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1,688 records · Page 85Linked to original sources
USGS2026

Spatio-temporal modeling for assessing geoenergy resources: A workflow applied to gas in place variation in coal beds

The ability to estimate spatio-temporal changes in hydrocarbon reservoir properties and energy resources within pore volumes is essential for optimizing production, reservoir management, geologic energy storage, and safety in underground mining operations. In coal seams, predicting remaining methane gas-in-place (GIP) is critical for quantifying producible gas and improving mine safety and productivity through effective ventilation planning. Although such changes are commonly evaluated using physics-based numerical simulation models, these approaches often require extensive data, calibration effort, and time. This study presents a spatio-temporal geostatistical modeling approach that bridges the gap between purely spatial models and full numerical simulations. The method is applied to a case study of coal seam degasification in the Mary Lee coal group, Black Warrior Basin, Alabama, USA, to estimate GIP evolution over time within a selected mining district. The analysis uses published data from prior natural gas production history-matching of degasification using vertical wells. Empirical spatial and temporal statistics were calculated for reservoir pressure and water saturation, and spatio-temporal variogram models were fitted to experimental variograms. These models provided the structural basis for spatio-temporal kriging, integrated with spatial estimates of time-invariant parameters (porosity, density, and thickness) to estimate GIP. This approach enabled estimation of GIP changes over time, including periods without data. Boxplots of GIP estimates indicated systematic depletion and decreasing spatial variability, reflecting the impacts of degasification. Comparison with cumulative gas production from empirical well records showed approximately 85% agreement based on a relative similarity metric. Spatio-temporal GIP estimates were also used to estimate methane emissions to longwall ventilation systems and compared with reported emissions from the U.S. EPA Greenhouse Gas Reporting Program, showing similar distributions (≈80%) given data limitations. Overall, this integrated modeling approach provides time-dependent GIP estimates with broader implications for resource assessment applications.

Alabama↗
USGS2024

Mapping Arundo donax (Arundo cane) with multispectral imagery before, during, and after herbicide treatment along the Rio Grande in Webb County, Texas, 2020–21

Arundo donax , commonly called Arundo cane, giant reed, or Carrizo cane, is an invasive bamboo-like perennial grass common in riparian areas throughout the southwestern United States. In Texas, not only does it negatively affect riparian ecosystems, but it has also become a problem for border security because it reduces visibility along the Rio Grande. To address these problems, in 2015 the Texas State Soil and Water Conservation Board was authorized by the Texas State Legislature to develop a program to eradicate Arundo cane along the Rio Grande. In 2020, the Texas State Soil and Water Conservation Board applied imazapyr and glyphosate herbicides along a 19.3-kilometer reach of the Rio Grande, northwest of Laredo, Texas. The U.S. Geological Survey, in cooperation with the Texas State Soil and Water Conservation Board and the Webb Soil and Water Conservation District, used WorldView-3 Standard high-resolution satellite imagery to map Arundo cane extent along the reach before , during , and after the herbicide-treatment period on June 30, 2020, September 26, 2020, and May 7, 2021, respectively. A maximum likelihood supervised classification analysis was computed on the images to map the spatial extent and estimate the area covered by Arundo cane. The estimated area covered by Arundo cane in the before classification was 1,282,000 square meters, in the during classification was 1,064,000 square meters, and in the after classification was 1,108,000 square meters. The qualitative comparison of the three images shows that there was an overall decrease in vegetation classified as Arundo cane throughout the study area.

Texas↗
USGS1999

Reconfigured-Channel Monitoring and Assessment Program

A U.S. Geological Survey program to monitor and assess channel reconfiguration activity is described. A data base available on the world wide web will enable land-management agencies and other interested parties to evaluate the long-term success of various channel reconfiguration projects. A demonstration project on the Lake Fork of the Gunnison River, Colorado, illustrates the program objectives and approach.

Colorado↗
USGS2024

Declining groundwater storage expected to amplify mountain streamflow reductions in a warmer world

Groundwater interactions with mountain streams are often simplified in model projections, potentially leading to inaccurate estimates of streamflow response to climate change. Here, using a high-resolution, integrated hydrological model extending 400 m into the subsurface, we find groundwater an important and stable source of historical streamflow in a mountainous watershed of the Colorado River. In a warmer climate, increased forest water use is predicted to reduce groundwater recharge resulting in groundwater storage loss. Losses are expected to be most severe during dry years and cannot recover to historical levels even during simulated wet periods. Groundwater depletion substantially reduces annual streamflow with intermittent conditions predicted when precipitation is low. Expanding results across the region suggests groundwater declines will be highest in the Colorado Headwater and Gunnison basins. Our research highlights the tight coupling of vegetation and groundwater dynamics and that excluding explicit groundwater response to warming may underestimate future reductions in mountain streamflow.

Nature Water↗
USGS2025

No evidence for an active margin-spanning megasplay fault at the Cascadia Subduction Zone

It has been previously proposed that a megasplay fault within the Cascadia accretionary wedge, spanning from offshore Vancouver Island to Oregon, has the potential to slip during a future Cascadia subduction zone earthquake. This hypothetical fault has major implications for tsunami size and arrival times and is included in disaster-planning scenarios currently in use in the region. This hypothesis is evaluated in this study using CASIE21 deep-penetrating and U.S. Geological Survey high-resolution seismic reflection profiles. We map changes in wedge structural style and seismic character to identify the inner-outer wedge transition zone where a megasplay fault has been previously hypothesized to exist and evaluate evidence for active faulting within this zone. Our results indicate that there is not an active, through-going megasplay fault in Cascadia, but instead, the structure and activity of faulting at the inner-outer wedge transition zone is highly variable and segmented along strike, consistent with the segmentation of other physical and mechanical properties in Cascadia. Wedge sedimentation, plate dip, and subducting topography are proposed to play a major role in controlling megasplay fault development and evolution. Incorporating updated megasplay fault location, geometry, and activity into modeling of Cascadia earthquakes and tsunamis could help better constrain associated hazards.

British Columbia, Oregon, Washington↗
USGS2026

Chronic exposure to waterborne nickel significantly reduced growth of juvenile crayfish (Faxonius virilis)

Crayfish are critical functional components of aquatic ecosystems. Previous research has documented adverse effects of mineral extraction on crayfish. Here, we characterize potential risks of mining-derived waterborne nickel (Ni) to crayfish by documenting the effects of dissolved Ni on growth and food consumption of juvenile virile crayfish ( Faxonius virilis) in a 28-day chronic laboratory exposure. Nominal Ni concentrations ranged from 31.25 to 500 micrograms per liter (µg/L; pH = 7.96 ± 0.20, hardness = 150 ± 1 milligrams per liter as calcium carbonate). Crayfish survival, carapace length, and wet weight were measured. After 28 days of exposure, a 24-h feeding trial was performed to determine differences in food consumption. During the growth trial, 99% of crayfish survived. Change in wet weight and final wet weight were the most sensitive endpoints, with 20% effect concentrations of 24.8 and 22.6 µg/L Ni, respectively. Crayfish exposed to an average of 438 µg/L Ni consumed 41% less, and weighed 65.1% less, than control crayfish. These results suggest chronic, sublethal exposure to waterborne Ni may have negative effects on crayfish growth. Reduced growth and consumption rates in crayfish could have wide-ranging consequences throughout aquatic ecosystems since crayfish are consumers, prey, keystone trophic regulators, and ecosystem engineers. Finally, these results could inform bioenergetics and may be coupled with population models to predict potential changes in population sizes of native and invasive crayfishes.

Ecotoxicology↗
USGS2025

Fingerprinting magmatic REE deposit sources with zircon petrochronology

Carbonatites and associated alkaline silicate rocks are of considerable economic interest due to their enrichments in rare earth elements. The petrogenesis and source(s) of these complexes, however, are poorly understood. Models propose either mantle plume-derived carbon-rich melts or a mantle source enriched by subduction-related metasomatism. We use zircon trace elements to fingerprint carbonatite-alkaline complex sources, focusing on the economically significant 1.4 Ga Mountain Pass intrusive suite (MPIS). Autocrystic zircon from MPIS alkaline silicate rocks are enriched in Th and U relative to Nb suggesting a subduction influenced, oxidized source region. Lower Sc/Yb, higher Ti concentrations, and the absence of Eu anomalies in autocrystic zircon suggest derivation from a less hydrous, hotter, and deeper mantle source relative to arc-related 1.8–1.6 Ga inherited zircon. These data are best explained by syn- to post-collisional Mesoproterozoic reactivation of a subduction-metasomatized mantle source. The source and tectonic setting of the MPIS contrasts with Mesoproterozoic Gifford Creek and Bayan Obo carbonatites which exhibit plume-like compositions and are associated with rifts, suggesting different sources and tectonic settings for these economically significant deposits. We demonstrate that zircon petrochronology is a robust method for distinguishing carbonatite sources and can inform more targeted exploration strategies for critical mineral resources.

Conference Paper↗
USGS2024

Potential climate and human water-use effects on water-quality trends in a semiarid, western U.S. watershed: Fountain Creek, Colorado, USA

Nutrients, total dissolved solids (TDS), and trace elements affect the suitability of water for human and natural needs. Here, trends in such water-quality constituents are analyzed for 1999–2022 for eight nested monitoring sites in the 24,000 km 2 Fountain Creek watershed in Colorado, USA, by using the weighted regressions on time, discharge, and season (WRTDS) methodology. Fountain Creek shares characteristics with other western U.S. watersheds: (1) an expanding but more water-efficient population, (2) a heavy reliance on imported water, (3) a semiarid climate trending towards warmer and drier conditions, and (4) shifts of water from agricultural to municipal uses. The WRTDS analysis found both upward and downward trends in the concentrations of nutrients that reflected possible shifts in effluent management, instream uptake, and water conservation by a watershed population that grew by about 40%. Selenium, other trace elements, and TDS can pose water-quality challenges downstream and their concentrations were found to have a downwards trend. Those trends could be driven by either a warming and drying of the local climate or decreased agricultural irrigation, as both would reduce recharge and subsequent mobilization from natural geologic sources via groundwater discharge. The patterns illustrate how changes in climate and water use may have affected water quality in Fountain Creek and demonstrate the patterns to look for in other western watersheds.

Colorado↗
USGS2025

Gulf Coast Basin CORE-CM initiative final report

The Bureau of Economic Geology at the University of Texas at Austin (UT-BEG) is leading the Gulf Coast Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) Initiative to assess the potential to produce critical minerals (CMs), including rare earth elements (REEs) from coal, coal ash, and produced water related to oil and gas production, and related materials (alumina processing waste [red mud], heavy mineral sands, graphite, and zeolite) within the Gulf Coast Basin. This project represents the first phase in a long-term program and provides reconnaissance data that will be foundational for future work by assessing resources and suggesting plans to be conducted in future work and expanding stakeholder engagement. The project includes several tasks designed to identify, characterize, and assess several necessary aspects for development of CMs and REEs in the Gulf Coast Basin.

Gulf Coast basin↗
USGS2025

Linking stream-reach nitrogen loads and groundwater “reachsheds” to inform wastewater-nitrogen management actions, Cape Cod, Massachusetts

Study Region Cape Cod, Massachusetts, U.S.A. Study Focus Anthropogenic nitrogen (N) is a key factor in degrading groundwater and surface-water quality, particularly in coastal New England where onsite wastewater systems are prevalent. This study evaluated whether direct N-load measurements in streams on Cape Cod, Massachusetts, coupled with flow-path information from groundwater-flow models, can effectively identify potential land areas where nitrogen mitigation could substantially reduce loads to receiving waters. Nitrogen fluxes were measured along 63 stream reaches during winter and summer and paired with simulated groundwater recharge areas to identify and rank potential areas for reduction of nonpoint-source N inputs. New Hydrologic Insights for the Region Reach-scale nitrate-N loads ranged from −39.1–1182 kg-N/yr per 100 m of stream, indicating spatially variable groundwater inputs across seasons. “Reachsheds” — areas contributing groundwater recharge to specific stream reaches — were delineated using a regional groundwater-flow model. Strong correlations were found between observed N loads and land-use characteristics, especially the number of septic systems and total N inputs from the sum of considered sources. Observed N loads were moderately correlated with recharge area size and wastewater flow estimates. Correlating reach-specific groundwater N loads with land use and parcel-scale nitrogen-yield data identified reachsheds with the highest potential for N load reduction. This approach enables targeted implementation of restoration efforts to optimize nutrient management and support regional load reduction.

Massachusetts↗
USGS2024

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

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

Water Resources Research↗
USGS2025

Beyond optimality: Dryland ecosystems infrequently use water efficiently for carbon gain

Optimality theory assumes plants maximize carbon gain per unit water lost and is often implemented to scale leaf-level carbon gain and water use to regional and global scales. Optimality theory is often mathematically represented by assuming plant water-use efficiency (WUE) scales with VPD k , where k = ½ represents expected optimal behavior. It is unclear, however, if this relationship holds in arid and semi-arid ecosystems that are strongly impacted by soil and atmospheric moisture status. We used data from seven flux tower sites along an aridity gradient in New Mexico to answer: how does the relationship between WUE and VPD compare to expectations based on optimality theory? To address this question, we integrated the Dynamic Evapotranspiration Partitioning Approach for Rapid Timescales with a stochastic antecedent model to estimate ecosystem-level WUE (GPP/T) and the net sensitivity of WUE to VPD, or k Dynamic , which we compare to the theoretical optimal sensitivity of k = ½. Our results show that optimality theory is not always appropriate, and k Dynamic often deviates from ½, especially at some of the more arid sites or during periods of low soil moisture. At less arid, higher elevation sites, k Dynamic is most consistent with optimality theory at moderate VPD levels, but not at high VPD. In general, the sensitivity of WUE to VPD is highly variable such that k Dynamic exhibits notable daily and seasonal variability, suggesting highly dynamic stomatal behavior. These results emphasize that representing plant water-use strategies as dynamic in time and space is critical to improving large-scale estimates of plant water use.

New Mexico↗
USGS2026

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen↗
USGS2026

SlideDetect: Spatio-temporal landslide detection using a three-dimensional convolutional neural network

Landslides pose a serious and ongoing threat to both human lives and infrastructure worldwide; therefore, it is of interest to predict where and when landslides are likely to occur. Advances in machine learning techniques have spurred numerous studies aimed at estimating relative landslide propensity, but are limited to spatial (as opposed to temporal) prediction due to the sparsity of landslide timing data. We address this data gap by training SlideDetect, a 3-dimensional convolutional neural network (3D CNN), to identify landslides based on their spatial and temporal occurrence within multitemporal image stacks. We use an inventory of landsides triggered by the 2018 Hokkaido earthquake and two years of monthly composite optical imagery spanning this event. The model can identify not only landslide location but also landslide date with an area under the precision-recall curve (PR-AUC) of 0.84. We further present a new standard for presenting PR curve results that explicitly compares model performance at different confidence thresholds, allowing for clearer model evaluation and comparison. Our new approach to constraining landslide timing paired with this more consistent and objective method for evaluating model performance shows considerable promise, and with further application and testing, SlideDetect could enhance the data availability and tools needed to advance landslide hazard and risk assessments.

JGR Machine Learning and Computation↗
USGS1998

Methods and guidelines for effective model calibration; with application to UCODE, a computer code for universal inverse modeling, and MODFLOWP, a computer code for inverse modeling with MODFLOW

This report documents methods and guidelines for model calibration using inverse modeling. The inverse modeling and statistical methods discussed are broadly applicable, but are presented as implemented in the computer programs UCODE, a universal inverse code that can be used with any application model, and MODFLOWP, an inverse code limited to one application model. UCODE and MODFLOWP perform inverse modeling, posed as a parameter-estimation problem, by calculating parameter values that minimize a weighted least-squares objective function using nonlinear regression. Minimization is accomplished using a modified Gauss-Newton method, and prior, or direct, information on estimated parameters can be included in the regression. Inverse modeling in many fields is plagued by problems of instability and nonuniqueness, and obtaining useful results depends on (1) defining a tractable inverse problem using simplifications appropriate to the system under investigation and (2) wise use of statistics generated using calculated sensitivities and the match between observed and simulated values, and associated graphical analyses. Fourteen guidelines presented in this work suggest ways of constructing and calibrating models of complex systems such that the resulting model is as accurate and useful as possible.

Water-Resources Investigations Report↗
USGS2024

Telecommunications fiber for sensing earthquake aftershocks: Progress and hurdles

Aftershocks offer valuable clues to earthquake behavior. The challenge: quickly deploying sensors to capture the early details of earthquake ruptures within the zone of aftershocks. Telecommunication fibers might be an answer, providing denser networks in otherwise difficult areas, potentially faster than traditional methods.

Conference Paper↗
USGS2025

Anomalous shear stress variation in wet granular medium: Implications for landslide lateral faults

Landslide assessments typically focus on the mechanical properties of the basal shear zone, but lateral faults are frequently overlooked, possibly due to their lower normal stresses and variably saturated conditions. Using double-cylinder shear experiments on wet granular systems as analogs for landslide lateral faults, we observe anomalous shear stress variations with fluid volume fractions, defying an expected unimodal relationship associated with capillary cohesion. At low fluid volume fractions, shear strength weakens as the wet grain assembly experiences reduced lateral pressure and increased boundary slip. This boundary slip subsequently vanishes, with an abrupt strengthening due to the dilation of the grain assembly against fluid surface tension as saturation approaches. Strike-slip motion and confinement in this system explain the strength anomaly, highlighting a critical role of lateral faults in landslide stability, particularly in cases where dynamics cannot be adequately explained by monitored pore-water pressure or basal friction.

Geophysical Research Letters↗
USGS2024

Preparing for today's and tomorrow's water-resources challenges in eastern Long Island, New York

Freshwater is a vital natural resource. Although New York is a water-rich State, the wise and economical use of water resources is needed to ensure that there is enough water of adequate quality for both human and ecological needs—both for today and for tomorrow. Nowhere in New York is this more evident than in Nassau and Suffolk Counties on Long Island, where the public water supply is obtained from the sole-source aquifers located directly beneath the nearly 3 million people who live there. In 2023, in eastern Long Island’s Suffolk County, groundwater was pumped from these aquifers by more than 1,100 public water-supply wells to meet the needs of about 1.5 million people.

New York↗