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Fully contained laboratory earthquakes: The effect of asperity aspect ratio and free surfaces

Corner frequency ( f c ) and seismic moment ( M 0 ) are key parameters derived from seismic signals that are used to characterize earthquake stress drop, rupture area, and slip. These parameters are also affected by fault geometry and boundary conditions. However, the systematic study of these effects in laboratory settings has been challenging. This study presents laboratory earthquake experiments that examine how rupture dynamics are influenced by (a) the aspect ratio of rectangular PMMA velocity-weakening (VW) asperities surrounded by the Teflon velocity-strengthening (VS) patches, and (b) whether the sides of a VW asperity are confined with VS patches or are free surfaces. We found that increasing confinement by reducing free surfaces or increasing the VW asperity aspect ratio stabilizes fault slip, so that higher normal stress is required to transition from aseismic to seismic slip. Increased confinement and high aspect ratios also reduced M 0 and increased f c , both of which were determined from the radiated seismic waves. M 0 and f c were primarily controlled by the shorter dimension of the VW asperity. Analysis of high-frequency acoustic emission signals revealed that ruptures on high-aspect-ratio VW asperities propagated more unidirectionally, whereas ruptures on square VW asperities were more complex. Further, the high-aspect-ratio asperities were more likely to be eroded by surrounding VS regions while low-aspect-ratio asperities were more likely to rupture into the VS surroundings. These results demonstrate that both the confinement from surrounding stable areas and the geometry of the seismogenic patch can affect rupture nucleation, propagation, and seismic source characteristics.

JGR Solid Earth

To heal or not to heal?: 1. The effect of pore fluid pressure on the frictional healing behavior of lithologies in Oklahoma

The competition between fault healing (i.e., re-strengthening) and fault loading determines the timing and magnitude of fault failure within the seismic cycle. Repeating earthquakes can give observational estimates of fault healing rates, however, it is difficult to link laboratory studies of frictional healing and observed healing rates from repeating earthquakes in part because of uncertainty in lithology at depth. Due to well-constrained and relatively simple geology, earthquakes in Oklahoma can be linked to the granitic basement rock and to the Arbuckle Group, which is primarily composed of dolomite at earthquake depths. Here, we conduct friction experiments to measure healing rates of the two earthquake-bearing lithologies at confining pressures representative of earthquake depths and pore pressures ranging from 0% to 80% of the confining pressure. We measure frictional healing by executing slide-hold-slide tests with hold times ranging from 3 s to 3000 s. The friction experiments on the Troy Granite indicate that pore fluid pressure does not greatly affect healing rate. On the other hand, the dolomite of the Arbuckle Group exhibits decreased healing with increased pore fluid pressure, with weakening at the highest pore pressure. We hypothesize that this is due to an increase in dissolution of dolomite at high pore pressures/low effective normal stress. These healing rates are used in the companion paper to understand the moment-recurrence time behavior of repeating earthquakes in Prague, Oklahoma. This work has implications for possible enhanced dissolution and weakening behavior of the Arbuckle Group during wastewater injection activities.

Oklahoma

Three-dimensional seismic velocity models for the San Francisco Bay region, California from joint body-wave and surface-wave tomography validated by waveform simulation

A high-resolution seismic velocity model for both P and S waves is essential for the San Francisco Bay (SFB) region to accurately simulate earthquake ground motions and assess seismic hazards in this high-risk region. We present new three-dimensional P-wave and S-wave velocity (Vp and Vs) models of the SFB region developed using joint tomographic inversion with a rich set of earthquake and active-source body-wave data and ambient-noise surface-wave data. We designed a dynamic balance strategy to effectively balance the contributions of body-wave and surface-wave data during each iteration of the inversion. Owing to the complementary resolution of body-wave and surface-wave data, our new models are significantly improved compared to previous tomographic models. Major geologic features in the SFB region, including low-velocity basins, high-velocity Franciscan Complex, granite, and gabbro rocks, and across-fault velocity contrasts, are imaged in our Vp and Vs models. Compared to the geology-based U.S. Geological Survey velocity model, our new model has better defined structures for some important areas that are of great concern for seismic hazard assessment, such as the Sacramento-San Joaquin Delta, and the 2014 magnitude 6.0 South Napa earthquake area. We validated our model by simulating waveforms for a set of moderate-magnitude earthquakes. The good performance of our model in waveform simulation indicates its potential for improving ground motion simulation and seismic hazard assessment in the SFB region.

California

Induced earthquakes are generally not tidally triggered in Oklahoma and Kansas

Human-induced earthquakes occur along critically stressed faults as injected wastewater simultaneously heightens fluid pressure and pushes faults to failure. We investigate the possibility that small stresses imposed by Earth tides could trigger earthquakes in the induced seismicity region of Oklahoma and Kansas from 2011 to 2018. We decluster a catalog consisting of ∼110,000 earthquakes using three methods (Reasenberg, nearest-neighbor distance, and phase-bin). We find no significant tidal earthquake triggering using Schuster's p -value test for the declustered catalogs as a whole. We search for localized triggering using discretized space-time cells and find ∼0–6% of cells have significant tidal triggering which is close to what is randomly expected (5%) and indicates there is an insignificant amount of tidal triggering for the full study region. One area that has significant p -values across multiple time windows, ∼2014–2016 is ∼15 km from a region of large wastewater injection volume. It is possible that localized tidal triggering occurs for this time and area because faults remain critically stressed and are particularly susceptible to slip under the small stress load from the semidiurnal tide. Possible explanations for the lack of tidal triggering in our broader study are that the pre-seismic stressing rate in the earthquake nucleation area is faster than the tidal stressing rate (∼3 kPa/day), faults are not close enough to critically stressed to be affected by tidal forcing, and that nucleation occurs over longer periods than the tides considered in this study (∼1, ∼14 days). Fluid injection could be the source of a higher pre-seismic stress rate.

Kansas, Oklahoma

From collision to subduction: Thermal-kinematic inversions constrain plate boundary structure and dip-slip activity in southwestern New Zealand

Constraints on three-dimensional fault system geometry and kinematics are required to understand both long-term tectonics and contemporary seismic hazard. In many cases, these parameters must be inferred from a combination of different data or analyses. Here, we invert low-temperature thermochronological data to quantitatively parameterize both the crustal-scale geometry and late Cenozoic dip-slip activity of the plate boundary system in southwest New Zealand. We find that the modern transpressive plate boundary system has accommodated the bulk of Australian-Pacific Plate convergence since establishment in the middle Miocene-early Pliocene. Shortening has occurred via (a) dextral-reverse slip on the moderate angle, listric central Alpine Fault décollement, and (b) reverse-slip on either the sharply curved, anti-listric northern Puysegur subduction interface or low-angle offshore thrust fault system that splays from the high-angle southern Alpine Fault at depth. We resolve late Cenozoic shortening rates on these structures that are indistinguishable, and interpret these to reflect the transfer of convergent deformation outboard of the predominantly strike-slip southern Alpine Fault. Our work helps elucidate the transition from strain localized oblique continental collision to strain partitioned subduction. We also provide an estimate of the across-strike width of the central-southern Alpine Fault section boundary at seismogenic depths. This is the first quantitative constraint on the geometry of a structural feature inferred to have arrested several major prehistoric earthquakes. This study furthers understanding of fault structure and dip-slip kinematics along the greatest sources of seismic hazard in and offshore of southwest New Zealand.

South Island

Multi-scale geophysical imaging of a hydrothermal system in Yellowstone National Park, USA

Little is known about the local plumbing systems that fuel Yellowstone’s famous hot springs, geysers and mud pots. A multi-method, multi-scale geophysical investigation was carried out in the Obsidian Pool Thermal Area (OPTA) to: (i) delineate the lateral extent of the hydrothermal area and associated surface features; (ii) estimate the dimensions of the upflow zone and identify its main controlling structures; (iii) assess fluids circulation pathways from depth to surface. Ground and airborne geophysical data were acquired to connect local and regional scales, from shallow to large depths. Maps of surface electrical resistivity show a strong correlation with hydrothermal features. At in-termediate depths, electrical resistivity permits delineating the upper limit of the upflow zone, while Poisson’s ratio highlights differences in subsurface fluid content. Combining these results with surface observations and topographic information, we speculate that differential mixing of hydrothermal and fresh water could explain the wide diversity of features observed at OPTA. Low electrical resistivity observed at large depths also suggest that a vast upflow zone, controlled by rhyolite flows and conjugate faults, underlies the OPTA. We speculate that hydrothermal fluids rise along fractures and reach the surface in topographic lows to form hydrothermal features. Our results show that synoptic, multi-scale geophysical measurements provide a roadmap for understanding where and how geologic heterogeneity, topography, fluid-gas separation, and the mixing of thermal and meteoric waters conspire to produce the wide variety of Yellowstone’s renowned hydrothermal features.

Wyoming

Interplay between tectonics and submarine mass transport deposits in Cortes Basin: New high-resolution geophysics in the Outer California Borderland

The Outer California Borderland (OCB) is an active transform plate boundary offshore Southern California, where the relationship between faulting and submarine mass transport deposits (MTDs) remains poorly understood. Onshore paleoseismic data provide high-resolution earthquake records, whereas marine geophysical data capture longer-term histories. Offshore fault systems pose hazards to infrastructure and dense coastal populations, particularly when linked to submarine landslides. We present new high-resolution geophysical data set (cruise SR2303), including bathymetric and CHIRP sub-bottom data integrated with legacy seismic reflection data and chronostratigraphic constraints from ODP Site 1012 to examine Quaternary MTD recurrence and tectonic controls in the Cortes Basin, OCB. Bathymetry shows deformational features, including slide scarps and previously unmapped fault segments with evidence of Holocene activity. CHIRP profiles reveal 10 stacked MTDs in the East Cortes Basin and 8 in the West Cortes Basin, spanning ∼752 ka with an average recurrence of ∼83.6 ± 1 ka. Acoustic imaging shows 7 MTD intervals coinciding with fault offset increments and fault growth suggesting earthquake-triggered mass wasting. A strong association between MTD occurrences and sea-level extremes also supports glacio-eustatic contribution to slope failure. Stratigraphic correlations suggest quasi-synchronous MTDs across the eastern and western areas, likely triggered by larger eathquakes in the Quaternary. Although the identified MTDs occur relatively far from the Southern California coast, they still pose a potential tsunamigenic hazard requiring further assessment. Moreover, if linked to earthquakes along major strike-slip faults, for example, the Ferrelo fault, the MTDs may provide valuable proxies to constrain rupture scenarios and fault connectivity within the understudied OCB.

California

Cajon Pass and the southern San Andreas Fault System: Earthquake cycle stress accumulation and present-day loading

With over a century since the last major rupture affecting the wider Los Angeles region, tectonic stress has steadily built along the southern San Andreas and San Jacinto fault systems, raising concerns of an imminent large earthquake. Cajon Pass, located at the junction of these faults, represents a critical site for potential through-going ruptures in Southern California. We constructed new 4D earthquake cycle simulations using a 1000-year paleoseismic rupture history of the San Andreas Fault System (SAFS) to assess spatial and temporal variations in stress. A semi-analytic Fourier transform model was used to compute stress from 3D dislocations in an elastic plate overlying a Maxwell viscoelastic half-space, assuming a complete coseismic reset of resolved shear stress on ruptured elements. Results show highest stress accumulation north of Cajon Pass (∼1.8 MPa/100 years) due to greater slip rates, and lower rates south of Cajon Pass (∼1.0–1.5 MPa/100 years). By 2025, Coulomb stress is estimated at 2.8 MPa on the Mojave South (MOS) segment, 1.8 MPa on the North San Bernardino (NSB1) segment and 3.6 MPa on the San Jacinto Bernardino (SJB) segment. Segments accumulate stresses with characteristic ranges of pre-event stress interpreted as failure thresholds: 1.2–2.7 MPa for MOS, 0.4–1.6 MPa for NSB1, and 1.2–2.9 MPa for SJB. When the stress disparity between segments SJB and MOS narrows, the faults appear to rupture jointly, suggesting that stress levels may control how Cajon Pass acts as an earthquake gate. These results may inform seismic hazard assessments by linking stress evolution to fault interactions.

California

Structural evolution and slip rate variations through time of the Puente-Hills blind-thrust fault beneath Los Angeles: Implications for seismic hazard and folding kinematics

Using seismic reflection profiles, historical well logging data, and luminescence and radiocarbon ages, we determine a Pleistocene-Holocene slip history for the central, Santa Fe Springs segment of the Puente Hills blind-thrust fault (PHT), a major seismogenic fault situated beneath the urbanized Los Angeles metropolitan region. We analyze the geometry of correlative stratigraphic units in the forelimb and backlimb of the overlying growth-fold, the Santa Fe Springs anticline, and determine the uplift of seven age-correlative markers. Uplift measurements are converted to thrust displacements on the underlying PHT using a structural method laid out by Don et al. (2022, https://doi.org/10.1785/0120220048 ) that accounts for the geometry of the fault. These data indicate that deep thrust displacement on the PHT is partially consumed updip in the creation of a hanging-wall fault-bend fold, with forelimb growth strata recording <80% of the slip documented within the backlimb. Chronological data from growth strata yield age constraints for folding and faulting on the underlying PHT, providing a detailed incremental slip history derived from both the forelimb and backlimb folding for seven discrete growth horizons, spanning the past 1.4 million years. The resulting six incremental slip rates demonstrate that fault slip has varied through time from the middle Pleistocene to the Holocene. Moreover, these results reveal synchronous acceleration of both the central, Santa Fe Springs and western, Los Angeles segments of the fault system since late Pleistocene time (after 200 ka) and slip rates of greater than 2 mm/yr on the downdip, backlimb, fault-ramp below the anticline.

California

Efficient physics‐informed ground‐motion simulations with reduced‐order models: CyberShake implications and high‐resolution site terms for southern San Andreas fault earthquakes

Recent advances in Probabilistic Seismic Hazard Analysis (PSHA) leverage physics‐based ground‐motion simulations to estimate seismic hazard, such as the CyberShake project. However, computational costs quickly escalate when performing PSHA for numerous faults or sites and can become prohibitively expensive. To reduce computational demands, CyberShake uses reciprocity and interpolates physics‐informed corrections from simulations conducted at fewer locations, but the accuracy of these interpolations remains poorly quantified. To quantify the interpolation accuracy, we derive high‐resolution, frequency‐dependent site terms for southern California and compare them with interpolated site terms using the CyberShake approach. We accomplish this by performing a set of earthquake point‐source simulations distributed along the nonplanar fault geometry for the southern San Andreas fault (SSAF) extending from Bombay Beach to Lake Hughes. Using SeisSol, we simulate three minutes of viscoelastic seismic wave propagation for these sources and store the horizontal‐component Green’s functions for 480,000 sites. We then use a scientific machine learning approach based on interpolated proper orthogonal decomposition to construct an accurate reduced‐order model of the Green’s functions to efficiently predict effective amplitude spectra (EAS) for finite‐source rupture models of SSAF earthquakes. Using minimum curvature interpolation with tension, as used in CyberShake, we compare the interpolated site terms against our high‐resolution site terms. We identify local discrepancies with EAS differing by up to a factor of approximately three. Furthermore, we identify locations where unexpectedly high or low ground motions are missed when using the interpolated dataset for these earthquakes. We estimate that our approach may be used within CyberShake to reduce the time‐to‐solution by a factor of 336 for the entire earthquake rupture forecast. Our analysis of physics‐based site terms provides more insight into the seismic hazard due to SSAF ruptures and guides future developments by combining high‐performance computing and reduced‐order modeling techniques for PSHA.

California

Implications of physics-based M9 ground motions on liquefaction-induced damage in the Cascadia Subduction Zone: Looking forward and backward

Given the likelihood of future M9 Cascadia Subduction Zone (CSZ) earthquakes, various estimates of the resulting, regional ground motions have been made, including a suite of 30 physics-based simulations that reflect key modeling uncertainties. However, because the last CSZ interface rupture occurred in 1700 CE, the shaking expected in such an event is especially uncertain, as are the impacts to the built and living environments. Like other coseismic impacts, soil liquefaction poses a significant threat and must be considered by any scenario study used to inform planning and response, or to focus mitigation resources. Liquefaction is also notable for its potential to “ground truth” ground-motion estimates, given that its presence or absence in the geologic record can provide constraint on the intensities of shaking in past events. It is thus an important phenomenon looking both forward and backward. Accordingly, using recent physics-based simulations, this study (1) predicts liquefaction in M9 CSZ ruptures at 400 locations in Oregon, Washington, and British Columbia (BC) using an array of cone-penetration-test based models and (2) uses paleoliquefaction evidence at ten sites spanning from Southern Oregon to Vancouver, BC to constrain possible ground-motion intensities experienced in the 1700 CE earthquake. The forward predictions indicate that liquefaction in M9 events could be pervasive in the region and affect numerous population hubs, with the potential for damage across hundreds of square kilometers. The backward analyses suggest that 1700 CE ground-motion intensities may have been less than expected from M9 simulations in some northern portions of the CSZ (e.g. Seattle), given the paucity of 1700 CE liquefaction evidence in these areas. Ultimately, further discovery and analysis of CSZ paleoliquefaction, or lack thereof, will confirm or modify this possibility and the conclusions drawn herein.

Oregon, Washington

Dietary bioavailability of uranium to a model freshwater invertebrate

Uranium (U) mining increases environmental exposures. Understanding how U is taken up by organisms can aid in evaluating the potential for bioaccumulation and toxicity. Although the importance of aqueous geochemical speciation is well recognized for U bioavailability after dissolved exposures, far less is known about the processes controlling U bioavailability after dietary exposures. This study characterizes the biogeochemical drivers of dietary U uptake in the freshwater snail Lymnaea stagnalis in laboratory experiments. Solids tested included benthic diatoms pre-exposed to dissolved U(VI), soils from contaminated U mine sites, and colloidal hydrous ferric oxide (HFO) synthesized in the presence of dissolved U(VI) or with U complexed by natural organic matter (NOM). Results showed that U was bioavailable from all solids. Uranium assimilation efficiency (AE), a proxy for dietary U bioavailability, varied among solids. AE was lowest for the U-contaminated soils (25 ± 17%) and highest for the U-laden diatoms (71 ± 13%). AE varied slightly among HFO preparations, suggesting modest influences of NOM and iron on U bioavailability. Increases in dietary U exposures reduced feeding rates, and the extent of feeding inhibition appeared inversely related to U bioavailability. The high U assimilation and range of bioavailability have implications for toxicity risks inferred without considering dietary uptake.

Environmental Science and Technology

Tephra from Kīlauea’s 2008–2018 lava lake eruption—Proximal deposits and dispersal characteristics

A network of ten buckets was established early in the 2008–2018 summit eruption at Kīlauea to collect proximal tephra ejected from the new, informally named the “Overlook crater”; the buckets were emptied on most days of the eruption thereafter. This report summarizes the results of more than 2,400 different sampling intervals (most 1–3 days long) during the eruption, focusing on the physical and dispersal characteristics of the tephra deposits. The network was within about 300 meters south of the vent to capture tephra dispersed by the dominant northeast trade wind. The juvenile tephra mainly reflected spattering at the southeast (SE) sink, a downwelling area in the southeastern part of the lava lake in the Overlook crater that remained in the same area throughout the eruption, with admixtures of solid rock and secondary minerals derived from the wall of the crater. The proportion of juvenile material to lithic material ranged widely early in the eruption but was generally greater than 90 percent for the last 6 years of the eruption as lake level rose and the crater walls decreased in height and became more stable. The accumulation rate of tephra at each bucket was strongly dependent on the location of the bucket and reflects the interplay between lava lake level and wind direction and speed. The mass per unit area (m/a) of collected tephra was a maximum of about 97 kilograms per square meter for the entire eruption, equivalent to a thickness of about 75 millimeters. Thirty-two explosive events with a volcanic explosivity index of −2 to −4 deposited much of the tephra in the network. Fifteen of these rock-fall-induced events occurred within 6 days of one another. Pele’s hair, a volcanic glass predominantly associated with quieter activity at the vent in the final half of the eruption, was dispersed more than 60 kilometers downwind from the lava lake and formed a nearly continuous deposit near the Overlook crater. This eruption was probably the most frequently sampled long-lasting eruption in history, but most of the deposits are ephemeral. The collected samples, although generally of small mass, are retained by the Hawaiian Volcano Observatory and are available for detailed study.

Hawaii

Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites: Insights from deep learning

We developed a suite of models using deep learning to make hindcast predictions of the 7‐day average backward‐looking nitrate concentration at 46 predominantly agricultural sites across the midwestern and eastern United States. The models used daily observations of discharge and meteorological variables and watershed attributes describing anthropogenic modification to hydrology, nitrogen application, climate, groundwater, land use, watershed physiographic attributes, and soils. Across all sites, discharge and watershed soil and physiographic attributes showed a strong influence on model performance. Analysis of drivers across sites revealed considerable regional differences related to controlling processes such as groundwater contributions. We tested several ways to pool data across sites to develop accurate models and make the most effective use of available data. Single‐site models, in which models are trained and tested at a single location, showed generally strong predictive performance (median Kling‐Gupta Efficiency = 0.66), and accuracy at poorly performing sites could be improved by grouping sites with similar characteristics. Developing a single model for all sites reduced performance at several locations with distinct characteristics, suggesting that there is a threshold of dissimilarity beyond which more data does not improve the model. While many deep learning studies have shown that national or even global models can outperform local models, it is not clear that this is true for water quality constituents. This study demonstrates how data can be combined effectively, using deep learning to develop accurate and interpretable models of instream nitrate at sites where varying processes are responsible for changes in nitrate concentration.

Water Resources Research

A roadmap for identifying and interpreting physical processes and national water model prediction bias associated with baseflow index regimes across the contiguous United States

Understanding how groundwater–surface water interactions shape streamflow variability is critical for diagnosing low flow behavior and prediction bias in continental scale hydrologic models. We present a process informed framework that links observed baseflow (BF) dynamics, watershed attributes, and National Water Model (NWM) performance across the contiguous United States. Using daily observed streamflow from 797 reference quality streamgages, we developed monthly baseflow index (BFI) signatures using a streamgage specific, calibrated digital filter. Hierarchical clustering of these signatures identified seven distinct BFI regimes capturing regional and seasonal variability. We evaluated NWM v3.0 retrospective streamflow performance within each regime using multiple hydrograph and flow duration curve-based metrics. Model skill varied systematically across regimes: mixed flow systems were simulated most accurately, while predominantly BF dominated and quickflow dominated regimes exhibited substantially poorer performance. Across nearly all regimes, the NWM underestimated observed BFI magnitude and frequently failed to reproduce seasonal BF patterns, indicating systematic biases in simulated low flow contributions. To relate these regimes to potential process controls, we trained a Random Forest classifier using static watershed attributes and applied Shapley Additive Explanations to identify features most strongly associated with each regime. Results highlight regionally varying influences, including the dominant role of snow fraction and seasonal runoff timing in snow dominated basins and the importance of evapotranspiration and aridity in quickflow dominated systems. Collectively, these findings demonstrate how hydrologic signatures combined with interpretable machine learning can diagnose regime specific model biases and generate process-based hypotheses about limitations in large scale hydrologic prediction systems.

contiguous United States

Characterization and simulation of the quantity and quality of water in the Highland Lakes, Texas, 1983-92

The Highland Lakes, located in central Texas, are a series of seven reservoirs on the Colorado River (Lake Buchanan, Inks Lake, Lake Lyndon B. Johnson, Lake Marble Falls, Lake Travis, Lake Austin, and Town Lake). The reservoirs provide hydroelectric power for the area. In addition, Lake Austin and Town Lake also provide the public water supply for the Austin metropolitan area. Saline water released from Natural Dam Salt Lake during 1987&ndash;89 caused increased concern among water managers that high-salinity water entering the Highland Lakes could result in waterquality problems, necessitating additional treatment of the water. The maximum dissolved solids concentrations for the reservoirs after the saline inflow were about two to three times the average concentrations before the inflow. The maximum concentrations of chloride and sulfate after the inflow were about three to five times the average concentrations before the inflow. The concentrations of dissolved solids, chloride, and sulfate in Lake Buchanan, Inks Lake, Lake Lyndon B. Johnson, and Lake Marble Falls were less than the concentrations of the applicable water-quality standards by the end of 1990. Concentrations of these constituents in Lake Travis, Lake Austin, and Town Lake did not decrease to previous levels, which were less than the concentrations of the applicable waterquality standards, until the end of 1991. Constituent concentrations for Lake Buchanan and Inks Lake; for Lake Lyndon B. Johnson and Lake Marble Falls; and for Lake Travis, Lake Austin, and Town Lake were similar because of the relative storage capacities and location of tributary inflows. From the initial increase in constituent concentrations in Lake Buchanan (summer 1987) in response to the saline inflow, the high-salinity water passed through the entire Highland Lakes in about 3.5 years. A mathematical mass-balance model was used to simulate the input and movement of highsalinity water through the Highland Lakes and to estimate monthly mean concentrations of dissolved solids, chloride, and sulfate for wet, average, and dry hydrologic conditions. The simulated median monthly concentrations during the 10-year simulation period for each reservoir generally are larger for the average condition than for the wet condition and generally are larger for the dry condition than for the average condition. The simulated concentrations of dissolved solids, chloride, and sulfate decreased to levels less than the concentrations of the applicable water-quality standards in about 2 to 5 years after the saline water inflow of 1987&ndash;89 was simulated for the three hydrologic conditions. Results from the simulations indicate that saline inflows to the Highland Lakes similar to those of the releases from Natural Dam Salt Lake during 1987&ndash;89 are unlikely to cause large increases in future concentrations of dissolved solids, chloride, and sulfate in the Highland Lakes. The results also indicate that high-salinity water will continue to be diluted as it is transported downstream through the Highland Lakes, even during extended dry periods.

Texas

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions

Assessment of western Oregon debris-flow hazards in burned and unburned environments

In the steep and mountainous environment of western Oregon, debris flows pose a considerable threat to property, infrastructure and life. Wildfire is commonly known to increase the susceptibility of steep slopes to debris flows, but the extent of this process in the western Cascades is not well understood. The US Geological Survey (USGS) currently estimates postfire debris-flow likelihood and triggering rainfall thresholds using a model calibrated to a southern California inventory of debris flows generated by excess runoff within the first year after fire. Because of a lack of available data, this model has not been tested in western Oregon, or in locations where postfire debris flows initiate via other mechanisms (e.g., shallow landslides or in-channel failures). Using repeat field observations and aerial imagery, we developed two new debris-flow inventories within and adjacent to the perimeters of five 2020 wildfires in western Oregon: Archie Creek, Holiday Farm, Beachie Creek, Lionshead and Riverside. The first inventory focuses on postfire debris flows (2020–2022); the second focuses on debris flows prior to fires (1995–2020). Our inventories of prefire and postfire debris flows were used to document initiation mechanisms in Oregon's western Cascades and to evaluate the effects of wildfire. We found that wildfire changed the distribution of debris-flow initiation mechanisms in the western Cascades. After the wildfires, annual rates of runoff-generated debris flows increased by 22% and the number of shallow landslide-initiated debris flows decreased by 17% relative to before the wildfires. Despite this shift, shallow landsliding was the dominant debris-flow initiation mechanism in both unburned and burned environments. We found the performance of the current USGS debris-flow likelihood model was degraded relative to other previously tested locations across the intermountain western United States. Our results highlight the need for improved postfire hazard assessment in western Oregon based on regional model calibration that is tuned to the dominant debris-flow initiation mechanisms.

Oregon