Surface water is an irreplaceable resource for human survival and environmental sustainability. Accurate, finely detailed cartographic representations of hydrologic streamlines are critically important in various scientific domains, such as assessing the quantity and quality of present and future water resources, modeling climate changes, evaluating agricultural suitability, mapping flood inundation, and monitoring environmental changes. Conventional approaches to detecting such streamlines cannot adequately incorporate information from the complex three-dimensional (3D) environment of streams and land surface features. Such information is vital to accurately delineate streamlines. In recent years, high accuracy lidar data has become increasingly available for deriving both 3D information and terrestrial surface reflectance. This study develops an attention U-net model to take advantage of high-accuracy lidar data for finely detailed streamline detection and evaluates model results against a baseline of multiple traditional machine learning methods. The evaluation shows that the attention U-net model outperforms the best baseline machine learning method by an average F1 score of 11.25% and achieves significantly better smoothness and connectivity between classified streamline channels. These findings suggest that our deep learning approach can harness high-accuracy lidar data for fine-scale hydrologic streamline detection, and in turn produce desirable benefits for many scientific domains.
Recreational waters are primary attractions at many national and state parks where feral swine populations are established, and thus are possible hotspots for visitor exposure to feral swine contaminants. Microbial source tracking (MST) was used to determine spatial and temporal patterns of fecal contamination in Congaree National Park (CONG) in South Carolina, U.S.A., which has an established population of feral swine and is a popular destination for water-based recreation. Water samples were collected between December 2017 and June 2019 from 18 surface water sites distributed throughout CONG. Host specific MST markers included human (HF183), swine (Pig2Bac), ruminant (Rum2Bac), cow (CowM3), chicken (CL), and a marker for shiga toxin producing Escherichia coli (STEC; stx2). Water samples were also screened for culturable Escherichia coli (E. coli) as part of a citizen science program. Neither the cow nor chicken MST markers were detected during the study. The human marker was predominantly detected at boundary sites or could be attributed to upstream sources. However, several detections within CONG without concurrent detections at upstream external sites suggested occasional internal contamination from humans. The swine marker was the most frequently detected of all MST markers, and was present at sites located both internal and external to the Park. Swine MST marker concentrations ≥ 43 gene copies/mL were associated with culturable E. coli concentrations greater than the U.S. Environmental Protection Agency beach action value for recreational waters. None of the MST markers showed a strong association with detection of the pathogenic marker (stx2). Limited information about the health risk from exposure to fecal contamination from non-human sources hampers interpretation of the human health implications.
Along the rugged Southeast Alaska coast, 30 kilometers northeast of the state capital Juneau, a tidewater glacier has largely defied global trends by steadily advancing for most of the past century while most glaciers on Earth retreated. This 55-kilometer-long and nearly 1,500-meter-thick tidewater glacier, named Taku Glacier, or T'aaḵú Ḵwáan Sít'i in the language of the Indigenous Tlingit people, has been the focus of continuous scientific study for more than 70 years. Some records even extend back to the mid-18th century. With this long observation record and the glacier’s year-round accessibility and proximity to Juneau and adjacent research facilities, Taku provides an unparalleled locale to study tidewater glaciers and their response to Earth’s rapidly changing climate.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EO154856","usgsCitation":"McNeil, C., Amundson, J., O’Neel, S., Motyka, R., Sass, L., Truffer, M., Ziemann, J., and Campbell, S., 2021, The imminent calving retreat of Taku Glacier: Eos, American Geophysical Union, https://doi.org/10.1029/2021EO154856.","ipdsId":"IP-118556","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":453402,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021eo154856","text":"Publisher Index Page"},{"id":384576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"102","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McNeil, Christopher J. 0000-0003-4170-0428 cmcneil@usgs.gov","orcid":"https://orcid.org/0000-0003-4170-0428","contributorId":5803,"corporation":false,"usgs":true,"family":"McNeil","given":"Christopher J.","email":"cmcneil@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":812693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amundson, Jason","contributorId":255634,"corporation":false,"usgs":false,"family":"Amundson","given":"Jason","affiliations":[{"id":51619,"text":"University of Alaska, Southeast","active":true,"usgs":false}],"preferred":false,"id":812694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":812695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Motyka, Roman","contributorId":255635,"corporation":false,"usgs":false,"family":"Motyka","given":"Roman","affiliations":[{"id":51619,"text":"University of Alaska, Southeast","active":true,"usgs":false}],"preferred":false,"id":812696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":812697,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Truffer, Martin","contributorId":255636,"corporation":false,"usgs":false,"family":"Truffer","given":"Martin","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":812698,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ziemann, Jenna","contributorId":255637,"corporation":false,"usgs":false,"family":"Ziemann","given":"Jenna","email":"","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":812699,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Campbell, Seth","contributorId":255638,"corporation":false,"usgs":false,"family":"Campbell","given":"Seth","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":812700,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70218762,"text":"70218762 - 2021 - A 100-km wide slump along the upper slope of the Canadian Arctic was likely preconditioned for failure by brackish pore water flushing","interactions":[],"lastModifiedDate":"2021-03-12T13:47:50.163175","indexId":"70218762","displayToPublicDate":"2021-02-18T07:42:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"A 100-km wide slump along the upper slope of the Canadian Arctic was likely preconditioned for failure by brackish pore water flushing","docAbstract":"Exploration of the continental slope of the Canadian Beaufort Sea has revealed a remarkable coalescence of slide scars with headwalls between 130 and 1100 m water depth (mwd). With increased depth, the scars widen and merge into one gigantic regional slide scar that is more than 100 km wide below ~1100 mwd. To understand the development of these features, five sites were investigated with an Autonomous Underwater Vehicle, which provided 1-m bathymetric grids and Chirp profiles, and surveyed with a Remotely Operated Vehicle. The morphologies are consistent with retrograde failures that occurred on failure planes located between 30 and 75 m below the modern seafloor. At issue is whether the continental slope in this area is preconditioned for failure. While rapid sedimentation during glacial periods, and the presence of shallow gas cannot be ruled out, given the geological environment, it is unclear that they are primary preconditioning factors. Evidence of widespread flushing of the slope with brackish waters, and observed flows of brackish water within slide scars, suggest fluid venting and overpressure may play a role in the development of the extensive slope failures seen along this margin. The impact of pore water salinity changes at the depth of the failure plane on slope stability has not been considered in marine settings previously.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2021.106453","usgsCitation":"Paull, C., Dallimore, S., Caress, D., Gwiazda, R., Lundsten, E., Anderson, K., Melling, H., Jin, Y., Duchesne, M., S-G., K., Kim, S., Riedel, M., King, E., and Lorenson, T., 2021, A 100-km wide slump along the upper slope of the Canadian Arctic was likely preconditioned for failure by brackish pore water flushing: Marine Geology, v. 435, 106453, 16 p., https://doi.org/10.1016/j.margeo.2021.106453.","productDescription":"106453, 16 p.","ipdsId":"IP-118551","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453405,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2021.106453","text":"Publisher Index Page"},{"id":384346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Arctic Sea, Canadian Beaufort Sea","volume":"435","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Paull, C. 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However, they simultaneously receive substantial inflows from a variety of ungaged sources including stormwater returns, tile drainage, and irrigation runoff that help sustain flow during dry periods. Due to the inability to identify sources or directly gage many of these inflows, there is a clear need for methods to understand source origination while quantifying potential gains and losses over highly impacted reaches. In the context of the Logan River Observatory, historical gage data illustrate the importance of ungaged and unidentified inflows on maintaining or enhancing flows in both urban and agricultural reaches containing large diversions. To understand the inflows in this portion of the Logan River, we first analysed water samples for ions collected from a subset of representative inflow sources and applied clustering analyses to establish inflow source classifications and associated ion concentration ranges. These representative concentration ranges, combined with mainstem flow and river ion samples taken at sub‐reach scales, allow for the application of flow and mass balances to quantify inflow rates from different sources as well as any losses. These calculations demonstrate significant gains and losses occurring in many sub‐reaches during three sampling events. The dominant land use (urban or agriculture) and flow regime at the time of sampling were the primary drivers of gains and losses. These exchanges were found to be most important below large diversions during low flow conditions. This highlights the need to classify inflow sources (urban or agriculture, surface or groundwater) and estimate their contributions to anticipate instream consequences of land use and water management decisions. As irrigation and water conveyance practices become more efficient, a portion of these ungaged inflows could be diminished or eliminated, thus further depleting streamflow during dry periods.
The U.S. Geological Survey (USGS) National Water-Use Science Project strives to report water-use estimates using the best available information for the period of the estimates. The information available on water used for irrigation activities varies from State to State and in some areas from county to county within a State, which results in many information sources and methods being used to estimate water withdrawals and consumption for the Nation. The variety of estimation methods makes it difficult to compare information across States and makes it difficult to understand how different methods or data sources bias irrigation water-use estimates and trends over time. The sources of information and methods used by USGS Water Science Centers to estimate irrigation water use (the number of irrigated acres by irrigation system type, withdrawal values by water source type, and consumed-water values) for 2015 are compiled and described herein to assist with interpreting the water-use estimates. State-level summaries of information sources and methods are compiled in appendix 1, and a dataset of calendar-year, county-level estimates of actual evapotranspiration for the conterminous United States and Hawaii is provided in an associated USGS data release.
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U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
Marine heatwaves are global phenomena that can have major impacts on the structure and function of coastal ecosystems. By mid-2014, the Pacific Marine Heatwave (PMH) was evident in intertidal waters of the northern Gulf of Alaska and persisted for multiple years. While offshore marine ecosystems are known to respond to these warmer waters, the response of rocky intertidal ecosystems to this warming is unclear. Intertidal communities link terrestrial and marine ecosystems and their resources are important to marine and terrestrial predators and to human communities for food and recreation, while simultaneously supporting a growing coastal tourism industry. Given that current climate change projections suggest increased frequency and duration of marine heatwaves, monitoring and understanding the impacts of heatwaves on intertidal habitats is important. As part of the Gulf Watch Alaska Long-Term Monitoring program, we examined rocky intertidal community structure at 21 sites across four regions spanning 1,200 km of coastline: Western Prince William Sound, Kenai Fjords National Park, Kachemak Bay, and Katmai National Park and Preserve. Sites were monitored annually from 2012 to 2019 at mid and low tidal strata. Before-PMH (2012–2014), community structure differed among regions. We found macroalgal foundation species declined during this period mirroring patterns observed elsewhere for subtidal habitat formers during heatwave events. The region-wide shift from an autotroph-macroalgal dominated rocky intertidal to a heterotroph-filter-feeder dominated state concurrent with the changing environmental conditions associated with a marine heatwave event suggests the PMH had Gulf-wide impacts to the structure of rocky intertidal communities. During/after-PMH (2015–2019), similarities in community structure increased across regions, leading to a greater homogenization of these communities, due to declines in macroalgal cover, driven mostly by a decline in the rockweed, Fucus distichus, and other fleshy red algae in 2015, followed by an increase in barnacle cover in 2016, and an increase in mussel cover in 2017. Strong, large-scale oceanographic events, like the PMH, may override local drivers to similarly influence patterns of intertidal community structure.
Kelp forests form an important biogenic habitat that responds to natural and human drivers. Global concerns exist about threats to kelp forests, yet long-term information is limited and research suggests that trends are geographically distinct. We examined distribution of the bull kelp Nereocystis luetkeana over 145 years in South Puget Sound (SPS), a semi-protected inner basin in a fjord estuary complex in the northeast Pacific Ocean. We synthesized 48 historical and modern Nereocystis surveys and examined presence/absence within 1-km segments along 452 km of shoreline. Compared to the earliest baseline in 1878, Nereocystis extent in 2017 decreased 63%, with individual sub-basins showing up to 96% loss. Losses have persisted for decades, across a range of climate conditions. In recent decades, Nereocystis predominantly occurred along shorelines with intense currents and mixing, where temperature and nutrient concentrations did not reach thresholds for impacts to Nereocystis performance, and high current speeds likely excluded grazers. Losses predominated in areas with elevated temperature, lower nutrient concentrations, and relatively low current velocities. The pattern of long-term losses in SPS contrasts with stability in floating kelp abundance during the last century in an area of the Salish Sea with greater wave exposure and proximity to oceanic conditions. These findings support the hypothesis that kelp beds along wave-sheltered shorelines exhibit greater sensitivity to environmental stressors. Additionally, shorelines with strong currents and deep-water mixing may provide refugia within sheltered systems.
","language":"English","publisher":"PLOS ONE","doi":"10.1371/journal.pone.0229703","usgsCitation":"Berry, H., Mumford, T., Calloway, M., Ferrier, L., Christiaen, B., Dowty, P., vanArendonk, N.R., and Grossman, E.E., 2021, Long-term changes in kelp forests in an inner basin of the Salish Sea: PLoS, v. 16, no. 2, e0229703, 27 p., https://doi.org/10.1371/journal.pone.0229703.","productDescription":"e0229703, 27 p.","ipdsId":"IP-116575","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453416,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0229703","text":"Publisher Index Page"},{"id":385440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.3984375,\n 46.70973594407157\n ],\n [\n -121.86035156249999,\n 46.70973594407157\n ],\n [\n -121.86035156249999,\n 48.019324184801185\n ],\n [\n -123.3984375,\n 48.019324184801185\n ],\n [\n -123.3984375,\n 46.70973594407157\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Berry, H.D.","contributorId":257840,"corporation":false,"usgs":false,"family":"Berry","given":"H.D.","email":"","affiliations":[{"id":52135,"text":"WA Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mumford, T.F.","contributorId":257841,"corporation":false,"usgs":false,"family":"Mumford","given":"T.F.","email":"","affiliations":[{"id":52136,"text":"Marine Agronomics LLC","active":true,"usgs":false}],"preferred":false,"id":815161,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Calloway, M.","contributorId":257844,"corporation":false,"usgs":false,"family":"Calloway","given":"M.","affiliations":[{"id":52135,"text":"WA Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815162,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ferrier, L.","contributorId":257845,"corporation":false,"usgs":false,"family":"Ferrier","given":"L.","email":"","affiliations":[{"id":52135,"text":"WA Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815163,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christiaen, B.","contributorId":257842,"corporation":false,"usgs":false,"family":"Christiaen","given":"B.","email":"","affiliations":[{"id":52135,"text":"WA Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815164,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dowty, P.","contributorId":257843,"corporation":false,"usgs":false,"family":"Dowty","given":"P.","email":"","affiliations":[{"id":52135,"text":"WA Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815165,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":815140,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"vanArendonk, Nathan R. 0000-0003-3911-995X","orcid":"https://orcid.org/0000-0003-3911-995X","contributorId":219469,"corporation":false,"usgs":false,"family":"vanArendonk","given":"Nathan","email":"","middleInitial":"R.","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":815141,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70221225,"text":"70221225 - 2021 - Stewardship and management of freshwater ecosystems: From Leopold's land ethic to a freshwater ethic","interactions":[],"lastModifiedDate":"2021-06-09T14:16:44.014248","indexId":"70221225","displayToPublicDate":"2021-02-17T06:51:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Stewardship and management of freshwater ecosystems: From Leopold's land ethic to a freshwater ethic","docAbstract":"Mountain ranges generate clouds, precipitation, and perennial streamflow for water supplies, but the role of forest cover in mountain hydrometeorology and cloud formation is not well understood. In the Luquillo Experimental Forest of Puerto Rico, mountains are immersed in clouds nightly, providing a steady precipitation source to support the tropical forest ecosystems and human uses. A severe drought in 2015 and the removal of forest canopy (defoliation) by Hurricane Maria in 2017 created natural experiments to examine interactions between the living forest and hydroclimatic processes. These unprecedented land-based observations over 4.5 y revealed that the orographic cloud system was highly responsive to local land-surface moisture and energy balances moderated by the forest. Cloud layer thickness and immersion frequency on the mountain slope correlated with antecedent rainfall, linking recycled terrestrial moisture to the formation of mountain clouds; and cloud-base altitude rose during drought stress and posthurricane defoliation. Changes in diurnal cycles of temperature and vapor-pressure deficit and an increase in sensible versus latent heat flux quantified local meteorological response to forest disturbances. Temperature and water vapor anomalies along the mountain slope persisted for at least 12 mo posthurricane, showing that understory recovery did not replace intact forest canopy function. In many similar settings around the world, prolonged drought, increasing temperatures, and deforestation could affect orographic cloud precipitation and the humans and ecosystems that depend on it.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2021646118","usgsCitation":"Scholl, M.A., Bassiouni, M., and Torres-Sanchez, A.J., 2021, Drought stress and hurricane defoliation influence mountain clouds and moisture recycling in a tropical forest: PNAS, v. 118, no. 7, e2021646118, 8 p., https://doi.org/10.1073/pnas.2021646118.","productDescription":"e2021646118, 8 p.","ipdsId":"IP-117419","costCenters":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":453423,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7896295","text":"Publisher Index Page"},{"id":436507,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UQCN4T","text":"USGS data release","linkHelpText":"Temperature, relative humidity and cloud immersion data for Luquillo Mountains, eastern Puerto Rico, 2014-2019"},{"id":383390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.94543457031249,\n 18.152376614237202\n ],\n [\n -65.5718994140625,\n 18.152376614237202\n ],\n [\n -65.5718994140625,\n 18.449649414656722\n ],\n [\n -65.94543457031249,\n 18.449649414656722\n ],\n [\n -65.94543457031249,\n 18.152376614237202\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":810446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bassiouni, Maoya 0000-0001-5795-9894","orcid":"https://orcid.org/0000-0001-5795-9894","contributorId":251732,"corporation":false,"usgs":false,"family":"Bassiouni","given":"Maoya","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":810447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Torres-Sanchez, Angel J. 0000-0002-5595-021X ajtorres@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-021X","contributorId":5623,"corporation":false,"usgs":true,"family":"Torres-Sanchez","given":"Angel","email":"ajtorres@usgs.gov","middleInitial":"J.","affiliations":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810448,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218177,"text":"sir20215002 - 2021 - Multilevel groundwater monitoring of hydraulic head, water temperature, and chemical constituents in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2014–18","interactions":[],"lastModifiedDate":"2021-02-17T12:58:55.815161","indexId":"sir20215002","displayToPublicDate":"2021-02-16T13:00:15","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5002","displayTitle":"Multilevel Groundwater Monitoring of Hydraulic Head, Water Temperature, and Chemical Constituents in the Eastern Snake River Plain Aquifer, Idaho National Laboratory, Idaho, 2014–18","title":"Multilevel groundwater monitoring of hydraulic head, water temperature, and chemical constituents in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2014–18","docAbstract":"Radiochemical and chemical wastewater discharged to infiltration ponds and disposal wells since the early 1950s at the Idaho National Laboratory (INL), southeastern Idaho, has affected the water quality of the eastern Snake River Plain (ESRP) aquifer. In 2006, the U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, added a multilevel well-monitoring network to their ongoing monitoring program to begin describing the vertical movement and distribution of the chemical constituents in the ESRP aquifer.
The multilevel monitoring system (MLMS) at the INL has been ongoing since 2006, and this report summarizes data collected during 2014–18 from 11 multilevel monitoring wells. Hydraulic head (head) and groundwater temperature data were collected, including 177 measurements from hydraulically isolated depth intervals from 448.0 to 1,377.6 feet below land surface. One port (port 3) within well USGS 134 was not monitored owing to a valve failure.
Note: This is a partial abstract.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215002","collaboration":"DOE/ID-22254Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
Milford Lake has been listed as impaired and designated hypereutrophic because of excessive nutrient loading, specifically biologically available orthophosphate. It is the largest lake by surface area in Kansas and is a reservoir built for purposes including water supply and recreation. In 2015, the Kansas Department of Health and Environment (KDHE) divided the lake into three zones (Zones A, B, and C) for recreational monitoring of harmful algal blooms (HABs). Upstream Zone C has historically been more affected by HABs than Zones B and A, and Zone C has historically had the highest phosphorus concentrations.
The U.S. Geological Survey, in cooperation with the KDHE, completed a study in 2017–18 to assess the spatial and temporal variability of nutrients and algae in the Republican River (the primary inflow to Milford Lake) and Milford Lake using spatially and temporally dense data. During the study period, discrete water-quality samples were collected at 36 lake sites, 21 river sites, and 1 pond. All samples were analyzed for nutrients; some samples were also analyzed for chlorophyll, phycocyanin, microcystin, and (or) phytoplankton community composition and abundance. Results from this study provide perspective for understanding the potential role nutrient and algal conditions have in facilitating the formation of HABs and may inform future actions to prevent and mitigate HABs and their potential effects on human and environmental health.
In 2017, one low-flow floating synoptic on the Republican River into Zone C of Milford Lake and one 24-hour synoptic in Zone C of Milford Lake were completed. Results from the low-flow floating synoptic on July 17, 2017, at 21 river sites, 8 lake sites, and 1 pond site indicated that the Republican River was not contributing dissolved orthophosphate or total phosphorus concentrations higher than those in the main body of Milford Lake.
No patterns in nutrient or total microcystin concentrations were evident from the 24-hour synoptic at two sites on August 24–25, 2017. Total nitrogen was dominated by total Kjeldahl nitrogen (TKN) at both sites. Different oscillation activity in algal biomass and chlorophyll at the two sites demonstrated the variable nature of algal accumulations and their effects on nutrient and dissolved oxygen concentrations. Different patterns in chlorophyll and microcystin concentrations indicate that the relation between algal biomass and cyanotoxin concentrations were different at the two sites, possibly because of differences among algal communities present at each site.
Three whole-lake synoptics through Zones A, B, and C in Milford Lake were completed on July 10, August 9, and October 16–17, 2018, at 30 lake sites. Orthophosphate was consistently at least 77 percent of total phosphorus at all sites except the two most uplake sites. At the two most uplake sites, orthophosphate was between 52 and 72 percent of the total phosphorus present at the site.
Concentrations of TKN were not consistently increasing or decreasing during 2018. Total nitrogen was dominated by TKN in July and August. Very low concentrations of dissolved nitrate plus nitrite indicate that the nutrient was likely tied up in algal biomass. By October, total nitrogen was approximately one-half TKN and one-half dissolved nitrate plus nitrite. Higher concentrations of dissolved orthophosphate and dissolved nitrate plus nitrite in October than in July and August were likely caused by reduced biological activity (less uptake of nutrients) and lower air and water temperatures. Multiple inflow events (streamflow greater than median daily value) between August and October also may have moved nutrients through the lake.
Chlorophyll, phycocyanin, microcystin, and phytoplankton samples were collected at eight sites in 2018. Most sites had their highest chlorophyll concentrations in August. The three most uplake sites had their highest phycocyanin concentrations in July, whereas the other five sites had their highest phycocyanin concentrations in August. Two of 23 samples had detections of total microcystin (0.11 and 0.12 microgram per liter). Phytoplankton community composition mainly consisted of Bacillariophyta, Chlorophyta, Cryptophyta, and Cyanobacteria. Phytoplankton community composition and abundance data described broad seasonal patterns and did not capture the full range of possible conditions at each site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205135","collaboration":"Prepared in cooperation with the Kansas Department of Health and Environment","usgsCitation":"Leiker, B.M., Abel, J.R., Graham, J.L., Foster, G.M., King, L.R., Stiles, T.C., and Buley, R.P., 2021, Spatial and temporal variability of nutrients and algae in the Republican River and Milford Lake, Kansas, June through November 2017 and May through November 2018: U.S. Geological Survey Scientific Investigations Report 2020–5135, 53 p., https://doi.org/10.3133/sir20205135.","productDescription":"Report: viii, 53 p.; 3 Data Releases; Dataset","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-116622","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":383231,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":383228,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XO24L3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Phytoplankton data for Milford Lake, Kansas, June through October 2018"},{"id":383226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5135/coverthb.jpg"},{"id":383227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5135/sir20205135.pdf","text":"Report","size":"6.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5135"},{"id":383230,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZA2HE7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Vertical profiles of water-quality data from two sites in Milford Lake, Kansas, August 24–25, 2017"},{"id":383229,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CX2GFI","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Time-lapse photography of Milford Lake, Kansas, June through November 2017 and June through November 2018"}],"country":"United States","state":"Kansas","otherGeospatial":"Republican River, Milford Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.12875366210938,\n 39.03838632847035\n ],\n [\n -96.82937622070312,\n 39.03838632847035\n ],\n [\n -96.82937622070312,\n 39.32367475355144\n ],\n [\n -97.12875366210938,\n 39.32367475355144\n ],\n [\n -97.12875366210938,\n 39.03838632847035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
Resource managers in the Pacific Northwest (USA) actively thin second-growth forests to accelerate the development of late-successional conditions and seek to expand these restoration thinning treatments into riparian zones. Riparian forest thinning, however, may impact stream temperatures–a key water quality parameter often regulated to protect stream habitat and aquatic organisms. To better understand the effects of riparian thinning on shade, light, and stream temperature, we employed a manipulative field experiment following a replicated Before-After-Control-Impact (BACI) design in three watersheds in the redwood forests of northern California, USA. Thinning treatments were intended to reduce canopy closure or basal area within the riparian zone by up to 50% on both sides of the stream channel along a 100–200 m stream reach. We found that responses to thinning ranged widely depending on the intensity of thinning treatments. In the watersheds with more intensive treatments, thinning reduced shade, increased light, and altered stream thermal regimes in thinned and downstream reaches. Thinning shifted thermal regimes by increasing maximum temperatures, thermal variability, and the frequency and duration of elevated temperatures. These thermal responses occurred primarily during summer but also extended into spring and fall. Longitudinal profiles indicated that increases in temperature associated with thinning frequently persisted downstream, but downstream effects depended on the magnitude of upstream temperature increases. Model selection analyses indicated that local changes in shade as well as upstream thermal conditions and proximity to upstream treatments explained variation in stream temperature responses to thinning. In contrast, in the study watershed with less intensive thinning, smaller changes in shade and light resulted in minimal stream temperature responses. Collectively, our data shed new light on the stream thermal responses to riparian thinning. These results provide relevant information for managers considering thinning as a viable restoration strategy for second-growth riparian forests.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0246822","usgsCitation":"Roon, D., Dunham, J.B., and Groom, J.D., 2021, Shade, light, and stream temperature responses to riparian thinning in second-growth redwood forests of northern California: PLoS ONE, v. 16, no. 2, e0246822, 25 p., https://doi.org/10.1371/journal.pone.0246822.","productDescription":"e0246822, 25 p.","ipdsId":"IP-124305","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":453427,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0246822","text":"Publisher Index Page"},{"id":384959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Redwood National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.21142578125,\n 41.50034959128928\n ],\n [\n -123.651123046875,\n 41.50034959128928\n ],\n [\n -123.651123046875,\n 42.00032514831621\n ],\n [\n -124.21142578125,\n 42.00032514831621\n ],\n [\n -124.21142578125,\n 41.50034959128928\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Roon, David","contributorId":257063,"corporation":false,"usgs":false,"family":"Roon","given":"David","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":813772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Groom, Jeremiah D","contributorId":257065,"corporation":false,"usgs":false,"family":"Groom","given":"Jeremiah","email":"","middleInitial":"D","affiliations":[{"id":51978,"text":"Groom Analytics, LLC","active":true,"usgs":false}],"preferred":false,"id":813774,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218783,"text":"70218783 - 2021 - The role of hydrates, competing chemical constituents, and surface composition on CLNO2 formation","interactions":[],"lastModifiedDate":"2021-03-12T13:46:18.062877","indexId":"70218783","displayToPublicDate":"2021-02-15T07:45:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7760,"text":"Environmental Science Technology","active":true,"publicationSubtype":{"id":10}},"title":"The role of hydrates, competing chemical constituents, and surface composition on CLNO2 formation","docAbstract":"Atomic chlorine (Cl•) affects air quality and atmospheric oxidizing capacity. Nitryl chloride (ClNO2) – a common Cl• source–forms when chloride-containing aerosols react with dinitrogen pentoxide (N2O5). A recent study showed that saline lakebed (playa) dust is an inland source of particulate chloride (Cl–) that generates high ClNO2. However, the underlying physiochemical factors responsible for observed yields are poorly understood. To elucidate these controlling factors, we utilized single particle and bulk techniques to determine the chemical composition and mineralogy of playa sediment and dust samples from the southwest United States. Single particle analysis shows trace highly hygroscopic magnesium and calcium Cl-containing minerals are present and likely facilitate ClNO2 formation at low humidity. Single particle and mineralogical analysis detected playa sediment organic matter that hinders N2O5 uptake as well as 10 Å-clay minerals (e.g., Illite) that compete with water and chloride for N2O5. Finally, we show that the composition of the aerosol surface, rather than the bulk, is critical in ClNO2 formation. These findings underscore the importance of mixing state, competing reactions, and surface chemistry on N2O5 uptake and ClNO2 yield for playa dusts and, likely, other aerosol systems. Therefore, consideration of particle surface composition is necessary to improve ClNO2 and air quality modeling.
Coral reefs generate substantial volumes of carbonate sediment, which is redistributed throughout the reef‐lagoon system. However, there is little understanding of the specific processes that transport this sediment produced on the outer portions of coral reefs throughout a reef‐lagoon system. Furthermore, the separate contributions of currents, sea‐swell waves, and infragravity waves to transport, which are all strongly influenced by the presence of a reef, is not fully understood. Here, we show that in reef‐lagoon systems most suspended sediment is transported close to the seabed and can, at times, be suspended higher in the water column during oscillatory flow transitions (i.e., near slack flow) at sea‐swell wave frequencies, and during the peak onshore oscillatory velocity phase at infragravity wave frequencies. While these wave frequencies contribute to the transport of suspended sediment offshore and onshore, respectively, the net flux is small. Mean currents are the primary transport mechanism and responsible for almost 2 orders of magnitude more suspended‐sediment flux than sea‐swell and infragravity waves. Whilst waves may not be the primary mechanism for the transport of sediment, our results suggest they are an important driver of sediment suspension from the seabed, as well as contributing to the partitioning of sediment grain sizes from the reef to the shoreline. As the ocean wave climate changes, sea level rises, and the composition of reef benthic communities change, the relative importance of mean currents, sea‐swell waves, and infragravity waves is likely to change, and this will affect how sediment is redistributed throughout reef‐lagoon systems.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JC017010","usgsCitation":"Pomeroy, A., Storlazzi, C.D., Rosenberger, K.J., Lowe, R., Hansen, J., and Buckley, M.L., 2021, The contribution of currents, sea-swell waves, and infragravity waves to suspended-sediment transport across a coral reef-lagoon system.: JGR Oceans, v. 126, no. 3, e2020JC017010, 26 p., https://doi.org/10.1029/2020JC017010.","productDescription":"e2020JC017010, 26 p.","ipdsId":"IP-124202","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453454,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jc017010","text":"Publisher Index Page"},{"id":385282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Ningaloo Reef","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 113.6370849609375,\n -22.550610920226646\n ],\n [\n 113.69888305664062,\n -22.532853707527117\n ],\n [\n 113.76068115234374,\n -22.38690459799015\n ],\n [\n 113.8623046875,\n -22.146707780012616\n ],\n [\n 113.98452758789062,\n -21.86532228248991\n ],\n [\n 113.27041625976562,\n -21.90737455082829\n ],\n [\n 113.13858032226562,\n -22.673580199535557\n ],\n [\n 113.27316284179688,\n -22.823023136184315\n ],\n [\n 113.66729736328125,\n -22.72172372713301\n ],\n [\n 113.6810302734375,\n -22.658373466642733\n ],\n [\n 113.653564453125,\n -22.58104653946133\n ],\n [\n 113.6370849609375,\n -22.550610920226646\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Pomeroy, Andrew","contributorId":182033,"corporation":false,"usgs":false,"family":"Pomeroy","given":"Andrew","affiliations":[],"preferred":false,"id":814613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":814614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":814615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowe, Ryan","contributorId":177845,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","affiliations":[],"preferred":false,"id":814616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Jeff","contributorId":149139,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","affiliations":[],"preferred":false,"id":814617,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":814618,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219003,"text":"70219003 - 2021 - Months-long spike in aqueous Arsenic following domestic well installation and disinfection: Short- and long-term drinking water quality implications","interactions":[],"lastModifiedDate":"2021-03-19T11:47:19.096213","indexId":"70219003","displayToPublicDate":"2021-02-13T07:28:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2331,"text":"Journal of Hazardous Materials","active":true,"publicationSubtype":{"id":10}},"title":"Months-long spike in aqueous Arsenic following domestic well installation and disinfection: Short- and long-term drinking water quality implications","docAbstract":"Exposure to high concentration geogenic arsenic via groundwater is a worldwide health concern. Well installation introduces oxic drilling fluids and hypochlorite (a strong oxidant) for disinfection, thus inducing geochemical disequilibrium. Well installation causes changes in geochemistry lasting 12 + months, as illustrated in a recent study of 250 new domestic wells in Minnesota, north-central United States. One study well had extremely high initial arsenic (1550 µg/L) that substantially decreased after 15 months (5.2 µg/L). The drilling and development of the study well were typical and ordinary; nothing observable indicated the very high initial arsenic concentration. We hypothesized that oxidation of arsenic-containing sulfides (which lowers pH) combined with low pH dissolution of arsenic-bearing Fe (oxyhydr)oxides caused the very high arsenic concentration. Geochemical equilibrium considerations and modeling supported our hypothesis. Groundwater equilibrium redox conditions are poised at the Fe(III)(s)/Fe(II)(aq) stability boundary, indicating arsenic-bearing Fe (oxyhydr)oxide mineral sensitivity to pH and redox changes. Changing groundwater geochemistry can have negative implications for home water treatment (e.g., reduced arsenic removal efficiency, iron fouling), which can lead to ongoing but unrecognized hazard of arsenic exposure from domestic well water. Our results may inform arsenic mobilization processes and geochemical sensitivity in similarly complex aquifers in Southeast Asia and elsewhere.
Lawns as a landcover change substantially alter evapotranspiration, CO2, and energy exchanges and are of rising importance considering their spatial extent. We contrast eddy covariance (EC) flux measurements collected in the Denver, Colorado, USA metropolitan area in 2011 and 2012 over a lawn and a xeric tallgrass prairie. Close linkages between seasonal vegetation development, energy fluxes, and net ecosystem exchange (NEE) of CO2 were found. Irrigation of the lawn modified energy and CO2 fluxes and greatly contributed to differences observed between sites. Due to greater water inputs (precipitation + irrigation) at the lawn in this semi-arid climate, energy partitioning at the lawn was dominated by latent heat (LE) flux. As a result, evapotranspiration (ET) of the lawn was more than double that of tallgrass prairie (2011: 639(±17) mm vs. 302(±9) mm; 2012: 584(±15) mm vs. 265(±7) mm). NEE for the lawn was characterized by a longer growing season, higher daily net uptake of CO2, and growing season NEE that was also more than twice that of the prairie (2011: −173(±23) g C m−2 vs. -81(±10) g C m−2; 2012: −73(±22) g C m−2 vs. -21(±8) g C m−2). During the drought year (2012), temperature and water stress greatly influenced the direction and magnitude of CO2 flux at both sites. The results suggest that lawns in Denver can function as carbon sinks and conditionally contribute to the mitigation of carbon emissions - directly by CO2 uptake and indirectly through effects of evaporative cooling on microclimate and energy use.
During the Pacific marine heatwave of 2014–2016, abundance and quality of several key forage fish species in the Gulf of Alaska were simultaneously reduced throughout the system. Capelin (Mallotus catervarius), sand lance (Ammodytes personatus), and herring (Clupea pallasii) populations were at historically low levels, and within this community abrupt declines in portfolio effects identify trophic instability at the onset of the heatwave. Although compensatory changes in age‐structure, size, growth or energy content of forage fish were observed to varying degrees among all these forage fish, none were able to fully mitigate adverse impacts of the heatwave, which likely included both top‐down and bottom‐up forcing. Notably, changes to the demographic structure of forage fish suggested size‐selective removals typical of top‐down regulation. At the same time, zooplankton community structure may have driven bottom‐up regulation as copepod community structure shifted towards smaller, warm‐water species, and euphausiid biomass was reduced owing to the loss of cold‐water species. Mediated by these impacts on the forage fish community, an unprecedented disruption of the normal pelagic food web was signaled by higher trophic level disruptions during 2015–2016, when seabirds, marine mammals, and groundfish experienced shifts in distribution, mass mortalities, and reproductive failures. Unlike decadal‐scale variability underlying ecosystem regime shifts, the heatwave appeared to temporarily overwhelm the ability of the forage fish community to buffer against changes imposed by warm water anomalies, thereby eliminating any ecological advantages that may have accrued from having a suite of coexisting forage species with differing life history compensations.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15556","usgsCitation":"Arimitsu, M.L., Piatt, J.F., Hatch, S., Suryan, R., Batten, S., Bishop, M.A., Campbell, R.W., Coletti, H., Cushing, D., Gorman, K., Hopcroft, R.R., Kuletz, K.J., Marsteller, C.E., McKinstry, C., McGowan, D., Moran, J., Pegau, W., Schaefer, A., Schoen, S.K., Straley, J., and von Biela, V.R., 2021, Heatwave-induced synchrony within forage fish portfolio disrupts energy flow to top pelagic predators: Global Change Biology, v. 27, no. 9, p. 1859-1878, https://doi.org/10.1111/gcb.15556.","productDescription":"20 p.","startPage":"1859","endPage":"1878","ipdsId":"IP-123071","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":453466,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.15556","text":"Publisher Index Page"},{"id":383375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -135,\n 56.32872090717995\n ],\n [\n -138.1640625,\n 59.00662762374203\n ],\n [\n -143.37158203125,\n 60.18523283150752\n ],\n [\n -145.72265625,\n 60.3812902796077\n ],\n [\n -149.87548828125,\n 59.85585085709834\n ],\n [\n -152.2265625,\n 58.0546319113729\n ],\n [\n -153.91845703125,\n 56.47462805805594\n ],\n [\n -135,\n 56.32872090717995\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-03-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 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The white sucker hepatitis B virus (WSHBV) was first described in the white sucker (Catostomus commersonii), a freshwater teleost, and belongs to the genus Parahepadnavirus. At present, the host range of WSHBV and its impact on fish health are unknown, and neither genetic diversity nor association with fish health have been studied in any parahepadnavirus. Given the relevance of genomic diversity to disease outcome for the orthohepadnaviruses, we sought to characterize genomic variation in WSHBV and determine how it is structured among watersheds. We identified WSHBV-positive white sucker inhabiting tributaries of Lake Michigan, Lake Superior, Lake Erie (USA), and Lake Athabasca (Canada). Copy number in plasma and in liver tissue was estimated via qPCR. Templates from 27 virus-positive fish were amplified and sequenced using a primer-specific, circular long-range amplification method coupled with amplicon sequencing on the Illumina MiSeq. Phylogenetic analysis of the WSHBV genome identified phylogeographical clustering reminiscent of that observed with human hepatitis B virus genotypes. Notably, most non-synonymous substitutions were found to cluster in the pre-S/spacer overlap region, which is relevant for both viral entry and replication. The observed predominance of p1/s3 mutations in this region is indicative of adaptive change in the polymerase open reading frame (ORF), while, at the same time, the surface ORF is under purifying selection. Although the levels of variation we observed do not meet the criteria used to define sub/genotypes of human and avian hepadnaviruses, we identified geographically associated genome variation in the pre-S and spacer domain sufficient to define five WSHBV haplotypes. This study of WSHBV genetic diversity should facilitate the development of molecular markers for future identification of genotypes and provide evidence in future investigations of possible differential disease outcomes.
","language":"English","publisher":"MDPI","doi":"10.3390/v13020285","usgsCitation":"Adams, C., Blazer, V., Sherry, J., Cornman, R.S., and Iwanowicz, L., 2021, Phylogeographic genetic diversity in the white sucker hepatitis B Virus across the Great Lakes Region and Alberta, Canada: Viruses, v. 13, no. 2, 285, 17 p., https://doi.org/10.3390/v13020285.","productDescription":"285, 17 p.","ipdsId":"IP-109590","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":453470,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v13020285","text":"Publisher Index Page"},{"id":383276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, Michigan, Minnesota, Ohio, Wisconsin","otherGeospatial":"Athabasca River, Detroit River, Fox River, Lake Erie, Lake Michigan , Lake Superior, Milwaukee River, Root River, Sheboygan River, St. Louis River, Swan Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.900390625,\n 46.28622391806706\n ],\n [\n -91.62597656249999,\n 46.28622391806706\n ],\n [\n -91.62597656249999,\n 46.98025235521883\n ],\n [\n -92.900390625,\n 46.98025235521883\n ],\n [\n -92.900390625,\n 46.28622391806706\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.505859375,\n 42.68243539838623\n ],\n [\n -87.5830078125,\n 42.68243539838623\n ],\n [\n -87.5830078125,\n 44.77793589631623\n ],\n [\n -88.505859375,\n 44.77793589631623\n ],\n [\n -88.505859375,\n 42.68243539838623\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.8037109375,\n 41.178653972331674\n ],\n [\n -83.056640625,\n 41.178653972331674\n ],\n [\n -83.056640625,\n 42.5530802889558\n ],\n [\n -83.8037109375,\n 42.5530802889558\n ],\n [\n -83.8037109375,\n 41.178653972331674\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.64208984374999,\n 54.16243396806779\n ],\n [\n -113.15917968749999,\n 54.16243396806779\n ],\n [\n -113.15917968749999,\n 55.50374985927514\n ],\n [\n -115.64208984374999,\n 55.50374985927514\n ],\n [\n -115.64208984374999,\n 54.16243396806779\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Cynthia R 0000-0003-4383-530X","orcid":"https://orcid.org/0000-0003-4383-530X","contributorId":219530,"corporation":false,"usgs":false,"family":"Adams","given":"Cynthia R","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":810314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":810315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherry, Jim","contributorId":251691,"corporation":false,"usgs":false,"family":"Sherry","given":"Jim","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":810316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":810317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":810318,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218675,"text":"70218675 - 2021 - Airborne geophysical imaging of weak zones on Iliamna Volcano, Alaska: Implications for slope stability","interactions":[],"lastModifiedDate":"2021-03-05T13:52:47.045359","indexId":"70218675","displayToPublicDate":"2021-02-12T07:44:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Airborne geophysical imaging of weak zones on Iliamna Volcano, Alaska: Implications for slope stability","docAbstract":"Water‐saturated, hydrothermally altered rocks reduce the strength of volcanic edifices and increase the potential for sector collapses and far‐traveled mass flows of unconsolidated debris. Iliamna Volcano is an andesitic stratovolcano located on the western side of the Cook Inlet, ∼225 km southwest of Anchorage and is a source of repeated avalanches. The widespread snow and ice cover on Iliamna Volcano make surface alteration difficult to identify. However, intense hydrothermal alteration significantly reduces both the electrical resistivity and magnetization of volcanic rock and can therefore be identified with airborne geophysical measurements. We use airborne electromagnetic and magnetic data to map snow and ice thickness and identify underlying alteration zones at Iliamna Volcano, Alaska. Resistivities were calculated to an average depth of >300 m, and a 3‐D susceptibility model extends from the surface to the base of the volcano, about 3,000 m below the summit. Geophysical models image low resistivity (<30 ohm‐m) and low susceptibilities near the summit of Iliamna and below its older vent complex, with the low susceptibilities indicating alteration up to ∼800 m in thickness. Thin conductors (∼50–100 m thick) on the edifice slopes coincide with recorded locations of repeated debris avalanches over the past ∼60 years and are attributed to saturated zones at high elevation. Three‐dimensional slope stability models based upon the geophysically constrained alteration distribution suggest the edifice of Iliamna is unstable and could lead to collapse scars ∼400 m deep near the current and former vent complexes.
In recent years, benthic algae have been increasing in abundance in the littoral zones of oligotrophic lakes, but causality has been hard to assign. We used field and laboratory experiments to explore the implications of increasing water temperature and nutrient availability for benthic algal assemblages and ecosystem processes in a Colorado alpine lake. We tested the effect of nutrient enrichment on the relative abundance of algal taxonomic groups in situ using nutrient diffusing substrata. We manipulated temperature and nutrient concentrations in laboratory assays to assess their interactive effects on ecosystem function of chlorophyte-dominated benthic assemblages. Nutrient enrichment with both N and P favored Chlorophyta (green algae) in field experiments and produced the highest overall algal biomass. In the absence of nutrient enrichment, the relative abundance of Bacillariophyta (diatoms) was substantially greater than that of Chlorophyta and cyanobacteria. In laboratory assays, N uptake increased but net ecosystem production decreased with warming temperatures, resulting in reduced N-use efficiency. Even though dissolved organic C (DOC) substantially increased in solution after all laboratory incubations, lower DOC concentrations in the assays with added P and warmer temperatures suggest nutrients and warming stimulated heterotrophic microorganisms as well as primary producers. Our results demonstrate that nutrient availability stimulates Chlorophyta in benthic algal assemblages and that the increase in chlorophytes may alter ecosystem processes with ongoing, rapid environmental change, including N cycling and metabolic functions in oligotrophic lake littoral habitats.
Concentrations, loads, and yields of nitrate plus nitrite, total nitrogen, and total phosphorus were assessed in the Iowa River upstream from the Coralville Reservoir in east-central Iowa. The results of this study describe baseline nutrient transport during two historical reference periods, 1980–96 and 2006–10, that can be used to evaluate the progress of the implementation of reduction strategies in the Middle Iowa River Basin. Where available, nutrient data during the more recent period 2011–18 are also described. Data included nutrient concentrations and streamflow from multiple Federal, State, and Tribal agencies, and loads were computed using multiple techniques to provide valuable insights, which would otherwise not be possible.
Despite an upward trend for mean annual and base streamflow (the trend in high streamflow was not significant), average nutrient loads and yields in the Iowa River were smaller in the recent period (2011–18) than in either historical reference period. Notably smaller loads during the 2012 drought, however, caused pronounced skewed average loads for 2011–18. Comparisons among periods were difficult to make because of a short period of data upstream from Marshalltown, Iowa, at the upstream boundary of the study area and a lack of recent data near Marengo, Iowa, at the downstream boundary of the study area. Though spring and summer loads were a disproportionate part of annual loads, up to 90 percent, seasonal load comparisons to determine load reduction were more sensitive to one or the other historical period than was assessment of annual loads. Runoff-transport relations may provide an additional tool to assess load reduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205148","collaboration":"Prepared in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa","usgsCitation":"Garrett, J.D., and Kalkhoff, S.J., 2021, Nutrient concentrations, loads, and yields in the Middle Iowa River Basin, Iowa: U.S. Geological Survey Scientific Investigations Report 2020–5148, 22 p., https://doi.org/10.3133/sir20205148.","productDescription":"Report: vii, 22 p.; 1 Table; Dataset","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-116761","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":383240,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5148/sir20205148_table1.1.csv","text":"Table 1.1","size":"23.3 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5148 Table 1.1","linkHelpText":"— Tributary sites in the Middle Iowa River Basin, upstream of Coralville Reservoir"},{"id":383239,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5148/sir20205148_table1.1.xlsx","text":"Table 1.1","size":"28.1 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5148 Table 1.1","linkHelpText":"— Tributary sites in the Middle Iowa River Basin, upstream of Coralville Reservoir"},{"id":383241,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":383238,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5148/sir20205148.pdf","text":"Report","description":"SIR 2020–5148"},{"id":383237,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5148/coverthb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Middle Iowa River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.065673828125,\n 41.380930388318\n ],\n [\n -90.911865234375,\n 41.529141988723104\n ],\n [\n -90.9613037109375,\n 41.79179268262892\n ],\n [\n -91.2249755859375,\n 42.020732852644294\n ],\n [\n -91.5655517578125,\n 42.17968819665961\n ],\n [\n -91.900634765625,\n 42.34636533160187\n ],\n [\n -92.142333984375,\n 42.66224137632748\n ],\n [\n -92.3291015625,\n 42.984558134256076\n ],\n [\n -92.5323486328125,\n 43.18114705939968\n ],\n [\n -92.7685546875,\n 43.20917969039356\n ],\n [\n -92.9058837890625,\n 43.08894918346591\n ],\n [\n -92.8564453125,\n 42.807491865911544\n ],\n [\n -92.6641845703125,\n 42.55712670332118\n ],\n [\n -92.46093749999999,\n 42.28137302193453\n ],\n [\n -92.1148681640625,\n 42.00848901572399\n ],\n [\n -91.8731689453125,\n 41.70982942509964\n ],\n [\n -91.6644287109375,\n 41.40565583808169\n ],\n [\n -91.4117431640625,\n 41.1455697310095\n ],\n [\n -91.175537109375,\n 41.000629848685385\n ],\n [\n -91.0052490234375,\n 40.9964840143779\n ],\n [\n -90.911865234375,\n 41.017210578228436\n ],\n [\n -90.94482421875,\n 41.104190944576466\n ],\n [\n -90.99426269531249,\n 41.21585377825921\n ],\n [\n -91.04919433593749,\n 41.25716209782705\n ],\n [\n -91.065673828125,\n 41.380930388318\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
The Harford County Department of Public Works and the U.S. Geological Survey have been working cooperatively to monitor continuous streamflow at several streamgages in Harford County, Maryland, including Bynum Run and Winters Run. A perceived recent uptick in the number of flooding events in the Bynum Run and Winters Run watersheds have led to questions about the relative frequency and magnitude of floods experienced by county residents. Precipitation, stage (water elevation), and peak flow analyses and trends were evaluated. Although there was no one contributor to point to for the perceived increase in flooding, it is most likely attributable to a combination of precipitation, stage, and peak flow. There have been numerous rainfall events with exceedingly long return intervals, but none were statistically out of the ordinary. The stages of the streams at higher flows are slightly higher (less than 0.5 feet) than historical stages, but likely are not great enough to cause a significant increase in flooding. The ratings (stage discharge relationship) for the streams have changed slightly. The latest ratings indicate erosion and deposition in the streambed over the years of observation, but again these alone do not result in more flooding. These factors taken together may point to an observational bias for incidental flooding. With the increase in land development, there may simply be more observations of flooding in the county.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215007","collaboration":"Prepared in cooperation with the Harford County Department of Public Works","usgsCitation":"Nealen, C.W., and Doheny, E.J., 2021, Precipitation, peak streamflow, and inundation in the Bynum Run and Winters Run watersheds in Harford County, Maryland: U.S. Geological Survey Scientific Investigations Report 2021–5007, 12 p., https://doi.org/10.3133/sir20215007.","productDescription":"vi, 12 p.","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095939","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":383193,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5007/sir20215007.pdf","text":"Report","size":"3.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5007"},{"id":383192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5007/coverthb.jpg"}],"country":"United States","state":"Maryland","county":"Harford County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.5032958984375,\n 39.2492708462234\n ],\n [\n -75.89355468749999,\n 39.50404070558415\n ],\n [\n -75.882568359375,\n 39.7240885773337\n ],\n [\n -76.8658447265625,\n 39.72831341029745\n ],\n [\n -76.5032958984375,\n 39.2492708462234\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228