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Fish beta diversity associated with hydrologic and anthropogenic disturbance gradients in contrasting stream flow regimes

Understanding the role of hydrologic variation in structuring aquatic communities is crucial for successful conservation and sustainable management of native freshwater biodiversity. Partitioning beta diversity into the additive components of spatial turnover and nestedness can provide insight into the forces driving variability in fish assemblages across stream flow regimes. We examined stream fish beta diversity across hydrologic and anthropogenic disturbance gradients using long-term (1916–2016) site occurrence records ( n = 17,375) encompassing 252 species. We assessed total beta diversity (Sørensen dissimilarity), spatial turnover, and nestedness of fish assemblages in contrasting stream flow regimes across a gradient of decreasing flow stability: groundwater stable ( n = 77), groundwater ( n = 67), groundwater flashy ( n = 175), perennial runoff ( n = 141), runoff flashy ( n = 255), and intermittent ( n = 63) streams. Differences in total beta diversity among the stream flow regimes were driven predominantly (>86 %) by spatial turnover (i.e. species replacement) as opposed to nestedness (i.e. species loss or gain). Total fish beta diversity and spatial turnover were highest in streams with intermediate flow stability (groundwater flashy), while more flow-stable streams (groundwater stable and groundwater) had lower turnover and higher nestedness. Species turnover was also strongly associated with seasonal variation in hydrology across all flow regimes, but these relationships were most evident for assemblages in intermittent streams. Distance-based statistical comparisons showed significant correlations between beta diversity and anthropogenic disturbance variables, including dam density, dam storage volume and water withdrawals in catchments of groundwater stable streams, while hydrologic variables were more strongly correlated with beta diversity in streams with runoff-dominated and flashy flow regimes. The high spatial turnover of species implies that fish conservation actions would benefit from watershed-focused approaches targeting multiple streams with wide spatial distribution, as opposed to simply focusing on preserving sites with the greatest number of species.

Science of the Total Envionrment

Ground-motion aleatory-variability models for Puerto Rico and the U.S. Virgin Islands

I develop independent logic trees for aleatory variability for crustal and subduction-zone (interface and intraslab) earthquakes for seismic hazards analyses in Puerto Rico and the U.S. Virgin Islands (PRVI) from existing suites of ground-motion models (GMMs) and from ground-motion datasets, including a regional PRVI dataset. The aleatory variability models are parameterized using a partially nonergodic partitioning of standard deviation that consists of independently developed between-event ( ), site-to-site ( ), and event-corrected single-station ( ) standard deviation components. The effects of nonlinear site response on aleatory variability are incorporated through additional terms that modify the standard deviation components. Because one goal of this work is to develop independent logic trees for aleatory variability that synthesize the aleatory variability models from GMMs, I make use of the functional forms of the input GMMs. The PRVI dataset contains a limited number of stations with high-quality site metadata and does not contain records from earthquakes with magnitudes greater than 6.1, so I choose not to develop the aleatory variability models from the regional dataset alone. Instead, the standard deviation components from regional ground-motion data are evaluated against the components derived from GMMs and from available global datasets, and regionalized standard deviation components are incorporated where there is evidence that regional effects exhibit substantial differences. The resulting logic trees for aleatory variability consist of models of and that are consistent with semiempirical GMMs for active crustal and subduction-zone regimes, and two alternative models of , including one model that exhibits site-to-site variability informed by PRVI data, with values that exceed global models. The aleatory variability models may be considered in future hazards assessments in PRVI to simplify the hazard calculations, to incorporate regional ground-motion variability effects, and to enable direct logic-tree weighs of aleatory variability.

Puerto Rico, U.S. Virgin Islands

Geologic framework and Holocene sand thickness offshore of Seven Mile Island, New Jersey

The U.S. Geological Survey assessed the Quaternary evolution of Seven Mile Island, New Jersey, to quantify coastal sediment availability, which is crucial for establishing sediment budgets, understanding sediment dispersal, and managing coastlines. This report presents preliminary interpretations of seismic profiles, maps of Holocene sand thickness from the shoreline to 2 kilometers offshore, and tables quantifying the volume of available sediment along the coastal margin based on data collected during 2021 and 2022. The results reveal spatial variability in the thickness and cross-shore extent of Holocene sand. The study area was separated into northern, central, and southern zones by using underlying stratigraphy and geomorphic features. The characteristics and spatial extent of the Holocene sand deposit indicate that hydrodynamic processes contribute to its spatial variability. Northern Seven Mile Island contains the thickest deposits of Holocene sand that were formed by sediment bypass around the Townsends Inlet ebb-tidal delta. Specifically, swash bars have welded to the updrift end of Seven Mile Island and have formed thick deposits of Holocene sand that thicken landward and taper seaward. Despite their thickness, these deposits have the smallest cross-shore extent; therefore, northern Seven Mile Island has the smallest volume of Holocene sand of the three geomorphic zones. Central Seven Mile Island has the thinnest Holocene sand deposits because this section of the barrier island is outside the influence of ebb-tidal deltas. Southern Seven Mile Island has the greatest volumes of Holocene sand because of increased accommodation and deposition adjacent to the Hereford Inlet ebb-tidal delta. Even though tidal inlets exert variable influence on the three geomorphic zones, sediment is distributed fairly uniformly within each geomorphic zone; each of the three zones contains 31.05–36.48 percent of the volume of available Holocene sand.

New Jersey

Using public participatory geographic information systems (PPGIS) to explore uses and values for Mojave Trails National Monument, California

Many people ascribe a variety of values to public lands and waters, but some values are more difficult to assess and quantify than others. Public participatory geographic information systems (PPGIS) are tools that have been used to help quantify and map the public’s diverse values for a landscape. This work describes the first known Office of Management and Budget–approved use of PPGIS by a Department of the Interior bureau. The U.S. Geological Survey developed an internet-based application to aid in gathering PPGIS data, called Values Mapping for Planning in Regional Ecosystems (VaMPIRE). Further, this work describes the first pilot of the VaMPIRE application in coordination with the Bureau of Land Management to collect spatial data and other survey data regarding the public’s uses of and values for locations within Mojave Trails National Monument. We emailed the link to the VaMPIRE application to an interested party email list in 2024 with 207 valid emails and received 74 responses; we also received 47 responses from members of an off-roading social media group. Of the list of 16 value options, recreation was the most popular value for the monument, followed by wilderness and inspirational. Over 1,000 points were placed throughout the monument, indicating locations people use or value, with the locations spread throughout the entire monument. Additionally, most survey respondents stated their ability to receive benefits in locations they mapped would not change in response to a hypothetical scenario related to recreational facility development. This report describes exploratory results from the first use of the VaMPIRE tool in Mojave Trails National Monument and includes reflections on how the process went and considerations for future use of VaMPIRE.

California

Using gridded seismicity to forecast the long-term spatial distribution of earthquakes for the 2025 Puerto Rico and U.S. Virgin Islands National Seismic Hazard Model

Gridded (or background) seismicity models are a critical component of probabilistic seismic hazard assessments, accounting for off‐fault and smaller‐magnitude earthquakes. They are typically developed by declustering and spatially smoothing an earthquake catalog to estimate a long‐term seismicity rate that can be used to forecast future earthquakes. Here, we present new gridded seismicity models for use in the 2025 National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). The previous PRVI NSHM was released in 2003, and our new models incorporate updates to both data and methodology. We utilize an updated earthquake catalog based on improved Puerto Rico Seismic Network data with newly characterized completeness epochs. The catalog is divided into crustal, subduction interface, and intraslab seismicity using new methods and Slab2 subduction zone geometries. To forecast the long‐term spatial distribution of earthquakes, we use an updated methodology developed for the 2023 U.S. 50‐state NSHM, considering three declustering methods and two spatial smoothing methods based on 2D Gaussian kernels. To adapt it for the complex seismotectonics of the region, we also adopt probabilistic methods to account for events with unknown depths and uncertainties in tectonic classification, and develop a new method for spatial scaling to counteract the effects of spatial variability in network coverage while maintaining the use of smaller events. Finally, we test the performance of these spatial models in forecasting the location of M w ≥ 5earthquakes in the region. Our updated methodology improves the representation of epistemic uncertainty relative to the 2003 model, and our results demonstrate the effectiveness of the new measures we have introduced to address heterogeneities in network detection and systematically evaluate forecast performance.

Puerto Rico, U.S. Virgin Islands

A seismic nodal deployment to understand magmatic structure in the vicinity of the Pahala earthquake swarm

In summer-fall 2022, 80 three-component SmartSolo IGU-BD3C-5 nodal seismometers were deployed surrounding the Pāhala seismic swarm on the Island of Hawaiʻi, with the goal of improving seismicity catalogs, and seismic velocity images of the crust and upper mantle in this region. The Pāhala swarm, located south of Mauna Loa and Kīlauea, has been the site of a multiyear sustained swarm of seismicity at depths of ~ 25 – 40 km, with order of magnitude increases in rate in 2015, and then again in 2019. This seismicity is possibly related to the input of magma from the mantle plume below, which may then be subsequently transported to volcanic edifices. However, these processes remain enigmatic, in part due to a lack of precise earthquake locations and seismic velocity models in this region. Here we provide an overview of the deployment, an assessment of the quality of the collected data, and discuss the viability of the dataset for local earthquake relocation, tomography, and teleseismic receiver functions. Through comparisons with proximal permanent broadband and short period instruments, we find that the nodes produce high quality data, particularly at periods shorter than 5 s, although we find, document, and correct discrepancies with the gain and polarities of the instruments. We successfully record signals from teleseismic earthquakes, even at periods longer than 5 s (the corner of the flat response of the nodes). We also record local earthquakes, including details related to source characteristics. This indicates that the data is likely to prove useful for investigations using both local and teleseismic earthquake signals to better understand the connections between the deep and shallow magmatic systems of Hawaiʻi. While this deployment provides a snapshot in time, its success may provide a useful benchmark for future studies as the volcanic systems of Hawaiʻi continue to evolve in the future.

Hawaii

Pesticides in surface waters of the Upper Colorado River Basin, Colorado, 1996-98

Forty-four river, stream, and drain sites in the Upper Colorado River Basin in Colorado were sampled during 1996-98 to determine the occurrence and distribution of pesticides in the basin. In a fixed-station study, 57 surface-water samples were collected from October 1996 through January 1998 at four sites. Each site was sampled approximately monthly for up to a year, with more frequent sampling during the spring and summer growing season. In a synoptic study, surface-water samples were collected at 43 sites in the agricultural areas of the Grand Valley and the Uncompahgre River Valley in May 1998. Each site was sampled once. Pesticide concentrations generally were low and varied seasonally and across land uses. Thirty-five pesticides were detected at least once in the two studies, and 11 pesticides accounted for almost 82 percent of the detections. Herbicides were more commonly detected than insecticides, and only the herbicides alachlor and atrazine were detected in more than 50 percent of the samples. Carbofuran was the most commonly detected insecticide and was detected in 19 percent of the samples. Pesticide detections increased and were measured at higher concentrations in the summer months and at the agriculture sites. All pesticide concentrations were less than drinking-water standards, and most complied with human-health advisories and criteria for the protection of freshwater aquatic life. Pesticides in the Upper Colorado River Basin in Colorado were detected slightly less frequently and generally at lower concentrations than in 20 National Water-Quality Assessment Program study-unit basins that collected water-quality data from 1992 through 1996. Results from surface-water sampling conducted during 1996?98 in the Upper Colorado River Basin in Colorado indicate that beneficial uses of water were not being impaired by the presence of pesticides in surface waters in the basin.

Colorado

Refinements to the attenuated propagation of local earthquake shaking (APPLES) ground-motion-based earthquake early warning algorithm

We refined the Attenuated ProPagation of Local Earthquake Shaking (APPLES) ground-motion-based earthquake early warning (EEW) approach, and directly compare APPLES performance with that of the source-characterization-based U.S. ShakeAlert EEW system for a suite of historical earthquakes in the U.S. West Coast and Japan. APPLES is an extension of the Propagation of Local Undamped Motion (PLUM) algorithm in which observed shaking intensity at seismic stations is used to forward-predict intensity distributions to surrounding areas using an attenuation model derived from an intensity prediction equation. We test new configuration options within APPLES, such as using the second highest estimated ground motion rather than the maximum, to better match median ground-motion observations and reduce alerts for small magnitude earthquakes, both of which are key alerting priorities within ShakeAlert. We evaluate these configurations alongside ShakeAlert by comparing the ground-motion estimation accuracy and available warning times relative to station observations and ShakeMap distributions. Our preferred APPLES configuration produces accurate ground-motion estimates and corresponds better with median observations compared to ShakeAlert’s estimates. This preferred configuration substantially reduces alert issuance for M < 5.0 earthquakes compared to the previous APPLES configuration, and alert-release criteria can further restrict alerts to primarily M ≥ 5.5 earthquakes without requiring magnitude estimation. Prioritizing matching median-observed ground motions may reduce APPLES warning times compared to configurations that were tuned to avoid missed alerts (such as those that use the maximum estimated ground motions), which can lead to shorter warning times compared to ShakeAlert for the same alert threshold. However, station-based warning time assessments demonstrate that APPLES can outperform ShakeAlert for high target thresholds. APPLES is a simple, independent EEW approach that may improve the robustness of EEW for the West Coast of the U.S.

California, Oregon, Washington

Slip rate for the Rose Canyon fault through San Diego, California, based on analysis of GPS data: Evidence for a potential Rose Canyon–San Miguel-Vallecitos fault connection?

The Rose Canyon fault is the southern extension of the larger Newport–Inglewood–Rose Canyon fault system, which represents a major structural boundary in the Inner Continental Borderland (ICB) offshore of southern California. Ten to fifteen percent of total plate boundary motion in southern California is thought to be accommodated by the faults of the ICB, but the exact distribution of slip is uncertain. With an onshore segment, the Rose Canyon fault offers an opportunity to measure the slip rate using traditional geodetic methods. In this study, we use Global Positioning System (GPS) surface velocities from a combined campaign and continuous GPS network to constrain elastic models of the Rose Canyon fault. We then compare the observed surface velocities with proposed conceptual models of regional fault connections that facilitate the transfer of slip into the Rose Canyon fault to assess how well the observations are explained by the models. The results of elastic half‐space models suggest that the Rose Canyon fault may be slipping toward the higher end of geologic estimates, with the preferred model indicating a slip rate of 2.4 ± 0.5 mm/yr. Although limited in terms of near‐fault benchmarks, we find an improved model fit using an asymmetrical elastic half‐space model and a higher slip rate, suggesting a potential rheological contrast across the Rose Canyon fault, similar to observations from the northern Newport–Inglewood fault segments. Observed GPS surface velocities, background seismicity, and gravity anomalies south of San Diego Bay point toward a more easterly trace for the Rose Canyon fault, suggesting a possible connection with the San Miguel–Vallecitos fault system. Such a connection could increase the potential rupture lengths of future earthquakes and have important consequences for regional seismic hazards.

California

Groundwater flow model for the Des Moines River alluvial aquifer near Des Moines, Iowa

Des Moines Water Works (DMWW) is a regional municipal water utility that provides residential and commercial water resources to about 600,000 customers in Des Moines, Iowa, and surrounding municipalities in central Iowa. DMWW has identified a need for increased water supply and is exploring the potential for expanding groundwater production capabilities in the Des Moines River alluvial aquifer, where it operates two radial collector wells (RCWs). The U.S. Geological Survey, in cooperation with DMWW, completed a study of the Des Moines River alluvial aquifer and interactions of the RCWs with the aquifer; no previously published model has included the existing well locations, which is the focus of this model. A conceptual and numerical groundwater flow model have been developed to characterize the Des Moines River alluvial aquifer under existing conditions, to simulate water levels observed in the RCWs, and to provide publicly accessible hydrologic data and research that advance understanding of the regional hydrologic system and can potentially be used in the future to evaluate groundwater production scenarios. Model performance was assessed by comparing observed and simulated groundwater levels that included water level elevations, water level changes, water level inequality observations, surface water streamflow, and change in surface water volume from upstream to downstream. Water table elevation in the aquifer layers is on average slightly overestimated with average absolute value error less than 1.5 meters at both RCWs and less than 2.5 meters for all observation wells in the alluvial aquifer layers. The model also accurately simulated water tables greater than the RCW design minimum (a water level threshold at which RCW pumping is reduced) in all timesteps for which water level observation data existed. Water table elevation error was higher in other model layers that were not the focus of the study, and the model did not accurately match streamflow targets.

Iowa

Sensitivity of benthic biota and toxicity of cadmium, cobalt, copper, nickel, lead, and zinc mixtures in Washington, United States, and British Columbia, Canada

Relative sensitivities and responses of juvenile white sturgeon ( Acipenser transmontanus ), Hyalella azteca , two families of mayfly (Ephemerellidae, Heptageniidae), one family of caddisfly (Brachycentridae), and a natural community of benthic macroinvertebrates (BMI) to multiple metals are predicted using previously collected laboratory and field samples and a metal mixture model. Biological responses in single metal exposures are used to parameterize toxicity functions, which include accumulations of hydrogen and selected metals on biological receptors, intrinsic potencies of hydrogen and metals, sensitivities of organisms, and times of exposure. The model then is used to predict responses in multiple metal laboratory exposures and field-collected porewater. The following sensitivity sequence in porewater was determined based on endpoints of survival or total abundance: juvenile white sturgeon greater than (>) Ephemerellidae family > Hyalella azteca > Heptageniidae family about equal to (~) benthic macroinvertebrate community > Brachycentridae family. The fraction of porewater samples that are predicted to have adverse impacts on benthic biota (20-percent or greater negative response) depends on organism sensitivities and metal toxicities, and ranges from 44 to 48 percent for juvenile white sturgeon, 23 to 26 percent for the Ephemerellidae family, 16 to 22 percent for Hyalella azteca , 5 to 8 percent for the Heptageniidae family and BMI community, and 0 percent for the caddisfly family. The most toxic porewater in the upper Columbia River Basin (UCR) is at the backwater bar site at Deadmans Eddy and China Bend. The model also indicates that the element responsible for the most toxic conditions in UCR porewater is copper for all organisms, except Hyalella azteca and the metal-insensitive Brachycentridae family. Copper and lead result in the most toxic conditions for Hyalella azteca . This approach and results can aid in assessing metal toxicity and its potential risk to aquatic biota in ecosystems impacted by historical mining activities.

British Columbia, Washington

The 2023 Alaska National Seismic Hazard Model

US Geological Survey (USGS) National Seismic Hazard Models (NSHMs) are used extensively for seismic design regulations in the United States and earthquake scenario development, as well as risk assessment and mitigation for both buildings and infrastructure. This 2023 update of the long-term, time-independent Alaska NSHM includes substantial changes to both the earthquake rupture forecast (ERF) and ground motion models (GMMs). The ERF includes numerous additions to the finite-fault model, considers two deformation models, and introduces updated declustering and smoothing algorithms in the gridded background seismicity model. For the Alaska–Aleutian subduction zone, megathrust earthquakes occur on an updated structural and segmentation model, and the moment magnitude (M) 8+ rupture and rate model include a logic tree branch that considers slip rates derived from geodetic models of interface coupling. The megathrust model considers multiple models of down-dip width, and magnitudes are computed using newly developed scaling relations. For subduction intraslab events and subduction interface events with M < 7, the 2023 update uses a smoothed seismicity model with rupture depths derived from Slab2. The 2023 model updates GMMs in all tectonic settings using the recently published Next Generation Attenuation Subduction (NGA-Sub) GMMs for subduction interface and intraslab events, and the NGA-West2 GMMs for active crustal settings. Collectively, additions and updates to the Alaska NSHM result in hazard increases across most of south-central Alaska relative to the previous model, published in 2007. These changes are primarily due to the adoption of updated rate models for the large-magnitude interface events and the NGA-Sub GMMs that have much higher aleatory variability (sigma), consistent with global observations, and that include models of epistemic uncertainty.

Alaska

The 3D Elevation Program—Supporting the economy of Massachusetts

Introduction Massachusetts extends from the mountains of the Appalachian system in the west of the State to the sandy beaches and rocky shorelines of the Atlantic coast in the east. Inland topographic data support a wide range of important activities, including geologic mapping, transportation planning, forest and wildlife management, quantifying ecological services, water supply protection, commonwealth-wide infrastructure planning, local site planning, and flood-plain management. Nearshore bathymetry can be used to support coastal portions of the Commonwealth by addressing the combined threats of ocean warming, strong storm surge, and rising sea levels. The maintenance and (or) expansion of Massachusetts ports (for instance, Boston, New Bedford) and Cape Cod sediment management depends upon the accurate mapping of bathymetry and the frequent influx of sediment and redeposition. Critical applications that address the broad range of requirements depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Massachusetts. The status of available and in-progress 3DEP baseline lidar data in Massachusetts is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $1.23 million in new benefits annually to Massachusetts. The top 10 Massachusetts business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Massachusetts

A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA

We develop a partially nonergodic ground-motion model (GMM) for Fourier amplitude spectra for the San Francisco Bay Area, California, USA, using the Bayless and Abrahamson (2019) GMM as a reference ergodic GMM and developing location-dependent adjustments to the predicted median and variance. We compile regional ground-motion data from moment magnitude (𝑀 w ) >3 earthquakes occurring during 2000–2022 for which magnitude information is available in the U.S. Geological Survey Comprehensive Catalog (Guy et al., 2015). The data set predominantly consists of records from 𝑀 w 3.5–4.5 earthquakes but includes three well-recorded 𝑀 w > 5 events. Ground-motion residuals are evaluated using the time-averaged shear-wave velocity in the top 30 m (𝑉 S30 ) from the California-specific map of Thompson et al. (2018) and basin-depth site parameters from the seismic velocity model of Aagaard and Hirakawa (2021). The 𝑉 S30 dependence and basin-depth scaling of the reference ergodic GMM of Bayless and Abrahamson (2019) are evaluated and modified with the updated data set. We compute maps of site adjustments using a varying-coefficient model that considers the spatial correlation structure and uncertainties at each observation location. The spatial covariance model is developed using ground-motion residuals that are standardized by the uncertainty model, which allows for consideration of the aleatory variability in developing the site adjustments. The covariance model is fit considering the means and standard deviations of the site terms at all locations. The use of partially nonergodic median adjustments results in modified variance components of the within-event variability. Due to the low number of large-magnitude earthquakes that control seismic hazard in the data set, we do not modify between-event variance; however, we present adjustments to site-to-site variability for use in partially nonergodic hazard assessments.

California

Simulation-based scenario ShakeMaps for large magnitude (MW6.5+) crustal earthquakes on the Seattle, Tacoma, and southern Whidbey Island faults, Washington, USA

Scenario ground‐motion maps based on empirical ground‐motion models (GMMs) provide a rapid and generally reliable means of estimating the amplitude and distribution of earthquake shaking. However, because GMMs are designed for broad applicability, they often rely on simplified representations of Earth structure, which can limit their accuracy in regions with complex source, path, and site effects. This can substantially impact the accuracy of predicted shaking in areas like western Washington State, where deep, interconnected basin structure exerts a strong influence on seismic‐wave propagation. In this study, we present a new suite of simulation‐based scenario ShakeMaps that characterize ground shaking from large‐magnitude ( ⁠ M W 6.5–7.5) earthquakes on the Seattle, Tacoma, and southern Whidbey Island faults. These maps are developed using results from recent 3D wave propagation simulations ( Stone et al. , 2022 , 2023 , 2025 ) that incorporate realistic rupture geometries, variable slip distributions, and a regional 3D seismic velocity model with shallow soils. Broadband ground motions are estimated by combining the low‐frequency (<1 Hz) deterministic seismograms from these studies with high‐frequency (1–10 Hz) stochastic seismograms. Simulated ground motions are corrected to account for the enforced minimum shear‐wave velocity and nonlinear site response. The resulting ShakeMaps represent median ground‐shaking estimates derived from multiple rupture scenarios with varying slip distributions and hypocenter locations for each fault. To extend ShakeMap coverage beyond the simulation domain (i.e., into eastern Washington, northern Oregon, and southwestern British Columbia), we scale GMM‐based ground‐motion estimates using amplification patterns observed in the simulations. These new ShakeMaps reveal the substantial influence of deep basin structure on shaking intensity, underscoring the importance of considering crustal structure complexity in regional hazard assessments for the Pacific Northwest.

Washington

Estimation of reservoir storage capacity and geomorphic change detection analysis from a multibeam bathymetric survey of Randy Poynter Lake, Rockdale County, Georgia

Rockdale County Department of Water Resources has a directive to update estimates of the reservoir storage capacity of Randy Poynter Lake, located in northern Georgia, and to assess recent sedimentation and associated storage capacity loss. In 2022, the U.S. Geological Survey completed a multibeam bathymetric survey of Randy Poynter Lake to update storage capacity estimates and to quantify storage capacity change since the first multibeam bathymetric survey in 2012 in consideration of estimated errors inherent to bathymetric surveys. Data from the 2022 survey were used to generate contours of the reservoir as well as compute storage capacity at regular increments of water-surface elevation. Storage capacity comparisons between 2012 and 2022 at Randy Poynter Lake show minimal changes that are within the estimated uncertainties, with consistent or slightly increased storage capacities observed at most water-surface elevations and reductions observed at the remaining few elevations. Comparison of the multibeam bathymetric data collected in 2012 with data collected in 2022 further allowed for a formal geomorphic change detection analysis to map, quantify, and infer causation of morphological change over time with respect to a level of detectable change. The volume change in Randy Poynter Lake for the decade between 2012 and 2022 was slightly net-depositional and within the estimated uncertainty. The spatial distribution of sediment deposition was primarily concentrated in the northern portion of the lake, where the principal tributary flows into Randy Poynter Lake. The results of the geomorphic change analysis were used to further understand the future implications to storage capacity change. Despite the challenges of confirming systematic biases because of uncertainties exceeding the observed changes, insights from the study help predict long-term reservoir sediment accumulation, indicating a reservoir half-life extending about 650 years from 2022 on the basis of the current sediment yield estimates.

Georgia

Cursed? Why one does not simply add new data sets to supervised geothermal machine learning models

Recent advances in machine learning (ML) identifying areas favorable to hydrothermal systems indicate that the resolution of feature data remains a subject of necessary improvement before ML can reliably produce better models. Herein, we consider the value of adding new features or replacing other, low-value features with new input features in existing ML pipelines. Our previous work identified stress and seismicity as having less value than the other feature types (i.e., heat flow, distance to faults, and distance to magmatic activity) for the 2008 USGS hydrothermal energy assessment; hence, a fundamental question regards if the addition of new but partially correlated features will improve resulting models for hydrothermal favorability. Therefore, we add new maps for shear strain rate and dilation strain rate to fit logistic regression and XGBoost models, resulting in new 7-feature models that are compared to the old 5-feature models. Because these new features share a degree of correlation with the original relatively uninformative stress and seismicity features, we also consider replacement of the two lower-value features with the two new features, creating new 5-feature models. Adding the new features improves the predictive skill of the new 7-feature model over that of the old 5-feature model; albeit, that improvement is not statistically significant because the new features are correlated with the old features and, consequently, the new features do not present considerable new information. However, the new 5-feature XGBoost model has a statistically significant increase in predictive skill for known positives over the old 5-feature model at p = 0.06. This improved performance is due to the lower-dimensional feature space of the former than that of the latter. In higher-dimensional feature space, relationships between features and the presence or absence of hydrothermal systems are harder to discern (i.e., the 7-feature model likely suffers from the “curse of dimensionality”).

Geothermal Resources Council Transactions

Following the tug of the audience from complex to simplified hazards maps at Cascade Range volcanoes

Volcano-hazard maps are broadly recognized as important tools for forecasting and managing volcanic crises and for disseminating spatial information to authorities and people at risk. As scientists, we might presume that hazards maps can be developed at the time and with the methods of our discretion, yet the co-production of maps with stakeholder groups, who have programmatic needs of their own, can sway the timing, usability, and acceptance of map products. We examine two volcano hazard map-making efforts by staff at the U.S. Geological Survey. During the 1990s and early 2000s scientists developed a series of hazard assessments and maps with detailed zonations for volcanoes in Washington and Oregon. In 2009, the National Park Service expressed the need for simplified versions of the existing hazard maps for a high-profile visitor center exhibit. This request created an opportunity for scientists to rethink the objectives, scope, content, and map representations of hazards. The primary focus of this article is a discussion of processes used by scientists to distill the most critical information within the official parent maps into a series of simplified maps using criteria specified. We contextualize this project with information about development of the parent maps, public response to the simplified hazard maps, the value of user engagement in mapmaking, and with reference to the abundance of guidance available to the next generation of hazard-mapmakers. We argue that simplified versions of maps should be developed in tandem with any hazard maps that contain technical complexities, not as a replacement, but as a mechanism to broaden awareness of hazards. We found that when scientists endeavor to design vivid and easy-to-understand maps, people in many professions find uses for them within their organization’s information products, resulting in extensive distribution.

Washington