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At least 235 records · Page 13Linked to original sources
USGS2001

Nonlinear inversion of borehole-radar tomography data to reconstruct velocity and attenuation distribution in earth materials

A nonlinear tomographic inversion method that uses first-arrival travel-time and amplitude-spectra information from cross-hole radar measurements was developed to simultaneously reconstruct electromagnetic velocity and attenuation distribution in earth materials. Inversion methods were developed to analyze single cross-hole tomography surveys and differential tomography surveys. Assuming the earth behaves as a linear system, the inversion methods do not require estimation of source radiation pattern, receiver coupling, or geometrical spreading. The data analysis and tomographic inversion algorithm were applied to synthetic test data and to cross-hole radar field data provided by the US Geological Survey (USGS). The cross-hole radar field data were acquired at the USGS fractured-rock field research site at Mirror Lake near Thornton, New Hampshire, before and after injection of a saline tracer, to monitor the transport of electrically conductive fluids in the image plane. Results from the synthetic data test demonstrate the algorithm computational efficiency and indicate that the method robustly can reconstruct electromagnetic (EM) wave velocity and attenuation distribution in earth materials. The field test results outline zones of velocity and attenuation anomalies consistent with the finding of previous investigators; however, the tomograms appear to be quite smooth. Further work is needed to effectively find the optimal smoothness criterion in applying the Tikhonov regularization in the nonlinear inversion algorithms for cross-hole radar tomography.

New Hampshire↗
USGS2001

Evaluation of flash-flood discharge forecasts in complex terrain using precipitation

Operational prediction of flash floods produced by thunderstorm (convective) precipitation in mountainous areas requires accurate estimates or predictions of the precipitation distribution in space and time. The details of the spatial distribution are especially critical in complex terrain because the watersheds are generally small in size, and small position errors in the forecast or observed placement of the precipitation can distribute the rain over the wrong watershed. In addition to the need for good precipitation estimates and predictions, accurate flood prediction requires a surface-hydrologic model that is capable of predicting stream or river discharge based on the precipitation-rate input data. Different techniques for the estimation and prediction of convective precipitation will be applied to the Buffalo Creek, Colorado flash flood of July 1996, where over 75 mm of rain from a thunderstorm fell on the watershed in less than 1 h. The hydrologic impact of the precipitation was exacerbated by the fact that a significant fraction of the watershed experienced a wildfire approximately two months prior to the rain event. Precipitation estimates from the National Weather Service's operational Weather Surveillance Radar-Doppler 1988 and the National Center for Atmospheric Research S-band, research, dual-polarization radar, colocated to the east of Denver, are compared. In addition, very short range forecasts from a convection-resolving dynamic model, which is initialized variationally using the radar reflectivity and Doppler winds, are compared with forecasts from an automated-algorithmic forecast system that also employs the radar data. The radar estimates of rain rate, and the two forecasting systems that employ the radar data, have degraded accuracy by virtue of the fact that they are applied in complex terrain. Nevertheless, the radar data and forecasts from the dynamic model and the automated algorithm could be operationally useful for input to surface-hydrologic models employed for flood warning. Precipitation data provided by these various techniques at short time scales and at fine spatial resolutions are employed as detailed input to a distributed-parameter hydrologic model for flash-flood prediction and analysis. With the radar-based precipitation estimates employed as input, the simulated flood discharge was similar to that observed. The dynamic-model precipitation forecast showed the most promise in providing a significant discharge-forecast lead time. The algorithmic system's precipitation forecast did not demonstrate as much skill, but the associated discharge forecast would still have been sufficient to have provided an alert of impending flood danger.

Journal of Hydrologic Engineering↗
USGS2026

Sentinel-2 for chlorophyll-a water quality monitoring: A review of validation evidence and application potential

Water quality monitoring is integral to preserving the health of freshwater ecosystems, and satellite remote sensing has emerged as one monitoring method. Sentinel-2, in particular, has been valuable for water quality monitoring due to its 5-day global temporal revisit time and spatial resolution that ranges from 10 to 60 metres. Sentinel-2 can be used to measure and monitor chlorophyll-a, which historically has been used as an indicator of water quality, eutrophication and harmful algal blooms. Our goal was to review aquatic chlorophyll-a Sentinel-2 research to assess the types of validation evidence reported. Validation evidence is defined here as the set of information key to assessing algorithm performance, and include the spatial and temporal scales of satellite validation, reported in situ sampling method context information, demonstration of validation results through plots, and appropriate algorithm performance metrics. We highlight how the body of literature collectively contributes to advancing a national scale chlorophyll-a product that could support future resource management applications. Our review of 122 published studies indicated that much of the validation evidence corresponded to early stages, as defined by the NASA data maturity framework, due to a limited focus on individual lakes and limited detail on methodology for reproducibility. Prioritizing data accessibility for both in situ data and satellite workflows used in published studies; reporting methods with transparency and consistency; and using standard algorithm performance metrics could provide a consistent framework to support and enhance the utility of satellite inland water quality research. These three quality assurance mechanisms can promote effective evaluation of approaches for remote sensing of chlorophyll-a. Adopting these quality criteria could enable the integration of validation evidence from multiple studies, supporting more spatially and temporally representative products that would advance these approaches towards maturation for broader application.

International Journal of Remote Sensing↗
USGS2007

Compression of the Global Land 1-km AVHRR dataset

Large datasets, such as the Global Land 1-km Advanced Very High Resolution Radiometer (AVHRR) Data Set (Eidenshink and Faundeen 1994), require compression methods that provide efficient storage and quick access to portions of the data. A method of lossless compression is described that provides multiresolution decompression within geographic subwindows of multi-spectral, global, 1-km, AVHRR images. The compression algorithm segments each image into blocks and compresses each block in a hierarchical format. Users can access the data by specifying either a geographic subwindow or the whole image and a resolution (1,2,4, 8, or 16 km). The Global Land 1-km AVHRR data are presented in the Interrupted Goode's Homolosine map projection. These images contain masked regions for non-land areas which comprise 80 per cent of the image. A quadtree algorithm is used to compress the masked regions. The compressed region data are stored separately from the compressed land data. Results show that the masked regions compress to 0·143 per cent of the bytes they occupy in the test image and the land areas are compressed to 33·2 per cent of their original size. The entire image is compressed hierarchically to 6·72 per cent of the original image size, reducing the data from 9·05 gigabytes to 623 megabytes. These results are compared to the first order entropy of the residual image produced with lossless Joint Photographic Experts Group predictors. Compression results are also given for Lempel-Ziv-Welch (LZW) and LZ77, the algorithms used by UNIX compress and GZIP respectively. In addition to providing multiresolution decompression of geographic subwindows of the data, the hierarchical approach and the use of quadtrees for storing the masked regions gives a marked improvement over these popular methods.

International Journal of Remote Sensing↗
USGS2009

Development of time series stacks of Landsat images for reconstructing forest disturbance history

Forest dynamics is highly relevant to a broad range of earth science studies, many of which have geographic coverage ranging from regional to global scales. While the temporally dense Landsat acquisitions available in many regions provide a unique opportunity for understanding forest disturbance history dating back to 1972, large quantities of Landsat images will need to be analysed for studies at regional to global scales. This will not only require effective change detection algorithms, but also highly automated, high level preprocessing capabilities to produce images with subpixel geolocation accuracies and best achievable radiometric consistency, a status called imagery-ready-to-use (IRU). This paper describes a streamlined approach for producing IRU quality Landsat time series stacks (LTSS). This approach consists of an image selection protocol, high level preprocessing algorithms and IRU quality verification procedures. The high level preprocessing algorithms include updated radiometric calibration and atmospheric correction for calculating surface reflectance and precision registration and orthorectification routines for improving geolocation accuracy. These automated routines have been implemented in the Landsat Ecosystem Disturbance Adaptive System (LEDAPS) designed for processing large quantities of Landsat images. Some characteristics of the LTSS developed using this approach are discussed.

International Journal of Digital Earth↗
USGS2017

FinDer v.2: Improved real-time ground-motion predictions for M2-M9 with seismic finite-source characterization

Recent studies suggest that small and large earthquakes nucleate similarly, and that they often have indistinguishable seismic waveform onsets. The characterization of earthquakes in real time, such as for earthquake early warning, therefore requires a flexible modeling approach that allows a small earthquake to become large as fault rupture evolves over time. Here, we present a modeling approach that generates a set of output parameters and uncertainty estimates that are consistent with both small/moderate (≤M6.5) and large earthquakes (>M6.5) as is required for a robust parameter interpretation and shaking forecast. Our approach treats earthquakes over the entire range of magnitudes (>M2) as finite line-source ruptures, with the dimensions of small earthquakes being very small (<100 m) and those of large earthquakes exceeding several tens to hundreds of kilometres in length. The extent of the assumed line source is estimated from the level and distribution of high-frequency peak acceleration amplitudes observed in a local seismic network. High-frequency motions are well suited for this approach, because they are mainly controlled by the distance to the rupturing fault. Observed ground-motion patterns are compared with theoretical templates modeled from empirical ground-motion prediction equations to determine the best line source and uncertainties. Our algorithm extends earlier work by Böse et al. for large finite-fault ruptures. This paper gives a detailed summary of the new algorithm and its offline performance for the 2016 M7.0 Kumamoto, Japan and 2014 M6.0 South Napa, California earthquakes, as well as its performance for about 100 real-time detected local earthquakes (2.2 ≤ M ≤ 5.1) in California. For most events, both the rupture length and the strike are well constrained within a few seconds (<10 s) of the event origin. In large earthquakes, this could allow for providing warnings of up to several tens of seconds. The algorithm could also be useful for resolving fault plane ambiguities of focal mechanisms and identification of rupturing faults for earthquakes as small as M2.5.

California↗
USGS2019

A combinatorial approach to determine earthquake magnitude distributions on a variable slip-rate fault

Combinatorial methods are used to determine the spatial distribution of earthquake magnitudes on a fault whose slip rate varies along strike. Input to the problem is a finite sample of earthquake magnitudes that span 5 kyr drawn from a truncated Pareto distribution. The primary constraints to the problem are maximum and minimum values around the target slip-rate function indicating where feasible solutions can occur. Two methods are used to determine the spatial distribution of earthquakes: integer programming and the greedy-sequential algorithm. For the integer-programming method, the binary decision vector includes all possible locations along the fault where each earthquake can occur. Once a set of solutions that satisfy the constraints is found, the cumulative slip misfit on the fault is globally minimized relative to the target slip-rate function. The greedy algorithm sequentially places earthquakes to locally optimize slip accumulation. As a case study, we calculate how earthquakes are distributed along the megathrust of the Nankai subduction zone, in which the slip rate varies significantly along strike. For both methods, the spatial distribution of magnitudes depends on slip rate, except for the largest magnitude earthquakes that span multiple sections of the fault. The greedy-sequential algorithm, previously applied to this fault (Parsons et al., 2012), tends to produce smoother spatial distributions and fewer lower magnitude earthquakes in the low slip-rate section of the fault compared to the integer-programming method. Differences in results from the two methods relate to how much emphasis is placed on minimizing the misfit to the target slip rate (integer programming) compared to finding a solution within the slip-rate constraints (greedy sequential). Specifics of the spatial distribution of magnitudes also depend on the shape of the target slip-rate function: i.e. stepped at the section boundaries versus a smooth function. This study isolates the effects of slip-rate variation along a single fault in determining the spatial distribution of earthquake magnitudes, helping to better interpret results from more complex, interconnected fault systems.

Geophysical Journal International↗
USGS2003

Mapping the spatial distribution and time evolution of snow water equivalent with passive microwave measurements

This paper presents an algorithm that estimates the spatial distribution and temporal evolution of snow water equivalent and snow depth based on passive remote sensing measurements. It combines the inversion of passive microwave remote sensing measurements via dense media radiative transfer modeling results with snow accumulation and melt model predictions to yield improved estimates of snow depth and snow water equivalent, at a pixel resolution of 5 arc-min. In the inversion, snow grain size evolution is constrained based on pattern matching by using the local snow temperature history. This algorithm is applied to produce spatial snow maps of Upper Rio Grande River basin in Colorado. The simulation results are compared with that of the snow accumulation and melt model and a linear regression method. The quantitative comparison with the ground truth measurements from four Snowpack Telemetry (SNOTEL) sites in the basin shows that this algorithm is able to improve the estimation of snow parameters.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2020

Hierarchical computing for hierarchical models in ecology

Bayesian hierarchical models allow ecologists to account for uncertainty and make inference at multiple scales. However, hierarchical models are often computationally intensive to fit, especially with large datasets, and researchers face trade-offs between capturing ecological complexity in statistical models and implementing these models. We present a recursive Bayesian computing (RB) method that can be used to fit Bayesian models efficiently in sequential MCMC stages to ease computation and streamline hierarchical inference. We also introduce transformation-assisted RB (TARB) to create unsupervised MCMC algorithms and improve interpretability of parameters. We demonstrate TARB by fitting a hierarchical animal movement model to obtain inference about individual- and population-level migratory characteristics. Our recursive procedure reduced computation time for fitting our hierarchical movement model by half compared to fitting the model with a single MCMC algorithm. We obtained the same inference fitting our model using TARB as we obtained fitting the model with a single algorithm. For complex ecological statistical models, like those for animal movement, multi-species systems, or large spatial and temporal scales, the computational demands of fitting models with conventional computing techniques can limit model specification, thus hindering scientific discovery. Transformation-assisted RB is one of the most accessible methods for reducing these limitations, enabling us to implement new statistical models and advance our understanding of complex ecological phenomena.

Article↗
USGS2009

Representing pump-capacity relations in groundwater simulation models

The yield (or discharge) of constant-speed pumps varies with the total dynamic head (or lift) against which the pump is discharging. The variation in yield over the operating range of the pump may be substantial. In groundwater simulations that are used for management evaluations or other purposes, where predictive accuracy depends on the reliability of future discharge estimates, model reliability may be enhanced by including the effects of head-capacity (or pump-capacity) relations on the discharge from the well. A relatively simple algorithm has been incorporated into the widely used MODFLOW groundwater flow model that allows a model user to specify head-capacity curves. The algorithm causes the model to automatically adjust the pumping rate each time step to account for the effect of drawdown in the cell and changing lift, and will shut the pump off if lift exceeds a critical value. The algorithm is available as part of a new multinode well package (MNW2) for MODFLOW.

Ground Water↗
USGS2012

Moderating Argos location errors in animal tracking data

1. The Argos System is used worldwide to satellite-track free-ranging animals, but location errors can range from tens of metres to hundreds of kilometres. Low-quality locations (Argos classes A, 0, B and Z) dominate animal tracking data. Standard-quality animal tracking locations (Argos classes 3, 2 and 1) have larger errors than those reported in Argos manuals. 2. The Douglas Argos-filter (DAF) algorithm flags implausible locations based on user-defined thresholds that allow the algorithm's performance to be tuned to species' movement behaviours and study objectives. The algorithm is available in Movebank – a free online infrastructure for storing, managing, sharing and analysing animal movement data. 3. We compared 21,044 temporally paired global positioning system (GPS) locations with Argos location estimates collected from Argos transmitters on free-ranging waterfowl and condors (13 species, 314 individuals, 54,895 animal-tracking days). The 95th error percentiles for unfiltered Argos locations 0, A, B and Z were within 35·8, 59·6, 163·2 and 220·2 km of the true location, respectively. After applying DAF with liberal thresholds, roughly 20% of the class 0 and A locations and 45% of the class B and Z locations were excluded, and the 95th error percentiles were reduced to 17·2, 15·0, 20·9 and 18·6 km for classes 0, A, B and Z, respectively. As thresholds were applied more conservatively, fewer locations were retained, but they possessed higher overall accuracy. 4. Douglas Argos-filter can improve data accuracy by 50–90% and is an effective and flexible tool for preparing Argos data for direct biological interpretation or subsequent modelling.

Methods in Ecology and Evolution↗
USGS2005

A modified beam-to-earth transformation to measure short-wavelength internal waves with an acoustic Doppler current profiler

The algorithm used to transform velocity signals from beam coordinates to earth coordinates in an acoustic Doppler current profiler (ADCP) relies on the assumption that the currents are uniform over the horizontal distance separating the beams. This condition may be violated by (nonlinear) internal waves, which can have wavelengths as small as 100-200 m. In this case, the standard algorithm combines velocities measured at different phases of a wave and produces horizontal velocities that increasingly differ from true velocities with distance from the ADCP. Observations made in Massachusetts Bay show that currents measured with a bottom-mounted upward-looking ADCP during periods when short-wavelength internal waves are present differ significantly from currents measured by point current meters, except very close to the instrument. These periods are flagged with high error velocities by the standard ADCP algorithm. In this paper measurements from the four spatially diverging beams and the backscatter intensity signal are used to calculate the propagation direction and celerity of the internal waves. Once this information is known, a modified beam-to-earth transformation that combines appropriately lagged beam measurements can be used to obtain current estimates in earth coordinates that compare well with pointwise measurements. ?? 2005 American Meteorological Society.

Journal of Atmospheric and Oceanic Technology↗
USGS1996

Lithologic analysis from multispectral thermal infrared data of the alkalic rock complex at Iron Hill, Colorado

Airborne thermal-infrared multispectral scanner (TIMS) data of the Iron Hill carbonatite-alkalic igneous rock complex in south-central Colorado are analyzed using a new spectral emissivity ratio algorithm and confirmed by field examination using existing 1:24 000-scale geologic maps and petrographic studies. Color composite images show that the alkalic rocks could be clearly identified and that differences existed among alkalic rocks in several parts of the complex. An unsupervised classification algorithm defines four alkalic rock classes within the complex: biotitic pyroxenite, uncompahgrite, augitic pyroxenite, and fenite + nepheline syenite. Felsic rock classes defined in the surrounding country rock are an extensive class consisting of tuff, granite, and felsite, a less extensive class of granite and felsite, and quartzite. The general composition of the classes can be determined from comparisons of the TIMS spectra with laboratory spectra. Carbonatite rocks are not classified, and we attribute that to the fact that dolomite, the predominant carbonate mineral in the complex, has a spectral feature that falls between TIMS channels 5 and 6. Mineralogical variability in the fenitized granite contributed to the nonuniform pattern of the fenite-nepheline syenite class. The biotitic pyroxenite, which resulted from alteration of the pyroxenite, is spatially associated and appears to be related to narrow carbonatite dikes and sills. Results from a linear unmixing algorithm suggest that the detected spatial extent of the two mixed felsic rock classes was sensitive to the amount of vegetation cover. These results illustrate that spectral thermal infrared data can be processed to yield compositional information that can be a cost-effective tool to target mineral exploration, particularly in igneous terranes.

Geophysics↗
USGS2007

Generalization of von Neumann analysis for a model of two discrete half-spaces: The acoustic case

Evaluating the performance of finite-difference algorithms typically uses a technique known as von Neumann analysis. For a given algorithm, application of the technique yields both a dispersion relation valid for the discrete time-space grid and a mathematical condition for stability. In practice, a major shortcoming of conventional von Neumann analysis is that it can be applied only to an idealized numerical model - that of an infinite, homogeneous whole space. Experience has shown that numerical instabilities often arise in finite-difference simulations of wave propagation at interfaces with strong material contrasts. These interface instabilities occur even though the conventional von Neumann stability criterion may be satisfied at each point of the numerical model. To address this issue, I generalize von Neumann analysis for a model of two half-spaces. I perform the analysis for the case of acoustic wave propagation using a standard staggered-grid finite-difference numerical scheme. By deriving expressions for the discrete reflection and transmission coefficients, I study under what conditions the discrete reflection and transmission coefficients become unbounded. I find that instabilities encountered in numerical modeling near interfaces with strong material contrasts are linked to these cases and develop a modified stability criterion that takes into account the resulting instabilities. I test and verify the stability criterion by executing a finite-difference algorithm under conditions predicted to be stable and unstable. ?? 2007 Society of Exploration Geophysicists.

Geophysics↗
USGS2021

The impact of 3D finite‐fault information on ground‐motion forecasting for earthquake early warning

We identify aspects of finite‐source parameterization that strongly affect the accuracy of estimated ground motion for earthquake early warning (EEW). EEW systems aim to alert users to impending shaking before it reaches them. The U.S. West Coast EEW system, ShakeAlert, currently uses two algorithms based on seismic data to characterize the earthquake’s location, magnitude, and origin time, treating it as a point or line source. From this information, ShakeAlert calculates shaking intensity and alerts locations where shaking estimates exceed a threshold. Several geodetic EEW algorithms under development would provide 3D finite‐fault information. We investigate conditions under which this information produces sufficiently better intensity estimates to potentially improve alerting. Using scenario crustal and subduction interface sources, we (1) identify the most influential source geometry parameters for an EEW algorithm’s shaking forecast, and (2) assess the intensity alert thresholds and magnitude ranges for which more detailed source characterization affects alert accuracy. We find that alert regions determined using 3D‐source representations of correct magnitude and faulting mechanism are generally more accurate than those obtained using line sources. If a line‐source representation is used and magnitude is calculated from the estimated length, then incorrect length estimates significantly degrade alert region accuracy. In detail, the value of 3D‐source characterization depends on the user’s chosen alert threshold, tectonic regime, and faulting style. For the suite of source models we tested, the error in shaking intensity introduced by incorrect geometry could reach levels comparable to the intrinsic uncertainty in ground‐motion calculations (e.g., 0.5–1.3 modified Mercalli intensity [MMI] units for MMI 4.5) but, especially for crustal sources, was often less. For subduction interface sources, 3D representations substantially improved alert area accuracy compared to line sources, and incorrect geometry parameters were more likely to cause error in calculated shaking intensity that exceeded uncertainties.

Bulletin of the Seismological Society of America↗
USGS2025

ShakeAlert® version 3: Expected performance in large earthquakes

The ShakeAlert earthquake early warning (EEW) system partners along with U.S. Geological Survey (USGS) licensed operators deliver EEW alerts to the public and trigger automated systems when a significant earthquake is expected to impact California, Oregon, or Washington. ShakeAlert’s primary goal is to provide usable warning times before the arrival of damaging shaking. EEW is most likely to achieve this goal in large‐magnitude earthquakes. In recent years, ShakeAlert has gone through a series of upgrades to its underlying scientific algorithms aimed at improved performance during large earthquakes. Version 3 of this software recently went live in the production system and includes improvements to all algorithms. The main seismic algorithms that detect an earthquake and characterize its location, magnitude, and fault rupture orientation are faster than older versions. Other key changes include: using real‐time geodetic data to characterize the magnitude growth in large earthquakes; the introduction of an alert pause procedure to compromise between speed near the epicenter and improved accuracy at larger distances; and the inclusion of a nonergodic site‐response model in the ground‐motion predictions. ShakeAlert has achieved its primary goal of usable warning times before strong shaking at some locations in real‐time operations in recent M 6 earthquakes. Using offline tests, we demonstrate usable warning times are possible for many sites with peak shaking values of modified Mercalli intensity (MMI) 7–8 in M 7+ earthquakes and also for many MMI 8–9 sites in M 8+ earthquakes. ShakeAlert partners use a variety of MMI and magnitude thresholds in deciding when to alert their users within bounds set by the USGS. Our study shows that there is room to raise the magnitude thresholds up to about M 5.5 without adversely affecting performance in large earthquakes. The ground‐motion criteria are more complex owing to a significant drop‐off in warning times between the MMI 4 and 5 levels of predicted shaking. However, widely used ShakeAlert products, such as the MMI 3 and 4 contour products, can provide sufficiently long warning times before strong shaking in moderate‐to‐great earthquakes to enable a range of protective actions.

Bulletin of the Seismological Society of America↗
USGS2018

Sensor suite: The Albuquerque Seismological Laboratory Instrumentation Testing Suite

To standardize parameters used in seismometer testing and calibration and to make these algorithms accessible to the seismological community, we have developed a new seismometer testing software package called Albuquerque Seismological Laboratory (ASL) Sensor Test Suite. This software is written in Java and makes use of Seismological Exchange for Earthquake Data (SEED) format. Our goal is not to be all‐inclusive but instead to focus on a few of the instrumentation tests we view as critical when verifying a sensor’s performance. The tests include self‐noise, relative azimuth, relative gain, and estimation of the poles and zeros. For the self‐noise and the relative azimuth, we also include three‐component versions of these tests to allow for the case of sensors with potentially different orientations (e.g., boreholes). The software has been made available on GitHub with the hope that it will be useful for other seismologists who need to quickly verify various sensor parameters without having to write their own versions of the algorithms. Furthermore, by using a common platform and processing algorithms, it becomes possible to compare results among different tests with similar processing methods being used for both.

Seismological Research Letters↗
USGS2019

Characterizing seismogenic fault structures in Oklahoma using a relocated template matched catalog

Oklahoma is one of the most seismically active places in the United States as a result of industry activities. In order to characterize the fault networks responsible for these earthquakes in Oklahoma, we relocated a large-scale template matching catalog between 2010-2016 using the GrowClust algorithm . This relocated catalog is currently the most complete statewide catalog for Oklahoma during this seven-year window. Using this relocated catalog, we identified seismogenic fault segments by developing an algorithm that clusters earthquakes and then identifies linear trends within each cluster. Considering the large number of earthquakes in Oklahoma, this algorithm made the process of identifying previously unmapped seismogenic faults more approachable and objective. We identify approximately 2500 seismogenic fault segments which are in general agreement with focal mechanisms and optimally oriented relative to maximum principle stress measurements. We demonstrate that these fault orientations can be used to approximate the maximum principle stress orientations.

Oklahoma↗