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USGS2023

Strength recovery in quartzite is controlled by changes in friction in experiments at hydrothermal conditions up to 200°C

The rate of fault zone restrengthening between earthquakes can be influenced by both frictional and cohesive healing processes. Friction is dependent on effective normal stress while cohesion is independent of normal stress, potentially explaining—in part—the lack of depth dependence of earthquake stress drops. Although amenable to laboratory testing, few studies have systematically addressed the normal stress dependence of restrengthening rate. This is partially due to difficulty in separating relative contributions of friction and cohesion in recovery of fault strength. We present results from a series of slide-hold-slide tests on thin layers (≤10 𝜇m) of ultrafine quartz gouge that develop during shearing of initially bare-surface quartzite. Tests were conducted at 10 MPa constant pore pressure, 20–200 MPa constant effective normal stress, and temperatures of 22°–200°C. Restrengthening, defined as the difference between peak shear stress measured after resumption of sliding and steady-state sliding shear stress, increases with the log of hold duration. The 200°C healing rate, 0.014 per e-fold increase in time, is comparable to that determined from seismological observations along the Calaveras Fault, California. Construction of Mohr-Coulomb failure envelopes shows that changes in cohesion are small (<1 MPa) and independent of hold durations to 10 5 s, indicating that the increased strength is due to changes in the friction coefficient. These experimental results are inconsistent with the hypothesis that cohesive healing explains the depth independence of earthquake stress drop, but higher temperatures, longer time-scales, and more complex mineralogy could facilitate cohesive healing in natural fault systems.

Journal of Geophysical Research - Solid Earth↗

USGS2023

High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia

During a volcanic crisis, high-rate, localized deformation can indicate magma close to the surface, with important implications for eruption forecasting. However, only a few such examples have been reported, because frequent, dense monitoring is needed. High-resolution Synthetic Aperture Radar (SAR) is capable of achieving <1 m spatial resolution and sub-weekly revisit times, but is under-used. Here we use high-resolution satellite SAR imagery from COSMO-SkyMed, TerraSAR-X, and Sentinel-1 to detect intra-crater uplift preceding the November 2017 onset of eruptive activity at Agung, Indonesia. Processing the SAR imagery with an up-to-date, accurate, high-resolution digital elevation model was crucial for preventing aliasing of the deformation signal and for accurate georeferencing. We show that >15 cm of line-of-sight shortening occurred over a 400-by-400 m area on the crater floor in September-October 2017, accompanying a deep seismic swarm and flank dyke intrusion. We attribute the deformation to the pressurization of a shallow (<200 m deep) hydrothermal system by the injection of magmatic gases and fluids. We also observe a second pulse of intra-crater deformation of 3–5 cm within 4 days to 11 hr prior to the first phreatomagmatic eruption, which is consistent with interaction between the hydrothermal system and the ascending magma. This phreatomagmatic eruption created the central pathway used during the final stages of magma ascent. Our observations have important implications for understanding unrest and eruption forecasting, and demonstrate the potential of monitoring with high-resolution SAR.

Agung Volcano, Bali↗

USGS2023

Identification of seismo-volcanic regimes at Whakaari/White Island (New Zealand) via systematic tuning of an unsupervised classifier

We present an algorithm based on Self-Organizing Maps (SOM) and k-means clustering to recognize patterns in a continuous 12.5-year tremor time series recorded at Whakaari/White Island volcano, New Zealand (hereafter referred to as Whakaari). The approach is extendable to a variety of volcanic settings through systematic tuning of the classifier. Hyperparameters are evaluated by statistical means, yielding a combination of “ideal” SOM parameters for the given data set. Extending from this, we applied a Kernel Density Estimation approach to automatically detect changes within the observed seismicity. We categorize the Whakaari seismic time series into regimes representing distinct volcano-seismic states during recent unrest episodes at Whakaari (2012/2013, 2016, and 2019). There is a clear separation in classification results between background regimes and those representing elevated levels of unrest. Onset of unrest is detected by the classifier 6 weeks before the August 2012 eruption, and ca. 3.5 months before the December 2019 eruption, respectively. Regime changes are corroborated by changes in commonly monitored tremor proxies as well as with reported volcanic activity. The regimes are hypothesized to represent diverse mechanisms including: system pressurization and depressurization, degassing, and elevated surface activity. Labeling these regimes improves visualization of the 2012/2013 and 2019 unrest and eruptive episodes. The pre-eruptive 2016 unrest showed a contrasting shape and nature of seismic regimes, suggesting differing onset and driving processes. The 2016 episode is proposed to result from rapid destabilization of the shallow hydrothermal system, while rising magmatic gases from new injections of magma better explain the 2012/2013 and 2019 episodes.

Whakaari, White Island↗

USGS2024

Observations of flocs in an estuary and implications for computation of settling velocity

The settling velocity ( w s ) in estuarine environments can impact whether a region is eroding or accreting sediment on the bed, yet determining this rate can be an indirect process requiring a number of assumptions. Accurate determination of w s is especially needed for numerical models to reproduce observed sediment concentrations at the appropriate timescale. We collected information on suspended sediment flocculation at a channel site (13 m deep) and a shallows site (4 m deep) within South San Francisco Estuary, alongside timeseries of flow, wave statistics, turbulent shear, and bottle samples analyzed for both w s and particle size. Using the measurements of floc size and settling velocity, we performed a sensitivity analysis on the unknown parameters in the general explicit formula for settling velocity. The collected particle size distribution data show that multiple classes of flocs are present; these are characterized as flocculi, microflocs, and macroflocs. We show that w s of flocculi is closest to w s for the full distribution. The determined parameter values lead to near-bed mass-weighted settling velocities (standard deviation) of 1.18 (0.55) and 0.22 (0.15) mm/s at the channel and shallows sites, respectively. Modeling efforts can use this work to help select an appropriate sediment model and parameter values.

California↗

USGS2023

Flow development and entrainment in turbulent particle-laden jets

Explosive eruptions expel volcanic gases and particles at high pressures and velocities. Within this multiphase fluid, small ash particles affect the flow dynamics, impacting mixing, entrainment, turbulence, and aggregation. To examine the role of turbulent particle behavior, we conducted an analogue experiment using a particle-laden jet. We used compressed air as the carrier fluid, considering turbulent conditions at Reynolds numbers from approximately 5,000 to 20,000. Two different particles were examined: 14-μm diameter solid nickel spheres and 13-μm diameter hollow glass spheres. These resulted in Stokes numbers between 1 and 35 based on the convective scale. The particle mass percentage in the mixture is varied from 0.3% to more than 20%. Based on a 1-D volcanic plume model, these Stokes numbers and mass loadings corresponded to millimeter-scale particle diameters at heights of 4–8 km above the vent during large, sustained eruptions. Through particle image velocimetry, we measured the mean flow behavior and the turbulence statistics in the near-exit region, primarily focusing on the dispersed phase. We show that the flow behavior is dominated by the particle inertia, with high Stokes numbers reducing the entrainment by more than 40%. When applied to volcanic plumes, these results suggest that high-density particles can greatly increase the probability of column collapse.

Journal of Geophysical Research: Atmospheres↗

USGS2022

Multi-stage soil-hydraulic recovery and limited ravel accumulations following the 2017 Nuns and Tubbs wildfires in Northern California

Wildfire can impact soil-hydraulic properties by reducing saturated hydraulic conductivity and sorptivity, making recently burned landscapes prone to debris flows and flash floods. The post-fire hazard window can range from years to decades. In Northern California, where wildfire frequency is steadily increasing, the impact and soil-hydraulic recovery from wildfires is unknown. Following the October 2017 Nuns and Tubbs fires in the Northern Bay Area of California, we established 41 monitoring sites for repeat tension-disc infiltrometer measurements of field-saturated hydraulic conductivity ( K fs ) over 3.5 years. Our site arrays, which encompass grasslands, chaparral, and oak and conifer forests across a range in lithology, show a marked decrease in K fs following the wildfires and a swift partial recovery following the initial post-fire rainy season. Our time series reveals a complex path to soil-hydraulic recovery marked by distinct seasonal stages. Analysis of changing K fs , sorptivity, and infiltration model residuals collectively suggests that these stages are related to transitions between soil-hydraulic processes like structural soil sealing from rainsplash, thermal cracking of bare soil, and vegetation regrowth. While soil infiltration rates were strongly impacted by the 2017 fires, dry ravel estimates are an order of magnitude less for similar slopes than the 2009 Station fire in the San Gabriel mountains of Southern California, suggesting that limited ravel flux may insufficiently load channels for debris flows that initiate from within-channel failure. Our analysis suggests that burned landscapes in the Northern Bay Area of California may experience rapid soil-hydraulic recovery and limited pathways toward post-fire debris flow initiation.

California↗

USGS2022

Can lava flow like water? Assessing applications of critical flow theory to channelized basaltic lava flows

Flowing lava and water have dramatically different physical properties but can form similar hydraulic structures, including undular hydraulic jumps, or standing wave trains. In water flows, undular hydraulic jumps are evidence of critical flow (Froude number ∼1) and open-channel hydraulic theory provides a powerful tool for estimating flow depth and velocity. Monitoring these parameters in an active lava channel is inherently challenging, but essential for calculating lava discharge (effusion rate), a primary control on the rate of flow front advance and ultimate flow runout distance. We analyze undular hydraulic jumps in both water and lava flows to assess the conditions under which they form and, by extension, the potential use of critical flow theory to estimate, in real time, lava flow velocity, depth, and discharge. Experimental data for water flows show that these structures mark the transition from supercritical to subcritical flow. Undular hydraulic jumps in the near-vent lava channel of the 2018 lower East Rift Zone eruption of Kīlauea, Hawaiʻi also reflect critical flow conditions; their wavelengths scale with flow depth and velocity, consistent with hydraulic theory. Calculated lava effusion rates are similar to estimates made using more traditional approaches (Jeffreys', 1925, https://doi.org/10.1080/14786442508634662 , equation based on lava viscosity, density, and channel slope) and with lava volumes derived from topographic-change mapping. From this we conclude that critical flow phenomena show great potential to track flow dynamics and inform hazard assessment for a wide range of geophysical fluids.

Journal of Geophysical Research - Earth Surface↗

USGS2023

Time-lapse seafloor surveys reveal how turbidity currents and internal tides in Monterey Canyon interact with the seabed at centimeter-scale

Here we show how ultra-high resolution seabed mapping using new technology can help to understand processes that sculpt submarine canyons. Time-lapse seafloor surveys were conducted in the axis of Monterey Canyon, ∼50 km from the canyon head (∼1,840 m water depth) over an 18-month period. These surveys comprised 5-cm resolution multibeam bathymetry, 1-cm resolution lidar bathymetry, and 2-mm resolution stereophotographic imagery. Bathymetry data reveal centimeter-scale textures that would be undetectable by more traditional survey methods. Upward-looking Acoustic Doppler Current Profilers at the site recorded the flow character of internal tides and the passage of three turbidity currents, while sediment cores collected from the site record flow deposits. Combined with flow and core data, the bathymetry shows how turbidity currents and internal tides modify the seabed. The turbidity currents drape sediment across the site, infilling bedform troughs and smoothing erosional features carved by the internal tides (e.g., rippled scours). Turbidity currents with speeds of 0.9–3.3 m/s failed to cause notable bedform movement, which is surprising given that flows with similar speeds produced rapid bedform migration elsewhere, including the upper Monterey Canyon. The lack of migration may be related to the character of the underlying substrate or indicate that turbidity currents at the site lack dense, near-bed layers. The scale of scours produced by the internal tides (≤0.7 m/s) approaches the scale of features recorded in the ancient rock record. Thus, these results illustrate how the scale gap between seabed mapping technology and the rock record may eventually be bridged.

California↗

USGS2023

Mapping landslide susceptibility over large regions with limited data

Landslide susceptibility maps indicate the spatial distribution of landslide likelihood. Modeling susceptibility over large or diverse terrains remains a challenge due to the sparsity of landslide data (mapped extent of known landslides) and the variability in triggering conditions. Several different data sampling strategies of landslide locations used to train a susceptibility model are used to mitigate this challenge. However, to our knowledge, no study has systematically evaluated how different sampling strategies alter a model's predictor effects (i.e., how a predictor value influences the susceptibility output) critical to explaining differences in model outputs. Here, we introduce a statistical framework that examines the variation in predictor effects and the model accuracy (measured using receiver operator characteristics) to highlight why certain sampling strategies are more effective than others. Specifically, we apply our framework to an array of logistic regression models trained on landslide inventories collected at sub-regional scales over four terrains across the United States. Results show significant variations in predictor effects depending on the inventory used to train the models. The inconsistent predictor effects cause low accuracies when testing models on inventories outside the domain of the training data. Grouping test and training sets according to physiographic and ecological characteristics, which are thought to share similar triggering mechanisms, does not improve model accuracy. We also show that using limited landslide data distributed uniformly over the entire modeling domain is better than using dense but spatially isolated data to train a model for applications over large regions.

California, Kentucky, North Carolina, West Virgini↗

USGS2022

The influence of drying on the aeolian transport of river-sourced sand

Transgression and regression of water levels (stages) have impacted the evolution of aeolian landforms and sedimentary deposits throughout geologic history. We studied this phenomenon over a five-day period of reduced flow on the Colorado River in Grand Canyon National Park, AZ, USA, in March 2021. These transient low flows exposed river-channel sand deposits to the air, causing progressive desiccation (drying) and thereby making these deposits susceptible to aeolian transport. We measured aeolian threshold friction velocities ( u *t ) for sand saltation and PM10 dust emissions, as well as other characteristics, on a subaerially exposed sandbar and downwind aeolian dunefield during each day of the low river flow. The sandbar transitioned from supply-limited to transport-limited aeolian sediment transport conditions during the regression in river water stage. A possible tipping point between the two transport conditions occurred approximately 48 hours after the drop in river flow. The empirically measured u *t decreased as the sandbar sediment dried with increased subaerial exposure time. Theoretical estimates and empirical measurements of u *t corresponded closely on the aeolian dunefield and on the sandbar when it was drier during the third and fourth day of the experiment. Eighty-seven percent of the variability in u *t was explained by empirical models that provide practical estimates of aeolian transport potential of subaerial river sediment deposits using monitoring data that are commonly available in this and other river systems. The work provides theoretical insight into the response of aeolian processes to sediment supply changes driven by periods of anthropogenic activity, drought, and climate change.

Arizona↗

USGS2023

Impacts of spontaneous waterfall development on bedrock river longitudinal profile morphology

River profiles are shaped by climatic and tectonic history, lithology, and internal feedbacks between flow hydraulics, sediment transport and erosion. In steep channels, waterfalls may self-form without changes in external forcing (i.e., autogenic formation) and erode at rates faster or slower than an equivalent channel without waterfalls. We use a 1-D numerical model to investigate how self-formed waterfalls alter the morphology of bedrock river longitudinal profiles. We modify the standard stream power model to include a slope threshold above which waterfalls spontaneously form and a rate constant allowing waterfalls to erode faster or slower than other fluvial processes. Using this model, we explore how waterfall formation alters both steady state and transient longitudinal profile forms. Our model predicts that fast waterfalls create km-scale reaches in a dynamic equilibrium with channel slope held approximately constant at the threshold slope for waterfall formation, while slow waterfalls can create local channel slope maxima at the location of slow waterfall development. Furthermore, slow waterfall profiles integrate past base level histories, leading to multiple possible profile forms, even at steady-state. Consistency between our model predictions and field observations of waterfall-rich rivers in the Kings and Kaweah drainages in the southern Sierra Nevada, California, supports the hypothesis that waterfall formation can modulate river profiles in nature. Our findings may help identify how bedrock channels are influenced by waterfall erosion and aid in distinguishing between signatures of external and internal perturbations, thereby strengthening our ability to interpret past climate and tectonic changes from river longitudinal profiles.

Journal of Geophysical Research - Earth Surface↗

USGS2022

A model of the spatiotemporal dynamics of soil carbon following coastal wetland loss applied to a Louisiana salt marsh in the Mississippi River Deltaic Plain

The potential for carbon sequestration in coastal wetlands is high due to protection of carbon (C) in flooded soils. However, excessive flooding can result in the conversion of the vegetated wetland to open water. This transition results in the loss of wetland habitat in addition to the potential loss of soil carbon. Thus, in areas experiencing rapid wetland submergence, such as the Mississippi River Delta, coastal wetlands could become a significant source of carbon emissions if land loss is not mitigated. To accurately assess the capacity of wetlands to store (or emit) carbon in dynamic environments, it is critical to understand the fate of soil carbon following the transition from vegetated wetland to open water. We developed a simple soil carbon model representing soil depths to 1 m using the data collected from a Louisiana coastal salt marsh in the Mississippi River Deltaic Plain to predict soil carbon density and stock following the transition from a vegetated salt marsh to an open water pond. While immediate effects of ponding on the distribution of carbon within the 1-m soil profile were apparent, there were no effects of ponding on the overall, integrated, carbon stocks 14 years, following wetland submergence. Rather, the model predicts that soil carbon losses in the first meter will be realized over long periods of time (∼200 years) due to changes in the source of carbon (biomass vs. mineral sediment) with minimal losses through mineralization.

Louisiana↗

USGS2022

A process-model perspective on recent changes in the carbon cycle of North America

Continental North America has been found to be a carbon (C) sink over recent decades by multiple studies employing a variety of estimation approaches. However, several key questions and uncertainties remain with these assessments. Here we used results from an ensemble of 19 state-of-the-art dynamic global vegetation models from the TRENDYv9 project to improve these estimates and study the drivers of its interannual variability. Our results show that North America has been a C sink with a magnitude of 0.37 ± 0.38 (mean and one standard deviation) PgC year −1 for the period 2000–2019 (0.31 and 0.44 PgC year −1 in each decade); split into 0.18 ± 0.12 PgC year −1 in Canada (0.15 and 0.20), 0.16 ± 0.17 in the United States (0.14 and 0.17), 0.02 ± 0.05 PgC year −1 in Mexico (0.02 and 0.02) and 0.01 ± 0.02 in Central America and the Caribbean (0.01 and 0.01). About 57% of the new C assimilated by terrestrial ecosystems is allocated into vegetation, 30% into soils, and 13% into litter. Losses of C due to fire account for 41% of the interannual variability of the mean net biome productivity for all North America in the model ensemble. Finally, we show that drought years (e.g., 2002) have the potential to shift the region to a small net C source in the simulations (−0.02 ± 0.46 PgC year −1 ). Our results highlight the importance of identifying the major drivers of the interannual variability of the continental-scale land C cycle along with the spatial distribution of local sink-source dynamics.

Journal of Geophysical Research Biogeosciences↗

USGS2023

Variation in leaf reflectance spectra across the California flora partitioned by evolutionary history, geographic origin, and deep time

Evolutionary relatedness underlies patterns of functional diversity in the natural world. Hyperspectral remote sensing has the potential to detect these patterns in plants through inherited patterns of leaf reflectance spectra. We collected leaf reflectance data from across the California flora from plants grown in a common garden. Regions of the reflectance spectra vary in the depth and strength of phylogenetic signal. We also show that these differences are much greater than variation due to the geographic origin of the plant. At the phylogenetic extent of the California flora, spectral variation explained by the combination of ecotypic variation (divergent evolution) and convergent evolution of disparate lineages was minimal (3 to 7 %) but statistically significant. Interestingly, at the extent of a single genus ( Arctostaphylos ) no unique variation could be attributed to geographic origin. However, up to 18% of the spectral variation among Arctostaphylos individuals was shared between phylogeny and intraspecific variation stemming from ecotypic differences (i.e., geographic origin). Future studies could conduct more structured experiments (e.g., transplants or observations along environmental gradients) to disentangle these sources of variation and include other intraspecific variation (e.g., plasticity). We constrain broad scale spectral variability due to ecotypic sources, providing further support for the idea that phylogenetic clusters of species might be detectable through remote sensing. Phylogenetic clusters could represent a valuable dimension of biodiversity monitoring and detection.

California↗

USGS2024

Reply to comment on "Five decades of observed daily precipitation reveal longer and more variable drought events across much of the western United States"

Paciorek and Wehner raise important questions around our use of the Mann-Kendall nonparametric trend test on smoothed data for analyzing long-term hydrometeorological trends in Zhang et al. (2021, https://doi.org/10.1029/2020gl092293 ). We thank them for initiating this important conversation and their gracious cooperation in exploring the issues addressed in their comment. In this reply we confirm the inflation of significant p -values by our choice to smooth, illustrate the relatively minor impacts on the main conclusions of our paper, and add our voices to those of Paciorek and Wehner in highlighting the lack of methodology for hypothesis testing across multiple stations that have spatial structure (i.e., testing for regionally consistent trends).

western United States↗

USGS2023

Accuracy of finite fault slip estimates in subduction zone regions with topographic Green's functions and seafloor geodesy

Until recently, the lack of seafloor geodetic instrumentation and the use of unrealistically simple, half-space based forward models have resulted in poor resolution of near-trench slip in subduction zone settings. Here, we use a synthetic framework to investigate the impact of topography and geodetic data distribution on coseismic slip estimates in various subduction zone settings. We calculate surface displacements in two synthetic topographic domains that have topography similar to that of Chile and Japan, respectively. We then attempt to image target slip distributions by using a Bayesian approach to solve for slip with two sets of Green's functions—one that accounts for topography and one that does not—and five sets of 50 or more observation points selected from the synthetic surface displacements. Three of these sets of observation points are entirely onland, and two include 5–10 seafloor geodetic sites. We find that the use of topographic Green's functions always improves inferred slip models, and with seafloor geodetic data, it enables an almost perfect recovery of a target slip model, even in the near-trench region. Critically, our results demonstrate that it would be impossible for non-topographic Green's functions to properly recover the true slip distribution, particularly in the near-trench region. We also perform a parameter study with approximately 4,000 slip models estimated using a least-square approach, and find that topographic Green's functions yield significantly more accurate slip models in cases where good data (well distributed and reasonably dense) are available, even in the absence of seafloor geodetic sites.

Journal of Geophysical Research: Solid Earth↗

USGS2023

Pre-eruptive outgassing and pressurization, and post-fragmentation bubble nucleation, recorded by vesicles in breadcrust bombs from vulcanian activity at Guagua Pichincha Volcano, Ecuador

Breadcrust bombs formed during Vulcanian eruptions are assumed to originate from the shallow plug or dome. Their rim to core texture reflects the competition between cooling and degassing timescales, which results in a dense crust with isolated vesicles contrasting with a highly vesicular vesicle network in the interior. Due to relatively fast quenching, the crust can shed light on pre- and syn-eruptive conditions prior to or during fragmentation, whereas the interior allows us to explore post-fragmentation vesiculation. Investigation of pre- to post-fragmentation processes in breadcrust bombs from the 1999 Vulcanian activity at Guagua Pichincha, Ecuador, via 2D and 3D textural analysis reveals a complex vesiculation history, with multiple, spatially localized nucleation and growth events. Large vesicles (Type 1), present in low number density in the crust, are interpreted as pre-eruptive bubbles formed by outgassing and collapse of a permeable bubble network during ascent or stalling in the plug. Haloes of small, syn-fragmentation vesicles (Type 2), distributed about large vesicles, are formed by pressurization and enrichment of volatiles in these haloes. The nature of the pressurization process in the plug is discussed in light of seismicity and ground deformation signals, and previous textural and chemical studies. A third population (Type 3) of post-fragmentation small vesicles appears in the interior of the bomb, and growth and coalescence of Type 2 and 3 vesicles causes the transition from isolated to interconnected bubble network in the interior. We model the evolution of viscosity, bubble growth rate, diffusion timescales, bubble radius and porosity during fragmentation and cooling. These models reveal that thermal quenching dominates in the crust whereas the interior undergoes a viscosity quench caused by degassing, and that the transition from crust to interior corresponds to the onset of percolation and development of permeability in the bubble network.

Guagua Pichincha Volcano↗

USGS2023

Quantifying site effects and their influence on earthquake source parameter estimations using a dense array in Oklahoma

We investigate the effects of site response on source parameter estimates using earthquakes recorded by the LArge-n Seismic Survey in Oklahoma (LASSO). While it is well known that near-surface unconsolidated sediments can cause an apparent breakdown of earthquake self-similarity, the influence of laterally varying site conditions remains unclear. We analyze site conditions across the 1825-station array on a river plain within an area of 40 km by 23 km using vertical ground motions from 14 regional earthquakes. While the source radiation pattern controls P-wave ground motions below 8 Hz, the surface geology correlates with P-wave ground motions above 8 Hz and S-wave ground motions at 2–21 Hz. Stations installed in alluvial sediments have vertical ground motions that can exceed three times the array median. We use the variation of ground motion of regional earthquakes across the array as a proxy for site effects. The corner frequencies and stress drops of local earthquakes ( M L = 0.01–3) estimated using a standard single-spectra approach show negative correlations with the site-effect proxy, while the seismic moments show positive correlations. In contrast, the spectral-ratio approach effectively shows no correlation. The overall bias is small as expected for this relatively homogeneous structure; accurate estimation of site-related biases requires at least 30 stations. Correcting for site-related biases reduces the standard deviations of the source parameters by less than 13% of the total variations. Remaining variations are partially associated with source directivity and model misfits— as small earthquakes can have complex ruptures.

Oklahoma↗