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

At least 631 records · Page 35Linked to original sources

USGS2026

Steps toward a satellite-based global volcano monitoring and early warning system: From pilot to demonstrator to GVEWERS

The consequences of volcanic eruptions span a broad range. Large explosive eruptions that recur every several hundred to thousands of years can impact global climate, but even small eruptions of a magnitude that takes place multiple times each year someplace on Earth can have devastating effects given the large number of people who live near volcanoes. Ground-based monitoring is inadequate or lacking at many of the world’s active volcanoes, but satellite observations can fill important gaps and provide operational awareness of volcanic unrest and eruptions. The need for satellite monitoring of volcanoes has been articulated in numerous international agreements, and for some datasets, like thermal and ultraviolet imagery, daily or sub-daily monitoring has been incorporated into operational volcano surveillance. Utilization of high-resolution synthetic aperture radar (SAR) and optical datasets, however, has lagged. Since 2014, the Committee on Earth Observing Satellites (CEOS) has sponsored a series of projects designed to enhance access to, and utilization of, high-resolution SAR and optical satellite imagery for volcano monitoring. The efforts have culminated in the development of the Global Volcano Early Warning and Eruption Response from Space (GVEWERS) initiative—a global and sustainable program intended to support volcano hazards assessment and mitigation. GVEWERS builds on lessons learned from a decade of CEOS volcano projects while also providing a foundation for continuing to improve the accessibility and exploitation of satellite data for better anticipating and responding to hazardous volcanic eruptions.

Bulletin of Volcanology↗

USGS2026

What a difference a day makes: When and where are daily satellite observations of morphology and deformation needed during volcanic eruptions and unrest?

Daily high-spatial-resolution satellite imagery at active volcanoes could be used to anticipate eruptions and save lives, but is only rarely available or used in real time. Specifically, daily repeat coverage of ground deformation, topography, and surface morphology at volcanoes is now possible using high-spatial resolution optical and radar imagery (< 10 m/pixel). However, multiple satellites are needed—either constellations of four or more sibling satellites or a “virtual constellation” using several different types of satellites. As part of the Global Volcano Early Warning and Eruption Response from Space (G-VEWERS) project of the Committee on Earth Observation Satellites (CEOS), we review case studies at both erupting and restless volcanoes to identify scenarios where near-daily radar (both backscatter images and interferometric products) or optical data captured noteworthy changes, including Merapi and Mount Agung, Indonesia; La Soufrière, St. Vincent; Colima, Mexico; Kīlauea, Hawaiʻi; and Fagradalsfjall, Iceland. Finally, we consider the resources needed to scale this globally. There are 40–50 volcanoes erupting at any given time, but currently only about 10% have daily imaging at high-spatial-resolution. The allocations of high-spatial-resolution imagery available through G-VEWERS and other open datasets (~10,000 scenes/year) are < 60% of what is needed (~17,000 scenes/year) for daily imaging of all restless and erupting volcanoes. We therefore propose criteria to prioritize where daily satellite high-spatial-resolution observations may be useful continuously or under emergency conditions based on the threat and the type of volcano/eruption.

Bulletin of Volcanology↗

USGS2026

The influence of surface crust dynamics and sediment availability on aeolian dust emission from ephemeral lake beds: Evidence from Etosha Pan, Namibia

Ephemeral lake beds (playas) are major global sources of atmospheric mineral dust, yet controls governing sediment availability and emission potential at fine spatial scales remain poorly constrained. This study presents the first in situ measurements of surface erodibility and potential PM 10 emission fluxes from Etosha Pan, Namibia. Threshold shear velocities and PM 10 emission fluxes were quantified using a Portable In-Situ Wind ERosion Laboratory (PI-SWERL) across five surface types spanning highly emissive hotspots to non-emissive consolidated salt crusts. Threshold shear velocities ranged from 0.38 m s −1 on deflated clay-rich surfaces to >1.14 m s −1 on recently inundated or cemented salt crusts, and PM 10 fluxes at u ⁎ = 0.56 m s −1 varied by more than three orders of magnitude. Emissions were highest where degraded efflorescent crusts exposed fine sediment, whereas halite-rich crusts exhibited greater mechanical strength and resisted wind erosion despite low surface moisture. X-ray diffraction analyses confirmed spatial variability in evaporite and silicate mineral assemblages, with halite abundance inversely related to dust emission potential. Antecedent hydrological conditions regulated sediment availability. Moderate wetting–drying cycles promoted weak, emissive crusts, whilst persistently wet or dry conditions were associated with continuous, resistant crusts and reduced emissions. Distinct emission regimes arose from differences in crust failure and saltation feedbacks, highlighting sub-landform-scale variability in dust sources. Crust dynamism, driven by spatial variability in surface conditions and antecedent hydrological regime, is identified as a key, under-represented control on dust emission. The relationships quantified here provide new empirical constraints for improving the representation of sediment availability in global dust modelling.

Etosha Pan↗

USGS2026

Oil in the Alaska North Slope gas hydrate reservoir: Micro-CT and flow simulation insights into permeability

Gas hydrate-bearing sands on the Alaska North Slope (ANS) host minor volumes of crude oil whose impact on formation permeability has never been quantified relative to a gas hydrate reservoir system. Here, we combine in situ pressure-core microcomputed-tomography (μ-CT), thermogravimetric analysis (TGA), gas-chromatography–mass-spectrometry (GC–MS), scanning-electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), and Stokes-flow simulation to (i) quantify oil saturation, (ii) infer its source, and (iii) evaluate its influence on permeability after gas-hydrate dissociation. μ-CT and SEM-EDS imaging identify the host sediment as silty, with some grain-coating clay present. Eight representative 300 3 -voxel subvolumes extracted from a preserved pressure core (Core 15P-3c, from the B1 sand (unit B), HYDRATE 02 Geo Data Well (GDW), 886.96–887.29 m measured depth, MD) exhibit porosities of 0.34–0.37 and an average oil saturation of 0.09 ± 0.03, in comparison to an independent TGA-based estimate of 0.16. GC-MS fingerprints obtained from an adjacent depressurized core (Core 17P-1, 891.37–891.44 m MD), together with oil pore habit revealed by μ-CT, suggest that the oil is partly native but also includes contributions from mineral oil-based drilling fluid contamination. Further analysis of oil–porewater interactions and flushing tests confirms that native oil saturation in the analyzed samples ranges from 0.04 to 0.08 with an average of approximately 0.06, and the oil is highly immobile. Flow simulations demonstrate that the native oil saturation of ≈0.06 reduces permeability by approximately 50% due to both pore blockage and increased flow-path tortuosity. These findings reveal the potential presence of native oil within the ANS gas hydrate reservoir and suggest that future simulation models may need to account for its impact on permeability to improve long-term performance predictions of gas and water production.

Alaska↗

USGS2026

Perceptions of parcel-level wildfire risk differ between homeowners and trained assessors in wildland-urban interface communities across the western United States

Wildfire risk mitigation on private property is central to reducing community wildfire vulnerability. Homeowners have control over many of the key factors that contribute to wildfire risk on their parcels, yet vulnerable conditions persist. One potential explanation is a misalignment between homeowners' and trained assessors' perceptions of parcel-level wildfire risk. Prior research has documented a “risk gap” in a single community wherein owners often underestimate their parcel-level wildfire risk; however, it is unclear whether such misalignments are widespread. This study replicates and expands previous research by examining the parcel-level wildfire risk gap in 38 wildland–urban interface (WUI) communities across the Western United States using paired data from household surveys and parcel-level wildfire risk assessments by trained assessors. We find that homeowners and assessors often perceive parcel characteristics differently. Homeowners may systematically mis-weight their importance, tending to underweight key controllable factors such as building materials and defensible space, leading to meaningful divergence from trained assessor ratings. Accordingly, we also find that homeowners generally underestimate overall parcel wildfire risk compared to trained assessors. These results suggest that even when homeowners recognize attributes on their parcels that contribute to wildfire risk, they may not fully grasp how much the attributes contribute to overall parcel risk, potentially failing to recognize the need to undertake meaningful mitigation actions. The findings from this study contribute to the broader natural hazards literature on expert-layperson risk perception gaps and offer insights for improving wildfire communication, education, and mitigation strategies in WUI communities.

Alaska, Colorado, New Mexico, Utah, Wyoming↗

USGS2026

A ground-motion model derived using a generalized mean rupture distance for large slab interface earthquakes

Source–station distance is a central input to ground‐motion models (GMMs) for predicting seismic shaking. GMM development uses distance metrics including the Joyner–Boore distance, which is the shortest distance from an observation point to the surface projection of the earthquake rupture, and R rup the shortest distance to the rupture in three dimensions. Thompson and Baltay (2018) proposed the generalized mean rupture distance R p to address observed near‐fault ground‐motion saturation. R p accounts for the contribution to the shaking of all parts of the rupture and provides a simple method for incorporating spatially variable slip. They used R p to develop a GMM for shallow crustal earthquakes, assuming uniform slip. Here, we investigate the improvement offered by an R p ‐based GMM for large subduction interface earthquakes by recalibrating the path term for a published GMM ( Parker et al. , 2022 ) using R p derived from distributed slip models (DSMs). Inspection of within‐event and total residuals indicates that the recalibrated model fits the data at least as well as an alternative in which the path term was recalibrated using R rup and the same dataset. Incorporating slip information in its entirety or trimming the DSM geometry is preferable to assuming uniform moment release on a prescribed model fault that extends beyond the actual ruptured area. R p tuned to minimize model uncertainty is closer to the maximum distance to rupture for peak ground velocity (PGV) than acceleration, possibly reflecting the contribution to high‐frequency shaking of slip on local asperities. However, when the moment is concentrated far from stations, PGV is fit adequately with R p closer to R rup ⁠ . Our results suggest incorporating slip‐derived moment release through R p could improve GMMs for slab interface events, especially if the implementation of R p ‐based models is refined using a larger dataset of earthquakes with greater geographic diversity to account for regional ground‐motion variations.

Seismological Research Letters↗

USGS2026

Colored shaded-relief bathymetric and acoustic-backscatter maps of Jenkinson Lake with orthomosaic of the Sly Park Creek and Hazel Creek area, California

The Caldor Fire was ignited on August 14, 2021, and burned almost 222,000 acres (898 square kilometers) in forested terrain of the central and western Sierra Nevada, California. During the subsequent two months, the fire burned nearly all of Sly Park Creek watershed in El Dorado County. The El Dorado Irrigation District manages the water supply for the area using storage in Jenkinson Lake, a 1.6-kilometer- (1.0-mile-) wide and 3.6-kilometer- (2.2-mile-) long reservoir, located south of the town of Pollock Pines. Several weeks after the fire, the U.S. Geological Survey began investigations into post-fire landscape responses, including sediment yield, by measuring new sediment deposition in Jenkinson Lake. This study focused on the collection and processing of bathymetric and acoustic-backscatter data, as well as onshore aerial imagery in and around Jenkinson Lake, to support wildfire science after the Caldor Fire. A colored shaded-relief bathymetric map (sheet 1) and an acoustic backscatter map (sheet 2) show the lake floor morphology and backscatter intensities.

California↗

USGS2026

Flood-inundation maps of the Blue River and major tributaries in and near Kansas City, Missouri, 2023–25

Digital flood-inundation maps for 35.5 miles of the Blue River, in and near Kansas City, Missouri, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Kansas City. Maps were also developed for a combined 7.3 miles of Brush Creek (4.4 miles) and Indian Creek (2.9 miles), two primary tributaries to the Blue River in the study reach. The flood-inundation maps, available through the USGS Flood Inundation Mapping Program website at https://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding, depth of water above first-floor elevations in selected buildings, water velocity, water-surface elevations, and time of travel corresponding to selected water levels or gage heights (hereafter referred to as “stages”) at nine reference USGS streamgages—five on the Blue River (USGS station numbers 06893590, 06893578, 06893500, 06893150, and 06893100), two on Brush Creek (USGS station numbers 06893562 and 06893557), one on Indian Creek (USGS station number 06893390), and one on the Missouri River (USGS station number 06893000). Near-real-time stages at these streamgages may be obtained from USGS Water Data for the Nation at https://doi.org/10.5066/F7P55KJN or the National Weather Service National Water Prediction Service at http://water.noaa.gov/ , which also forecasts flood hydrographs at seven of these sites (USGS station numbers 06893000, 06893590, 06893578, 06893500, 06893150, 06893557, and 06893390). Flood profiles were computed for eight map reaches by means of two-dimensional hydraulic models. The models were calibrated using the USGS-developed stage–streamflow relations at each reference streamgage. Two map reaches on the lower Blue River also include the effects of backwater from the Missouri River on flood inundation extent and hydraulic characteristics. The hydraulic models were used to compute water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datums. The profile stages ranged from the National Weather Service “Action Stage” or near bankfull to a stage exceeding the highest recorded water level at each streamgage. The simulated water-surface profiles were then combined with a digital elevation model (derived from light detection and ranging data having a nonvegetated vertical accuracy of a maximum 10-centimeter root-mean-square error) to delineate the area flooded at each water level and the associated hydraulic characteristics. The availability of these maps, along with information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel, resource managers, and residents with information that could be critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Kansas, Missouri↗

USGS2026

The path to FAIR research models: Lessons learned

Numerical modeling of Earth surface processes emerged as an important scientific tool in the late 1960s to mid-1970s, driven by the development of finite element methods in computer science. These advancements, initially applied in civil engineering, enabled scientists to simulate complex geological phenomena. At that time, models were often only described in publications, access was limited to researchers with direct connections to the developers, and the code was rarely documented for reuse, limiting their application beyond the original research context. The FAIR principles (Findability, Accessibility, Interoperability, and Reusability) as applied to data began to take shape in the 21st century with the rise of open science, digital repositories, and standardized data sharing frameworks. In the late 2010s, grassroots movements began to apply some of the FAIRness goals to numerical models. Subsequently, more formalized FAIR model principles were developed that addressed the specific needs of the scientific modeling community, resulting in the formulation of the FAIR principles for research software (FAIR4RS). In this study, we examine the development and implementation of strategies by two geoscience research infrastructures – the CSDMS (Community Surface Dynamics Modeling System) Model Repository and the U.S. Geological Survey Model Catalog – to enhance the FAIRness of models guided by FAIR4RS. Some of the development and implementation efforts described predate the formalization of FAIR and FAIR4RS principles, making this an ongoing and adaptive process. We evaluate the temporal progression towards increased FAIR4RS alignment across three phases of research infrastructure development: prototype, refinement, and growth and iteration. Although certain principles were more straightforward to implement early in prototypes of the catalog infrastructures, others required broader community collaboration during refinement, and some continue to pose practical challenges in the growth and iteration phase. By tracing these dynamics, our aim is to provide insights that can guide other modeling initiatives in effectively adopting FAIR4RS principles within their communities.

Geoscientific Model Development↗

USGS2026

Combining individual and close-kin mark–recapture to design an effective wildlife population survey

Close-kin mark–recapture (CKMR) is a promising approach for assessing population size of species that have been difficult to survey using more traditional methods. Here, we combine individual and close-kin mark–recapture in a single modeling framework (ICKMR) and provide an example of study design using this approach for Pacific walrus ( Odobenus rosmarus divergens ). We develop the ICKMR model and test it using simulated datasets, then use properties of the pseudo-likelihood to investigate the expected precision in estimates of abundance with different proposed survey designs. Our motivating example, the Pacific walrus, is an ice-associated marine mammal found in the Bering and Chukchi seas, where it is an important resource for Indigenous peoples. Pacific walrus abundance declined in the late 20th century, and it is currently a species of conservation concern due to potential impacts of climate change, particularly the loss of sea ice. To reduce uncertainty in population size estimates, researchers undertook a genetic mark–recapture sampling campaign from 2013 to 2017 and collected tissue samples from over 8000 individuals. Another campaign of a similar scale is ongoing (2023–2028). While sample collection was designed for individual mark–recapture, advances in CKMR methods and associated molecular techniques mean that these samples could also be suitable for CKMR. The advantages of CKMR over mark–recapture include an increased effective sample size (because each individual tags itself and its parents, siblings, and offspring) and additional insights into demographic quantities of interest. To make best use of genetic samples, we combine individual mark–recapture (IMR) with CKMR (ICKMR) and investigate whether different sampling strategies can increase precision in estimates of abundance. Our modeling approach includes special considerations for walrus life history, including a multi-year inter-birth interval. We found that expected coefficients of variation (CVs) of the ICKMR estimates of abundance, adult female survival, juvenile female survival, and proportion of breeding females are lower than those expected from IMR alone, and with ICKMR, fewer years of sampling can be conducted to obtain sufficient precision in estimates of abundance. This work demonstrates the utility of ICKMR and could be applicable across a variety of taxa.

Ecology↗

USGS2026

Comparison of data handling techniques for modeling bat acoustic activity

With the proliferation of acoustic sampling to investigate bat distribution and ecology, researchers have implemented a myriad of statistical modeling approaches to interpret findings. Bats are taxa of high conservation concern; therefore, ensuring the accuracy of species-level habitat association models is critical for informing management. We sought to determine prediction differences among statistical approaches to modeling counts of acoustic detections, using generalized linear mixed models with 8 acoustic data-handling techniques. We applied each approach or combination of approaches to a rare species, the northern long-eared bat ( Myotis septentrionalis ), and a common species, the eastern red bat ( Lasiurus borealis ), from summer survey results on a landscape in south-central Pennsylvania, USA, 2024. We evaluated the accuracy of habitat association models of bat acoustic activity at the species level using cross-validation and compared resulting predictions of models using spatial correlations. We determined that filtering data by automated identification software (Kaleidoscope Pro), the maximum likelihood estimate (MLE) P -value thresholds reduced relative mean absolute error (rMAE) in cross-validation of northern long-eared bat models. Using the MLE-retained data produced the most accurate predictions over using raw data or the overly conservative match ratio data. However, for the eastern red bat, the results from the most conservative approach of only retaining data with at least a 90% match ratio from software development training sets had the lowest rMAE. We have provided evidence that the current standard of filtering data by nightly MLE can result in more accurate and informative habitat-use acoustic activity models for rare bat species.

Pennsylvania↗

USGS2026

Abundance, trends, and challenges facing mountain goats throughout their North American distribution

Recent declines among some mountain goat ( Oreamnos americanus ) populations have heightened concern about their current status and ability to cope with future challenges. We conducted a range-wide assessment of the status of mountain goats across their distribution to understand the extent and patterns of change in recent years. We queried states, provinces, National Parks, and Indigenous governments with territories and reserves containing local wild populations, requesting updates on estimated mountain goat abundance and trends over time, as well as qualitative assessments of conservation challenges. We supplemented the questionnaires with existing literature (both published and available from agency websites). We subjected a subset of mountain goat population time−series to exploratory meta-analyses, examining covariates associated with rates of change. Respondents identified 203 units within which estimates were documented, a majority of which were raw counts from aircraft; fewer jurisdictions used site-specific sightability models, mark-recapture statistics, or other approaches to account for imperfect detection. Jurisdictions updated unit-specific estimates on average every 4.0 years (SD = 2.9, Min–Max = 1–24 years). Among 152 qualitative estimates of trends of native populations, 3% were reported as having increased substantially, 10% as having increased slightly, 24% as having declined slightly, and 14% as having declined substantially (49% reported either no detectable trend or insufficient data to identify a trend). Among 133 estimates of trends of introduced or pioneering populations, 5% increased substantially, 24% increased slightly, 20% declined slightly, and 11% declined substantially (40% reported no detectable trend). Jurisdiction-wide abundance estimates were lower than those previously published in all jurisdictions except Colorado and Oregon, and in Alaska, where trends were unclear. Intrinsic rates of increase ( r ) were positively associated with the population being introduced or pioneering, negatively associated with heavy snow and, to a lesser extent, with drought, but were not associated with abundance or presence of hunter harvest. Existing evidence suggested that many local populations, especially native populations, have declined, but understanding of specific causes has been constrained by limited monitoring capacity. Greater spatiotemporal monitoring effort and detailed studies would inform appropriate strategies to address threats and future challenges to mountain goats.

Wildlife Society Bulletin↗

USGS2026

Evaluating groundwater quality influences from oil field operations and other anthropogenic activities in an urban setting, Santa Fe Springs, California

Groundwater quality is often affected by anthropogenic activities in urban settings. This study examines groundwater quality in and around the Santa Fe Springs Oil Field in Los Angeles County, California, where oil and gas production commonly intersects with high density industrial, commercial and residential land uses. Utilizing a combination of new and historical data, we evaluated potential pathways that would allow for oil field formation fluids to migrate into groundwater and whether mixing may have occurred based on the distribution of groundwater and oil field formation fluid tracers in samples. Samples were analyzed for a wide array of constituents including volatile organic compounds, light hydrocarbons, major ions, and various isotopic compositions. Despite evidence of oil field infrastructure providing potential pathways of migration via uncemented annular spaces, casing breaches and historical disposal of oil field formation water in surface ponds, the distribution and occurrence of stable isotopes of water, chloride, boron, and total dissolved solids do not indicate mixing of oil field formation water and groundwater. However, methane isotopic signatures and the presence of heavier alkanes suggest gas from oil-bearing formations have migrated from depth via oil field well infrastructure. Volatile organic compound detections were mainly from manufactured compounds unrelated to oil and gas production, with a relatively limited number of petroleum hydrocarbons also detected. Volatile organic compounds were generally found in wells tapping shallow, modern aged groundwater, indicating anthropogenic activities occurring at or near land surface as the source. Study results suggest that while oil field infrastructure provides migration pathways for oil field formation fluids to be introduced into groundwater, urban land uses not related to oil and gas production are the primary drivers of groundwater quality degradation.

California↗

USGS2026

Significant coastal dune loss challenges California's climate resilience and biodiversity goals

Coastal sand dunes support unique biodiversity and buffer beaches and communities against storm impacts. However, these sensitive and dynamic ecosystems are increasingly threatened by erosion, sea-level rise (SLR), and encroaching coastal development. Restoration projects designed to re-establish the eco-geomorphic functions of degraded dunes and associated ecosystem services present a viable pathway to relieve these stressors. Yet, even for populated coasts like California, insufficient information on the location of dunes and patterns of change over time constrain regional efforts to identify suitable restoration/conservation sites, and forecast future impacts on vulnerable beach–dune systems. Here, we present a comprehensive assessment of coastal dune extent and loss, spanning 165 years and 9.5° of latitude across California. Areas and drivers of change were quantified by comparing historical and current dune extents generated using historical surveys, high-resolution aerial imagery, and LiDAR, combined with a machine-learning tool. Coastal dunes currently extend along 352 km (22%) of California's 1,625 km coastline, covering almost 300 km 2 . This represents a 60% (442 km 2 ) decrease in area since the mid-1800s with the loss, degradation, and fragmentation of many dune ecosystems attributed to urban development, altered land-uses, and erosion. Strong regional patterns of dune loss were evident, reflecting population demographics and land uses. Densely populated areas of southern California experienced the greatest dune losses (95%, 108 km 2 ), although substantial reductions were also found in central California (60%, 331 km 2 ). Our results highlight the magnitude of coastal change in California over time and can inform future conservation, restoration, and resilience-planning efforts and priorities.

California↗

USGS2026

Individual encounter data of six African carnivore species optimized for multi-species density estimation

The ability to estimate abundances of multiple wildlife species within an area is valuable for both conservation and ecological inquiry. Spatially explicit capture–recapture (SCR) methods are commonly used to obtain reliable population size estimates, particularly for low-density and individually identifiable carnivore species. However, estimating abundance within multi-species communities poses a methodological challenge as survey designs and analytical tools are primarily tailored for single target species. Here, we present a dataset of spatially referenced individual encounter histories of six carnivore species with varying space requirements (lion, Panthera leo ; leopard, Panthera pardus ; spotted hyena, Crocuta crocuta ; cheetah, Acinonyx jubatus ; serval, Leptailurus serval ; large-spotted genet, Genetta tigrina ). These data were collected in a South African game reserve using a camera trap array optimized for multi-species density estimation using SCR methods. This dataset will be a valuable resource for studying spatial processes among potentially interacting carnivores without the common pitfalls that come with by-catch data of non-target species, and will provide a much-needed case study for the further development of multi-species statistical method development.

Munywana Conservancy↗

USGS2026

Bridging remote sensing advances and management needs for small Prairie Pothole waterbodies using a multiscale accuracy assessment

Remote sensing of surface water provides a powerful tool to inform the management of waterfowl habitat, but there is little information available to directly assess the relative accuracy of different remote sensing datasets. Our objective was to understand how the characteristics of remotely sensed inundation datasets inform dataset accuracy, the reliable detection of small waterbodies, the distribution of surface water, observation frequency and completeness of data: all attributes relevant to the management of waterfowl habitat. We compared surface water composites from 10 remotely sensed surface water datasets from 2016 to 2021 to in-situ surface water data for three complexes of small waterbodies in the U.S. Prairie Pothole Region and evaluated their accuracy at the pixel, waterbody and local landscape scales. While all products had high per-pixel balanced accuracies (>0.75), we found distinct differences in waterbody area and landscape distribution estimates among datasets. Sentinel-1-based datasets provided a more complete set of observations over time and were more sensitive in detecting water presence in smaller waterbodies but were less accurate at identifying waterbody area than other datasets evaluated. Landsat datasets, alternatively, produced simpler landscape distributions that largely omitted the smallest waterbodies. While the datasets that either fused Sentinel-1 and −2 data collections or utilized local training data had the highest performances (e.g. balanced accuracy = 0.92), all datasets had use-case scenarios for which they may be informative. Our comparisons revealed differences that were not evident in traditional pixel-scale accuracy assessment, such as an 18-fold difference in the number of inundated waterbodies identified across remote sensing datasets. These findings provide novel insights for waterfowl conservation management on howremote sensing datasets may differ in their ability to monitor annual spring surface water presence within landscapes dominated by small waterbodies, such as the Prairie Pothole Region.

Minnesota, North Dakota↗

USGS2026

A practical framework for identifying genetic subpopulations and ESUs: Insights for IUCN assessments and broader management

Species conservation assessments evaluate extinction risk, and recovery potential, advancing species persistence through guiding resource prioritization and planning. Assessment frameworks, including the International Union for Conservation of Nature Red List and Green Status of Species, typically focus on species as a whole. Importantly, they do not routinely account for genetically distinct units or do not have standardized methods of unit delineation. This limits the representation of genetically distinct components, including adaptive genetic diversity that underpins long-term resilience and recovery. Incorporating standardized within-species units like subpopulations and Evolutionarily Significant Units (ESUs) into species assessments could help address this oversight. However, identifying and delineating such units remain challenging, particularly when molecular data are limited. Here, we propose a flexible framework that integrates molecular and non-molecular evidence to identify both subpopulations and ESUs across taxa, providing a practical tool to incorporate within-species diversity into conservation assessments.

BioScience↗

USGS2026

The US XPD-24–200—An isokinetic suspended-sediment and water-quality collapsible-bag sampler with point- or depth-integrating sampling capabilities

Accurate collection of fluvial suspended‑sediment and water‑quality samples is essential for understanding transport processes, evaluating river health, quantifying loads, and supporting regulatory and management decisions. Since 1939, the Federal Interagency Sedimentation Project (FISP) has led the development and standardization of sediment‑sampling equipment and methods across Federal agencies. Although substantial advancements have been made, the most recent point‑integrating sampler developed in 2006 has notable limitations, including insufficient sample volume for low‑concentration analyses and a mechanically complex pressure‑equalization system required for a rigid-bottle sample container. To address these limitations, FISP collaborated with Carnet Technology to design, fabricate, and test a new collapsible‑bag sampler capable of collecting larger sample volumes and operating as either a point‑integrating or depth‑integrating sampler. The resulting sampler, the US XPD‑24‑200, was evaluated through controlled tow‑tank tests and field testing in a lake environment. Results indicate that the US XPD‑24‑200 can collect a 5.5-fold increase in maximum sample volume than a pre-existing point sampler developed in 2006. The US XPD‑24‑200 performs isokinetically within the expected intake efficiency (IE) range under most conditions. Approximately 73 percent of IEs fell within the target range of 0.9–1.1. A mild bias was observed with IE values outside this range that were predominantly lower than 0.9 and occurred most frequently at the lower test velocities, whereas only 2 percent of IEs exceeded 1.1, primarily at the highest velocities tested. Tow‑tank tests produced tightly clustered IE values with low variability, demonstrating stable performance under controlled conditions. Lake towing tests exhibited more variability, reflecting natural environmental influences such as turbulence, temperature gradients, and unsteady inflow. Collectively, the results demonstrate that the US XPD‑24‑200 provides reliable IEs comparable to existing samplers while offering increased sample volume, reduced mechanical complexity, and enhanced operational flexibility.

Open-File Report↗