm, similar to the technique used to infer that tremor in parts of Shikoku is comprised of LFEs; however, in this case we do not assume the origin times or locations of any LFEs a priori. We search for LFEs using the running autocorrelation of tremor waveforms for 6 Hi-Net stations in the vicinity of the tremor source. Time lags showing strong similarity in the autocorrelation represent either repeats, or near repeats, of LFEs within the tremor. We test the method on an hour of Hi-Net recordings of tremor and demonstrates that it extracts both known and previously unidentified LFEs. Once identified, we cross correlate waveforms to measure relative arrival times and locate the LFEs. The results are able to explain most of the tremor as a swarm of LFEs and the locations of newly identified events appear to fill a gap in the spatial distribution of known LFEs. This method should allow us to extend the analysis of Shelly et al. (2007a) to parts of the Nankai Trough in Shikoku that have sparse LFE coverage, and may also allow us to extend our analysis to other regions that experience deep tremor, but where LFEs have not yet been identified. Copyright 2008 by the American Geophysical Union.

Geophysical Research Letters↗
USGS2009

Regional three-dimensional seismic velocity model of the crust and uppermost mantle of northern California

We present a three-dimensional (3D) tomographic model of the P wave velocity (Vp) structure of northern California. We employed a regional-scale double-difference tomography algorithm that incorporates a finite-difference travel time calculator and spatial smoothing constraints. Arrival times from earthquakes and travel times from controlled-source explosions, recorded at network and/or temporary stations, were inverted for Vp on a 3D grid with horizontal node spacing of 10 to 20 km and vertical node spacing of 3 to 8 km. Our model provides an unprecedented, comprehensive view of the regional-scale structure of northern California, putting many previously identified features into a broader regional context and improving the resolution of a number of them and revealing a number of new features, especially in the middle and lower crust, that have never before been reported. Examples of the former include the complex subducting Gorda slab, a steep, deeply penetrating fault beneath the Sacramento River Delta, crustal low-velocity zones beneath Geysers-Clear Lake and Long Valley, and the high-velocity ophiolite body underlying the Great Valley. Examples of the latter include mid-crustal low-velocity zones beneath Mount Shasta and north of Lake Tahoe. Copyright 2009 by the American Geophysical Union.

Journal of Geophysical Research B: Solid Earth↗
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↗
USGS2008

Boreal soil carbon dynamics under a changing climate: A model inversion approach

Several fundamental but important factors controlling the feedback of boreal organic carbon (OC) to climate change were examined using a mechanistic model of soil OC dynamics, including the combined effects of temperature and moisture on the decomposition of OC and the factors controlling carbon quality and decomposition with depth. To estimate decomposition rates and evaluate their variations with depth, the model was inverted using a global optimization algorithm. Three sites with different drainage conditions that represent a broad diversity of boreal black spruce ecosystems were modeled. The comparison among the models with different depth patterns of decomposition rates (i.e., constant, linear, and exponential decrease) revealed that the model with constant inherent decomposition rates through the soil profile was able to fit the observed data in the most efficient way. There were also lower turnover times in the wettest site compared to the drier site even after accounting for moisture and temperature differences. Taken together, these results indicate that decomposition (especially for the wetter site) was not accurately represented with standard moisture and temperature controls and that other important protection mechanisms (e.g., limitation of O 2 , redox conditions, and permafrost) rather than low inherent decomposition rates are responsible for the recalcitrance of deep OC. The simulation results also showed that most of the soil CO 2 efflux is generated from subsurface layers of OC because of the large OC stocks and optimal moisture conditions, suggesting that these deeper soil OC stocks are likely to be critically important to the future carbon dynamics.

Journal of Geophysical Research Biogeosciences↗
USGS2010

A universal approximation to grain size from images of non-cohesive sediment

The two-dimensional spectral decomposition of an image of sediment provides a direct statistical estimate, grid-by-number style, of the mean of all intermediate axes of all single particles within the image. We develop and test this new method which, unlike existing techniques, requires neither image processing algorithms for detection and measurement of individual grains, nor calibration. The only information required of the operator is the spatial resolution of the image. The method is tested with images of bed sediment from nine different sedimentary environments (five beaches, three rivers, and one continental shelf), across the range 0.1 mm to 150 mm, taken in air and underwater. Each population was photographed using a different camera and lighting conditions. We term it a “universal approximation” because it has produced accurate estimates for all populations we have tested it with, without calibration. We use three approaches (theory, computational experiments, and physical experiments) to both understand and explore the sensitivities and limits of this new method. Based on 443 samples, the root-mean-squared (RMS) error between size estimates from the new method and known mean grain size (obtained from point counts on the image) was found to be ±≈16%, with a 95% probability of estimates within ±31% of the true mean grain size (measured in a linear scale). The RMS error reduces to ≈11%, with a 95% probability of estimates within ±20% of the true mean grain size if point counts from a few images are used to correct bias for a specific population of sediment images. It thus appears it is transferable between sedimentary populations with different grain size, but factors such as particle shape and packing may introduce bias which may need to be calibrated for. For the first time, an attempt has been made to mathematically relate the spatial distribution of pixel intensity within the image of sediment to the grain size.

Journal of Geophysical Research F: Earth Surface↗
USGS2011

Detecting aseismic strain transients from seismicity data

Aseismic deformation transients such as fluid flow, magma migration, and slow slip can trigger changes in seismicity rate. We present a method that can detect these seismicity rate variations and utilize these anomalies to constrain the underlying variations in stressing rate. Because ordinary aftershock sequences often obscure changes in the background seismicity caused by aseismic processes, we combine the stochastic Epidemic Type Aftershock Sequence model that describes aftershock sequences well and the physically based rate‐ and state‐dependent friction seismicity model into a single seismicity rate model that models both aftershock activity and changes in background seismicity rate. We implement this model into a data assimilation algorithm that inverts seismicity catalogs to estimate space‐time variations in stressing rate. We evaluate the method using a synthetic catalog, and then apply it to a catalog of M ≥ 1.5 events that occurred in the Salton Trough from 1990 to 2009. We validate our stressing rate estimates by comparing them to estimates from a geodetically derived slip model for a large creep event on the Obsidian Buttes fault. The results demonstrate that our approach can identify large aseismic deformation transients in a multidecade long earthquake catalog and roughly constrain the absolute magnitude of the stressing rate transients. Our method can therefore provide a way to detect aseismic transients in regions where geodetic resolution in space or time is poor.

Journal of Geophysical Research B: Solid Earth↗
USGS2011

Hydrological mobilization of mercury and dissolved organic carbon in a snow-dominated, forested watershed: Conceptualization and modeling

The mobilization of mercury and dissolved organic carbon (DOC) during snowmelt often accounts for a major fraction of the annual loads. We studied the role of hydrological connectivity of riparian wetlands and upland/wetland transition zones to surface waters on the mobilization of Hg and DOC in Fishing Brook, a headwater of the Adirondack Mountains, New York. Stream water total mercury (THg) concentrations varied strongly (mean = 2.25 ± 0.5 ng L −1 ), and the two snowmelt seasons contributed 40% (2007) and 48% (2008) of the annual load. Methyl mercury (MeHg) concentrations ranged up to 0.26 ng L −1 , and showed an inverse log relationship with discharge. TOPMODEL‐simulated saturated area corresponded well with wetland areas, and the application of a flow algorithm based elevation‐above‐creek approach suggests that most wetlands become well connected during high flow. The dynamics of simulated saturated area and soil storage deficit were able to explain a large part of the variation of THg concentrations (r 2 = 0.53 to 0.72). In contrast, the simulations were not able to explain DOC variations and DOC and THg concentrations were not correlated. These results indicate that all three constituents, THg, MeHg, and DOC, follow different patterns at the outlet: (1) the mobilization of THg is primarily controlled by the saturation state of the catchment, (2) the dilution of MeHg suggests flushing from a supply limited pool, and (3) DOC dynamics follow a pattern different from THg dynamics, which likely results from differing gain and/or loss processes for THg and/or DOC within the Fishing Brook catchment.

New York↗
USGS2011

Simulating the impacts of disturbances on forest carbon cycling in North America: Processes, data, models, and challenges

Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process‐based procedures and algorithms to quantify the immediate and long‐term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty

Journal of Geophysical Research: Biogeosciences↗
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↗
USGS2012

Extended Kalman Filter framework for forecasting shoreline evolution

A shoreline change model incorporating both long- and short-term evolution is integrated into a data assimilation framework that uses sparse observations to generate an updated forecast of shoreline position and to estimate unobserved geophysical variables and model parameters. Application of the assimilation algorithm provides quantitative statistical estimates of combined model-data forecast uncertainty which is crucial for developing hazard vulnerability assessments, evaluation of prediction skill, and identifying future data collection needs. Significant attention is given to the estimation of four non-observable parameter values and separating two scales of shoreline evolution using only one observable morphological quantity (i.e. shoreline position).

Geophysical Research Letters↗
USGS2012

Detecting hidden volcanic explosions from Mt. Cleveland Volcano, Alaska with infrasound and ground-couples airwaves

In Alaska, where many active volcanoes exist without ground-based instrumentation, the use of techniques suitable for distant monitoring is pivotal. In this study we report regional-scale seismic and infrasound observations of volcanic activity at Mt. Cleveland between December 2011 and August 2012. During this period, twenty explosions were detected by infrasound sensors as far away as 1827 km from the active vent, and ground-coupled acoustic waves were recorded at seismic stations across the Aleutian Arc. Several events resulting from the explosive disruption of small lava domes within the summit crater were confirmed by analysis of satellite remote sensing data. However, many explosions eluded initial, automated, analyses of satellite data due to poor weather conditions. Infrasound and seismic monitoring provided effective means for detecting these hidden events. We present results from the implementation of automatic infrasound and seismo-acoustic eruption detection algorithms, and review the challenges of real-time volcano monitoring operations in remote regions. We also model acoustic propagation in the Northern Pacific, showing how tropospheric ducting effects allow infrasound to travel long distances across the Aleutian Arc. The successful results of our investigation provide motivation for expanded efforts in infrasound monitoring across the Aleutians and contributes to our knowledge of the number and style of vulcanian eruptions at Mt. Cleveland.

Alaska↗
USGS2012

Improving the accuracy of S0 2 column densities and emission rates obtained from upward-looking UV-spectroscopic measurements of volcanic plumes by taking realistic radiative transfer into account

Sulfur dioxide (SO 2 ) is monitored using ultraviolet (UV) absorption spectroscopy at numerous volcanoes around the world due to its importance as a measure of volcanic activity and a tracer for other gaseous species. Recent studies have shown that failure to take realistic radiative transfer into account during the spectral retrieval of the collected data often leads to large errors in the calculated emission rates. Here, the framework for a new evaluation method which couples a radiative transfer model to the spectral retrieval is described. In it, absorption spectra are simulated, and atmospheric parameters are iteratively updated in the model until a best match to the measurement data is achieved. The evaluation algorithm is applied to two example Differential Optical Absorption Spectroscopy (DOAS) measurements conducted at Kilauea volcano (Hawaii). The resulting emission rates were 20 and 90% higher than those obtained with a conventional DOAS retrieval performed between 305 and 315 nm, respectively, depending on the different SO 2 and aerosol loads present in the volcanic plume. The internal consistency of the method was validated by measuring and modeling SO2 absorption features in a separate wavelength region around 375 nm and comparing the results. Although additional information about the measurement geometry and atmospheric conditions is needed in addition to the acquired spectral data, this method for the first time provides a means of taking realistic three-dimensional radiative transfer into account when analyzing UV-spectral absorption measurements of volcanic SO 2 plumes.

Journal of Geophysical Research D: Atmospheres↗
USGS2012

Solar thematic maps for space weather operations

Thematic maps are arrays of labels, or "themes", associated with discrete locations in space and time. Borrowing heavily from the terrestrial remote sensing discipline, a numerical technique based on Bayes' theorem captures operational expertise in the form of trained theme statistics, then uses this to automatically assign labels to solar image pixels. Ultimately, regular thematic maps of the solar corona will be generated from high-cadence, high-resolution SUVI images, the solar ultraviolet imager slated to fly on NOAA's next-generation GOES-R series of satellites starting ~2016. These thematic maps will not only provide quicker, more consistent synoptic views of the sun for space weather forecasters, but digital thematic pixel masks (e.g., coronal hole, active region, flare, etc.), necessary for a new generation of operational solar data products, will be generated. This paper presents the mathematical underpinnings of our thematic mapper, as well as some practical algorithmic considerations. Then, using images from the Solar Dynamics Observatory (SDO) Advanced Imaging Array (AIA) as test data, it presents results from validation experiments designed to ascertain the robustness of the technique with respect to differing expert opinions and changing solar conditions.

Space Weather↗