Search USGS⌕ Search

SEARCH · Search USGS

Results for “Journal of the Air & Waste Management Association”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

1,691 records · Page 6Linked to original sources
USGS2025

Meet the people where they are: Assessing user needs for aftershock forecast products in El Salvador, Mexico and the United States

Aftershock forecasts can help communities reduce their seismic risk by conveying how many aftershocks can be expected following a large earthquake, and how the expected number of aftershocks and their corresponding ground shaking evolves over time and space. Prior work finds that graphical forecast products may communicate such information better than only text or numbers. To identify which visual products can serve multiple user groups, we held workshops with members of several professions, including emergency managers, engineers, critical infrastructure operators, public health specialists, science communicators, and more. We conducted these workshops in El Salvador, Mexico and the United States to understand which forecast products may be effective across different countries. In these workshops, users performed small-group activities to elicit the types of aftershock forecast information that would support decisions in their respective roles and how this information would optimally be displayed. Maps of shaking hazards were frequently requested across all professions and countries, even for dissimilar forecast uses. The design of these maps, and other product needs, were differentiated by profession, country and other factors. Other forecast products, including those showing forecasts about the magnitudes and time periods of future aftershocks, also served a variety of users, but for different types of decisions. We found a greater variation in user needs by profession than by country, and that user needs also vary with time, communication channel and other contextual factors. We discuss practical implications for user-centered visual communication of operational aftershock forecasts.

International Journal for Disaster Risk Reduction↗
USGS2026

Re-examining the growing degree day minimum for grass carp spawning initiation in Lake Erie: Have we missed the mark?

Understanding the timing of life history processes of invasive fish species, such as adult aggregations during spawning, allows natural resource managers to optimize targeted population control efforts. Temperature-based estimates of the timing of spawning initiation for grass carp ( Ctenopharyngodon idella ) exist from its native range, but have not previously been developed for grass carp reproduction in its invaded range in the Laurentian Great Lakes of North America. We accounted for differences among methods across studies and calculated cumulative growing degree days (GDD) for the dates of grass carp egg capture in Lake Erie tributaries (Sandusky, Maumee, and Huron rivers) during 2015–2024 and compared these values to the existing GDD base 15°C requirement estimate from the native range (633 GDD–15°C). The earliest egg detection in Lake Erie (Sandusky River) was 19 GDD–15°C or 361 GDD–5°C (latest egg detection was 2285 GDD–5°C from the Sandusky River), indicating that spawning was initiated up to 25 days earlier than would be predicted by the native range GDD. Moreover, spawning in Lake Erie tributaries occurred earlier than predicted for 58% of spawning events examined based on the native range GDD. The GDD values for spawning initiation in Lake Erie tributaries can be used to refine the timing of control efforts targeting pre-spawn and spawning adult fish, inform the timing of egg sampling, and provide linkages to existing early life stage models to infer the length of the growing season available for age-0 fish to reassess tributary suitability.

Lake Erie, Maumee, River, Sandusky river↗
USGS2024

Produced water geochemistry from hydraulically stimulated Niobrara Formation petroleum wells: Origin of salinity and temporal perspectives on treatment and reuse

Produced water (i.e., a mixture of returned injection fluids and geologic formation brines) represents the largest volumetric waste stream associated with petroleum production in the United States. As such, produced water has been the focus of intense study with emphasis on understanding the geologic origin of the fluids, environmental impacts of unintended or intentional release, disposal concerns, and their commodity (e.g., lithium) potential. However, produced water geochemistry from many active petroleum plays remain poorly constrained leading to knowledge gaps associated with the origin of brine salinity and parameters (e.g., radium levels) that can impact treatment, disposal, and possible reuse. Here we evaluate the major ion geochemistry, radium concentrations, and stable water isotope composition of ~120 produced water samples collected from 17 producing unconventional petroleum wells in Weld County, Colorado from the Late Cretaceous Niobrara Formation. This sample set encompasses eight produced water time series from four new wells across production days 0 to ~365 and from four established wells across production days ~1000 to ~1700. Additionally, produced water from nine other established Niobrara Formation wells were sampled at discrete time points ranging from day 458 to day 2256, as well as hydraulic fracturing input fluids. These results expand the available Niobrara Formation produced water geochemical data, previously limited to few wells sampled within the first year of production, allowing for the heterogeneity of major ions and radium to be evaluated. Furthermore, we explore the geochemical relationships between major ion ratios and stable water isotope composition to understand the origin of salinity in Niobrara Formation brines from the Denver-Julesburg Basin. These findings are discussed with perspective toward potential treatment and reuse of Niobrara produced water prior to disposal.

Colorado, Nebraska, Wyoming↗
USGS2024

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↗
USGS2024

SUTRA— A code for simulation of saturated-unsaturated, variable-density groundwater flow with solute or energy transport—Documentation of the version 4.0 enhancements—Freeze-thaw capability, saturation and relative-permeability relations, spatially varying properties, and enhanced budget and velocity outputs

Version 4.0 of the Saturated-Unsaturated Transport (SUTRA) software code provides the capability to simulate the freezing and thawing of groundwater during energy transport simulations under saturated and unsaturated conditions. In addition to the types of hydrogeologic processes that SUTRA has been able to simulate in the past, this version can be used to study the effects of the freeze-thaw process on the flow and energy dynamics of hydrogeologic systems. The freeze-thaw simulation capability accounts for the latent heat of fusion and allows thermal property values to vary with changing total-water saturation, liquid-water saturation, and ice saturation. It allows the effective permeability of the porous medium to change as a result of freezing and thawing. This version also provides several user-selectable relations for the dependence of total-water saturation on fluid pressure, the dependence of liquid-water saturation on temperature during freezing and thawing, and the dependence of relative permeability on liquid saturation, as well as three user-selectable formulae for defining the bulk thermal conductivity of a mixture of solid grains, liquid water, ice, and air. For unsaturated simulations without freezing, the selectable total-water saturation relations eliminate the need for the user to program these and their associated relative-permeability functions, as had been required in previous SUTRA versions. Optional nonlinear dependence of fluid density on temperature, which covers the range from supercooled (about −50 degrees Celsius) to superheated (about 400 degrees Celsius), is also provided. Additionally, this version makes it possible to spatially vary parameters that, in previous versions of SUTRA, were required to be spatially uniform: solid-matrix properties, adsorption parameters, and parameters for production of solute mass or energy. Spatial variation is also allowed for the newly included freeze-thaw process parameters. Additional enhancements provide (1) output of water-mass and energy budgets that include values of all component terms in the governing balance equations, and (2) output of Darcy velocities (fluid fluxes), in addition to the velocity output provided by previous SUTRA versions. These enhanced outputs allow fuller interpretation of simulation results, especially for freeze-thaw phenomena. The set of processes simulated by this version of SUTRA are useful for studying a wide range of hydrogeologic system types, conditions, and questions. For cryohydrogeologic simulations, however, this version of the code is limited in that (1) it does not simulate thermomechanical effects of freeze-thaw, (2) pressure changes due to water density change during freezing are neglected, (3) ice saturation cannot exceed the initial porosity of the simulated medium, and (4) cryosuction, the migration of liquid water toward freezing fronts, is neglected. Furthermore, this version does not account for air flow or for water vaporization and sublimation under unsaturated conditions.

Techniques and Methods↗
USGS2024

Greater sage-grouse habitat of Nevada and northeastern California—Integrating space use, habitat selection, and survival indices to guide areas for habitat management

Executive Summary Greater sage-grouse populations ( Centrocercus urophasianus ; hereafter sage-grouse) are threatened by a suite of disturbances and anthropogenic factors that have contributed to a net loss of sagebrush-dominant shrub cover in recent decades. Declines in sage-grouse populations are largely linked to habitat loss across their range. A key component of conservation and land use planning efforts for sage-grouse involves the continued monitoring and modeling of habitat requirements and suitability across its range. The Bureau of Land Management (BLM) is addressing the management of sage-grouse habitats on BLM-authorized public lands throughout the western United States through a land use planning amendment and associated environmental impact statement (86 FR 66331). More than 25 percent of the range-wide distribution of sage-grouse is within Nevada and northeastern California, and information on sage-grouse distribution and habitat requirements is important to guide appropriate management decisions. Therefore, the BLM has identified the need for updated spatially explicit information on sage-grouse habitat in Nevada and northeastern California to guide the land use planning amendment and associated management decisions. To address this need, researchers with the U.S. Geological Survey, in close cooperation with multiple State and Federal resource agency partners, including BLM, Nevada Department of Wildlife (NDOW) and California Department of Fish and Wildlife (CDFW), sought to map sage-grouse distribution and produce example habitat designations in these states. Herein, we report results of our primary study objective, which was to map sage-grouse habitat and create example habitat management areas, based on more than a decade of location and survival data collected from marked sage-grouse across the study region coupled with lek count survey data managed by the NDOW and the CDFW. We expanded on previously developed methodology to incorporate information on habitat selection and survival during reproductive life stages and specific seasons with updated sage-grouse location and known fate datasets, while also including brood-rearing areas that are understood to be threatened and important for population persistence. We combined predictive habitat map surfaces for each life stage and season with updated information on current occupancy patterns to classify habitat based on its suitability and probability of occupancy. We carried out additional steps to delineate specific example habitat management areas, specifically (1) incorporated corridors connecting key nesting and brood-rearing habitat, (2) corrected outputs for pre-wildfire habitat conditions within areas burned in the last 16 years, and (3) masked out areas of anthropogenic development. Our methodological example of deriving habitat management areas was intended to help inform decisions by BLM and other land managers regarding conservation and management of sage-grouse. Associated data products in the form of habitat maps provide updated, detailed, and comprehensive information about the status of habitats and can be useful to partner agencies in their efforts to designate and rank habitats for this species of high conservation concern in Nevada and California, with full recognition that on-the-ground field data and local sources of information and expertise should be used in conjunction with inferences from these models.

California, Idaho, Nevada↗
USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗
USGS2026

USGS 2025 critical minerals review

The United States Geological Survey (USGS) provides scientific information for the Department of Interior and the nation, consistent with its original mission expressed in the Organic Act of 1879 (43 U.S.C. 31): “the classification of the public lands and examination of the geological structure, mineral resources, and products within and outside the national domain.” Legislation such as the Energy Act of 2020 and the 2022 Infrastructure Investment and Jobs Act (43 USC 31l) and recent executive actions (Executive Orders 14154 , 14153, 14241 Secretary’s Orders 3417, 3418, 3422, 3436) underscore the importance of mineral resources and focus USGS activities on mapping and assessing mineral resources, with a particular focus on those presently identified as critical, both in ground and above ground in mine wastes. This article reviews selected activities and accomplishments by the USGS Mineral Resources Program related to critical minerals in 2025. Highlights include a new List of Critical Minerals, a first-ever national mine waste inventory, international minerals partnerships, mineral resource assessment advancements, and national data collection activities and outcomes of the Earth Mapping Resources Initiative (Earth MRI). The selected contributions are not comprehensive but are intended to demonstrate USGS leadership in critical mineral mapping and assessment, the importance of domestic and global partnerships, and the breadth of research activities that are responsive to national needs and priorities.

Mining Engineering↗
USGS2025

Geologic models underpinning the 2024 U.S. Geological Survey assessment of undiscovered oil and gas resources in the Hosston and Travis Peak Formations of the onshore Gulf Coast region, U.S.A.

The Early Cretaceous (Berriasian–Hauterivian) Hosston Formation in Louisiana and eastward is time correlative to the Travis Peak Formation of Texas and southern Arkansas. The formation is a first-order clastic sequence with a regional carbonate transgressive surface as an upper contact. The Hosston and Travis Peak formations contain conventional natural gas and oil accumulations that have been produced for nearly a century. These mature reservoirs contain terrigenous fluvial-deltaic, shore-zone, and paralic deposits across the productive trend; organic-lean mudstone and siltstone lithologies are found outboard of the Lower Cretaceous shelf margin. Producing reservoirs exhibit normal pressure gradients from 0.43 to 0.55 psi/ft (9.7 to 12.4 kpa/m), depths from 4000 to over 20,000 ft (1220 to 6100 m), and temperatures from 150 to 385°F (65 to 196°C). Wells are primarily vertical completions. The number of new field wildcats has been declining since the late 1990s. This paper presents comprehensive geologic models, which include lithofacies maps, structure and isopach maps, burial history models, regional seismic interpretations, and events charts that underpin the recently completed U.S. Geological Survey assessment of undiscovered, technically recoverable hydrocarbons within the Hosston and Travis Peak formations. This study also provides geographic and stratigraphic distributions of Hosston–Travis Peak reservoir properties, including geopressure, reservoir temperature, porosity, permeability, API gravity, and gas-oil ratios. Results indicate estimated undiscovered, technically recoverable mean resources of 28 million barrels of oil and 35.8 trillion cubic ft of gas in conventional and continuous accumulations within the Lower Cretaceous Hosston and Travis Peak formations of the onshore U.S. Gulf Coast region. Quantitative assessment results are detailed in U.S. Geological Survey Fact Sheet 2025–3021 and associated Data Release.

GCAGS Journal↗
USGS2024

Event classification, seismicity, and eruption forecasting at Great Sitkin Volcano, Alaska: 1999–2023

The frequency content of volcanogenic seismicity is often used to classify events and their spatial and temporal progression is then used to map subsurface volcanic processes. The progression of volcano-seismic events and associated source processes also plays a critical role in eruption forecasting. Here we develop and evaluate a computerized methodology for characterizing volcano-seismic event types using Frequency Index and Average Peak Frequency. We apply and test this technique at Great Sitkin Volcano, Alaska, classifying over 9000 hypocenters between 1999 and 2023. This 24-year time span covers periods of seismic quiescence, earthquake activity on nearby tectonic (bookshelf) faults, precursory unrest from 2016 to 2021, and the explosive onset in May 2021 of the ongoing effusive eruption. We use the spatial and temporal evolution of classified event types to map the active volcanic and tectonic processes, develop a conceptual model of the subsurface magmatic system, and perform a retrospective analysis of eruption forecasts at Great Sitkin Volcano between 2016 and the present. The classification and progression of hypocenters suggests the subsurface Great Sitkin Volcano magmatic system consists of a mid- to lower- crustal source zone between 10 and 40 km depth and an upper crustal magma storage area between −1 and 10 km depth (hypocenter depth is referenced to sea level and negative depths reflect height above sea level). The earliest precursors occurred in July 2016 and consisted of deep long-period and volcano-tectonic earthquakes at mid-crustal depths suggesting the subsequent unrest and eruption were triggered by a deeper intrusion of magma. This mid-crustal seismic activity was immediately followed by the onset upper-crustal long-period events and volcano-tectonic earthquakes VTs suggesting a strong linkage between the shallow and deeper portions of the magmatic system. The upper crustal area was likely capped by the 1974 lava dome until the magmatic explosion on May 26, 2021.

Alaska↗
USGS2021

Remote sensing-based actual evapotranspiration assessment in a data-scarce area of Brazil: A case study of the Urucuia Aquifer System

The large groundwater reserves of the Urucuia Aquifer System (UAS) enabled agricultural development and economic growth in the western Bahia State, in northeastern Brazil. Over the last several years, concern has grown around the aquifer’s diminishing water levels, and water balance (WB) studies are in demand. Considering the lack of measured actual evapotranspiration (ET a ), a major component of the water cycle, this work uses the Operational Simplified Surface Energy Balance (SSEBop) model to estimate ET a , and compares it to basin-scale estimates from the Soil Moisture Accounting Procedure (SMAP) monthly model and from an annual WB closure method, based on gridded meteorological data and the Gravity Recovery and Climate Experiment (GRACE) product. Additionally, a comparative assessment of different versions of the SSEBop parameterization was performed. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery was used to implement eight different versions of the SSEBop algorithm over the UAS between 2000 and 2013. SSEBop and SMAP ET a yielded similar seasonal patterns, with correlation coefficient (r) up to 0.65, mean difference (MD) of 0.8 mm/month and mean absolute difference (MAD) of 18.5 mm/month. Comparison of SSEBop annual ET a estimates to annual SMAP and WB closure estimates yielded low MD (12.1 and −7.3 mm/year, respectively) and MAD (82.5 and 82.8 mm/year, respectively), but also low r values (0.00 and 0.37, respectively). The comparison of the different SSEBop versions indicated the need to incorporate a calibration step of the aerodynamic heat resistance (r ah ) parameter. SSEBop results were also used for land cover and drought monitoring. Analysis indicates that agriculture, associated with an increasing trend of atmospheric evaporative demand, is responsible for the decrease in groundwater levels and streamflow in the studied time period.

Urucuia Aquifer System↗
USGS2026

Groundwater quality near an oil field in a stream-dominated recharge setting, California, USA

Alluvial valley aquifers are important sources of water supply in many areas but effects of co-located oil and gas development on these resources have not been widely reported, especially in settings where recharge is dominated by stream infiltration. Interpreting the presence of geochemical indicators in the context of hydrology, geology, and other factors provides a more complete understanding of the relations between groundwater and sources of oil-field fluids and aids in identifying risks associated with oil and gas development. Groundwater and Salinas River water samples were collected in an alluvial valley near the San Ardo Oil Field in Monterey County, California and analyzed for a wide range of dissolved chemical, gas, and isotopic constituents to determine if oil-field fluids (water and gas from oil-producing and non-producing zones) have mixed with fresh groundwater used for supply. Hydraulic gradients, age-dating tracers, and other geochemical indicators show that recharge from the Salinas River has the potential to dilute oil-field fluids that might migrate or seep into the aquifer. Groundwater and Salinas River water collected downgradient of the San Ardo Oil Field showed little or no evidence of mixing with oil-field fluids. Some samples within the oil field contained trace amounts of hydrocarbons or elevated temperatures, indicating that any potential effects from oil-field activities are minor or have been diluted by recharge from the Salinas River. The two samples with the most geochemical evidence of potential mixing with oil-field fluids (SP-18 and GW-17) were collected west of or along the Los Lobos fault, where naturally occurring hydrocarbons are near the land surface. Those samples are also near active or inactive oil-field wells, and so anthropogenic activities and pathways cannot be ruled out as a cause of trace detections of hydrocarbons and elevated temperatures in the aquifer.

California↗
USGS2025

Time-varying rates of organic and inorganic mass accumulation in southeast Louisiana marshes: Relationships to sea-level anomalies and tropical storms

Louisiana's coastal wetlands are complex systems that require a continuous input of organic and inorganic material to keep pace with relative sea-level rise. Coastal restoration projects such as sediment diversions are being implemented to mitigate land loss and increase availability of inorganic sediment to coastal wetlands, and marshes specifically rely on organic material to build soil volume and maintain surface elevation. Interannual-to-decadal sea-level anomalies such as hurricanes can affect marsh accretion, mineral deposition, and plant productivity. In this light, complex ecogeomorphic feedback controls whether a marsh surface is sustainable or eroded/drowns. This study performs some of the first differential vertical accretion rates (VARs) and organic and inorganic mass accumulation rates (MARs) over time in SE Louisiana marshes determined from the 210 Pb Constant Rate of Supply model, coupled with standard 137 Cs VARs. These accumulation rates over the past ∼100 years were measured from a total of six brackish and salt marsh locations in Barataria Basin near the proposed Mid-Barataria Sediment Diversion. They were then related to interannual sea-surface elevations at Grand Isle, Louisiana, over the last ∼60 years and recorded hurricane activity in the delta. Results show VARs range from 0.63 cm/y to 1.69 cm/y and total MARs range from 0.11 to 0.43 g/cm 2 /y. Temporally, VARs and MARs (total, inorganic, and organic) are characterized by gradual increases in rates with decreasing age along with episodic peaks in VARs and MARs. The findings of this study indicate that no relationship occurs between sea-level anomalies and VARs or organic and inorganic MARs; however, a strong relationship appears to occur between major hurricanes to VAR and MAR contributions. Furthermore, high water content (81 ± 8%) and organic-rich soils in the sediment cores highlight the significance of belowground biomass and associated pore volume in maintaining marsh elevation in the study area.

Louisiana↗
USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗
USGS2026

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↗
USGS2024

Assessing potential effects of oil and gas development activities on groundwater quality near and overlying the Elk Hills and North Coles Levee Oil Fields, San Joaquin Valley, California

Groundwater resources are utilized near areas of intensive oil and gas development in California’s San Joaquin Valley. In this study, we examined chemical and isotopic data to assess if thermogenic gas or saline water from oil producing formations have mixed with groundwater near the Elk Hills and North Coles Levee Oil Fields in the southwestern San Joaquin Valley. Major ion concentrations and stable isotope compositions were largely consistent with natural processes, including mixing of different recharge sources and water-rock interactions. Trace methane concentrations likely resulted from microbial rather than thermogenic sources. Trace concentrations of benzene and other dissolved hydrocarbons in three wells had uncertain sources that could occur naturally or be derived from oil and gas development activities or other anthropogenic sources. In the mid-1990s, two industrial supply wells had increasing Cl and B concentrations likely explained by mixing with up to 15 percent saline oil-field water injected for disposal in nearby injection disposal wells. Shallow groundwater along the western margin of Buena Vista Lake Bed had elevated Cl, B, and SO 4 concentrations that could be explained by accumulation of salts during natural wetting and drying cycles or, alternatively, legacy surface disposal of saline oil-field water in upgradient ephemeral drainages. This study showed that groundwater had relatively little evidence of thermogenic gas or saline water from oil and gas sources in most parts of the study area. However, the evidence for groundwater mixing with injected disposal water, and possibly legacy surface disposal water, demonstrates produced water management practices as a potential risk factor for groundwater-quality degradation near oil and gas fields. Additional studies in the San Joaquin Valley and elsewhere could improve understanding of such risks by assessing the locations, volumes, and types of produced water disposal practices used during the life of oil fields.

California↗
USGS2024

Near-real-time earthquake-induced fatality estimation using crowdsourced data and few-shot large-language models

When a damaging earthquake occurs, immediate information about casualties (e.g., fatalities and injuries) is critical for time-sensitive decision-making by emergency response and aid agencies in the first hours and days. Systems such as the Prompt Assessment of Global Earthquakes for Response (PAGER) by the U.S. Geological Survey (USGS) were developed to provide a forecast of such impacts within about 30 min of any significant earthquake globally. However, existing disaster-induced human loss estimation systems often rely on early casualty reports manually retrieved from global traditional media, which are labor-intensive, time-consuming, and have significant time latencies. Recent approaches use keyword matching and topic modeling to identify human casualty-relevant information from social media but tend to be error-prone when dealing with complex semantics in multi-lingual text data and parsing dynamically changing and conflicting human death and injury numbers shared by various unvetted sources in social media platforms. In this work, we introduce an end-to-end framework to significantly improve the timeliness and accuracy of global earthquake-induced human loss forecasting using multi-lingual, crowdsourced social media. Our framework integrates (i) a hierarchical casualty extraction model built upon large language models, prompt design, and few-shot learning to retrieve quantitative human loss claims from social media, (ii) a physical constraint-aware, dynamic-truth discovery model that discovers the truthful human loss from massive noisy and potentially conflicting human loss claims, and (iii) a Bayesian updating loss projection model that dynamically updates the final loss estimation using discovered truths. We test the framework in real-time on a series of global earthquake events in 2021 and 2022 and show that our framework effectively automates the retrieval of casualty information faster but with comparable accuracy to those now retrieved manually by the USGS. The code associated with this work is made available at: https://github.com/SusuXu-s-Lab/Hierarchical-Earthquake-Casualty-Information-Retrieval

International Journal of Disaster Risk Reduction↗
USGS2026

Potential impacts of groundwater pumping on stream temperature are greatest in streams with substantial cold groundwater inflows

Groundwater pumping-induced reductions in streamflow (known as ‘streamflow depletion’) have been documented worldwide, but potential impacts of streamflow depletion on stream temperature are not well understood. Here, we use two types of models to identify potential impacts of pumping on stream temperature across the conterminous United States (CONUS) to determine which aspects of a stream's annual thermograph (thermal signatures) can be used to monitor and manage streamflow depletion impacts on stream temperature. We used long-term streamflow and stream temperature data from 30 streamgages across CONUS and surrogate models of streamflow depletion to analyse potential stream temperature impacts at each site. We compared two different stream temperature modelling approaches: (i) a process-based energy balance model and (ii) statistical regression models based on air temperature and stream discharge. We calculated a suite of thermal signatures under depleted and non-depleted conditions for each stream and found that maximum annual 7-day temperature and annual temperature range are potentially the most sensitive to streamflow depletion, with potential changes of at least 2°C at > 70% of the sites when using the process-based model. We also found that the regression-based models predicted much less sensitivity of stream temperature to streamflow depletion than the process-based model. This work provides an initial evaluation and sensitivity analysis of the potential impacts of streamflow depletion on stream temperature. We demonstrate that stream temperature may be most sensitive to pumping in streams with a high proportion of flow sourced from relatively cold groundwater inputs, and that regression-based stream temperature models may underpredict stream temperature changes caused by streamflow depletion.

conterminous United States↗