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USGS2025

Reservoir thermal energy storage pre-assessment for the United States

Storing thermal energy underground for later use in electricity production or direct-use heating/cooling is a promising, viable, and economical green energy option. Reservoir thermal energy storage (RTES) is one such option, which stores energy in underutilized permeable strata with low ambient groundwater flow rates and more geochemically evolved (e.g. brackish/saline) waters relative to overlying principal aquifer systems. The U.S. Geological Survey has begun assessing RTES potential nationally by focusing on five generalized geologic regions (Basin and Range, Coastal Plain, Illinois Basin, Michigan Basin, Pacific Northwest) across the United States. Hydrogeologic reservoir models are developed for the following eight metropolitan area cities within those regions to evaluate RTES performance across different climates and subsurface conditions: Albuquerque, New Mexico; Charleston, South Carolina; Chicago and Decatur, Illinois; Lansing, Michigan; Memphis, Tennessee; Phoenix, Arizona; and Portland, Oregon. Evaluated metrics include estimated required well spacing, thermal storage capacity, and thermal recovery efficiency through time. Also considered for each reservoir are potential complicating factors, including reservoir depth, thermally driven free convection, and groundwater salinity. This work focuses on direct-use cooling because the need for cooling modern office buildings greatly exceeds that for heating in most parts of the country (Falta and others, 2016); however, the evaluated metrics are also relevant to heating and electricity applications. Results indicate that favorable RTES conditions exist in each region, with the Coastal Plain and Basin and Range being especially favorable for thermal storage capacity, while the Pacific Northwest and Michigan Basin excel at energy recovery for the evaluated cooling application. The results underscore the utility of developing maps of thermal storage capacity, subsurface temperature models, and volumetric estimates of thermal storage capacity to serve as key RTES resource classification standards. Overall, this pre-assessment provides a basic understanding of RTES potential in several cities and geologic regions throughout the country and will aid ongoing thermal energy storage assessment efforts.

Arizona, Illinois, Michigan, New Mexico, Oregon, S↗
USGS2026

Ice sheet dynamics drive pronounced changes in the subsurface freshwater-saltwater interface

Saltwater is migrating into freshwater aquifers globally with water quality and biogeochemical implications, yet saltwater intrusion in glaciated regions is sparsely investigated. Field observations suggest that groundwater head in glaciated systems is influenced by ice sheet forcings and provides evidence that seawater infiltrated into offshore aquifers during past deglaciation events. To understand links between ice sheet dynamics, groundwater head, and saltwater intrusion, we use numerical models to explore the effects of deglaciation on nearshore head and salinity distributions. We find that ice sheet thinning diminishes groundwater head, and the resulting shift in subsurface pressure gradients drives rapid landward movement of the subsurface freshwater-saltwater interface up to 4.0 km or 1.3 m per m ice sheet loss. Results highlight an overlooked saltwater intrusion mechanism that aligns with field observations and affects glaciated coastlines undergoing ice sheet retreat, underscoring the need to consider this mechanism in studies of contemporary coastal water quality.

Geophysical Research Letters↗
USGS2026

Ductile and brittle Rio Grande Rift deformation in Oligocene granite records a two-stage rift history in southern Colorado

The timing and nature of early deformation in the Rio Grande Rift remains poorly constrained. We present evidence for the earliest structural signature of rift extension in the Sangre de Cristo Range, southern Colorado, based on new geologic mapping, structural analysis, rock magnetic data, and thermochronology. These analyses focus on the ~30.0 Ma granite of Chokecherry Canyon, which hosts discrete low-angle mylonitic shear zones and a distributed, gently SW-dipping protomylonitic fabric. Incremental stretching axes, stretching lineations, and Kmax magnetic lineations plunge gently WSW. Quartz microstructures and crystallographic orientations indicate dominantly coaxial strain in the protomylonite and general shear in the discrete shear zones. Quartz c-axis opening-angle thermometry suggests deformation at ~420–540°C. Thermal modeling of ⁴⁰Ar/³⁹Ar K-feldspar data indicates rapid post magmatic cooling below the brittle–plastic transition, supporting shear-zone formation immediately after emplacement. Slow cooling from ~20–13 Ma was followed by renewed rapid cooling at ~13 Ma, interpreted as the onset of extensional exhumation along the Sangre de Cristo Fault System. These results show that extension in the northern Rio Grande Rift was active by ~30 Ma, earlier than previously recognized. We propose a two-stage model for northern Rio Grande Rift evolution: Stage I (30–23 Ma) records ENE–WSW extension localized in low-angle mylonitic shear zones associated with mid-crustal intrusions; Stage II (≤18 Ma) reflects brittle high-angle normal faulting, focused exhumation, and rift narrowing. Stage I magmatism and deformation along the western range front likely established crustal weaknesses that guided later fault development.

Colorado↗
USGS2026

Linking distribution and return-on-investment models to optimize woody management for prairie grouse in Nebraska

Grasslands in Nebraska, USA, face threats from agricultural conversion, urban development, and woody encroachment, all of which negatively affect prairie grouse ( Tympanuchus spp.) populations. To optimize conservation planning, Nebraska wildlife agencies developed probabilistic area-based surveys for greater prairie-chicken ( T. cupido ) and sharp-tailed grouse ( T. phasianellus ) to sample landscapes across a range of environmental conditions. This design improves historical surveys and enables the development of distribution models that quantitatively define habitat associations and support scenario-based conservation planning. Using survey data collected during 2020–2022, we modeled prairie grouse occurrence and abundance as functions of land cover, topography, and climate using Bayesian logistic and zero-inflated negative binomial models with regularized horseshoe priors. We then conducted a maximum potential return-on-investment analysis of woody cover treatments, assuming sustained treatment success, relative to projected impacts of woody encroachment on prairie grouse populations by 2050. Among modeled associations were a positive association with grasslands having low woody cover and a negative association with grasslands having high woody cover. Across the 3-year period, median estimated annual populations were 142,380 for greater prairie-chicken (range of 95% CIs across years = 68,821–277,615) and 64,154 for sharp-tailed grouse (range of 95% CIs across years = 27,550–146,559). Under projected woody encroachment, mean predicted population declines were 10% for greater prairie-chicken (range of 95% CIs = 7–14%) and 6% for sharp-tailed grouse (range of 95% CIs = 5–7%). Areas with high prairie grouse density and low treatment costs in 2021, and high projected woody encroachment and population loss by 2050, offered the greatest return on investment for woody management. Return on investment was greatest in the northwestern Shortgrass Prairie ecoregion (northwestern Nebraska) for sharp-tailed grouse and the eastern Sandhills ecoregion (central Nebraska) for both species. These models underscore the value of evidence-based, quantitative approaches for prioritizing conservation actions on working lands. Scenario-based modeling could be extended to guide other treatments, such as optimizing restoration (e.g., Conservation Reserve Program) or incentivizing grassland persistence in areas with predicted climate resilience.

Nebraska↗
USGS2026

Multi-objective optimization of a hydro-economic model in an over-allocated agricultural basin

Groundwater depletion for agricultural irrigation poses significant environmental and economic challenges. This study introduces a proof-of-concept that combines hydro-economic modeling, scenario-based modeling, and multi-objective optimization to manage pumping curtailment in an over-allocated basin in the western United States. Three optimization scenarios were evaluated, each offering different degrees of management flexibility. Results reveal that scenarios with finer spatial resolution achieved greater environmental benefits per unit profit loss. Additionally, strategies allowing fractional reductions in curtailed wells–rather than complete shutdowns based on water rights seniority–substantially improved efficiency, highlighting the value of increased decision-making flexibility. Although scenario testing can aid stakeholder engagement and strategy exploration, multi-objective optimization provides a systematic framework to quantify tradeoffs between competing objectives. This combined approach demonstrates promise for building consensus and supporting the design of sustainable water management strategies that balance agricultural livelihoods with ecosystem preservation.

Oregon↗
USGS2026

Monitoring changes in Landsat thermal features in urban and non-urban interfaces from 1986 to 2023 in two international urban centers: Implications for climate and global issues

Rapid urbanization is reshaping thermal environments worldwide, with the strongest impacts occurring at the interface between urban and non-urban areas. Impervious surfaces, as key indicators of urban expansion, are critical for monitoring urban growth and assessing surface urban heat island (SUHI) effects. Land use and land cover change (LULCC) provides an essential link between urban dynamics and their environmental and societal consequences. Here, we integrated the U.S. Geological Survey (USGS) Climate Global Issues (CGI) Land Cover Product with Landsat thermal time-series to investigate SUHI evolution in two contrasting metropolitan regions: Wuhan, China, and Brasília, Brazil. Using data spanning 1986–2023, we analyzed the relationships between land cover, Landsat-based land surface temperature (LST), and SUHI intensity, and identified persistent thermal hotspots. Results demonstrate that the land cover data utilized increases the accuracy of impervious surface mapping along urban–rural gradients. Average SUHI intensities were 3.4 °C in Wuhan and 3.3 °C in Brasília, with statistically significant warming trends of 0.04 °C/year and 0.01 °C/year, respectively. Maximum temperature proved to be a robust indicator of SUHI intensification, capturing long-term upward trends. Our findings highlight the important role of urban land cover dynamics in shaping temporal SUHI variability and hotspot emergence. This prototype framework demonstrates the scientific and policy value of combining long-term land cover monitoring information with satellite thermal monitoring to quantify and track SUHI at city scale, supporting sustainable urban planning and climate adaptation strategies.

Remote Sensing↗
USGS2025

Flow heterogeneity controls dissolution dynamics in topologically complex rocks

Rock dissolution is a common subsurface geochemical reaction affecting pore space properties, crucial for reservoir stimulation, carbon storage, and geothermal energy. Predictive models for dissolution remain limited due to incomplete understanding of the mechanisms involved. We examine the influence of flow, transport, and reaction regimes on mineral dissolution using 29 time-resolved data from 3D rocks. We find that initial pore structure significantly influences the dissolution pattern, with reaction rates up to two orders of magnitude lower than batch conditions, given solute and fluid-solid boundary constraints. Flow unevenness determines the location and rate of dissolution. We propose two models describing expected dissolution patterns and effective reaction rates based on dimensionless metrics for flow, transport, and reaction. Finally, we analyze feedback between evolving flow and pore structure to understand conditions that regulate/reinforce dissolution hotspots. Our findings underscore the major impact of flow arrangement on reaction-front propagation and provide a foundation for controlling dissolution hotspots.

Geophysical Research Letters↗
USGS2026

Groundwater dependency and hydroclimatic influences on riparian and upland vegetation productivity, Upper San Pedro, Arizona, United States

In arid and semi-arid regions, groundwater sustains vegetation through subsurface water access, yet the responses of groundwater-dependent ecosystems (GDEs) to changing hydroclimate and groundwater availability are relatively understudied. This study investigates seasonal and spatial patterns in vegetation greenness using Landsat Enhanced Vegetation Index (EVI) values across riparian and upland zones in the semi-arid Upper San Pedro (USP) watershed, southern Arizona, which experiences a bimodal precipitation regime. We paired 25 years (2000–2024) of EVI and depth to groundwater (DTG) data from 89 wells and climate metrics (precipitation and vapour pressure deficit) to quantify the sensitivity of vegetation to subsurface moisture as well as atmospheric moisture supply and demand. Vegetation at wells near the USP riparian area showed strong associations between EVI and DTG anomalies during the monsoon season, indicating sustained groundwater use even during this wet period when summer precipitation is abundant. In contrast, upland vegetation that lacked access to groundwater showed minimal sensitivity in EVI to DTG and was generally less responsive to vapour pressure deficit. Interestingly, the riparian GDEs were not decoupled from precipitation and climate variability. These results underscore the importance of groundwater for maintaining riparian productivity and highlight the utility of remote sensing in identifying vegetation-climate-groundwater linkages across heterogeneous dryland landscapes.

Arizona↗
USGS2026

Transcriptional changes in wild Yukon River Chinook Salmon associated with Ichthyophonus infections

Objective We compared differentially expressed genes in Chinook Salmon Oncorhynchus tshawytscha with three divergent Ichthyophonus statuses (undetected, subclinical infections, or clinical disease; n = 100) to investigate associated transcriptomic responses. Disease associated with the fish parasite Ichthyophonus sp. was first diagnosed in adult Chinook Salmon from the Yukon River in the late 1980s and has subsequently been implicated in premature host mortality. Methods Chinook Salmon tissue sample collections and Ichthyophonus infection data were leveraged from a multi-agency collaboration during summer 2022 at three locations along the main-stem Yukon River that spanned nearly 2,000 km of freshwater migration (lower, middle, and upper river). We sequenced the transcriptome and compared this to infection status based on routine diagnostic procedures. Results Among the 17,569 genes for which messenger RNA was detected, we identified a transcription signature in the skeletal muscle that was associated with Ichthyophonus infections and included 53 differentially expressed genes. The differentially expressed genes and their pathways included those known for involvement in immune functions, energy synthesis, cellular breakdown, and reproduction—all processes that are known to be influenced by senescence during spawning migrations. Conclusions Results demonstrate a clear transcriptional difference between diseased fish (clinical disease group) and those in which Ichthyophonus was undetected, including identifying candidate markers for infection in this population. These results provide a foundation for development of nonlethal biomarkers to evaluate potential Ichthyophonus infections in Chinook Salmon based on gene transcription, protein products, or gene variants (e.g., polymorphisms).

Journal of Aquatic Animal Health↗
USGS2025

Drone-based radiometric surveys provide high-resolution mine waste characterization

Airborne radiometric surveys use passive geophysical techniques to characterize geochemical variations at or near earth’s surface. These methods have been used for a variety of mapping applications, including mineral resource evaluation. However, detailed characterization of smaller geologic targets, including mine waste features, requires flying at lower altitudes and with tighter line spacing than is feasible with traditional aircraft. Here, a small uncrewed aircraft system (sUAS) equipped with a radiometric sensor was used to acquire high-resolution gamma-spectrometry over small mine waste features and a low-grade stockpile in southwestern New Mexico. The sUAS radiometric system mapped local variability within each survey area and revealed ~2–10 m wide zones where radioelements K, Th, and U may be elevated 2–10× the surrounding material. Additionally, the sUAS radiometric data revealed radioelement variability across survey sites, which correlated reasonably well with variability seen in geochemical samples at each survey site, even though samples collected from individual sites showed high local variability. The sUAS data characterized local heterogeneity within mine waste and other small geologic targets at scales of a few meters to tens of meters, which is not possible with traditional crewed aircraft, and with continuity of coverage that is not possible with ground surveys, thus filling a key gap in geophysical survey spatial resolution.

New Mexico↗
USGS2024

Cold blood in warming waters: Effects of air temperature, precipitation, and groundwater on Gulf Sturgeon thermal habitats in a changing climate

Objective In a changing climate, the effects of air temperature, precipitation, and groundwater on water temperature and thermal habitat suitability for Gulf Sturgeon Acipenser desotoi , listed as threatened under the U.S. Endangered Species Act, are not well understood. Hence, we incorporated these factors into thermal habitat models to forecast how Gulf Sturgeon may be affected by wide‐ranging climate change scenarios in 2024–2074. Methods Using data from the Choctawhatchee River, Florida, we developed precipitation‐ and groundwater‐corrected air–water temperature models, compared their accuracy with that of conventional air–water temperature models used in fisheries management, and projected future Gulf Sturgeon thermal habitat suitability for normal physiological functioning and fieldwork (i.e., population sampling and telemetry surgeries) in summer (May–August) under 16 climate change scenarios. Result Precipitation‐ and groundwater‐corrected models were more accurate than conventional air–water temperature models (mean improvement in adjusted R 2 = +0.45; range = +0.09 to +0.75). Water temperature was projected to warm at widely variable rates across climate change scenarios encompassing different air temperature, precipitation, and groundwater regimes. Importantly, Gulf Sturgeon summer aggregation areas were cooler and influenced more by precipitation and groundwater and less by air temperature than were non‐aggregation areas. If precipitation and groundwater—as drivers of cooling—become warm in a changing climate, summer aggregation areas were projected to exhibit thermal habitat degradation equivalent to or greater than that of non‐aggregation areas. Conclusion Our results add hydrological context to the premise that aggregation areas provide cool water and energetic savings for Gulf Sturgeon during summer, underscoring the importance of protecting these habitats through groundwater conservation, water quality monitoring, and riparian/watershed habitat management. Our findings indicate that identifying thermally appropriate times for fieldwork activities will be increasingly important and time‐restricted as climate change intensifies. However, our research provides managers with a portfolio of water temperature models and an accurate, cost‐effective, management‐relevant approach to forecasting thermal habitat conditions for Gulf Sturgeon and other species in a changing climate.

Alabama, Florida↗
USGS2025

Towards mobile wind measurements using joust configured ultrasonic anemometer for applications in gas flux quantification

Small uncrewed aerial systems (sUASs) can be used to quantify emissions of greenhouse and other gases, providing flexibility in quantifying these emissions from a multitude of sources, including oil and gas infrastructure, volcano plumes, wildfire emissions, and natural sources. However, sUAS-based emission estimates are sensitive to the accuracy of wind speed and direction measurements. In this study, we examined how filtering and correcting sUAS-based wind measurements affects data accuracy by comparing data from a miniature ultrasonic anemometer mounted on a sUAS in a joust configuration to highly accurate wind data taken from a nearby eddy covariance flux tower (aka the Tower). These corrections had a small effect on wind speed error, but reduced wind direction errors from 50° to >120° to 20–30°. A concurrent experiment examining the amount of error due to the sUAS and the Tower not being co-located showed that the impact of this separation was 0.16–0.21 ms − 1 "> ms − 1 , a small influence on wind speed errors. Lower wind speed errors were correlated with lower turbulence intensity and higher relative wind speeds. There were also some loose trends in diminished wind direction errors at higher relative wind speeds. Therefore, to improve the quality of sUAS-based wind measurements, our study suggested that flight planning consider optimizing conditions that can lower turbulence intensity and maximize relative wind speeds as well as include post-flight corrections.

Alaska↗
USGS2025

Road salt collection and redistribution at an urban rain garden on sandy soil, Gary, Indiana

Rain gardens installed as green infrastructure to divert storm runoff from entering combined sewers also collect dissolved constituents and particulates. An urban rain garden in northwestern Indiana, USA, was continuously monitored from November 2019 to May 2021 to evaluate the fate of dissolved constituents entering the rain garden in runoff. Physical and chemical properties of soils in the rain garden were also monitored, along with underlying groundwater. Linear regression models relating specific conductance to chloride concentration indicated that the 0.0371-ha (3998 square feet) rain garden collected approximately 1490 kg (3285 pounds) of road salt from the surrounding 0.2228 ha (24,500 square feet) of impervious surfaces. Soils and groundwater were seasonally affected by road salt application but carryover from year to year was not indicated. Rain garden soil permeability (5.20 × 10 −5 to 9.72 × 10 −5 m/s) remained unchanged during the study period and soil organic carbon generally increased under native vegetation. The results suggest that a rain garden built on sandy soil can divert substantial quantities of runoff and dissolved constituents from combined sewers; however, chloride is transported to sub-infrastructure groundwater that eventually discharges to adjacent waterways with concentrations lower than those observed in runoff.

Indiana↗
USGS1990

Preconditioned Conjugate-Gradient 2 (PCG2), a computer program for solving ground-water flow equations

This report documents PCG2: a numerical code to be used with the U.S. Geological Survey modular three-dimensional, finite-difference, ground-water flow model. PCG2 uses the preconditioned conjugate-gradient method to solve the equations produced by the model for hydraulic head. Linear or nonlinear flow conditions may be simulated. PCG2 includes two reconditioning options: modified incomplete Cholesky preconditioning, which is efficient on scalar computers; and polynomial preconditioning, which requires less computer storage and, with modifications that depend on the computer used, is most efficient on vector computers. Convergence of the solver is determined using both head-change and residual criteria. Nonlinear problems are solved using Picard iterations. This documentation provides a description of the preconditioned conjugate gradient method and the two preconditioners, detailed instructions for linking PCG2 to the modular model, sample data inputs, a brief description of PCG2, and a FORTRAN listing.

Water-Resources Investigations Report↗
USGS2025

Updating regional‐scale geospatial liquefaction models with locally available geotechnical data

We present a method to update the geospatial liquefaction model used by the U.S. Geological Survey’s near‐real‐time ground failure product with subsurface geotechnical data. The geospatial model estimates liquefaction probability from peak ground velocity (via ShakeMap) and geospatial susceptibility proxies. In many regions, additional information relevant to constraining liquefaction likelihood is also available, including surface geology maps and subsurface geotechnical measurements. There is currently no mechanism to use these data in the ground failure product liquefaction model, even though these data could provide more precise constraints on spatial variations in the lithologic character of the soil (surface geology) and direct measurements of the subsurface mechanical properties that affect liquefaction occurrence and severity (geotechnical measurements). In this study, we develop a method to integrate these data with the geospatial model and assess how these data can improve regional‐scale predictions. We develop a Bayesian updating framework and apply it to the 1989 magnitude 6.9 Loma Prieta, California, earthquake, for which mapped observations are available to evaluate performance. We constrain the Bayesian framework with 373 Northern California cone penetration tests and liquefaction susceptibility classes based on the mapped surface geology. This Bayesian model incorporates geotechnical information into the geospatial model and more accurately predicts liquefaction occurrences than the geospatial model, while sacrificing less accuracy in terms of predicting the absence of liquefaction than the geotechnical model. In future applications, this approach could be adapted to update other geospatial models using locally available subsurface data.

California↗
USGS2024

Metal mobilization from thawing permafrost to aquatic ecosystems is driving rusting of Arctic streams

Climate change in the Arctic is altering watershed hydrologic processes and biogeochemistry. Here, we present an emergent threat to Arctic watersheds based on observations from 75 streams in Alaska’s Brooks Range that recently turned orange, reflecting increased loading of iron and toxic metals. Using remote sensing, we constrain the timing of stream discoloration to the last 10 years, a period of rapid warming and snowfall, suggesting impairment is likely due to permafrost thaw. Thawing permafrost can foster chemical weathering of minerals, microbial reduction of soil iron, and groundwater transport of metals to streams. Compared to clear reference streams, orange streams have lower pH, higher turbidity, and higher sulfate, iron, and trace metal concentrations, supporting sulfide mineral weathering as a primary mobilization process. Stream discoloration was associated with dramatic declines in macroinvertebrate diversity and fish abundance. These findings have considerable implications for drinking water supplies and subsistence fisheries in rural Alaska.

Alaska↗
USGS2025

USGS addresses needs for lithium calibration and quality control materials for pLIBS analysis

Lithium (Li) is a globally important commodity used for energy storage, national defense, human health, and advanced technologies. Lithium resource development requires identifying deposits with elevated concentrations and optimal mineralogy, typically associated with select clays and pegmatites. Lithium is a light, highly reactive alkali metal with low atomic mass that is difficult to detect and quantify using conventional portable geochemical techniques such as X-ray fluorescence (XRF). However, portable laser-induced breakdown spectroscopy (pLIBS) is a powerful analytical technique for lithium exploration due to its ability to analyze solids quickly with minimal preparation. The expanded utility of pLIBS is hampered by the lack of matrix-matched calibration and quality control (QC) materials. The United States Geological Survey (USGS) has developed in-house lithium calibration and QC materials for lithium in clay and pegmatite matrices to address this limitation. We present the workflow and implementation of a custom-built matrix specific calibration on a SciAps Z-300 pLIBS, using proprietary Profile Builder software. The implementation of the custom calibration and quality control standards enables us to collect semiquantitative results directly from the pLIBS while in the field. Ultimately, this calibration has improved confidence in sample selection and collection in the field, providing more efficient site characterization.

Conference Paper↗