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Widespread mortality of Pacific salmon Oncorhynchus spp. returning to spawn in Alaska coincided with record-breaking air temperatures and prolonged drought in summer 2019. Extreme environmental conditions are expected to happen more frequently with rapid climate change and challenge the notion that Alaska could indefinitely provide abundant, cool freshwater habitat for Pacific salmon. A total of 110 geographically widespread opportunistic observations of premature mortality (carcasses) were collected from a variety of sources. Premature mortalities were documented for Pink Salmon Oncorhynchus gorbuscha, Sockeye Salmon O. nerka, Chum Salmon O. keta, Chinook Salmon O. tshawytscha, and Coho Salmon O. kisutch. Additionally, observations of Pink Salmon returning to spawn in Prince William Sound streams in 2019, obtained from systematic aerial surveys conducted annually, revealed low migration success in 87% of rain-driven streams (n = 30), 52% of snow-driven streams (n = 65), and only 18% of glacier-driven streams (n = 11). Salmon mortality observations were consistent with death due to heat stress resulting from high water temperatures or drought caused hypoxia and stranding. Developing a better understanding of how broad-scale climate patterns manifest at the stream scale can help us determine whether a major shift in Pacific salmon productivity is underway and inform fisheries management plans to better mitigate future risks.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/fsh.10705","usgsCitation":"von Biela, V.R., Sergeant, C.J., Carey, M.P., Liller, Z., Russell, C.M., Quinn-Davidson, S., Rand, P., Westley, P., and Zimmerman, C.E., 2022, Premature mortality observations among Alaska’s Pacific salmon during record heat and drought in 2019: Fisheries, v. 47, no. 4, p. 157-168, https://doi.org/10.1002/fsh.10705.","productDescription":"12 p.","startPage":"157","endPage":"168","ipdsId":"IP-124149","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":435967,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P920AL34","text":"USGS data release","linkHelpText":"Observations Documenting Premature Mortality Among Alaska's Pacific Salmon in 2019"},{"id":399809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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The snail kite (Rostrhamus sociabilis plumbeus), an endangered, wetland-dependent raptor, is highly sensitive to changes in hydrology. Climate-driven changes in water level will likely affect snail kite populations—altering reproductive success and survival rates. Identifying the mechanisms mediating the direct and indirect effects of climate on snail kite populations and the range of future climate conditions is important to the conservation of this species. When water levels are low, snail kite nest initiation and nest success decrease owing to decreased availability of their primary prey applesnails (Pomacea spp.), unstable nesting sites, and increased predator access. Dry events also lead to decreased adult and juvenile survival. In the next 80 years, temperatures and potential evapotranspiration are projected to increase in central and southern Florida. Although future precipitation volume is more uncertain, increased temperatures and evaporative loss may lead to increased frequency, duration, and severity of low-water events. Additionally, rapidly rising water levels have adverse effects on snail kite reproductive success—destroying nests, preventing access to apple snails, and reducing apple snail productivity. Finally, it is likely that future climate will favor more frequent dry conditions and extreme heavy rainfall events, both of which are directly linked to decreased reproductive success and survival. The potential effects of climate change may be buffered by the availability of alternative prey (non-native applesnails) that are more tolerant of anticipated conditions. In highly controlled southern Florida waterbodies, regional water-management decisions may buffer or exacerbate waterbody accession and recession rates.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211104A","usgsCitation":"Lyons, M.P., LeDee, O.E., and Boyles, R., 2021, Potential effects of climate change on snail kites (Rostrhamus sociabilis plumbeus) in Florida: U.S. Geological Survey Open-File Report 2021–1104–A, 12 p., https://doi.org/10.3133/ofr20211104A.","productDescription":"vi, 12 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-131203","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":393183,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1104/a/images"},{"id":393182,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1104/a/ofr20211104A.XML","size":"75.8 kB","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2021–1104 XML"},{"id":393181,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1104/a/ofr20211104A.pdf","text":"Report","size":"5.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1104"},{"id":393180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1104/a/coverthb3.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park, Lake Okeechobee, Kissimmee Chain of Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.0791015625,\n 25.64152637306577\n ],\n [\n -80.408935546875,\n 25.64152637306577\n ],\n [\n -80.408935546875,\n 26.204734267107604\n ],\n [\n -81.0791015625,\n 26.204734267107604\n ],\n [\n -81.0791015625,\n 25.64152637306577\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.287841796875,\n 26.598351182358293\n ],\n [\n -80.496826171875,\n 26.598351182358293\n ],\n [\n -80.496826171875,\n 27.293689224852407\n ],\n [\n -81.287841796875,\n 27.293689224852407\n ],\n [\n -81.287841796875,\n 26.598351182358293\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.73553466796874,\n 27.761329874505204\n ],\n [\n -80.96649169921874,\n 27.761329874505204\n ],\n [\n -80.96649169921874,\n 28.497660832963447\n ],\n [\n -81.73553466796874,\n 28.497660832963447\n ],\n [\n -81.73553466796874,\n 27.761329874505204\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Midwest Climate Adaptation Science Center
U.S. Geological Survey
1954 Buford Avenue
St Paul, MN 55108

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2022-02-15","noUsgsAuthors":false,"publicationDate":"2022-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, Marta P. 0000-0002-8117-8710 mlyons@usgs.gov","orcid":"https://orcid.org/0000-0002-8117-8710","contributorId":270223,"corporation":false,"usgs":true,"family":"Lyons","given":"Marta","email":"mlyons@usgs.gov","middleInitial":"P.","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":828808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LeDee, Olivia E. 0000-0002-7791-5829","orcid":"https://orcid.org/0000-0002-7791-5829","contributorId":199985,"corporation":false,"usgs":true,"family":"LeDee","given":"Olivia E.","affiliations":[],"preferred":false,"id":828809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyles, Ryan 0000-0001-9272-867X","orcid":"https://orcid.org/0000-0001-9272-867X","contributorId":221983,"corporation":false,"usgs":true,"family":"Boyles","given":"Ryan","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":828810,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237179,"text":"70237179 - 2022 - High abundance of a single taxon (amphipods) predicts aquatic macrophyte biodiversity in prairie wetlands","interactions":[],"lastModifiedDate":"2022-10-04T11:36:17.269282","indexId":"70237179","displayToPublicDate":"2022-02-15T06:33:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"High abundance of a single taxon (amphipods) predicts aquatic macrophyte biodiversity in prairie wetlands","docAbstract":"

Conservation programs often aim to protect the abundance of individual species and biodiversity simultaneously. We quantified relations between amphipod densities and aquatic macrophyte (large plants and algae) diversity to test a hypothesis that biodiversity can support high abundance of a single taxonomic group. Amphipods (Gammarus lacustris and Hyalella azteca) are key forage for waterfowl and are declining in the Prairie Pothole Region of North America. We sampled a large gradient of amphipod densities (0–7050 amphipods/m3) in 49 semi-permanent wetlands, and 50% of the study wetlands had high amphipod densities (> 500 amphipods/m3). Generalized linear models revealed G. lacustris and H. azteca densities increased exponentially with macrophyte diversity indices. Further, H. azteca densities were greatest at moderate levels of submersed vegetation biomass. Community analyses showed both amphipod species were positively associated with diverse macrophyte assemblages and negatively associated with high coverage of cattails (Typha spp.), a taxon that creates monotypic stands, as well as bladderwort (Utricularia spp.), a carnivorous plant. Our results indicate that amphipods could be used as an umbrella species for protecting diverse macrophyte communities in semi-permanent and permanent wetlands of North America’s Prairie Pothole Region.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1007/s10531-022-02379-9","usgsCitation":"Larson, D.M., DeJong, D., Anteau, M.J., Fitzpatrick, M.J., Keith, B.R., Schilling, E.G., and Thoele, B., 2022, High abundance of a single taxon (amphipods) predicts aquatic macrophyte biodiversity in prairie wetlands: Conservation Biology, v. 31, p. 1073-1093, https://doi.org/10.1007/s10531-022-02379-9.","productDescription":"21 p.","startPage":"1073","endPage":"1093","ipdsId":"IP-125387","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":448796,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10531-022-02379-9","text":"Publisher Index Page"},{"id":435968,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9INBET3","text":"USGS data release","linkHelpText":"Macrophyte and amphipod surveys in prairie wetlands of Minnesota in year 2019"},{"id":407850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","noUsgsAuthors":false,"publicationDate":"2022-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Danelle M. 0000-0001-6349-6267","orcid":"https://orcid.org/0000-0001-6349-6267","contributorId":228838,"corporation":false,"usgs":true,"family":"Larson","given":"Danelle","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":853568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeJong, Demmey","contributorId":297160,"corporation":false,"usgs":false,"family":"DeJong","given":"Demmey","email":"","affiliations":[{"id":64304,"text":"Augsburg University","active":true,"usgs":false}],"preferred":false,"id":853569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":853570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitzpatrick, Megan J.","contributorId":290649,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Megan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":853571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keith, Breanna R.","contributorId":290647,"corporation":false,"usgs":false,"family":"Keith","given":"Breanna","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":853572,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schilling, Emily G. 0000-0001-9920-4908","orcid":"https://orcid.org/0000-0001-9920-4908","contributorId":297161,"corporation":false,"usgs":false,"family":"Schilling","given":"Emily","email":"","middleInitial":"G.","affiliations":[{"id":64304,"text":"Augsburg University","active":true,"usgs":false}],"preferred":false,"id":853573,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thoele, Barry","contributorId":297162,"corporation":false,"usgs":false,"family":"Thoele","given":"Barry","email":"","affiliations":[{"id":64306,"text":"Lincoln Bait LCC","active":true,"usgs":false}],"preferred":false,"id":853574,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70238946,"text":"70238946 - 2022 - Fishway Entrance Palisade","interactions":[],"lastModifiedDate":"2023-01-10T16:06:21.874488","indexId":"70238946","displayToPublicDate":"2022-02-14T10:01:03","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9958,"text":"Final Technical Report","active":true,"publicationSubtype":{"id":1}},"title":"Fishway Entrance Palisade","docAbstract":"This technical report summarizes the work that was conducted by the University of Massachusetts Amherst and the United States Geological Survey (USGS), along with other project partners, on the Fishway Entrance Palisade (EP), a projected funded through the Department of Energy’s (DOE) funding opportunity titled ‘Innovative Solutions for Fish Passage at Hydropower Dams’ (DE‐FOA‐0001662). The period of performance ranged from September 1, 2018 through September 30, 2021. \n\nThe EP is a novel fish passage engineering technology designed to provide more favorable entry conditions for fish and to reduce costs relative to conventional fishway auxiliary water systems (AWS). The EP project has four primary components.\n\nFirst, the Northeast United States Auxiliary Water Systems Database was created (Northeast Fishway Auxiliary Water Systems Database Section). The database, developed with material provided by the U.S. Fish and Wildlife Service, contains information on fishway type (e.g., lift, Denil, pool and weir) and Auxiliary Water System (AWS) details (e.g., water conveyance method, diffuser type) for 60 hydroelectric sites in the region. Findings indicate that nearly 4 out of every 10 fishway in the region is a fish lift and approximately 1 out of every 4 is a Denil ladder. The remainder are a mix of vertical slot fishways, pool and weirs, and Ice Harbor fishways. Furthermore, over half of all AWS systems use floor diffusers to discharge the auxiliary (or attraction) water into the entrance of a fishway, whereas only 14% use wall diffusers.\n\nSecond, limited experiments on a conventional AWS with live, actively migrating fish were conducted at the USGS Easter Ecological Science Center (EESC) S.O. Conte Research Laboratory (Conventional Auxiliary Water System Experiments Section). This study determined how water velocity through a wall diffuser, without turning vanes or timber baffles to distribute the flow, affects the behavior and passage of adult American shad, a conservative surrogate species for migratory fish on the East Coast. Two gross diffuser velocity treatments were examined, 0.5 ft/s and 1.0 ft/s. These wall diffuser velocities represented current (0.5 ft/s) and past (1.0 ft/s) design criteria guidelines set forth by the USFWS North Atlantic-Appalachian Region (Rojas 2020; USFWS 2019). Six trials with a total of 151 American Shad were conducted in June of 2019 for the two treatments. \n\nNo differences in American shad passage efficiency were discovered between the two treatments, while approximately 3 in every 4 attempts were successful at passing the diffuser. While these results may appear to indicate that the generally accepted gross wall diffuser velocity criteria for American shad of 0.5 ft/s could be safely increased to 1.0 ft/s, further analysis is warranted. Furthermore, it is unknown how other migratory and resident fish species that traverse these structures would be impacted by such a change. \n\nStudying the wall diffuser hydraulics led to an important AWS observation. Without turning vanes or timber baffles in this study, doubling the diffuser area was insufficient at producing the type of flow field change one may expect by halving the gross diffuser velocity. Instead, the flow fields throughout each treatments study area were similar, which led to similar results in shad performance. This not only highlights the importance of installing flow guidance devices like turning vanes, but also to the importance of properly maintaining them, which can be costly.\n\nThird, more expansive experiments on the novel EP were conducted in the spring of 2019 and 2021 (Fishway Entrance Palisade Experiments). The goal of this study was to determine how adult American shad responded to a variety of conditions at a full-scale EP. A total of six treatments were examined by changing the average auxiliary channel velocity between 1.0 and 5.0 ft/s in intervals of 1.0 ft/s and by inserting/removing an entrance gate at the opening of the fishway. Thirty trials with a total of 1,273 shad were conducted over the two years.\n\nIn all treatments, at least ~7 out of every 10 fish successfully passed the EP diffuser and swam into the entrance channel within the 3.5-hour long trial, highlighting the general effectiveness of the novel AWS technology. In both study years, lower velocities through the EP diffuser led to increased shad performance, though performance peaked for the 2 ft/s velocity treatment. This treatment condition represents an approximate six-fold increase in gross diffuser velocity relative to conventional auxiliary water systems, which in turn presents opportunities for cost savings (e.g., reduction in diffuser size).\n\nShad performance, in general, was worse in 2019 than in 2021, potentially due to the different run timing when our trials were conducted (2019 trials occurred near the end of the migration season, unlike in 2021). Treatments in 2019 had approximately a 20% reduction in entrance efficiency by the trial end, including a 16.7% drop for the 3 ft/s velocity treatment in 2019 relative to 2021 (the only carryover treatment between years). \n\nLastly, adding an entrance gate caused a significant delay to entry. The time to 25% entry raised ~20 minutes from the near instantaneous 25% entry that was reported for the other treatments conducted in the same year (2021). Though by the end of the 3.5-hour trial, the overall entrance efficiency nearly matched those of the other 2021 treatments.\n\nThe fourth and final component of the EP project was an economic analysis that focused on the cost of attraction and environmental flows (Modeling Power Generation Losses Due to Environmental and Fish Passage Attraction Flows at a Run-Of-River Hydroelectric Operation in the Northeast). The study assessed the economic impact of meeting environmental flow requirements at a representative hydroelectric facility and fish lift in the Northeast. An initial finding of the study was that there is a paucity of published data on the costs of meeting attraction and environmental flows. This is due, in part, to the proprietary nature of this data. To explore the costs associated with these flows, three types of environmental flows were assessed: upstream fishway attraction flows, downstream fishway attraction flows, and habitat maintenance minimum flows. A physics-based model was developed and calibrated with three years of hourly generation and flow data as inputs. Gage flow inputs were adjusted and used to calculate power generated. To address hydrologic variability, the model was executed to simulate 30 years of historical flows.\n\nResults indicate that both interannual and seasonal climatic factors impact the costs of meeting environmental flow requirements. Generation potential is most strongly curtailed during dry years in terms of maximizing the capacity factor (the percent of time a plant generates at capacity). Dry years, and especially dry summers, have the most significant costs associated with mitigation flows. Of the three types of flows, habitat flows are most costly in terms of power production, followed by upstream attraction flows. Downstream attraction flows are least costly. This finding is the likely result of differences in both flow rates and duration of the seasonal requirement for each flow. Overall, environmental flows represented a 2-12% loss in annual generation, but losses during a dry summer can reach over 20%.","language":"English","publisher":"U.S. Department of Energy","doi":"10.2172/1905243","usgsCitation":"Mulligan, K., Palmer, R., Towler, B., Haro, A., Lake, B., Rojas, M., and Lotter, E., 2022, Fishway Entrance Palisade: Final Technical Report, 23 p., https://doi.org/10.2172/1905243.","productDescription":"23 p.","ipdsId":"IP-138003","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":448800,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1905243","text":"External Repository"},{"id":411632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.05182598949801,\n 44.89319311674552\n ],\n [\n -68.3175817931259,\n 47.33465807108087\n ],\n [\n -69.24621769928491,\n 47.283640086042396\n ],\n [\n -70.6255546394362,\n 45.53467504444376\n ],\n [\n -73.37060956424577,\n 44.92914333096371\n ],\n [\n -83.12438010438365,\n 34.6176223177726\n ],\n [\n -80.40129683431417,\n 31.8360293402377\n ],\n [\n -75.74355199471707,\n 35.10791041480914\n ],\n [\n -75.21833415636709,\n 38.125898555273295\n ],\n [\n -72.87164643954584,\n 40.72488283550473\n ],\n [\n -69.8736057821464,\n 41.750002105411085\n ],\n [\n -70.47472444522607,\n 43.094355406979275\n ],\n [\n -67.05182598949801,\n 44.89319311674552\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mulligan, Kevin 0000-0002-3534-4239 kmulligan@usgs.gov","orcid":"https://orcid.org/0000-0002-3534-4239","contributorId":177024,"corporation":false,"usgs":true,"family":"Mulligan","given":"Kevin","email":"kmulligan@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmer, Richard","contributorId":202903,"corporation":false,"usgs":false,"family":"Palmer","given":"Richard","affiliations":[],"preferred":false,"id":859309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Towler, Brett","contributorId":141164,"corporation":false,"usgs":false,"family":"Towler","given":"Brett","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":859310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haro, Alexander 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":139198,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lake, Bjorn","contributorId":300039,"corporation":false,"usgs":false,"family":"Lake","given":"Bjorn","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":859312,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rojas, Marcia","contributorId":300040,"corporation":false,"usgs":false,"family":"Rojas","given":"Marcia","email":"","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":859313,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lotter, Elizabeth","contributorId":300041,"corporation":false,"usgs":false,"family":"Lotter","given":"Elizabeth","email":"","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":859314,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228674,"text":"70228674 - 2022 - A statistical framework for integrating nonparametric proxy distributions into geological reconstructions of relative sea level","interactions":[],"lastModifiedDate":"2022-02-16T15:22:51.655089","indexId":"70228674","displayToPublicDate":"2022-02-14T09:19:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5542,"text":"Advances in Statistical Climatology, Meteorology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"A statistical framework for integrating nonparametric proxy distributions into geological reconstructions of relative sea level","docAbstract":"

Robust, proxy-based reconstructions of relative sea-level (RSL) change are critical to distinguishing the processes that drive spatial and temporal sea-level variability. The relationships between individual proxies and RSL can be complex and are often poorly represented by traditional methods that assume Gaussian likelihood distributions. We develop a new statistical framework to estimate past RSL change based on nonparametric, empirical modern distributions of proxies in relation to RSL, applying the framework to corals and mangroves as an illustrative example. We validate our model by comparing its skill in reconstructing RSL and rates of change to two previous RSL models using synthetic time-series datasets based on Holocene sea-level data from South Florida. The new framework results in lower bias, better model fit, and greater accuracy and precision than the two previous RSL models. We also perform sensitivity tests using sea-level scenarios based on two periods of interest – meltwater pulses (MWPs) and the Holocene – to analyze the sensitivity of the statistical reconstructions to the quantity and precision of proxy data; we define high-precision indicators, such as mangroves and the reef-crest coral Acropora palmata, with 2σ vertical uncertainties within ± 3 m and lower-precision indicators, such as Orbicella spp., with 2σ vertical uncertainties within ± 10 m. For reconstructing rapid rates of change in RSL of up to ∼ 40 m kyr−1, such as those that may have characterized MWPs during deglacial periods, we find that employing the nonparametric model with 5 to 10 high-precision data points per kiloyear enables us to constrain rates to within ± 3 m kyr−1 (1σ). For reconstructing RSL with rates of up to ∼ 15 m kyr−1, as observed during the Holocene, we conclude that employing the model with 5 to 10 high-precision (or a combination of high- and low-precision) data points per kiloyear enables precise estimates of RSL within ±∼\"> 2 m (2σ) and accurate RSL reconstructions with errors ≲ 0.7 m. Employing the nonparametric model with only lower-precision indicators also produces fairly accurate estimates of RSL with errors ≲1.50 m, although with less precision, only constraining RSL to ±∼\"> 3–4 m (2σ). Although the model performs better than previous models in terms of bias, model fit, accuracy, and precision, it is computationally expensive to run because it requires inverting large matrices for every sample. The new model also provides minimal gains over similar models when a large quantity of high-precision data are available. Therefore, we recommend incorporating the nonparametric likelihood distributions when no other information (e.g., reef facies or epibionts indicative of shallow-water environments to refine coral elevational uncertainties) or no high-precision data are available at a location or during a given time period of interest.

","language":"English","publisher":"Copernicus Publications","doi":"10.5194/ascmo-8-1-2022","usgsCitation":"Ashe, E.L., Khan, N.S., Toth, L., Dutton, A., and Kopp, R.E., 2022, A statistical framework for integrating nonparametric proxy distributions into geological reconstructions of relative sea level: Advances in Statistical Climatology, Meteorology and Oceanography, v. 8, p. 1-29, https://doi.org/10.5194/ascmo-8-1-2022.","productDescription":"29 p.","startPage":"1","endPage":"29","ipdsId":"IP-130546","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448803,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/ascmo-8-1-2022","text":"Publisher Index Page"},{"id":396013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2022-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashe, Erica L.","contributorId":279484,"corporation":false,"usgs":false,"family":"Ashe","given":"Erica","email":"","middleInitial":"L.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":834976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khan, Nicole S.","contributorId":213942,"corporation":false,"usgs":false,"family":"Khan","given":"Nicole","email":"","middleInitial":"S.","affiliations":[{"id":38935,"text":"Asian School of the Environment, Nanyang Technological University, 50 Nanyang Ave., Singapore 639798","active":true,"usgs":false}],"preferred":false,"id":834977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":834978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dutton, Andrea","contributorId":194113,"corporation":false,"usgs":false,"family":"Dutton","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":834979,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kopp, Robert E.","contributorId":194114,"corporation":false,"usgs":false,"family":"Kopp","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":834980,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228602,"text":"70228602 - 2022 - NWTOPT — A hyperparameter optimization approach for selection of environmental model solver settings","interactions":[],"lastModifiedDate":"2022-02-14T14:29:36.859424","indexId":"70228602","displayToPublicDate":"2022-02-14T08:25:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"NWTOPT — A hyperparameter optimization approach for selection of environmental model solver settings","docAbstract":"Hyperparameter optimization approaches were applied to improve performance and accuracy of groundwater flow models. Freely available new software, NWTOPT, is described that uses Tree of Parzen Estimators (TPE) and Random Search algorithms to optimize MODFLOW-NWTs solver settings. We ran 3500 trials on a steady-state and transient model. To quantify the performance of candidate solver settings, we defined a loss function based on time elapsed and mass balance error of the MODFLOW-NWT forward run. Before optimization the steady- state model ran in ~12 min and the transient model ran in ~5 h with acceptable mass balance error (<1%). After optimization runtimes were reduced to ~2.7 min (steady state) and ~48 min (transient) with errors below 0.1%. In both cases TPE found hyperparameters that resulted in faster running and lower error models than those found by Random Search. The time to complete the optimization trials was also shorter with the TPE algorithm.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105250","usgsCitation":"Newcomer, M.W., and Hunt, R., 2022, NWTOPT — A hyperparameter optimization approach for selection of environmental model solver settings: Environmental Modelling and Software, v. 147, p. 1-7, https://doi.org/10.1016/j.envsoft.2021.105250.","productDescription":"105250, 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-131832","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":448809,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105250","text":"Publisher Index Page"},{"id":435970,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CPBZJX","text":"USGS data release","linkHelpText":"NWTOPT"},{"id":395877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Newcomer, Max William 0000-0003-2491-546X","orcid":"https://orcid.org/0000-0003-2491-546X","contributorId":276318,"corporation":false,"usgs":true,"family":"Newcomer","given":"Max","email":"","middleInitial":"William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834746,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239098,"text":"70239098 - 2022 - Light and flow regimes regulate the metabolism of rivers","interactions":[],"lastModifiedDate":"2022-12-27T13:52:14.349473","indexId":"70239098","displayToPublicDate":"2022-02-14T07:40:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Light and flow regimes regulate the metabolism of rivers","docAbstract":"

Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management.

","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2121976119","usgsCitation":"Bernhardt, E.S., Savoy, P., Vlah, M.J., Appling, A.P., Koenig, L., Hall Jr., R., Arroita, M., Blaszczak, J., Carter, A.M., Cohen, M.J., Harvey, J., Heffernan, J.B., Helton, A.M., Hosen, J., Kirk, L., McDowell, W.H., Stanley, E.H., Yackulic, C., and Grimm, N.B., 2022, Light and flow regimes regulate the metabolism of rivers: Proceedings of the National Academy of Sciences, v. 119, no. 8, e2121976119, 5 p., https://doi.org/10.1073/pnas.2121976119.","productDescription":"e2121976119, 5 p.","ipdsId":"IP-135271","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":448811,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2121976119","text":"Publisher Index Page"},{"id":411062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Bernhardt, Emily. S","contributorId":300289,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily.","email":"","middleInitial":"S","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":860037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savoy, Philip 0000-0002-6075-837X","orcid":"https://orcid.org/0000-0002-6075-837X","contributorId":300288,"corporation":false,"usgs":true,"family":"Savoy","given":"Philip","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":860038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vlah, Michael J","contributorId":300353,"corporation":false,"usgs":false,"family":"Vlah","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":860039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Appling, Alison Paige 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":300354,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"Paige","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":860040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koenig, Lauren E 0000-0002-7790-330X","orcid":"https://orcid.org/0000-0002-7790-330X","contributorId":298697,"corporation":false,"usgs":false,"family":"Koenig","given":"Lauren E","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":860041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall Jr., Robert O","contributorId":292567,"corporation":false,"usgs":false,"family":"Hall Jr.","given":"Robert O","affiliations":[{"id":41061,"text":"Flathead Lake Biological Station, University of Montana, Polson, MT 59860","active":true,"usgs":false}],"preferred":false,"id":860042,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arroita, Maite 0000-0001-8754-7604","orcid":"https://orcid.org/0000-0001-8754-7604","contributorId":203307,"corporation":false,"usgs":false,"family":"Arroita","given":"Maite","email":"","affiliations":[{"id":36597,"text":"Flathead Lake Biological Station, University of Montana; University of the Basque Country","active":true,"usgs":false}],"preferred":false,"id":860043,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blaszczak, Joanna 0000-0001-5122-0829","orcid":"https://orcid.org/0000-0001-5122-0829","contributorId":225159,"corporation":false,"usgs":false,"family":"Blaszczak","given":"Joanna","email":"","affiliations":[{"id":41055,"text":"Natural Resources and Environmental Science, University of Nevada, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":false,"id":860044,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carter, Alice M. 0000-0002-7225-7249","orcid":"https://orcid.org/0000-0002-7225-7249","contributorId":298702,"corporation":false,"usgs":false,"family":"Carter","given":"Alice","email":"","middleInitial":"M.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":860045,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cohen, Matthew J.","contributorId":138990,"corporation":false,"usgs":false,"family":"Cohen","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":860046,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":860047,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Heffernan, James B. 0000-0001-7641-9949","orcid":"https://orcid.org/0000-0001-7641-9949","contributorId":211189,"corporation":false,"usgs":false,"family":"Heffernan","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":860048,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Helton, Ashley M. 0000-0001-6928-2104","orcid":"https://orcid.org/0000-0001-6928-2104","contributorId":298703,"corporation":false,"usgs":false,"family":"Helton","given":"Ashley","email":"","middleInitial":"M.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":860049,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hosen, J.D. 0000-0003-2559-0687","orcid":"https://orcid.org/0000-0003-2559-0687","contributorId":210149,"corporation":false,"usgs":false,"family":"Hosen","given":"J.D.","affiliations":[{"id":38085,"text":"Yale Univ.","active":true,"usgs":false}],"preferred":false,"id":860050,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kirk, Lily","contributorId":300290,"corporation":false,"usgs":false,"family":"Kirk","given":"Lily","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":860051,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"McDowell, William H.","contributorId":198684,"corporation":false,"usgs":false,"family":"McDowell","given":"William","email":"","middleInitial":"H.","affiliations":[{"id":18105,"text":"University of New Hampshire, Durham","active":true,"usgs":false}],"preferred":false,"id":860052,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":860053,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":860054,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Grimm, Nancy B.","contributorId":44058,"corporation":false,"usgs":false,"family":"Grimm","given":"Nancy","email":"","middleInitial":"B.","affiliations":[{"id":24511,"text":"Arizona State University, Tempe AZ USA 85287","active":true,"usgs":false}],"preferred":false,"id":860055,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70230406,"text":"70230406 - 2022 - Smoothed Particle Hydrodynamics simulations of reef surf zone processes driven by plunging irregular waves","interactions":[],"lastModifiedDate":"2022-04-12T12:20:14.982267","indexId":"70230406","displayToPublicDate":"2022-02-14T07:19:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Smoothed Particle Hydrodynamics simulations of reef surf zone processes driven by plunging irregular waves","docAbstract":"

As waves interact with the slopes of coral reefs and other steep bathymetry profiles, plunging breaking usually occurs where the free surface overturns and violent water motion is triggered. Resolving these surf zone processes pose significant challenges for conventional mesh-based hydrodynamic models, due to the rapidly-deforming nature of the free surface and associated flows. Yet the accurate prediction of these surf zone hydrodynamics is critical for predicting a wide range of nearshore processes driven by wave breaking (e.g., wave dissipation and energy transfers; mean water levels and currents; and wave runup). In this study we assess the ability of the mesh-free, Lagrangian particle-based numerical modelling approach Smoothed Particle Hydrodynamics (SPH) based on DualSPHysics, to simulate the fine-scale hydrodynamic processes driven by irregular wave transformation over a fringing reef profile, by comparing results against detailed experimental observations from a physical modelling study. To greatly improve the computational efficiency, the SPH model was coupled to the mesh-based multi-layer nonhydrostatic wave-flow model SWASH. With this coupled approach, SWASH was used to efficiently simulate the evolution of non-breaking waves from the wavemaker up to the fore reef slope, with the SPH model then used to simulate the detailed hydrodynamic processes over the reef from just offshore of the breakpoint to the shoreline. The SPH model was able to accurately reproduce the complex free surface deformations during plunging breaking, the spectral evolution of waves across the reef flat (including nonlinear wave shape), the mean water levels and currents, and wave runup at the shoreline. Using the long duration simulations (>400 wave periods), the model was able to reproduce the full range of wave motions over the reef (from sea-swell to infragravity frequencies), including the increasing dominance of low frequency waves towards the shoreline and the large cross-reef standing wave motions excited by the reef geometry.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocemod.2022.101945","usgsCitation":"Lowe, R.J., Altomare, C., Buckley, M.L., da Silva, R.F., Hansen, J.E., Rijnsdorp, D.P., Dominguez, J., and Crespo, A., 2022, Smoothed Particle Hydrodynamics simulations of reef surf zone processes driven by plunging irregular waves: Ocean Modelling, v. 171, 101945, 20 p., https://doi.org/10.1016/j.ocemod.2022.101945.","productDescription":"101945, 20 p.","ipdsId":"IP-131129","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448813,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2117/387691","text":"External Repository"},{"id":398535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"171","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":840332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Altomare, C.","contributorId":290134,"corporation":false,"usgs":false,"family":"Altomare","given":"C.","email":"","affiliations":[{"id":62343,"text":"Universitat Politecnica de Catalunya - BarcelonaTech (UPC)","active":true,"usgs":false}],"preferred":false,"id":840333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":840334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"da Silva, Renan F.","contributorId":261462,"corporation":false,"usgs":false,"family":"da Silva","given":"Renan","email":"","middleInitial":"F.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":840335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Jeff E.","contributorId":204340,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","email":"","middleInitial":"E.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":true,"id":840336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rijnsdorp, Dirk P.","contributorId":261463,"corporation":false,"usgs":false,"family":"Rijnsdorp","given":"Dirk","email":"","middleInitial":"P.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":840337,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dominguez, J.M.","contributorId":290135,"corporation":false,"usgs":false,"family":"Dominguez","given":"J.M.","email":"","affiliations":[{"id":62345,"text":"Universidade de Vigo","active":true,"usgs":false}],"preferred":false,"id":840338,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crespo, A.J.C.","contributorId":290136,"corporation":false,"usgs":false,"family":"Crespo","given":"A.J.C.","email":"","affiliations":[{"id":62345,"text":"Universidade de Vigo","active":true,"usgs":false}],"preferred":false,"id":840339,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70232359,"text":"70232359 - 2022 - Stable isotopes provide insight into sources and cycling of N compounds in the Sacramento-San Joaquin Delta, California, USA","interactions":[],"lastModifiedDate":"2022-06-29T12:17:10.512083","indexId":"70232359","displayToPublicDate":"2022-02-11T07:13:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Stable isotopes provide insight into sources and cycling of N compounds in the Sacramento-San Joaquin Delta, California, USA","docAbstract":"

River deltas and their diverse array of aquatic environments are increasingly impacted by anthropogenic inputs of nitrogen (N). These inputs can alter the N biogeochemistry of these systems and promote undesirable phenomena including harmful algae blooms and invasive aquatic macrophytes. To examine N sources and biogeochemical processes in the Sacramento-San Joaquin Delta, a river delta located in central California, USA, that is fed primarily by the Sacramento River, we utilized a multi-tracer approach that measured N species concentrations and stable isotope values monthly from April 2011 to November 2012 in samples collected from the channelized mainstem of the Sacramento River, two channelized distributaries of the Sacramento River, and the Cache Slough Complex, a network of Sacramento River tributaries and shallow water wetland habitat. We found that the Sacramento River and its channelized distributaries received N primarily in the form of NH4+ from treated wastewater effluent and that NH4+ was lost rapidly while NO3− was gained more slowly during subsequent downstream transit, driven by an array of biogeochemical processes whose identities could be constrained via examination of stable isotope values. The Cache Slough Complex, which was characterized by lower net flows and higher water residence times than the Sacramento River and its distributaries, received variable inputs of low conductivity water elevated in NH4+ from the Sacramento River and higher conductivity water elevated in NO3− from landward tributaries. Deviations from expected conservative mixing of these sources were spatially variable but broadly indicative of local inputs of treated wastewater effluent NO3−, conversion of Sacramento River NH4+ to NO3− via nitrification, uptake of NH4+ and NO3− by phytoplankton, and remineralization of organic N. These findings highlight both the diversity in N dynamics in anthropogenically impacted river delta environments and the utility of a multi-tracer approach in constraining these processes in such complex systems.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.151592","usgsCitation":"Fackrell, J.K., Kraus, T.E., Young, M.B., Kendall, C., and Peek, S., 2022, Stable isotopes provide insight into sources and cycling of N compounds in the Sacramento-San Joaquin Delta, California, USA: Science of the Total Environment, v. 816, 151592, 13 p., https://doi.org/10.1016/j.scitotenv.2021.151592.","productDescription":"151592, 13 p.","ipdsId":"IP-129598","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":402669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8988037109375,\n 37.75768707689704\n ],\n [\n -120.75622558593749,\n 37.75768707689704\n ],\n [\n -120.75622558593749,\n 38.997841307500714\n ],\n [\n -121.8988037109375,\n 38.997841307500714\n ],\n [\n -121.8988037109375,\n 37.75768707689704\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"816","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fackrell, Joseph K. 0000-0001-8148-3734","orcid":"https://orcid.org/0000-0001-8148-3734","contributorId":225515,"corporation":false,"usgs":true,"family":"Fackrell","given":"Joseph","email":"","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Megan B. 0000-0002-0229-4108 mbyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-0229-4108","contributorId":3315,"corporation":false,"usgs":true,"family":"Young","given":"Megan","email":"mbyoung@usgs.gov","middleInitial":"B.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":845341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, Carol 0000-0002-0247-3405 ckendall@usgs.gov","orcid":"https://orcid.org/0000-0002-0247-3405","contributorId":1462,"corporation":false,"usgs":true,"family":"Kendall","given":"Carol","email":"ckendall@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":845342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":845343,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228450,"text":"fs20223004 - 2022 - Colorado and Landsat","interactions":[],"lastModifiedDate":"2023-01-21T15:53:55.313826","indexId":"fs20223004","displayToPublicDate":"2022-02-10T15:07:20","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3004","displayTitle":"Colorado and Landsat","title":"Colorado and Landsat","docAbstract":"

Colorado’s geography seems designed to impress. Although the Rocky Mountains takes up only one-half of the State, more than 50 of its peaks rise at least 14,000 feet above sea level—far more “fourteeners” than any other State. Many of these mountains receive hundreds of inches of snow annually. The Rocky Mountains provide the Continental Divide, or watershed boundary, for North America. Three of the United States’ seven longest rivers originate in Colorado’s mountains: the Rio Grande, the Colorado, and the Arkansas Rivers. The mountains are also home to 11 national forests. Residents and tourists find many ways to appreciate the stunning views, from hiking and skiing to camping and birdwatching, in ecosystems that also include grasslands and shrublands.

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\"}}]}","edition":"Version 1.0: February 10, 2022; Version 1.1: January 13, 2023","contact":"

Program Coordinator, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-02-10","revisedDate":"2023-01-13","noUsgsAuthors":false,"publicationDate":"2022-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128240,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":834329,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70228216,"text":"ofr20211095 - 2022 - Report of the River Master of the Delaware River for the period December 1, 2011–November 30, 2012","interactions":[],"lastModifiedDate":"2026-03-25T17:40:42.809018","indexId":"ofr20211095","displayToPublicDate":"2022-02-10T12:45:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1095","displayTitle":"Report of the River Master of the Delaware River for the Period December 1, 2011–November 30, 2012","title":"Report of the River Master of the Delaware River for the period December 1, 2011–November 30, 2012","docAbstract":"

A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes diversion of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 59th annual report of the River Master of the Delaware River. It covers the 2012 River Master report year, the period from December 1, 2011 to November 30, 2012.

During the report year, precipitation in the upper Delaware River Basin was 43.35 inches or 97 percent of the long-term average. Combined storage in the Pepacton, Cannonsville, and Neversink Reservoirs remained high through late May, declined from then until mid-September, decreasing below 80 percent of combined capacity in late August, increased in late October, and decreased slightly in November 2012. Delaware River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program.

Diversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 52 days during the report year. Interim Excess Release Quantity and conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were also made during the report year. An agreement was signed on October 25, 2012, to increase discharge mitigation releases from the Neversink Reservoir due to potential impacts from Hurricane Sandy.

The quality of water in the Delaware River estuary between Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at various locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211095","usgsCitation":"DiFrenna, V.J., Andrews, W.J., Russell, K.L., Norris, J.M., and Mason, R.R., Jr., 2022, Report of the River Master of the Delaware River for the period December 1, 2011–November 30, 2012: U.S. Geological Survey Open-File Report 2021–1095, 101 p., https://doi.org/10.3133/ofr20211095.","productDescription":"x, 101 p.","numberOfPages":"101","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-123829","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":395538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1095/coverthb.jpg"},{"id":395539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1095/ofr20211095.pdf","text":"Report","size":"4.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1095"},{"id":501528,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112444.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey, New York, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.66259765625,\n 39.67337039176558\n ],\n [\n -73.65234375,\n 39.67337039176558\n ],\n [\n -73.65234375,\n 42.52069952914966\n ],\n [\n -76.66259765625,\n 42.52069952914966\n ],\n [\n -76.66259765625,\n 39.67337039176558\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Delaware River Master
Office of the Delaware River Master
U.S. Geological Survey
120 Route 209 South
Milford, PA 18337

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-02-10","noUsgsAuthors":false,"publicationDate":"2022-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"DiFrenna, Vincent J. 0000-0002-1336-7288","orcid":"https://orcid.org/0000-0002-1336-7288","contributorId":222850,"corporation":false,"usgs":true,"family":"DiFrenna","given":"Vincent J.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":833435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrews, William J. 0000-0003-4780-8835 wandrews@usgs.gov","orcid":"https://orcid.org/0000-0003-4780-8835","contributorId":328,"corporation":false,"usgs":true,"family":"Andrews","given":"William","email":"wandrews@usgs.gov","middleInitial":"J.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, Kendra L. 0000-0002-3046-7440","orcid":"https://orcid.org/0000-0002-3046-7440","contributorId":218135,"corporation":false,"usgs":true,"family":"Russell","given":"Kendra","email":"","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":833437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norris, J. Michael 0000-0002-7480-0161 mnorris@usgs.gov","orcid":"https://orcid.org/0000-0002-7480-0161","contributorId":1625,"corporation":false,"usgs":true,"family":"Norris","given":"J.","email":"mnorris@usgs.gov","middleInitial":"Michael","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833438,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mason, Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":2090,"corporation":false,"usgs":true,"family":"Mason","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":833439,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228449,"text":"sir20215118B - 2022 - Yucaipa valley integrated hydrological model","interactions":[{"subject":{"id":70228449,"text":"sir20215118B - 2022 - Yucaipa valley integrated hydrological model","indexId":"sir20215118B","publicationYear":"2022","noYear":false,"chapter":"B","displayTitle":"Yucaipa Valley Integrated Hydrological Model","title":"Yucaipa valley integrated hydrological model"},"predicate":"IS_PART_OF","object":{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","indexId":"sir20215118","publicationYear":"2022","noYear":false,"title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California"},"id":1}],"isPartOf":{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","indexId":"sir20215118","publicationYear":"2022","noYear":false,"title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California"},"lastModifiedDate":"2022-02-10T20:43:51.187857","indexId":"sir20215118B","displayToPublicDate":"2022-02-10T12:43:40","publicationYear":"2022","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":"2021-5118","chapter":"B","displayTitle":"Yucaipa Valley Integrated Hydrological Model","title":"Yucaipa valley integrated hydrological model","docAbstract":"

Introduction

The hydrologic system in the Yucaipa Valley watershed (YVW) was simulated using the coupled Groundwater and Surface-water FLOW model (GSFLOW; Markstrom and others, 2008). This study uses version 2.0 of GSFLOW, which is a combination of the Precipitation-Runoff Modeling System (PRMS; Markstrom and others, 2015), and the Newton-Raphson formulation of the Modular Groundwater-Flow Model (MODFLOW-NWT; hereafter referred to as MODFLOW; Harbaugh, 2005; Niswonger and others, 2011).

GSFLOW partitions the hydrologic system into three regions (fig. B1) that are linked by the exchange of unsaturated and saturated groundwater and surface water. The properties and processes within each region influence the flow of both groundwater and surface water into, out of, and within each region. The PRMS component of GSFLOW simulates Region 1, and the MODFLOW component simulates Regions 2 and 3. In the YVW, GSFLOW was applied as the simulation code and is referred to herein as the Yucaipa Integrated Hydrologic Model (YIHM; Alzraiee and others, 2022). In the YIHM, Region 1 includes the plant canopy, snowpack, and the soil zone; Region 2 includes the stream network; and Region 3 includes the subsurface beneath Regions 1 and 2 and consists of both the saturated and unsaturated zones. Soil-moisture conditions and head relations control the flow of both groundwater and surface water between regions. The maximum lateral extents of Regions 1 and 3 were defined using the surface-water drainage divides described in the “Description of Study Area” section of chapter A of this report. The boundaries for Region 2 are the lowest elevation of the streambeds, the stream channel widths, and the horizontal extent of the stream channels in the YVW. Flow across the unsaturated part of Region 3 is assumed to be vertical and does not cross the lateral boundary.

To simulate hydrologic processes occurring within the YVW using GSFLOW, a model domain was defined to match the surface watershed such that the domain includes each surficial hydrologic unit coinciding (at least partially) with the Yucaipa groundwater subbasin (hereafter referred to as “Yucaipa subbasin”) as defined in California Bulletin 118 (California Department of Water Resources, 2016). The resulting simulated domain (fig. B2) includes the Yucaipa subbasin and intersects partially with parts of the San Bernardino and San Timoteo groundwater subbasins (fig. B2). The area of the active model domain in YIHM is about 121 square miles (mi2). The developed YIHM can be used to improve understanding of the hydrologic processes in YVW and to simulate future management scenarios with different climatic and anthropogenic changes.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215118B","collaboration":"Prepared in cooperation with San Bernardino Valley Municipal Water District","usgsCitation":"Alzraiee, A.H., Engott, J.A., Cromwell, G., and Woolfenden, L., 2022, Yucaipa valley integrated hydrological model, chap. B in Cromwell, G., and Alzraiee, A.H., eds., Hydrology of the Yucaipa groundwater subbasin—Characterization and integrated numerical model, San Bernardino and Riverside Counties, California: U.S. Geological Survey Scientific Investigations Report 2021–5118-B, 76 p., https://doi.org/10.3133/sir20215118B.","productDescription":"Report: ix, 76 p., and data release","numberOfPages":"76","onlineOnly":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":395797,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118b.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":395800,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20215118A","text":"SIR 2021-5118 Chapter A","linkHelpText":"- Hydrogeologic Characterization of the Yucaipa Groundwater Subbasin"},{"id":395798,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118b.xml"},{"id":395799,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5118/images"},{"id":395795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5118/covrthbb.jpg"},{"id":395809,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K540DV","description":"Alzraiee, A.H., Engott, J.A., Cromwell, G., and Woolfenden, L., 2022, Yucaipa valley integrated hydrological model, chap. B in Cromwell, G., and Alzraiee, A.H., eds., Hydrology of the Yucaipa groundwater subbasin—Characterization and integrated numerical model, San Bernardino and Riverside Counties, California: U.S. Geological Survey Scientific Investigations Report 2021–5118-B, 76 p., https://doi.org/10.3133/sir20215118B."}],"contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2022-02-10","noUsgsAuthors":false,"publicationDate":"2022-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Alzraiee, Ayman H. 0000-0001-7576-3449","orcid":"https://orcid.org/0000-0001-7576-3449","contributorId":272120,"corporation":false,"usgs":true,"family":"Alzraiee","given":"Ayman","email":"","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cromwell, Geoffrey 0000-0001-8481-405X gcromwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-405X","contributorId":5920,"corporation":false,"usgs":true,"family":"Cromwell","given":"Geoffrey","email":"gcromwell@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woolfenden, Linda R. 0000-0003-3500-4709 lrwoolfe@usgs.gov","orcid":"https://orcid.org/0000-0003-3500-4709","contributorId":1476,"corporation":false,"usgs":true,"family":"Woolfenden","given":"Linda","email":"lrwoolfe@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834328,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230021,"text":"70230021 - 2022 - Performance of a carbon dioxide injection system at a navigation lock to control the spread of aquatic invasive species","interactions":[],"lastModifiedDate":"2022-03-25T13:34:34.841291","indexId":"70230021","displayToPublicDate":"2022-02-10T11:34:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2255,"text":"Journal of Environmental Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Performance of a carbon dioxide injection system at a navigation lock to control the spread of aquatic invasive species","docAbstract":"

Natural resource agencies need effective strategies to control the spread of aquatic invasive species (AIS) such as invasive fish, which can expand their range using rivers as hydrological pathways to access new areas. Lock and dam structures within major rivers are prospective locations to deploy techniques, such as carbon dioxide (CO2) infusion into lock water, that could impede upstream AIS migration without disrupting vessel passage and lock operation. The current pesticide label for CO2 in the United States allows injections of 100–150  mg/LCO2 as a behavioral deterrent treatment for invasive carps. This research describes the first operationalizing and testing of a CO2 injection and manifold distribution system at a 1,548,000-L navigation lock chamber on the Fox River near Kaukauna, Wisconsin, USA. Two chemical distribution manifolds located on the floor and wall of the chamber were independently tested to quantify mixing time, mixing homogeneity, injection efficiency, and operational power requirements under a range of operating parameters. Both manifold configurations were able to meet most performance benchmarks established during previous fish behavior studies. Certain limitations were exhibited and quantified for both manifold configurations in terms of mixing homogeneity and operational power. This research details the design and performance of CO2-to-water infusion systems that could be used to deter the spread of AIS at navigation pinch-points. These results may inform future CO2 system designs and operating conditions to support natural resource management plans to limit the spread of AIS.

","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)EE.1943-7870.0001987","usgsCitation":"Zolper, T.J., Smith, D., Jackson, P.R., and Cupp, A.R., 2022, Performance of a carbon dioxide injection system at a navigation lock to control the spread of aquatic invasive species: Journal of Environmental Engineering, v. 148, no. 4, 04022011, 18 p., https://doi.org/10.1061/(ASCE)EE.1943-7870.0001987.","productDescription":"04022011, 18 p.","ipdsId":"IP-127265","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":448830,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/(asce)ee.1943-7870.0001987","text":"Publisher Index Page"},{"id":397532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Kaukauna","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.25804471969604,\n 44.282831594282946\n ],\n [\n -88.25237989425659,\n 44.282831594282946\n ],\n [\n -88.25237989425659,\n 44.284690317258665\n ],\n [\n -88.25804471969604,\n 44.284690317258665\n ],\n [\n -88.25804471969604,\n 44.282831594282946\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zolper, Thomas J.","contributorId":210258,"corporation":false,"usgs":false,"family":"Zolper","given":"Thomas","email":"","middleInitial":"J.","affiliations":[{"id":38093,"text":"University of Wisconsin - Platteville","active":true,"usgs":false}],"preferred":false,"id":838708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David 0000-0001-6074-9257","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":1989,"corporation":false,"usgs":false,"family":"Smith","given":"David","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":838709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"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},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":838710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":838711,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228448,"text":"sir20215118A - 2022 - Hydrogeologic characterization of the Yucaipa groundwater subbasin","interactions":[{"subject":{"id":70228448,"text":"sir20215118A - 2022 - Hydrogeologic characterization of the Yucaipa groundwater subbasin","indexId":"sir20215118A","publicationYear":"2022","noYear":false,"chapter":"A","displayTitle":"Hydrogeologic Characterization of the Yucaipa Groundwater Subbasin","title":"Hydrogeologic characterization of the Yucaipa groundwater subbasin"},"predicate":"IS_PART_OF","object":{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","indexId":"sir20215118","publicationYear":"2022","noYear":false,"title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California"},"id":1}],"isPartOf":{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","indexId":"sir20215118","publicationYear":"2022","noYear":false,"title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California"},"lastModifiedDate":"2022-02-11T16:50:35.030326","indexId":"sir20215118A","displayToPublicDate":"2022-02-10T10:29:06","publicationYear":"2022","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":"2021-5118","chapter":"A","displayTitle":"Hydrogeologic Characterization of the Yucaipa Groundwater Subbasin","title":"Hydrogeologic characterization of the Yucaipa groundwater subbasin","docAbstract":"

Introduction

Water management in the Santa Ana River watershed in San Bernardino and Riverside Counties in southern California (fig. A1) is complex with various water purveyors navigating geographic, geologic, hydrologic, and political challenges to provide a reliable water supply to stakeholders. As the population has increased throughout southern California, so has the demand for water. The Yucaipa groundwater subbasin (hereafter referred to as “Yucaipa subbasin”), one of nine groundwater subbasins in what the California Department of Water Resources (DWR) refers to as the Upper Santa Ana Valley groundwater basin (California Department of Water Resources, 2016; fig. A1; the DWR naming convention is used within this report), is no exception; steady population growth since the 1940s and changes in water use have forced local water purveyors to regularly adapt their water infrastructure. Water demands within the Yucaipa subbasin have historically been supplied by groundwater, but water imported via the California State Water Project has augmented the total water supply through direct use and through anthropogenic recharge at the Wilson Creek and Oak Glen Creek spreading basins since 2002. Overall demand for groundwater continues to rise, and local water managers are concerned that despite the influx of imported water, groundwater levels may decline to a point where producing water will be uneconomical, severely limiting the ability of local agencies to meet water-supply demand.

To better understand the hydrogeology and water resources in the Yucaipa subbasin, the U.S. Geological Survey (USGS) initiated a study in cooperation with the San Bernardino Valley Municipal Water District (SBVMWD) to characterize and model the hydrologic system of the Yucaipa subbasin and the surrounding Yucaipa Valley watershed (YVW; fig. A2). To gain this comprehensive understanding, a three-dimensional (3D) hydrogeologic framework model (HFM; Cromwell and Matti, 2022) was constructed to quantify the structure and extent of hydrogeologic units in the YVW; the hydrologic system was conceptualized and quantified (described in chapter A); and the Yucaipa Integrated Hydrological Model (YIHM; described in chapter B) was developed to simulate the integrated surface-water and aquifer systems, including natural and anthropogenic recharge and discharge throughout the study area during 1947–2014.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215118A","collaboration":"Prepared in cooperation with San Bernardino Valley Municipal Water District","usgsCitation":"Cromwell, G., Engott, J.A., Alzraiee, A.H., Stamos, C.L., Mendez, G.O., Dick, M.C., and Bond, S., 2022, Hydrogeologic characterization of the Yucaipa groundwater subbasin, chap. A in Cromwell, G., and Alzraiee, A.H., eds., Hydrology of the Yucaipa groundwater subbasin—Characterization and integrated numerical model, San Bernardino and Riverside Counties, California: U.S. Geological Survey Scientific Investigations Report 2021–5118–A, 81 p., https://doi.org/10.3133/sir20215118A.","productDescription":"Report: vii, 81 p., and data release","numberOfPages":"81","onlineOnly":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":395793,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F7OYQR","description":"Cromwell, G., Matti, J.C., and Roberts, S.A., 2022, Data release of hydrogeologic data of the Yucaipa groundwater subbasin, San Bernardino and Riverside Counties, California: U.S. Geological Survey Sciencebase data release, https://doi.org/ 10.5066/ P9F7OYQR.","linkHelpText":"Data release of hydrogeologic data of the Yucaipa groundwater subbasin, San Bernardino and Riverside Counties, California"},{"id":395789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5118/covrthba.jpg"},{"id":395790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118a.pdf","text":"Report","size":"60 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":395791,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118a.xml"},{"id":395792,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5118/images"},{"id":395794,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20215118B","text":"SIR 2021-5118 Chapter B","linkHelpText":"- Yucaipa valley integrated hydrological model"}],"contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"
","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2022-02-10","noUsgsAuthors":false,"publicationDate":"2022-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Cromwell, Geoffrey 0000-0001-8481-405X gcromwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-405X","contributorId":5920,"corporation":false,"usgs":true,"family":"Cromwell","given":"Geoffrey","email":"gcromwell@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alzraiee, Ayman H. 0000-0001-7576-3449","orcid":"https://orcid.org/0000-0001-7576-3449","contributorId":272120,"corporation":false,"usgs":true,"family":"Alzraiee","given":"Ayman","email":"","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stamos-Pfeiffer, Christina 0000-0002-1007-9352 clstamos@usgs.gov","orcid":"https://orcid.org/0000-0002-1007-9352","contributorId":169089,"corporation":false,"usgs":true,"family":"Stamos-Pfeiffer","given":"Christina","email":"clstamos@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mendez, Gregory 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":139098,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834322,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dick, Meghan C. 0000-0002-8323-3787 mdick@usgs.gov","orcid":"https://orcid.org/0000-0002-8323-3787","contributorId":200745,"corporation":false,"usgs":true,"family":"Dick","given":"Meghan","email":"mdick@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834323,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bond, Sandra 0000-0003-0522-5287 sbond@usgs.gov","orcid":"https://orcid.org/0000-0003-0522-5287","contributorId":3328,"corporation":false,"usgs":true,"family":"Bond","given":"Sandra","email":"sbond@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834324,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228677,"text":"70228677 - 2022 - In situ enhancement and isotopic labeling of biogenic coalbed methane","interactions":[],"lastModifiedDate":"2022-03-17T16:57:12.26312","indexId":"70228677","displayToPublicDate":"2022-02-10T09:40:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"In situ enhancement and isotopic labeling of biogenic coalbed methane","docAbstract":"

Subsurface microbial (biogenic) methane production is an important part of the global carbon cycle that has resulted in natural gas accumulations in many coal beds worldwide. Laboratory studies suggest that complex carbon-containing nutrients (e.g., yeast or algae extract) can stimulate methane production, yet the effectiveness of these nutrients within coal beds is unknown. Here, we use downhole monitoring methods in combination with deuterated water (D2O) and a 200-liter injection of 0.1% yeast extract (YE) to stimulate and isotopically label newly generated methane. A total dissolved gas pressure sensor enabled real-time gas measurements (641 days preinjection and for 478 days postinjection). Downhole samples, collected with subsurface environmental samplers, indicate that methane increased 132% above preinjection levels based on isotopic labeling from D2O, 108% based on pressure readings, and 183% based on methane measurements 266 days postinjection. Demonstrating that YE enhances biogenic coalbed methane production in situ using multiple novel measurement methods has immediate implications for other field-scale biogenic methane investigations, including in situ methods to detect and track microbial activities related to the methanogenic turnover of recalcitrant carbon in the subsurface.

","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.1c05979","usgsCitation":"Barnhart, E.P., Ruppert, L., Heibert, R., Smith, H.J., Schweitzer, H., Clark, A., Weeks, E., Orem, W.H., Varonka, M., Platt, G.A., Shelton, J., Davis, K., Hyatt, R., McIntosh, J.C., Ashley, K., Ono, S., Martini, A.M., Hackley, K., Gerlach, R., Spangler, L., Phillips, A., Barry, M., Cunningham, A.B., and Fields, M.W., 2022, In situ enhancement and isotopic labeling of biogenic coalbed methane: Environmental Science and Technology, v. 56, no. 5, p. 3225-3233, https://doi.org/10.1021/acs.est.1c05979.","productDescription":"9 p.","startPage":"3225","endPage":"3233","ipdsId":"IP-135929","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":448833,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.1c05979","text":"Publisher Index 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wetlands","interactions":[],"lastModifiedDate":"2024-09-04T13:50:54.981462","indexId":"70256733","displayToPublicDate":"2022-02-10T08:32:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1564,"text":"Environmental Science and Pollution Research","active":true,"publicationSubtype":{"id":10}},"title":"Seed treatments containing neonicotinoids and fungicides reduce aquatic insect richness and abundance in midwestern USA–managed floodplain wetlands","docAbstract":"

Agrochemicals including neonicotinoid insecticides and fungicides are frequently applied as seed treatments on corn, soybeans, and other common row crops. Crops grown from pesticide-treated seed are often directly planted in managed floodplain wetlands and used as a soil disturbance or food resource for wildlife. We quantified invertebrate communities within mid-latitude floodplain wetlands and assessed their response to use of pesticide-treated seeds within the floodplain. We collected and tested aqueous and sediment samples for pesticides in addition to sampling aquatic invertebrates from 22 paired wetlands. Samples were collected twice in 2016 (spring [pre-water level drawdown] and autumn [post-water level flood-up]) followed by a third sampling period (spring 2017). Meanwhile, during the summer of 2016, a portion of study wetlands were planted with either pesticide-treated or untreated corn seed. Neonicotinoid toxic equivalencies (NI-EQs) for sediment (X̅ = 0.58 μg/kg), water (X̅ = 0.02 μg/L), and sediment fungicide concentrations (X̅ = 0.10 μg/kg) were used to assess potential effects on wetland invertebrates. An overall decrease in aquatic insect richness and abundance was associated with greater NI-EQs in wetland water and sediments, as well as with sediment fungicide concentration. Post-treatment, treated wetlands displayed a decrease in insect taxa-richness and abundance before recovering by the spring of 2017. Information on timing and magnitude of aquatic insect declines will be useful when considering the use of seed treatments for wildlife management. More broadly, this study brings attention to how agriculture is used in wetland management and conservation planning.

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Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Flood resilience in paired US–Mexico border cities: A study of binational risk perceptions","docAbstract":"

Disastrous floods in the twin cities of Nogales, Arizona, USA, and Nogales, Sonora, Mexico (collectively referred to as Ambos Nogales) occur annually in response to monsoonal summer rains. Flood-related hazards include property damage, impairment to sewage systems, sewage discharge, water contamination, erosion, and loss of life. Flood risk, particularly in Nogales, Sonora, is amplified by informal, “squatter” settlements in the watershed floodplain and associated development and infrastructure. The expected increase in precipitation intensity, resulting from climate change, poses further risk to flooding therein. We explore binational community perceptions of flooding, preferences for watershed management, and potential actions to address flooding and increase socio-ecological resilience in Ambos Nogales using standardized questionnaires and interviews to collect data about people and their preferences. We conducted 25 semi-structured interviews with local subject matter experts and gathered survey responses from community members in Ambos Nogales. Though survey response was limited, expected frequencies were high enough to conduct Chi-squared tests of independence to test for statistically significant relationships between survey variables. Results showed that respondents with previous experience with flooding corresponded with their level of concern about future floods. Additionally, respondents perceived greater flood-related risks from traveling across town and damage to vehicles than from inundation or damages to their homes or neighborhoods. Binationally, women respondents felt less prepared for future floods than men. On both sides of the border, community members and local experts agreed that Ambos Nogales lacks adequate preparation for future floods. To increase preparedness, they recommended flood risk education and awareness campaigns, implementation of green infrastructure, additional stormwater infrastructure (such as drainage systems), enhanced flood early warning systems, and reduction of flood flows through regulations to reduce the expansion of hard surfaces. This study contributes systematic collection of information about flood risk perceptions across an international border, including novel data regarding risks related to climate change and gender-based assessments of flood risk. Our finding of commonalities across both border communities, in perceptions of flood risk and in the types of risk reduction solutions recommended by community members, provides clear directions for flood risk education, outreach, and preparedness, as well as measures to enhance cross-border cooperation.

","language":"English","publisher":"Springer Link","doi":"10.1007/s11069-022-05225-x","usgsCitation":"Freimund, C.A., Garfin, G.M., Norman, L., Fisher, L., and Buizer, J., 2022, Flood resilience in paired US–Mexico border cities: A study of binational risk perceptions: Natural Hazards, v. 112, p. 1247-1271, https://doi.org/10.1007/s11069-022-05225-x.","productDescription":"25 p.","startPage":"1247","endPage":"1271","ipdsId":"IP-126099","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":448843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11069-022-05225-x","text":"Publisher Index Page"},{"id":396437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, Sonora","city":"Nogales","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.5606689453125,\n 30.840931139029916\n ],\n [\n -110.3466796875,\n 30.840931139029916\n ],\n [\n -110.3466796875,\n 32.194208672875384\n ],\n [\n -111.5606689453125,\n 32.194208672875384\n ],\n [\n -111.5606689453125,\n 30.840931139029916\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"112","noUsgsAuthors":false,"publicationDate":"2022-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Freimund, Christopher A.","contributorId":280033,"corporation":false,"usgs":false,"family":"Freimund","given":"Christopher","email":"","middleInitial":"A.","affiliations":[{"id":50057,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":835919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garfin, Gregg M.","contributorId":205905,"corporation":false,"usgs":false,"family":"Garfin","given":"Gregg","email":"","middleInitial":"M.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":835921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":835920,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Larry A.","contributorId":280034,"corporation":false,"usgs":false,"family":"Fisher","given":"Larry A.","affiliations":[{"id":50057,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":835922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buizer, James","contributorId":280035,"corporation":false,"usgs":false,"family":"Buizer","given":"James","email":"","affiliations":[{"id":50057,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":835923,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229026,"text":"70229026 - 2022 - Baseline gene expression levels in Falkland-Malvinas Island penguins: Towards a new monitoring paradigm","interactions":[],"lastModifiedDate":"2022-02-25T12:43:13.091378","indexId":"70229026","displayToPublicDate":"2022-02-09T06:40:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10135,"text":"Life","active":true,"publicationSubtype":{"id":10}},"title":"Baseline gene expression levels in Falkland-Malvinas Island penguins: Towards a new monitoring paradigm","docAbstract":"
Health diagnostics of wildlife have historically relied on the evaluation of select serum biomarkers and the identification of a contaminant or pathogen burden within specific tissues as an indicator of a level of insult. However, these approaches fail to measure the physiological reaction of the individual to stressors, thus limiting the scope of interpretation. Gene-based health diagnostics provide an opportunity for an alternate, whole-system, or holistic assessment of health, not only in individuals or populations but potentially in ecosystems. Seabirds are among the most threatened marine taxonomic groups in the world, with ~25% of this species currently listed as threatened or considered of special concern; among seabirds, the penguins (Family Spheniscidae) are the most threatened seabird Family. We used gene expression to develop baseline physiological indices for wild penguins in the Falkland-Malvinas Islands, and captive zoo penguins. We identified the almost complete statistical separation of penguin groups (gentoo Detroit Zoo, gentoo Falkland-Malvinas Islands, rockhopper Detroit Zoo, and rockhopper Falkland-Malvinas Islands) based on gene expression profiles. Implementation of long-term longitudinal studies would allow for the assessment of temporal increases or decreases of select transcripts and would facilitate interpretation of the drivers of change.
","language":"English","publisher":"MDPI","doi":"10.3390/life12020258","usgsCitation":"Bowen, L., Waters-Dynes, S.C., Stott, J., Duncan, A., Meyerson, R., and Woodhouse, S., 2022, Baseline gene expression levels in Falkland-Malvinas Island penguins: Towards a new monitoring paradigm: Life, v. 12, no. 2, 258, 15 p., https://doi.org/10.3390/life12020258.","productDescription":"258, 15 p.","ipdsId":"IP-137240","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448853,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/life12020258","text":"Publisher Index Page"},{"id":396470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Falkland-Malvinas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -61.435546875,\n -52.49615953109709\n ],\n [\n -57.15087890625,\n -52.49615953109709\n ],\n [\n -57.15087890625,\n -50.778155274659234\n ],\n [\n -61.435546875,\n -50.778155274659234\n ],\n [\n -61.435546875,\n -52.49615953109709\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":836152,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":836153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stott, Jeffrey L","contributorId":280430,"corporation":false,"usgs":false,"family":"Stott","given":"Jeffrey L","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":836154,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duncan, Ann","contributorId":280432,"corporation":false,"usgs":false,"family":"Duncan","given":"Ann","email":"","affiliations":[{"id":49095,"text":"Detroit Zoo","active":true,"usgs":false}],"preferred":false,"id":836155,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyerson, Randi","contributorId":146389,"corporation":false,"usgs":false,"family":"Meyerson","given":"Randi","email":"","affiliations":[{"id":16683,"text":"Toledo Zoo, Toledo, OH","active":true,"usgs":false}],"preferred":false,"id":836156,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Woodhouse, Sarah","contributorId":280434,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Sarah","email":"","affiliations":[{"id":57510,"text":"Henry Doorly Zoo and Aquarium","active":true,"usgs":false}],"preferred":false,"id":836157,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228695,"text":"70228695 - 2022 - Combining tangential flow filtration and size fractionation of mesocosm water as a method for the investigation of waterborne coral diseases","interactions":[],"lastModifiedDate":"2023-01-12T15:30:00.992526","indexId":"70228695","displayToPublicDate":"2022-02-08T11:24:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10116,"text":"Biology Methods and Protocols","active":true,"publicationSubtype":{"id":10}},"title":"Combining tangential flow filtration and size fractionation of mesocosm water as a method for the investigation of waterborne coral diseases","docAbstract":"

The causative agents of most coral diseases today remain unknown, complicating disease response and restoration efforts. Pathogen identifications can be hampered by complex microbial communities naturally associated with corals and seawater, which create complicating “background noise” that can potentially obscure a pathogen’s signal. Here, we outline an approach to investigate waterborne coral diseases that use a combination of coral mesocosms, tangential flow filtration, and size fractionation to reduce the impact of this background microbial diversity, compensate for unknown infectious dose, and further narrow the suspect pool of potential pathogens. As proof of concept, we use this method to compare the bacterial communities shed into six Montastraea cavernosa coral mesocosms and demonstrate this method effectively detects differences between diseased and healthy coral colonies. We found several amplicon sequence variants (ASVs) in the diseased mesocosms that represented 100% matches with ASVs identified in prior studies of diseased coral tissue, further illustrating the effectiveness of our approach. Our described method is an effective alternative to using coral tissue or mucus to investigate waterborne coral diseases of unknown etiology and can help more quickly narrow the pool of possible pathogens to better aid in disease response efforts. Additionally, this versatile method can be easily adapted to characterize either the entire microbial community associated with a coral or target-specific microbial groups, making it a beneficial approach regardless of whether a causative agent is suspected or is completely unknown.

","language":"English","publisher":"Oxford University Press","doi":"10.1093/biomethods/bpac007","usgsCitation":"Evans, J.S., Paul, V.J., Ushijima, B., and Kellogg, C.A., 2022, Combining tangential flow filtration and size fractionation of mesocosm water as a method for the investigation of waterborne coral diseases: Biology Methods and Protocols, v. 7, no. 1, bpac007, 8 p., https://doi.org/10.1093/biomethods/bpac007.","productDescription":"bpac007, 8 p.","ipdsId":"IP-133508","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448856,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biomethods/bpac007","text":"Publisher Index Page"},{"id":396118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","city":"Marathon","otherGeospatial":"Key West Nursery","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.14340209960938,\n 24.442148824865637\n ],\n [\n -81.6668701171875,\n 24.442148824865637\n ],\n [\n -81.6668701171875,\n 24.669482313373848\n ],\n [\n -82.14340209960938,\n 24.669482313373848\n ],\n [\n -82.14340209960938,\n 24.442148824865637\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.19583129882812,\n 24.61830581010988\n ],\n [\n -80.90469360351562,\n 24.61830581010988\n ],\n [\n -80.90469360351562,\n 24.79047481357294\n ],\n [\n -81.19583129882812,\n 24.79047481357294\n ],\n [\n -81.19583129882812,\n 24.61830581010988\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, James S. 0000-0002-9977-1627 jsevans@usgs.gov","orcid":"https://orcid.org/0000-0002-9977-1627","contributorId":279528,"corporation":false,"usgs":true,"family":"Evans","given":"James","email":"jsevans@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":835095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paul, Valerie J. 0000-0002-4691-1569","orcid":"https://orcid.org/0000-0002-4691-1569","contributorId":279530,"corporation":false,"usgs":false,"family":"Paul","given":"Valerie","email":"","middleInitial":"J.","affiliations":[{"id":57268,"text":"Smithsonian Marine Station","active":true,"usgs":false}],"preferred":false,"id":835096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ushijima, Blake","contributorId":91782,"corporation":false,"usgs":false,"family":"Ushijima","given":"Blake","email":"","affiliations":[{"id":13394,"text":"Hawai‘i Institute of Marine Biology","active":true,"usgs":false}],"preferred":false,"id":835097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":835098,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228381,"text":"70228381 - 2022 - Shoaling wave shape estimates from field observations and derived bedload sediment rates","interactions":[],"lastModifiedDate":"2022-02-09T16:23:50.789606","indexId":"70228381","displayToPublicDate":"2022-02-08T10:12:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Shoaling wave shape estimates from field observations and derived bedload sediment rates","docAbstract":"

The shoaling transformation from generally linear deep-water waves to asymmetric shallow-water waves modifies wave shapes and causes near-bed orbital velocities to become asymmetrical, contributing to net sediment transport. In this work, we used two methods to estimate the asymmetric wave shape from data at three sites. The first method converted wave measurements made at the surface to idealized near-bottom wave-orbital velocities using a set of empirical equations: the “parameterized” waveforms. The second method involved direct measurements of velocities and pressure made near the seabed: the “direct” waveforms. Estimates from the two methods were well correlated at all three sites (Pearson’s correlation coefficient greater than 0.85). Both methods were used to drive bedload-transport calculations that accounted for asymmetric waves, and the results were compared with a traditional excess-stress formulation and field estimates of bedload transport derived from ripple migration rates based on sonar imagery. The cumulative bedload transport from the parameterized waveform was 25% greater than the direct waveform, mainly because the parameterized waveform did not account for negative skewness. Calculated transport rates were comparable to rates estimated from ripple migration except during the largest event, when calculated rates were as much as 100 times greater, which occurred during high period waves.

","language":"English","publisher":"MDPI","doi":"10.3390/jmse10020223","usgsCitation":"Kalra, T., Suttles, S.E., Sherwood, C.R., Warner, J.C., Aretxabaleta, A., and Leavitt, G.R., 2022, Shoaling wave shape estimates from field observations and derived bedload sediment rates: Journal of Marine Science and Engineering, v. 10, no. 2, 223, 27 p., https://doi.org/10.3390/jmse10020223.","productDescription":"223, 27 p.","ipdsId":"IP-130494","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448866,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse10020223","text":"Publisher Index Page"},{"id":395674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Massachusetts, New York","otherGeospatial":"Fire Island, Martha Vineyard, Matanzas Inlet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.30260467529297,\n 29.898252057056208\n ],\n [\n -81.2739372253418,\n 29.898252057056208\n ],\n [\n -81.2739372253418,\n 29.916405869526507\n ],\n [\n -81.30260467529297,\n 29.916405869526507\n ],\n [\n -81.30260467529297,\n 29.898252057056208\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.57891845703125,\n 41.31907562295139\n ],\n [\n -70.52604675292969,\n 41.31907562295139\n ],\n [\n -70.52604675292969,\n 41.38041517477678\n ],\n [\n -70.57891845703125,\n 41.38041517477678\n ],\n [\n -70.57891845703125,\n 41.31907562295139\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.19744110107422,\n 40.61890405098613\n ],\n [\n 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ssuttles@usgs.gov","orcid":"https://orcid.org/0000-0002-4119-8370","contributorId":192272,"corporation":false,"usgs":true,"family":"Suttles","given":"Steven","email":"ssuttles@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":834049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":834050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":834051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":834052,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leavitt, Gibson Robert Scott 0000-0001-5362-9150","orcid":"https://orcid.org/0000-0001-5362-9150","contributorId":275364,"corporation":false,"usgs":true,"family":"Leavitt","given":"Gibson","email":"","middleInitial":"Robert Scott","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":834053,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228168,"text":"70228168 - 2022 - Perfluoroalkyl and polyfluoroalkyl substances in groundwater used as a source of drinking water in the eastern United States","interactions":[],"lastModifiedDate":"2022-03-17T16:48:46.028922","indexId":"70228168","displayToPublicDate":"2022-02-07T13:34:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Perfluoroalkyl and polyfluoroalkyl substances in groundwater used as a source of drinking water in the eastern United States","docAbstract":"In 2019, 254 samples were collected from five aquifer systems to evaluate per- and polyfluoroalkyl substance (PFAS) occurrence in groundwater used as a source of drinking water in the eastern United States. The samples were analyzed for 24 PFAS, major ions, nutrients, trace elements, dissolved organic carbon (DOC), volatile organic compounds (VOCs), pharmaceuticals, and tritium. Fourteen of the 24 PFAS were detected in groundwater, with 60% and 20% of public-supply and domestic wells, respectively, containing at least one PFAS detection. Concentrations of tritium, chloride, sulfate, DOC, and manganese+iron; percent urban land use within 500 m of the wells; and VOC and pharmaceutical detection frequencies were significantly higher in samples containing PFAS detections than in samples with no detections. Boosted Regression Tree models that consider 57 chemical and land-use variables show that tritium concentration, distance to the nearest fire-training area, percentage of urban land use, and DOC and VOC concentrations are the top five predictors of PFAS detections, consistent with hydrologic position, geochemistry, and land use being important controls on PFAS occurrence in groundwater. Model results indicate it may be possible to predict PFAS detections in groundwater using existing data sources.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.1c04795","usgsCitation":"McMahon, P.B., Tokranov, A.K., Bexfield, L.M., Lindsey, B.D., Johnson, T., Lombard, M.A., and Watson, E., 2022, Perfluoroalkyl and polyfluoroalkyl substances in groundwater used as a source of drinking water in the eastern United States: Environmental Science & Technology, v. 56, no. 4, p. 2279-2288, https://doi.org/10.1021/acs.est.1c04795.","productDescription":"10 p.","startPage":"2279","endPage":"2288","ipdsId":"IP-129437","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science 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corresponding improvements in estuarine water quality have not clearly materialized. Generalized additive models were used to directly link river flows and nutrient loads from the watershed to nutrient trends in the estuary on a station-by-station basis, which allowed for identification of exactly when and where responses are happening. Results show that Chesapeake Bay total nitrogen and total phosphorus conditions are mostly improving after accounting for variation in freshwater flow. Almost all of these improving nutrient concentrations in the estuary can be explained by reductions in watershed loads entering through 16 rivers and 145 nearby point sources. These two major types of loads from multiple locations across the watershed are together necessary and responsible for improving estuarine nutrient conditions, a finding that is highly relevant to managing valuable estuarine resources worldwide.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.1c05388","usgsCitation":"Murphy, R.R., Keisman, J.L., Harcum, J., Karrh, R., Lane, M.F., Perry, E.S., and Zhang, Q., 2022, Nutrient improvements in Chesapeake Bay: Direct effect of load reductions and implications for coastal management: Environmental Science & Technology, v. 56, p. 260-270, https://doi.org/10.1021/acs.est.1c05388.","productDescription":"11 p.","startPage":"260","endPage":"270","ipdsId":"IP-133943","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":448875,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.odu.edu/biology_fac_pubs/470","text":"Publisher Index Page"},{"id":395542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.256103515625,\n 36.87962060502676\n ],\n [\n -76.1572265625,\n 36.88840804313823\n ],\n [\n -75.97869873046874,\n 37.08585785263673\n ],\n [\n -75.96221923828125,\n 37.243448378654115\n ],\n [\n -75.92376708984375,\n 37.40943717748788\n ],\n [\n -75.78094482421875,\n 37.60987994374712\n ],\n [\n -75.574951171875,\n 37.965854128749434\n ],\n [\n -75.673828125,\n 38.13887716726548\n ],\n [\n -75.79742431640625,\n 38.39118617958438\n ],\n [\n -75.926513671875,\n 38.55460931253295\n ],\n [\n -75.95123291015625,\n 38.953001345359894\n ],\n [\n -75.80841064453125,\n 39.22799807055236\n ],\n [\n -75.80841064453125,\n 39.66702799810167\n ],\n [\n -75.91827392578125,\n 39.679712203159745\n ],\n [\n -76.3714599609375,\n 39.55700068337126\n ],\n [\n -76.717529296875,\n 39.30242456041487\n ],\n [\n -76.673583984375,\n 39.15136267949029\n ],\n [\n -76.6021728515625,\n 38.831149809348744\n ],\n [\n -76.5692138671875,\n 38.586820096127674\n ],\n [\n -76.48956298828125,\n 38.26406296833961\n ],\n [\n -76.57470703125,\n 37.55764242679522\n ],\n [\n -76.5032958984375,\n 37.142803443716836\n ],\n [\n -76.256103515625,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","noUsgsAuthors":false,"publicationDate":"2021-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Rebecca R.","contributorId":274698,"corporation":false,"usgs":false,"family":"Murphy","given":"Rebecca","email":"","middleInitial":"R.","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":833242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keisman, Jennifer L. 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Postharvest waste seed from cereal grains is a major dietary component of waterfowl in the Klamath Basin in northeastern California and southeastern Oregon, a region that plays host to over a million waterfowl annually. Understanding food abundance is critical to local waterfowl management; therefore, we conducted a study in 2008 to investigate waste grain densities in barley, oat, and wheat fields. We used hierarchal mixed effect models to assess several factors that may affect waste grain densities postharvest. We also compared the effects of residue management practices to measure the effect of these treatments. To understand the scope of postharvest practices, we conducted a weekly road survey to document treatments applied to fields in our study area. We found that region best explained the variance of postharvest waste grain in barley fields, where the Tule Lake region had 89% greater densities than Lower Klamath. Neither harvester age nor baling affected waste grain in oats fields. In wheat fields, the model containing region and lodging ranked highest, where the Tule Lake region had 66% greater waste densities than Lower Klamath, and lodging increased waste grain by 70%. Burning did not reduce waste grain in barley or oat fields. Chisel-disking reduced waste grain by 94% in wheat fields compared with postharvest. Our field treatment survey found that 70% of barley fields were untreated while 18% were disked and 13% were burned and flooded. We estimated that 82% of oat fields were burned postharvest, while 18% were burned and flooded. In wheat, 61% of fields were left untreated, while 16% were disked, 8% were chisel-plowed, and 7% were flooded postharvest. Flooding and burning occurred primarily on National Wildlife Refuges, while disking, chisel-plowing, and postharvest irrigation occurred solely on private properties. Our results indicate that reducing tillage treatments would boost accessibility of cereal grain food resources to waterfowl in the Klamath Basin, and incentives to flood grain fields on private properties should be considered for the same purpose when and where possible.

","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-20-091","usgsCitation":"Skalos, D., Fleskes, J., Kohl, J.D., Herzog, M.P., and Casazza, M.L., 2022, Assessment of cereal grain waste densities to aid waterfowl conservation planning in the Klamath Basin: Journal of Fish and Wildlife Management, v. 13, no. 1, p. 3-16, https://doi.org/10.3996/JFWM-20-091.","productDescription":"14 p.","startPage":"3","endPage":"16","ipdsId":"IP-125071","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448886,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-091","text":"Publisher Index Page"},{"id":395533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.222412109375,\n 42.00032514831621\n ],\n [\n -123.167724609375,\n 39.825413103424786\n ],\n [\n -119.981689453125,\n 42.00848901572399\n ],\n [\n -120.95947265624999,\n 43.874138181474734\n ],\n [\n -124.222412109375,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Skalos, Daniel A.","contributorId":250668,"corporation":false,"usgs":false,"family":"Skalos","given":"Daniel A.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":833396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":210345,"corporation":false,"usgs":false,"family":"Fleskes","given":"Joseph P.","affiliations":[],"preferred":false,"id":833397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kohl, Jeffery D.","contributorId":274848,"corporation":false,"usgs":false,"family":"Kohl","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":56673,"text":"California Department of Fish and Wildlife, 1010 Riverside Parkway, West Sacramento, CA 95605, USA","active":true,"usgs":false}],"preferred":false,"id":833398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833399,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":833400,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228148,"text":"sim3485 - 2022 - Bathymetric map, surface  area, and stage-capacity for the U.S. part of Lake Koocanusa, Lincoln County, Montana,  2016–18","interactions":[],"lastModifiedDate":"2026-03-31T21:21:02.52497","indexId":"sim3485","displayToPublicDate":"2022-02-04T11:14:19","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3485","displayTitle":"Bathymetric Map, Surface Area, and Stage-Capacity for the U.S. Part of Koocanusa Reservoir, Lincoln County, Montana, 2016–18","title":"Bathymetric map, surface  area, and stage-capacity for the U.S. part of Lake Koocanusa, Lincoln County, Montana,  2016–18","docAbstract":"

The U.S. Geological Survey and U.S. Army Corps of Engineers collected high-resolution multibeam sonar data during 2016–18 to compute stage-area and stage-capacity tables for the U.S. part of Koocanusa Reservoir in Lincoln County, northwestern Montana. Koocanusa Reservoir is a transboundary reservoir extending about 48 miles from Libby Dam upstream to the U.S. international boundary with Canada and another 42 miles within Canada to near Wardner, British Columbia. The upstream extent of the reservoir within Canada, where much of the sedimentation was previously documented, was not included in this study. Previously developed stage-area and stage-capacity tables were developed for the entire reservoir and could not be directly compared to the stage-area and stage-capacity tables from this study. Two discrete stage-area and stage-capacity values from the original survey (unknown survey date prior to 1980) were available for parts of the reservoir within the United States at the normal full-pool and normal minimum-pool elevations (2,459 and 2,287 U.S. survey feet above the National Geodetic Vertical Datum of 1929, respectively). At the normal full-pool elevation, the stage-area relation resulted in a 0.06-percent increase in surface-water acreage. Conversely, a 0.03-percent decrease in storage capacity at the normal full-pool elevation occurred. At the normal-minimum-pool elevation, the stage-area relation showed a 1.21-percent decrease in surface water from 14,487 to 14,314 acres. The usable storage capacity, defined as the volume of water between the normal full-pool and normal minimum-pool elevations, decreased by 0.39 percent (15,353 acre-feet). Results from this study indicate that a relatively minimal amount of sedimentation has occurred since initial filling in Koocanusa Reservoir for parts of the reservoir within the United States. Updated stage-area and stage-capacity tables for the entire reservoir will require additional bathymetric and topographic surveys for the parts of Koocanusa Reservoir within Canada.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3485","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Fosness, R.L., and Dudunake, T.J., 2022, Bathymetric map, surface  area, and stage-capacity for the U.S. part of Lake Koocanusa, Lincoln County, Montana,  2016–18: U.S. Geological Survey Scientific Investigations Map 3485, scale 1:100,000,  https://doi.org/10.3133/sim3485.","productDescription":"1 Plate: 30.00 × 35.00 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-121814","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":395469,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DOPNSN","text":"USGS data release","description":"USGS data release","linkHelpText":"U.S. Geological Survey and U.S. Army Corps of Engineers bathymetric survey of Koocanusa Reservoir, Lincoln County, Montana, 2016–2018 (ver. 2.0, August 2021)"},{"id":501890,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112443.htm","linkFileType":{"id":5,"text":"html"}},{"id":395468,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3485/sim3485.pdf","text":"Report","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3485"},{"id":395467,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3485/coverthb.jpg"}],"country":"United States","state":"Montana","county":"Lincoln County","otherGeospatial":"Koocanusa Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.367431640625,\n 48.38544219115483\n ],\n [\n -115.08453369140625,\n 48.38544219115483\n ],\n [\n -115.08453369140625,\n 49.00004203215395\n ],\n [\n -115.367431640625,\n 49.00004203215395\n ],\n [\n -115.367431640625,\n 48.38544219115483\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director , Idaho Water Science Center
U.S. Geological Survey
230 Collins Road  Boise, Idaho 83702-4520

","tableOfContents":"","publishedDate":"2022-02-04","noUsgsAuthors":false,"publicationDate":"2022-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudunake, Taylor J. 0000-0001-7650-2419 tdudunake@usgs.gov","orcid":"https://orcid.org/0000-0001-7650-2419","contributorId":213485,"corporation":false,"usgs":true,"family":"Dudunake","given":"Taylor","email":"tdudunake@usgs.gov","middleInitial":"J.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":833217,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228162,"text":"70228162 - 2022 - The role of hydraulic and geomorphic complexity in predicting invasive carp spawning potential: St. Croix River, Minnesota and Wisconsin, United States","interactions":[],"lastModifiedDate":"2022-02-07T18:02:04.365799","indexId":"70228162","displayToPublicDate":"2022-02-03T11:55:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The role of hydraulic and geomorphic complexity in predicting invasive carp spawning potential: St. Croix River, Minnesota and Wisconsin, United States","docAbstract":"

Since they were first introduced to the United States more than 50 years ago, invasive carp have rapidly colonized rivers of the Mississippi River Basin, with detrimental effects on native aquatic species. Their continued range expansion, and potential for subsequent invasion of the Great Lakes, has led to increased concern for the susceptibility of as-yet uncompromised lotic and lentic systems in the central United States. Because invasive carp eggs and larvae must drift in the river current for the first several days following spawning, numerical drift modeling has emerged as a useful technique for determining whether certain river systems and reaches have the potential to support suspension-to-hatching survival of invasive carp eggs, a critical first step in recruitment. Here we use one such numerical modeling approach, the Fluvial Egg Drift Simulator (FluEgg), to estimate bighead carp (Hypophthalmichthys nobilis) egg hatching success and larval retention in a 47.8-kilometer (km) reach of the multi-thread St. Croix River, Minnesota and Wisconsin, United States. We explore three approaches for obtaining the hydraulic data required by FluEgg, parameterizing the model with either (a) field hydraulic data collected within the main channel during a high-flow event, or hydraulic data output from a one-dimensional hydrodynamic model with both (b) steady, and (c) unsteady flows. We find that the three approaches, along with the range of water temperatures and discharge used in simulations, produce vastly different predictions of streamwise transport and in-river egg hatching probability (0% for field data, 0 to 96% for steady-state hydraulic modeling, and 1.8 to 65% for unsteady modeling). However, all FluEgg simulations, regardless of the source of hydraulic data, predicted that no larvae reach the gas bladder inflation stage within the study reach where nursery habitat is abundant. Overall, these results indicate that the lower St. Croix River is suitable for invasive carp spawning and egg suspension until hatching for a range of discharge and water temperatures. These results highlight the role of complex channel hydraulics and morphology, particularly multi-thread reaches, and their inclusion in ecohydraulic-suitability modeling to determine susceptibility of river systems for invasive carp reproduction. Our work also emphasizes the scientific value of multi-dimensional hydrodynamic models that can capture the spatial heterogeneity of flow fields in geomorphically complex rivers. This work may help to guide management efforts based on the targeted monitoring and control and improve invasive carp egg and larvae sampling efficiency.

","language":"English","publisher":"Public Library of Science (PLOS)","doi":"10.1371/journal.pone.0263052","usgsCitation":"Kasprak, A., Jackson, P.R., Lindroth, E.M., Lund, J.W., and Ziegeweid, J.R., 2022, The role of hydraulic and geomorphic complexity in predicting invasive carp spawning potential: St. Croix River, Minnesota and Wisconsin, United States: PLoS ONE, v. 17, no. 2, e0263052, 25 p., https://doi.org/10.1371/journal.pone.0263052.","productDescription":"e0263052, 25 p.","ipdsId":"IP-128244","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":448898,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0263052","text":"Publisher Index Page"},{"id":435980,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93K0UUI","text":"USGS data release","linkHelpText":"Bathymetric, water velocity, and water temperature data on the St. Croix River between St. Croix Falls, Wisconsin, and Stillwater, Minnesota, June 19-22, 2018"},{"id":395554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"St Croix River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.84408569335938,\n 44.98714175309689\n ],\n [\n -92.59552001953125,\n 44.98714175309689\n ],\n [\n -92.59552001953125,\n 45.42062422307843\n ],\n [\n -92.84408569335938,\n 45.42062422307843\n ],\n [\n -92.84408569335938,\n 44.98714175309689\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":245742,"corporation":false,"usgs":false,"family":"Kasprak","given":"Alan","affiliations":[{"id":49307,"text":"Current: Utah State University. Former: Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA","active":true,"usgs":false}],"preferred":false,"id":833274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"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},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindroth, Evan M. 0000-0002-9746-4359 elindroth@usgs.gov","orcid":"https://orcid.org/0000-0002-9746-4359","contributorId":264885,"corporation":false,"usgs":true,"family":"Lindroth","given":"Evan","email":"elindroth@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lund, J. William 0000-0002-8830-4468","orcid":"https://orcid.org/0000-0002-8830-4468","contributorId":211157,"corporation":false,"usgs":true,"family":"Lund","given":"J.","email":"","middleInitial":"William","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ziegeweid, Jeffrey R. 0000-0001-7797-3044 jrziege@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-3044","contributorId":4166,"corporation":false,"usgs":true,"family":"Ziegeweid","given":"Jeffrey","email":"jrziege@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833278,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}