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USGS2023

Insectivorous bat foraging tracks the availability of aquatic flies (Diptera)

Rivers and their adjacent riparian zones are model ecosystems for observing cross-ecosystem energy transfers. Aquatic insects emerging from streams, for example, are resource subsidies that support riparian consumers such as birds, spiders, lizards, and bats. We collaborated with recreational river runners in Grand Canyon, Arizona, USA, to record acoustic bat activity and sample riparian insects using light traps at dusk from April through October 2017–2020. River runners collected these data on 1,428 events over 611 sampling nights at 410 sites throughout a 470-km segment of the Colorado River. We documented 71 insect taxa in light traps and recorded 19 bat species with acoustic detectors. We hypothesized that bat activity along this highly regulated river segment would be influenced primarily by variation in prey availability, as compared to other habitat descriptors. We predicted that bat activity would be positively related to aquatic insect catch rates and unrelated to terrestrial insect abundance. We fit Bayesian regression models to test these hypotheses and to quantify the relationship between bat activity and a suite of environmental variables: time of year, time of day, distance from perennial tributaries, distance from rapids, channel width, geomorphic reach, tall vegetation cover, air temperature, and lunar phase. Bat activity was positively related to the abundance of aquatic flies (Diptera), which outcompeted all other prey categories and structural habitat descriptors in our models. Within our dusk sampling period, activity of small myotis (California myotis [ Myotis californicus ] and Yuma myotis [ M. yumanensis ]) was high late in the evening and canyon bats ( Parastrellus hesperus ), conversely, were more active early in the evening. Activity of canyon bats varied seasonally, with peak activity in August. Our results support the hypothesis that aquatic prey, specifically aquatic flies, are key predictors of bat activity along a large, regulated river corridor and demonstrate the power of community science as a tool for ecosystem monitoring.

Journal of Wildlife Management↗

USGS2010

Teaching citizen science skills online: Implications for invasive species training programs

Citizen science programs are emerging as an efficient way to increase data collection and help monitor invasive species. Effective invasive species monitoring requires rigid data quality assurances if expensive control efforts are to be guided by volunteer data. To achieve data quality, effective online training is needed to improve field skills and reach large numbers of remote sentinel volunteers critical to early detection and rapid response. The authors evaluated the effectiveness of online static and multimedia tutorials to teach citizen science volunteers (n = 54) how to identify invasive plants; establish monitoring plots; measure percent cover; and use Global Positioning System (GPS) units. Participants trained using static and multimedia tutorials provided less (p <.001) correct species identifications (63% and 67%) than did professionals (83%) across all species, but they did not differ (p =.125) between each other. However, their ability to identify conspicuous species was comparable to that of professionals. The variability in percent plant cover estimates between static (??10%) and multimedia (??13%) participants did not differ (p =.86 and.08, respectively) from those of professionals (??9%). Trained volunteers struggled with plot setup and GPS skills. Overall, the online approach used did not influence conferred field skills and abilities. Traditional or multimedia online training augmented with more rigorous, repeated, and hands-on, in-person training in specialized skills required for more difficult tasks will likely improve volunteer abilities, data quality, and overall program effectiveness. ?? Taylor & Francis Group, LLC.

Applied Environmental Education and Communication↗

USGS2018

Clarifying regional hydrologic controls of the Marañón River, Peru through rapid assessment to inform system-wide basin planning approaches

We use remote sensing to enhance the interpretation of the first baseline dataset of hydrologic, isotopic and hydrochemical variables spanning 620 km of the upper Marañón River, in Andean Peru, from the steep alpine canyons to the lower lying jungle. Remote, data-scarce river systems are under increased hydropower development pressure to meet rising energy demands. The upstream-downstream river continuum, which serves as a conduit for resource exchange across ecosystems, is at risk, potentially endangering the people, environments, and economies that rely on river resources. The Marañón River, one of the final free-flowing headwater connections between the Andes and the Amazon, is the subject of myriad large-scale hydropower proposals. Due to challenging access, environmental data are scarce in the upper Marañón, limiting our ability to do system-wide river basin planning. We capture key processes and transitions in the context of hydropower development. Two hydrologic regimes control the Marañón dry-season flow: in the higher-elevation upper reaches, a substantial baseflow is fed by groundwater recharged from wet season rains, in contrast to the lower reaches where the mainstem discharge is controlled by rain-fed tributaries that receive rain from lowland Amazon moisture systems. Sustainability of the upper corridor’s dry-season baseflow appears to be more highly connected to the massive natural storage capacity of extensive wetlands in the puna (alpine grasslands) than with cryospheric water inputs. The extent and conservation of puna ecosystems and glacier reservoirs may be interdependent, bringing to bear important conservation questions in the context of changing climate and land use in the region. More generally, this case study demonstrates an efficient combined remote sensing and field observation approach to address data scarcity across regional scales in mountain basins facing imminent rapid change.

Marañón River↗

USGS2016

Regional monitoring programs in the United States: Synthesis of four case studies from Pacific, Atlantic, and Gulf Coasts

Water quality monitoring is a cornerstone of environmental protection and ambient monitoring provides managers with the critical data they need to take informed action. Unlike site-specific monitoring that is at the heart of regulatory permit compliance, regional monitoring can provide an integrated, holistic view of the environment, allowing managers to obtain a more complete picture of natural variability and cumulative impacts, and more effectively prioritize management actions. By reviewing four long-standing regional monitoring programs that cover portions of all three coasts in the United States – Chesapeake Bay, Tampa Bay, Southern California Bight, and San Francisco Bay – important insights can be gleaned about the benefits that regional monitoring provides to managers. These insights include the underlying reasons that make regional monitoring programs successful, the challenges to maintain relevance and viability in the face of ever-changing technology, competing demands and shifting management priorities. The lessons learned can help other managers achieve similar successes as they seek to establish and reinvigorate their own monitoring programs.

California, Delaware, Florida, Maryland, New Jerse↗

USGS2016

Predicting arsenic in drinking water wells of the Central Valley, California

Probabilities of arsenic in groundwater at depths used for domestic and public supply in the Central Valley of California are predicted using weak-learner ensemble models (boosted regression trees, BRT) and more traditional linear models (logistic regression, LR). Both methods captured major processes that affect arsenic concentrations, such as the chemical evolution of groundwater, redox differences, and the influence of aquifer geochemistry. Inferred flow-path length was the most important variable but near-surface-aquifer geochemical data also were significant. A unique feature of this study was that previously predicted nitrate concentrations in three dimensions were themselves predictive of arsenic and indicated an important redox effect at >10 μg/L, indicating low arsenic where nitrate was high. Additionally, a variable representing three-dimensional aquifer texture from the Central Valley Hydrologic Model was an important predictor, indicating high arsenic associated with fine-grained aquifer sediment. BRT outperformed LR at the 5 μg/L threshold in all five predictive performance measures and at 10 μg/L in four out of five measures. BRT yielded higher prediction sensitivity (39%) than LR (18%) at the 10 μg/L threshold–a useful outcome because a major objective of the modeling was to improve our ability to predict high arsenic areas.

California↗

USGS2026

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE↗

USGS2025

Fisheries research and monitoring activities of the Lake Erie Biological Station, 2024

A comprehensive understanding of fish populations and their interactions is the cornerstone of modern fishery management and the basis for Lake Erie’s Fish Community Objectives (FCOs) developed in 2020 (Francis et al. 2020). The 2024 U.S. Geological Survey (USGS) Lake Erie Biological Station Annual Report is responsive to these FCOs and the USGS obligations via a Memorandum of Understanding (MOU 2017) with the Great Lakes Fishery Commission (GLFC) Council of Lake Committees (CLC) to provide scientific information in support of fishery management. Goals for the USGS Great Lakes Deepwater Fish Assessment and Ecological Studies were to monitor long-term changes in the fish community and track population dynamics of key fishes of interest to management agencies. Specific to Lake Erie, expectations were sustained investigations of native percids, prey fish populations, and Lake Trout. All work was conducted as part of the Deepwater Science Program under the authority of the Great Lakes Fishery Research Authorization Act of 2019 (16 USC §941h). The USGS 2024 Deepwater Science Program fieldwork began in Lake Erie in March and concluded in December, using trawl, gill net, hydroacoustic, lower trophic sampling devices, and telemetry methods. This work resulted in 44 bottom trawls covering 41 ha of lake bottom and catching 48,936 fish totaling 995 kg in the West Basin of Lake Erie, with detailed results described below. Overnight gill net sets (n=25) for coldwater species were performed in the East Basin of Lake Erie. A total of 8 km of gillnet was deployed during these surveys, which caught 106 fish, 92 of which were native coldwater species: Lake Trout, Burbot, and Lake Whitefish. Results from coldwater species assessments will be reported in the Coldwater Task Group report to the GLFC and the CLC (CTG 2025). These reports are used to inform Lake Trout stocking decisions and direct lamprey control measures (16 USC §939a). USGS hydroacoustic sampling included twenty-six 5-km transects (130 km total) in the Central Basin as part of a collaborative lake-wide survey with details and results reported by the Forage Task Group (FTG 2025). Lower trophic sampling provided data from zooplankton samples (n=12) and water quality profiles (n=12) to populate a database maintained by the Michigan Department of Natural Resources (MDNR), Ontario Ministry of Natural Resources (OMNR), Ohio Department of Natural Resources (ODNR), Pennsylvania Fish and Boat Commission (PFBC), and New York State Department of Environmental Conservation (NYSDEC). USGS also assisted CLC member agencies with deployment and maintenance of Great Lakes Acoustic Telemetry Observation System (GLATOS) infrastructure throughout all three Lake Erie basins and tributaries, supporting multiple coordinated telemetry investigations. This report presents biomass-based summaries of fish communities in western Lake Erie derived from USGS bottom trawl surveys conducted from 2013 to 2024 during June and September. The survey design compliments the August ODNR- OMNRF effort by reinforcing stock assessments with more robust data. Analyses herein evaluated trends in total biomass, abundance of dominant predator and forage species, non-native species composition, biodiversity, and community structure. Data from this effort are accessible for download (Keretz et al. 2025)

Lake Erie↗

USGS2020

Good practices for species distribution modeling of deep-sea corals and sponges for resource management: Data collection, analysis, validation, and communication

Resource managers in the United States and worldwide are tasked with identifying and mitigating trade-offs between human activities in the deep sea (e.g., fishing, energy development, and mining) and their impacts on habitat-forming invertebrates, including deep-sea corals and sponges (DSCS). Related management decisions require information about where DSCS occur and in what densities. Species distribution modeling (SDM) provides a cost-effective means of identifying potential DSCS habitat over large areas to inform these management decisions and data collection. Here we describe good practices for DSCS SDM, especially in the context of data collection and management applications. Managers typically need information regarding DSCS encounter probabilities, densities, and sizes, defined at sub-regional to basin-wide scales and validated using subsequent, targeted data collections. To realistically achieve these goals, we suggest analysts: 1) integrate available data sources in SDMs including fine-scale visual sampling and broad-scale resource surveys (e.g., fisheries trawl surveys); and 2) include environmental predictor variables representing multiple spatial scales, model residual spatial autocorrelation, and quantify prediction uncertainty. When possible, models fitted to presence-absence and density data are preferred over models fitted only to presence data, which are difficult to validate and can confound estimated probability of occurrence or density with sampling effort. Ensembles of models can provide robust predictions, while multi-species models leverage information across taxa and facilitate community inference. To facilitate the use of models by managers, predictions should be expressed in units that are widely understood and validated at an appropriate spatial scale using a sampling design that provides strong statistical inference. We present three case studies for the Pacific Ocean that illustrate good practices with respect to data collection, modeling, and validation; these case studies demonstrate it is possible to implement our good practices in real-world settings.

Frontiers in Marine Science↗

USGS2008

Arctic lake physical processes and regimes with implications for winter water availability and management in the national petroleum reserve alaska

Lakes are dominant landforms in the National Petroleum Reserve Alaska (NPRA) as well as important social and ecological resources. Of recent importance is the management of these freshwater ecosystems because lakes deeper than maximum ice thickness provide an important and often sole source of liquid water for aquatic biota, villages, and industry during winter. To better understand seasonal and annual hydrodynamics in the context of lake morphometry, we analyzed lakes in two adjacent areas where winter water use is expected to increase in the near future because of industrial expansion. Landsat Thematic Mapper and Enhanced Thematic Mapper Plus imagery acquired between 1985 and 2007 were analyzed and compared with climate data to understand interannual variability. Measured changes in lake area extent varied by 0.6% and were significantly correlated to total precipitation in the preceding 12 months (p < 0.05). Using this relation, the modeled lake area extent from 1985 to 2007 showed no long-term trends. In addition, high-resolution aerial photography, bathymetric surveys, water-level monitoring, and lake-ice thickness measurements and growth models were used to better understand seasonal hydrodynamics, surface area-to-volume relations, winter water availability, and more permanent changes related to geomorphic change. Together, these results describe how lakes vary seasonally and annually in two critical areas of the NPRA and provide simple models to help better predict variation in lake-water supply. Our findings suggest that both overestimation and underestimation of actual available winter water volume may occur regularly, and this understanding may help better inform management strategies as future resource use expands in the NPRA. ?? 2008 Springer Science+Business Media, LLC.

Environmental Management↗

USGS2019

Predicting attenuation of salinized surface- and groundwater-resources from legacy energy development in the Prairie Pothole Region

Oil and gas (energy) development in the Williston Basin, which partly underlies the Prairie Pothole Region in central North America, has helped meet U.S. energy demand for decades. Historical handling and disposal practices of saline wastewater co-produced during energy development resulted in salinization of surface and groundwater at numerous legacy energy sites. Thirty years of monitoring (1988–2018) at Goose Lake, which has been producing since the 1960s, documents long-term spatial and temporal changes in water quality from legacy energy development. Surface water quality was highly variable and decoupled from changes in groundwater quality, likely due to annual and regional climatic fluctuations. Therefore, changes in surface water-quality were not considered a reliable indicator of subsurface chloride migration. However, chloride concentrations in monitoring wells near wastewater sources exhibited systematic temporal reductions allowing for estimates of the time required for natural attenuation of groundwater to U.S. Environmental Protection Agency acute and chronic chloride toxicity benchmarks and a local background level. Point attenuation rates differed based on sediment type (outwash vs till) and yielded a range of predicted years when water-quality targets will be reached: acute – 2045 to 2113; chronic – 2069 to 2160; background – 2126 to 2275. Bulk attenuation rates from four separate years of data were used to calculate the distances chloride could migrate downgradient from the largest wastewater source. Potential distances of downgradient migration before dilution to water-quality targets decreased from 1989 to 2018: acute – 949 to 673 m; chronic – 1220 to 922 m; background – 1878 to 1525 m. Several downgradient wetlands are within these distances and will continue to receive saline contaminated groundwater for years. While these results demonstrate chloride attenuation at a legacy energy site, they also highlight the persistence of saline wastewater contamination and the need to mitigate future spills to prevent long-term salinization from energy development.

Montana↗

USGS2008

Landscape-scale evaluation of genetic structure among barrier-isolated populations of coastal cutthroat trout, Oncorhynchus clarkii clarkii

Relationships among landscape structure, stochastic disturbance, and genetic diversity were assessed by examining interactions between watershed-scale environmental factors and genetic diversity of coastal cutthroat trout (Oncorhynchus clarkii clarkii) in 27 barrier-isolated watersheds from western Oregon, USA. Headwater populations of coastal cutthroat trout were genetically differentiated (mean FST = 0.33) using data from seven microsatellite loci (2232 individuals), but intrapopulation microsatellite genetic diversity (mean number of alleles per locus = 5, mean He = 0.60) was only moderate. Genetic diversity of coastal cutthroat trout was greater (P = 0.02) in the Coast Range ecoregion (mean alleles = 47) than in the Cascades ecoregion (mean alleles = 30), and differences coincided with indices of regional within-watershed complexity and connectivity. Furthermore, regional patterns of diversity evident from isolation-by-distance plots suggested that retention of within-population genetic diversity in the Coast Range ecoregion is higher than that in the Cascades, where genetic drift is the dominant factor influencing genetic patterns. Thus, it appears that physical landscape features have influenced genetic patterns in these populations isolated from short-term immigration. ?? 2008 NRC.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2012

Vulnerability of recently recharged groundwater in principal aquifers of the United States to nitrate contamination

Recently recharged water (defined here as <60 years old) is generally the most vulnerable part of a groundwater resource to nonpoint-source nitrate contamination. Understanding at the appropriate scale the interactions of natural and anthropogenic controlling factors that influence nitrate occurrence in recently recharged groundwater is critical to support best management and policy decisions that are often made at the aquifer to subaquifer scale. New logistic regression models were developed using data from the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program and National Water Information System for 17 principal aquifers of the U.S. to identify important source, transport, and attenuation factors that control nonpoint source nitrate concentrations greater than relative background levels in recently recharged groundwater and were used to predict the probability of detecting elevated nitrate in areas beyond the sampling network. Results indicate that dissolved oxygen, crops and irrigated cropland, fertilizer application, seasonally high water table, and soil properties that affect infiltration and denitrification are among the most important factors in predicting elevated nitrate concentrations. Important differences in controlling factors and spatial predictions were identified in the principal aquifer and national-scale models and support the conclusion that similar spatial scales are needed between informed groundwater management and model development.

Environmental Science & Technology↗

USGS2014

Assessment of floodplain vulnerability during extreme Mississippi River flood 2011

Regional change in the variability and magnitude of flooding could be a major consequence of future global climate change. Extreme floods have the capacity to rapidly transform landscapes and expose landscape vulnerabilities through highly variable spatial patterns of inundation, erosion, and deposition. We use the historic activation of the Birds Point-New Madrid Floodway during the Mississippi and Ohio River Flooding of 2011 as a scientifically unique stress experiment to analyze indicators of floodplain vulnerability. We use pre- and postflood airborne Light Detection and Ranging data sets to locate erosional and depositional hotspots over the 540 km 2 agricultural Floodway. While riparian vegetation between the river and the main levee breach likely prevented widespread deposition, localized scour and deposition occurred near the levee breaches. Eroded gullies nearly 1 km in length were observed at a low ridge of a relict meander scar of the Mississippi River. Our flow modeling and spatial mapping analysis attributes this vulnerability to a combination of erodible soils, flow acceleration associated with legacy fluvial landforms, and a lack of woody vegetation to anchor soil and enhance flow resistance. Results from this study could guide future mitigation and adaptation measures in cases of extreme flooding.

Cairo, Illinois↗

USGS2025

Emerging investigator series: Post-wildfire sediment geochemical characterization reveals manganese reactivity and a potential link to water quality impairment in the Gallinas Creek watershed, New Mexico

Water quality post-wildfire is often impaired by increased turbidity and elevated concentrations of elements such as manganese (Mn) and iron (Fe). Precipitation events exacerbate these issues, due in part to increased erosion and transport of sediment from hillslopes to surface water. Both Mn and Fe are major redox-active elements in sediments that drive a variety of biogeochemical cycles, precipitate adsorptive phases, and can themselves be drinking water contaminants. By investigating Mn and Fe sediment geochemistry in post-wildfire sediment deposits, related water quality hazards can be assessed. To establish and strengthen this connection, we analyzed the geochemistry of sediment deposits and surface water in the Gallinas Creek watershed, New Mexico over 1.5 years post-wildfire. Analyses included particle size analysis, water extractions, sequential extractions and aqua regia extractions to determine metal partitioning in sediment deposits. Data demonstrate Mn concentrations were distributed across labile and reactive fractions, such as the exchangeable and oxyhydroxide fractions, while Fe concentrations were mainly associated with the residual fraction. Manganese concentrations in aqua regia extractions and several fractions of sequential extractions were also strongly and significantly correlated with fine-grained sediment while the same pools of Fe concentrations were not. Dissolved Mn concentrations in surface water were elevated (>50 μg L −1 ) multiple times over the 1.5 years post-wildfire, highlighting a relationship between sediment geochemistry and water quality. This work shows Mn in sediments mobilized post-wildfire has an influence on water quality and highlights how further investigation into Mn sediment redox processes and mineralogy post-wildfire can inform risk assessments and resource management.

New Mexico↗

USGS2005

Murre eggs ( Uria aalge and Uria lomvia ) as indicators of mercury contamination in the Alaskan marine environment

Sixty common murre ( Uria aalge ) and 27 thick-billed murre ( Uria lomvia ) eggs collected by the Seabird Tissue Archival and Monitoring Project (STAMP) in 1999−2001 from two Gulf of Alaska and three Bering Sea nesting colonies were analyzed for total mercury (Hg) using isotope dilution cold vapor inductively coupled mass spectrometry. Hg concentrations (wet mass) ranged from 0.011 μg/g to 0.357 μg/g (relative standard deviation = 76%), while conspecifics from the same colonies and years had an average relative standard deviation of 33%. Hg levels in eggs from the Gulf of Alaska (0.166 μg/g ± 0.011 μg/g) were significantly higher ( p < 0.0001) than in the Bering Sea (0.047 μg/g ± 0.004 μg/g). Within the Bering Sea, Hg was significantly higher ( p = 0.0007) in eggs from Little Diomede Island near the arctic than at the two more southern colonies. Although thick-billed and common murres are ecologically similar, there were significant species differences in egg Hg concentrations within each region ( p < 0.0001). In the Bering Sea, eggs from thick-billed murres had higher Hg concentrations than eggs from common murres, while in the Gulf of Alaska, common murre eggs had higher concentrations than those of thick-billed murres. A separate one-way analysis of variance on the only time−trend data currently available for a colony (St. Lazaria Island in the Gulf of Alaska) found significantly lower Hg concentrations in common murre eggs collected in 2001 compared to 1999 ( p = 0.017). Results from this study indicate that murre eggs may be effective monitoring units for detecting geographic, species, and temporal patterns of Hg contamination in marine food webs. The relatively small intracolony variation in egg Hg levels and the ability to consistently obtain adequate sample sizes both within and among colonies over a large geographic range means that monitoring efforts using murre eggs will have suitable statistical power for detecting environmental patterns of Hg contamination. The potential influences of trophic effects, physical transport patterns, and biogeochemical processes on these monitoring efforts are discussed, and future plans to investigate the sources of the observed variability are presented.

Environmental Science & Technology↗

USGS2024

Investigating the chemical space coverage of multiple chromatographic and ionization methods using non-targeted analysis on surface and drinking water collected using passive sampling

Multiple non-targeted analysis tools were used to look for a broad range of possible chemical contaminants present in surface and drinking water using liquid chromatography separation and high-resolution mass spectrometry detection, including both quadrupole time of flight (Q-ToF) and Orbitrap instruments. Two chromatographic techniques were evaluated on an LC-Q-ToF with electrospray ionization in both positive and negative modes: (1) the traditionally used reverse phase C18 and (2) the hydrophilic interaction liquid chromatography (HILIC) aimed to capture more polar contaminants that may be present in water. Multiple ionization modes were evaluated with an LC-Orbitrap, including electrospray (ESI) and atmospheric pressure chemical ionization (APCI), also in both positive and negative modes. A suspect screening library of over 1300 possible environmental contaminants, including pesticides, pharmaceuticals, personal care products, illicit drugs/drugs of abuse, and various anthropogenic markers was made with experimentally collected data with the LC-Q-ToF with both column types, with 227 chemicals being retained by the HILIC column. The non-targeted methods using multiple chromatographic and ionization modes were applied to environmental water samples collected with polar organic chemical integrative samplers (POCIS), including surface water upstream and downstream from wastewater effluent discharge, and the downstream drinking water intake and treated drinking water for three distinct sampling events. For the LC-Q-ToF, 442 chemical features were detected on the C18 column and 91 with the HILIC column in the POCIS extracts, while 556 features were found on the Orbitrap workflow by ESI and 131 features detected by APCI. Over 100 chemicals were tentatively identified by suspect screening and database searching. The comprehensive and systematic evaluation of these methods serve as a step in characterizing the chemical space covered when utilizing different chromatography and ionization methods, or different instrument workflows on complex environmental mixtures.

Science of the Total Environment↗

USGS2016

Flood-inundation maps for the Schoharie Creek at Prattsville, New York, 2014

Digital flood-inundation maps for a 2.6-mile reach of the Schoharie Creek at Prattsville, New York, were created by the U.S. Geological Survey (USGS) in cooperation with the New York State Department of Environmental Conservation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Schoharie Creek at Prattsville (station number 01350000). Near-real-time stages at this streamgage may be obtained online from the USGS National Water Information System ( http://waterdata.usgs.gov/ ) or the National Weather Service Advanced Hydrologic Prediction Service ( http://water.weather.gov/ahps/ ), which also forecasts flood hydrographs at this site. National Weather Service-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas and depths of flood inundation. Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the stage-discharge relation (rating 82.0) at the Schoharie Creek at Prattsville streamgage (station 01350000) and high-water marks from the flood of August 28, 2011. The hydraulic model was then used to compute 17 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to greater than the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model, derived from light detection and ranging (lidar) data having a 0.61-foot vertical root-mean squared error and 6.6-foot horizontal resolution, in order to delineate the area flooded at each water level. These flood-inundation maps, along with near-real-time stage data from USGS streamgages and forecasted stage data from the National Weather Service, can provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for postflood recovery efforts.

New York↗

USGS2010

Soil-test N recommendations augmented with PEST-optimized RZWQM simulations

Improved understanding of year-to-year late-spring soil nitrate test (LSNT) variability could help make it more attractive to producers. We test the ability of the Root Zone Water Quality Model (RZWQM) to simulate watershed-scale variability due to the LSNT, and we use the optimized model to simulate long-term field N dynamics under related conditions. Autoregressive techniques and the automatic parameter calibration program PEST were used to show that RZWQM simulates significantly lower nitrate concentration in discharge from LSNT treatments compared with areas receiving fall N fertilizer applications within the tile-drained Walnut Creek, Iowa, watershed (>5 mg N L-1 difference for the third year of the treatment, 1999). This result is similar to field-measured data from a paired watershed experiment. A statistical model we developed using RZWQM simulations from 1970 to 2005 shows that early-season precipitation and early-season temperature account for 90% of the interannual variation in LSNT-based fertilizer N rates. Long-term simulations with similar average N application rates for corn (Zea mays L.) (151 kg N ha-1) show annual average N loss in tile flow of 20.4, 22.2, and 27.3 kg N ha -1 for LSNT, single spring, and single fall N applications. These results suggest that (i) RZWQM is a promising tool to accurately estimate the water quality effects of LSNT; (ii) the majority of N loss difference between LSNT and fall applications is because more N remains in the root zone for crop uptake; and (iii) year-to-year LSNT-based N rate differences are mainly due to variation in early-season precipitation and temperature. Copyright ?? 2010 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Journal of Environmental Quality↗