Researchers are investigating the problem of estimating households with potable water service outages soon after an earthquake. Most of these modeling approaches are computationally intensive, have large proprietary data collection requirements or lack precision, making them unfeasible for rapid assessment, prioritization, and allocation of emergency water resources in large, complex disasters. This study proposes a new simplified analytical method—performed without proprietary water pipeline data—to estimate water supply needs after earthquakes, and a case study of its application in the HayWired earthquake scenario. In the HayWired scenario—a moment magnitude (Mw) 7.0 Hayward Fault earthquake in the San Francisco Bay Area, California (USA)—an analysis of potable water supply in two water utility districts was performed using the University of Colorado Water Network (CUWNet) model. In the case study, application of the simplified method extends these estimates of household water service outage to the nine counties adjacent to the San Francisco Bay, aggregated by a ~250 m2 (nine-arcsecond) grid. The study estimates about 1.38 million households (3.7 million residents) out of 7.6 million residents (2017, ambient, nighttime population) with potable water service outage soon after the earthquake—about an 8% increase from the HayWired scenario estimates.
","language":"English","publisher":"MDPI","doi":"10.3390/w13192635","usgsCitation":"Toland, J.C., and Wein, A., 2021, A simplified method for rapid estimation of emergency water supply needs after earthquakes: Water, v. 13, 2635, 27 p., https://doi.org/10.3390/w13192635.","productDescription":"2635, 27 p.","ipdsId":"IP-132813","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":450658,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13192635","text":"Publisher Index Page"},{"id":389813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.79968261718749,\n 37.24782120155428\n ],\n [\n -121.55273437499999,\n 37.24782120155428\n ],\n [\n -121.55273437499999,\n 38.324420427006544\n ],\n [\n -122.79968261718749,\n 38.324420427006544\n ],\n [\n -122.79968261718749,\n 37.24782120155428\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2021-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Toland, Joseph Charles 0000-0002-0092-0320","orcid":"https://orcid.org/0000-0002-0092-0320","contributorId":265976,"corporation":false,"usgs":true,"family":"Toland","given":"Joseph","email":"","middleInitial":"Charles","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":823911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":823912,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70224317,"text":"fs20213044 - 2021 - Managing water resources on Long Island, New York, with integrated, multidisciplinary science","interactions":[],"lastModifiedDate":"2021-09-27T12:11:24.513816","indexId":"fs20213044","displayToPublicDate":"2021-09-24T14:10:00","publicationYear":"2021","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":"2021-3044","displayTitle":"Managing Water Resources on Long Island, New York, with Integrated, Multidisciplinary Science","title":"Managing water resources on Long Island, New York, with integrated, multidisciplinary science","docAbstract":"Nutrients, harmful algal blooms, and synthetic chemicals like per- and polyfluoroalkyl substances (PFAS) and 1,4-dioxane threaten Long Island’s water resources by affecting the quality of drinking water and ecologically sensitive habitats that support the diverse wildlife throughout the island. Understanding the occurrence, fate, and transport of these potentially harmful chemicals is critical to protect these vital resources. The U.S. Geological Survey (USGS) is collecting and analyzing data to support informed water-resource management decisions. This fact sheet introduces ongoing efforts and future areas of study aimed to help water professionals develop a comprehensive science strategy to address contamination of the Long Island aquifer system, the sole source of drinking water for nearly 3 million people. These studies include surface and groundwater collection and groundwater flow modeling. Funding for the data collection has been provided by the USGS, New York State Department of Environmental Conservation, New York City Department of Environmental Protection, Suffolk County Water Authority, Nassau County Department of Public Works, State and local agencies, and Tribal and Federal partners. Without the foresight and long-term commitment of these funding partners, evaluating sustainability and planning for future water needs would not be possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213044","usgsCitation":"Breault, R.F., Masterson, J.P., Schubert, C.E., and Herdman, L.M., 2021, Managing water resources on Long Island, New York, with integrated, multidisciplinary science: U.S. Geological Survey Fact Sheet 2021–3044, 4 p., https://doi.org/10.3133/fs20213044.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131602","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":389579,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3044/fs20213044.pdf","text":"Report","size":"14.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021-3044"},{"id":389578,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3044/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.0478515625,\n 40.538851525354666\n ],\n [\n -73.7677001953125,\n 40.538851525354666\n ],\n [\n -73.1304931640625,\n 40.60561205826018\n ],\n [\n -72.5537109375,\n 40.76806170936614\n ],\n [\n -71.9549560546875,\n 40.97575093157534\n ],\n [\n -71.83959960937499,\n 41.10832999732831\n ],\n [\n -72.1417236328125,\n 41.24064190269475\n ],\n [\n -72.8338623046875,\n 41.10005163093046\n ],\n [\n -73.5205078125,\n 40.96330795307353\n ],\n [\n -73.883056640625,\n 40.83043687764923\n ],\n [\n -74.06982421875,\n 40.713955826286046\n ],\n [\n -74.0863037109375,\n 40.61812224225511\n ],\n [\n -74.0478515625,\n 40.538851525354666\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
This field trip highlights the results of recent U.S. Geological Survey (USGS) bedrock geologic mapping in four 7.5 min quadrangles in the western Connecticut highlands near Southbury, Connecticut, USA. The rocks are broadly within what Rodgers (1985) called the Hartland and Gneiss Dome belts of the Connecticut Valley Synclinorium (Rodgers, 1985; Fig. 1), the latter of which is now known as the Connecticut Valley–Gaspe Trough (Hibbard et al., 2006). The mapping occurred over two intervals: 2003–2005 and 2016–present. In the first, the goal was a detailed map of the early Mesozoic Pomperaug basin, which overlaps the four quadrangles. Portions of the basin had been separately mapped during the statewide 7.5 min quadrangle mapping campaign spanning the 1950s–1970s, resulting in an inaccurate depiction of the basin on the 1985 state geologic map (Rodgers, 1985). A new map of the basin was proposed in part to benefit an ongoing project by the USGS Connecticut Water Science Center to determine the contributions of natural and artificial contaminants to a public water-supply well in Woodbury, Connecticut, under the National Water-Quality Assessment (NAWQA) Program (Starn and Brown, 2007). The NAWQA project was partially funded by the Pomperaug River Watershed Coalition, which also provided logistical support to the geologic mapping project. Mapping of the basin was also a high priority for the Connecticut State Geologist at the time (Ralph Lewis, 2002, pers. comm.). The mapping resulted in an NEIGC (New England Intercollegiate Geologic Conference) field guide (Burton et al., 2005) and a 1:12,000-scale USGS open-file map (Burton, 2006) and was funded by the USGS National Cooperative Geologic Mapping Program (NCGMP).
The second phase of the mapping began in 2016 after the discovery of elevated levels of uranium and arsenic in domestic water wells in the igneous and metamorphic rocks that surround the sedimentary and volcanic rocks of the Pomperaug basin (Flanagan and Brown, 2017). Structural measurements in the surrounding crystalline rocks were made during Pomperaug basin mapping to better understand the tectonic setting, but a revision of the crystalline map units on Rodgers’ 1985 geologic map was not attempted. Nonetheless, discrepancies were noted between the new mapping and the 1985 map, particularly within the two northern quadrangles of Woodbury and Roxbury, which were originally mapped by Gates (1954) and Gates (1959), respectively. Based on these discrepancies, a new NCGMP project was proposed to remap the Woodbury and Roxbury 7.5 min quadrangles, commencing in the fall of 2016. The expected USGS product will be a two-quadrangle, 1:24,000-scale Scientific Investigations Map (SIM).
This field guide is not meant as a comprehensive review of all of the geologic research done in this area of Connecticut; rather, it looks at previous bedrock geologic mapping from the perspective of new and recent mapping in the four-quadrangle area and discusses the structural, stratigraphic, and nomenclatural revisions necessary for the next revision of the state geologic map.
Bulletin 17C (B17C) recommends fitting the log-Pearson Type III (LP−III) distribution to a series of annual peak flows at a streamgage by using the method of moments. The third moment, the skewness coefficient (or skew), is important because the magnitudes of annual exceedance probability (AEP) flows estimated by using the LP–III distribution are affected by the skew; interest is focused on the right-hand tail of the distribution, which represents the larger annual peak flows that correspond to small AEPs. For streamgages having modest record lengths, the skew is sensitive to extreme events like large floods, which cause a sample to be highly asymmetrical or “skewed.” For this reason, B17C recommends using a weighted-average skew computed from the skew of the annual peak flows for a given streamgage and a regional skew. This report presents an estimate of regional skew for a study area encompassing parts of eastern New York and Pennsylvania. A total of 232 candidate U.S. Geological Survey streamgages that were unaffected by extensive regulation, diversion, urbanization, or channelization were considered for use in the skew analysis; after screening for redundancy and pseudo record length (PRL) of at least 36 years, 183 streamgages were selected for use in the study.
Flood frequencies for candidate streamgages were analyzed by employing the expected moments algorithm, which extends the method of moments so that it can accommodate interval, censored, and historical/paleo flow data, as well as the multiple Grubbs-Beck test to identify potentially influential low floods in the data series. Bayesian weighted least squares/Bayesian generalized least squares regression was used to develop a regional skew model for the study area that would incorporate possible variables (basin characteristics) to explain the variation in skew in the study area. Ten basin characteristics were considered as possible explanatory variables; however, none produced a pseudo coefficient of determination greater than 1 percent; as a result, these characteristics did not help to explain the variation in skew in the study area. Therefore, a constant model that had a regional skew coefficient of 0.32 and an average variance of prediction at a new streamgage (AVPnew, which corresponds to the mean square error [MSE] of 0.11) was selected. The AVPnew corresponds to an effective record length of 68 years, a marked improvement over the Bulletin 17B national skew map, whose reported MSE of 0.302 indicated a corresponding effective record length of only 17 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215015","usgsCitation":"Veilleux, A.G., and Wagner, D.M., 2021, Methods for estimating regional skewness of annual peak flows in parts of eastern New York and Pennsylvania, based on data through water year 2013: U.S. Geological Survey Scientific Investigations Report 2021–5015, 38 p., https://doi.org/10.3133/sir20215015.","productDescription":"Report: vi, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114558","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":389079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5015/coverthb.jpg"},{"id":389080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5015/sir20215015.pdf","text":"Report","size":"6.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5015"},{"id":389081,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PGAL0D","text":"USGS data release","linkHelpText":"Regional flood skew for parts of the mid-Atlantic region (hydrologic unit 02) in eastern New York and Pennsylvania"}],"country":"United States","state":"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 -75.56396484375,\n 39.740986355883564\n ],\n [\n -75.03662109375,\n 40.04443758460856\n ],\n [\n -74.86083984375,\n 40.34654412118006\n ],\n [\n -75.16845703124999,\n 40.713955826286046\n ],\n [\n -74.970703125,\n 41.062786068733026\n ],\n [\n -74.619140625,\n 41.393294288784865\n ],\n [\n -74.1796875,\n 41.65649719441145\n ],\n [\n -73.54248046875,\n 42.17968819665961\n ],\n [\n -73.23486328124999,\n 43.02071359427862\n ],\n [\n -73.32275390625,\n 43.628123412124616\n ],\n [\n -73.45458984375,\n 43.77109381775651\n ],\n [\n -73.80615234375,\n 43.35713822211053\n ],\n [\n -74.28955078125,\n 43.14909399920127\n ],\n [\n -74.77294921875,\n 42.79540065303723\n ],\n [\n -75.34423828125,\n 42.73087427928485\n ],\n [\n -75.82763671875,\n 42.68243539838623\n ],\n [\n -76.35498046875,\n 42.68243539838623\n ],\n [\n -76.88232421875,\n 42.68243539838623\n ],\n [\n -77.23388671874999,\n 42.45588764197166\n ],\n [\n -77.607421875,\n 42.19596877629178\n ],\n [\n -77.607421875,\n 42.01665183556825\n ],\n [\n -77.6513671875,\n 41.409775832009565\n ],\n [\n -77.80517578125,\n 41.1290213474951\n ],\n [\n -77.9150390625,\n 40.53050177574321\n ],\n [\n -78.11279296875,\n 40.16208338164617\n ],\n [\n -78.46435546875,\n 39.67337039176558\n ],\n [\n -75.56396484375,\n 39.740986355883564\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Freshwater mussels are one of the most imperiled groups of animals in the world and are among the most sensitive species to a variety of chemicals. However, little is known about the sensitivity of freshwater mussels to wastewater effluents. The objectives of the present study were to (1) assess the toxicity of a permitted effluent, which entered the Deep Fork River, Oklahoma (USA), to a unionid mussel (Lampsilis siliquoidea) and to two standard test species (cladoceran Ceriodaphnia dubia; and fathead minnow Pimephales promelas) in short-term 7-day effluent tests; (2) evaluate the relative sensitivities of the three species to potassium (K), an elevated major ion in the effluent, using 7-day toxicity tests with KCl spiked into a Deep Fork River upstream reference water; (3) determine the potential influences of background water characteristics on the acute K toxicity to the mussel (96-h exposures) and cladoceran (48-h exposure) in four reconstituted waters that mimicked the hardness and ionic composition ranges of the Deep Fork River; and (4) determine the potential influence of temperature on acute K toxicity to the mussel. The effluent was found to be toxic to mussels and cladocerans, and it contained elevated concentrations of major cations and anions relative to the upstream Deep Fork River reference water. The K concentration in the effluent was 48-fold greater than in the upstream water. Compared with the standard species, the mussel was more than 4-fold more sensitive to the effluent in the 7-day effluent tests and more than 8-fold more sensitive to K in the 7-day K toxicity tests. The acute K toxicity to the mussel decreased by a factor of 2 when the water hardness was increased from soft (42 mg/L as CaCO3) to very hard (314 mg/L as CaCO3), whereas the acute K toxicity to the cladoceran remained almost the same as hardness increased from 84 to 307 mg/L as CaCO3. Acute K toxicity to the mussel at 23 °C was similar to the toxicity at an elevated temperature of 28 °C. The overall results indicate that the two standard test species may not represent the sensitivity of the tested mussel to both the effluent and K, and the toxicity of K was influenced by the hardness in test waters, but by a limited magnitude.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.5221","usgsCitation":"Kunz, J.L., Wang, N., Martinez, D., Dunn, S., Cleveland, D.M., and Steevens, J.A., 2021, The sensitivity of a unionid mussel (Lampsilis siliquoidea) to a permitted effluent and elevated potassium in the effluent: Environmental Toxicology and Chemistry, v. 40, no. 12, p. 3410-3420, https://doi.org/10.1002/etc.5221.","productDescription":"11 p.","startPage":"3410","endPage":"3420","ipdsId":"IP-129678","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":436187,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92YZGDX","text":"USGS data release","linkHelpText":"Chemical and biological data from a study on sensitivity of a unionid mussel (Lampsilis siliquoidea) to a permitted effluent and elevated potassium"},{"id":396104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","city":"Okmulgee","otherGeospatial":"Deep Fork National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.60827636718749,\n 35.546753306701\n ],\n [\n -95.92849731445312,\n 35.546753306701\n ],\n [\n -95.92849731445312,\n 35.69968630125204\n ],\n [\n -96.60827636718749,\n 35.69968630125204\n ],\n [\n -96.60827636718749,\n 35.546753306701\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martinez, David","contributorId":279598,"corporation":false,"usgs":false,"family":"Martinez","given":"David","email":"","affiliations":[{"id":57309,"text":"US Fish Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Suzanne","contributorId":279599,"corporation":false,"usgs":false,"family":"Dunn","given":"Suzanne","email":"","affiliations":[{"id":57309,"text":"US Fish Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835194,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262512,"text":"70262512 - 2021 - Upper Grand Coulee: New views of a channeled scabland megafloods enigma","interactions":[],"lastModifiedDate":"2025-01-17T15:29:50.650525","indexId":"70262512","displayToPublicDate":"2021-09-24T09:21:11","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Upper Grand Coulee: New views of a channeled scabland megafloods enigma","docAbstract":"New findings about old puzzles occasion rethinking of the Grand Coulee, greatest of the scabland channels. Those puzzles begin with antecedents of current upper Grand Coulee. By a recent interpretation, the upper coulee exploited the former high-level valley of a preflood trunk stream that had drained to the southwest beside and across Coulee anticline or monocline. In any case, a constriction and sharp bend in nearby Columbia valley steered Missoula floods this direction. Completion of upper Grand Coulee by megaflood erosion captured flood drainage that would otherwise have continued to enlarge Moses Coulee.
Upstream in the Sanpoil valley, deposits and shorelines of last-glacial Lake Columbia varied with the lake’s Grand Coulee outlet while also recording scores of Missoula floods. The Sanpoil evidence implies that upper Grand Coulee had approached its present intake depth early the last glaciation at latest, or more simply during a prior glaciation. An upper part of the Sanpoil section provides varve counts between the last tens of Missoula floods in a stratigraphic sequence that may now be linked to flood rhythmites of southern Washington by a set-S tephra from Mount St. Helens.
On the floor of upper Grand Coulee itself, recently found striated rock and lodgement till confirm the long-held view, which Bretz and Flint had shared, that cutting of upper Grand Coulee preceded its last-glacial occupation by the Okanogan ice lobe. A dozen or more late Missoula floods registered as sand and silt in the lee of Steamboat Rock.
Some of this field evidence about upper Grand Coulee may conflict with results of recent two-dimensional simulations for a maximum Lake Missoula. In these simulations only a barrier high above the present coulee intake enables floods to approach high-water marks near Wenatchee that predate stable blockage of Columbia valley by the Okanogan lobe. Above the walls of upper Grand Coulee, scabland limits provide high-water targets for two-dimensional simulations of watery floods. The recent models sharpen focus on water sources, prior coulee incision, and coulee’s occupation by the Okanogan ice lobe.
Field reappraisal continues downstream from Grand Coulee on Ephrata fan. There, some of the floods exiting lower Grand Coulee had bulked up with fine sediment from glacial Lake Columbia, upper coulee till, and a lower coulee lake that the fan itself impounded. Floods thus of debris-flow consistency carried outsize boulders previously thought transported by watery floods.
Below Ephrata fan, a backflooded reach of Columbia valley received Grand Coulee outflow of small, late Missoula floods. These late floods can—by varve counts in post-S-ash deposits of Sanpoil valley—be clocked now as a decade or less apart. Still farther downstream, Columbia River gorge choked the largest Missoula floods, passing peak discharge only one-third to one-half that released by the breached Lake Missoula ice dam.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2021.0062(07)","usgsCitation":"Waitt, R.B., Atwater, B., Lehnigk, K., Larsen, I., Bjornstad, B., Hanson, M., and O'Connor, J., 2021, Upper Grand Coulee: New views of a channeled scabland megafloods enigma, chap. of From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest, v. 62, p. 245-300, https://doi.org/10.1130/2021.0062(07).","productDescription":"56 p.","startPage":"245","endPage":"300","ipdsId":"IP-129810","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":481101,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2021.0062(07)","text":"Publisher Index Page"},{"id":480733,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Upper Grand Coulee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.50054736602212,\n 49.462558518080414\n ],\n [\n -125.44572643872874,\n 49.462558518080414\n ],\n [\n -125.44572643872874,\n 44.60810790414203\n ],\n [\n -117.50054736602212,\n 44.60810790414203\n ],\n [\n -117.50054736602212,\n 49.462558518080414\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Waitt, Richard B. 0000-0002-6392-5604 waitt@usgs.gov","orcid":"https://orcid.org/0000-0002-6392-5604","contributorId":2343,"corporation":false,"usgs":true,"family":"Waitt","given":"Richard","email":"waitt@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atwater, Brian F.","contributorId":349552,"corporation":false,"usgs":true,"family":"Atwater","given":"Brian F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":924413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lehnigk, Karin","contributorId":349556,"corporation":false,"usgs":false,"family":"Lehnigk","given":"Karin","affiliations":[{"id":83490,"text":"University of Massachusetts, Amherst, Mass.","active":true,"usgs":false}],"preferred":false,"id":924415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Isaac J.","contributorId":349557,"corporation":false,"usgs":false,"family":"Larsen","given":"Isaac J.","affiliations":[{"id":83490,"text":"University of Massachusetts, Amherst, Mass.","active":true,"usgs":false}],"preferred":false,"id":924416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bjornstad, Bruce N.","contributorId":349558,"corporation":false,"usgs":false,"family":"Bjornstad","given":"Bruce N.","affiliations":[{"id":83492,"text":"Ice Age Floodscapes, Richland, Wash.","active":true,"usgs":false}],"preferred":false,"id":924417,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hanson, Michelle A.","contributorId":349554,"corporation":false,"usgs":false,"family":"Hanson","given":"Michelle A.","affiliations":[{"id":83488,"text":"Saskatchewan Geological Survey, Regina, Sask.","active":true,"usgs":false}],"preferred":false,"id":924414,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":924418,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224546,"text":"70224546 - 2021 - The Biscuit Brook and Neversink Reservoir Watersheds: Long-term investigations of stream chemistry, soil chemistry, and aquatic ecology in the Catskill Mountains, New York, USA, 1983 to 2020","interactions":[],"lastModifiedDate":"2021-10-18T15:08:18.866454","indexId":"70224546","displayToPublicDate":"2021-09-24T08:50:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"The Biscuit Brook and Neversink Reservoir Watersheds: Long-term investigations of stream chemistry, soil chemistry, and aquatic ecology in the Catskill Mountains, New York, USA, 1983 to 2020","docAbstract":"This data note describes the Biscuit Brook and Neversink Reservoir watershed Long-Term Monitoring Data that includes: 1) stream discharge, (1983 – 2020 for Biscuit Brook and 1937 – 2020 for the Neversink Reservoir watershed), 2) stream water chemistry, 1983-2020, at 4 stations, 3) fish survey data from 16 locations in the watershed 1990-2019, 4) soil chemistry data from 2 headwater sub-watersheds, 1993-2012, and 5) periodic stream water chemistry sampling data from 364 locations throughout the watershed, 1983-2020. The Neversink Reservoir watershed in the Catskill Mountains of New York, USA drains an area of 172.5 km2. The watershed feeds one of 6 reservoirs in New York City's West of Hudson water supply, which accounts for about 90% of the city's water supply. Biscuit Brook is a 9.63 km2 tributary sub-watershed within the Neversink Reservoir watershed.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14394","usgsCitation":"Murdoch, P.S., Burns, D., McHale, M., Siemion, J., Baldigo, B., Lawrence, G.B., George, S.D., Antidormi, M.R., and Bonville, D.B., 2021, The Biscuit Brook and Neversink Reservoir Watersheds: Long-term investigations of stream chemistry, soil chemistry, and aquatic ecology in the Catskill Mountains, New York, USA, 1983 to 2020: Hydrological Processes, v. 35, e14394, 12 p., https://doi.org/10.1002/hyp.14394.","productDescription":"e14394, 12 p.","ipdsId":"IP-126065","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":450676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14394","text":"Publisher Index Page"},{"id":389807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Biscuit Brook and Neversink Reservoir Watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.62188720703125,\n 41.840920397579936\n ],\n [\n -74.60403442382812,\n 41.85319643776675\n ],\n [\n -74.53811645507812,\n 41.881831370505594\n ],\n [\n -74.44129943847656,\n 41.92629234083705\n ],\n [\n -74.28337097167969,\n 42.007978804701\n ],\n [\n -74.278564453125,\n 42.06509700139039\n ],\n [\n -74.30671691894531,\n 42.11095834849246\n ],\n [\n -74.3341827392578,\n 42.13133052651052\n ],\n [\n -74.4049072265625,\n 42.132858175814626\n ],\n [\n -74.44747924804688,\n 42.11707068963613\n ],\n [\n -74.48867797851562,\n 42.042153895364\n ],\n [\n -74.57725524902344,\n 41.984504674276074\n ],\n [\n -74.652099609375,\n 41.9528519300999\n ],\n [\n -74.73518371582031,\n 41.89869952106346\n ],\n [\n -74.74273681640625,\n 41.86291329896065\n ],\n [\n -74.70497131347656,\n 41.81636125072054\n ],\n [\n -74.64866638183594,\n 41.81175536180908\n ],\n [\n -74.62188720703125,\n 41.840920397579936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","noUsgsAuthors":false,"publicationDate":"2021-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Murdoch, Peter S. 0000-0001-9243-505X pmurdoch@usgs.gov","orcid":"https://orcid.org/0000-0001-9243-505X","contributorId":2453,"corporation":false,"usgs":true,"family":"Murdoch","given":"Peter","email":"pmurdoch@usgs.gov","middleInitial":"S.","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":824014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":824015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siemion, Jason 0000-0001-5635-6469 jsiemion@usgs.gov","orcid":"https://orcid.org/0000-0001-5635-6469","contributorId":127562,"corporation":false,"usgs":true,"family":"Siemion","given":"Jason","email":"jsiemion@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldigo, Barry P. 0000-0002-9862-9119","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":25174,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824020,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Antidormi, Michael R. 0000-0002-3967-1173 mantidormi@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-1173","contributorId":150722,"corporation":false,"usgs":true,"family":"Antidormi","given":"Michael","email":"mantidormi@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824021,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bonville, Donald B. 0000-0003-4480-9381","orcid":"https://orcid.org/0000-0003-4480-9381","contributorId":248849,"corporation":false,"usgs":true,"family":"Bonville","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824022,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70244091,"text":"70244091 - 2021 - Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach","interactions":[],"lastModifiedDate":"2023-06-01T14:04:48.814131","indexId":"70244091","displayToPublicDate":"2021-09-24T08:41:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach","docAbstract":"A continuous-variable Bayesian network (cBN) model is used to link watershed development and climate change to stream ecosystem indicators. A graphical model, reflecting our understanding of the connections between climate change, weather condition, loss of natural land cover, stream flow characteristics, and stream ecosystem indicators is used as the basis for selecting flow metrics for predicting macroinvertebrate-based indicators. Selected flow metrics were then linked to variables representing watershed development and climate change. We fit the model to data from two river basins in southeast US and the resulting model was used to simulate future stream ecological conditions using projected future climate and development scenarios. The three climate models predicted varying ecological condition trajectories, but similar worst-case ecological conditions. The established modeling approach couples mechanistic understanding with field data to develop predictions of management-relevant variables across a heterogeneous landscape. We discussed the transferability of the modeling approach.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2021.117685","usgsCitation":"Qian, S.S., Kennen, J., May, J., Freeman, M., and Cuffney, T.F., 2021, Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach: Water Research, v. 205, 117685, 11 p., https://doi.org/10.1016/j.watres.2021.117685.","productDescription":"117685, 11 p.","ipdsId":"IP-125255","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":450679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2021.117685","text":"Publisher Index Page"},{"id":417645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, South Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.52179800853753,\n 32.86310990611119\n ],\n [\n -78.95424437482033,\n 33.20732442214225\n ],\n [\n -78.83061042748197,\n 33.62402639579081\n ],\n [\n -78.03123021414571,\n 33.81848745598903\n ],\n [\n -77.49960057459164,\n 34.229007941502374\n ],\n [\n -77.20942075405912,\n 34.57053494448374\n ],\n [\n -78.04925882655441,\n 35.593623760054015\n ],\n [\n -79.61149509648914,\n 36.3847977489354\n ],\n [\n -80.69994996842892,\n 36.980415621762745\n ],\n [\n -81.2368093995407,\n 36.697683304342775\n ],\n [\n -81.66006417146134,\n 35.81807327161229\n ],\n [\n -80.92321025597303,\n 33.67553987083947\n ],\n [\n -80.06864524456462,\n 32.587876038945694\n ],\n [\n -79.52179800853753,\n 32.86310990611119\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"205","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qian, Song S. 0000-0002-2346-4903","orcid":"https://orcid.org/0000-0002-2346-4903","contributorId":306033,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[{"id":62440,"text":"Department of Environmental Sciences, University of Toledo, Toledo, OH 43606","active":true,"usgs":false}],"preferred":false,"id":874463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"May, Jason 0000-0002-5699-2112","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":224991,"corporation":false,"usgs":false,"family":"May","given":"Jason","affiliations":[{"id":41015,"text":"Deceased (ex-USGS)","active":true,"usgs":false}],"preferred":false,"id":874465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":874466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cuffney, Thomas F 0000-0003-1164-5560","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":306032,"corporation":false,"usgs":false,"family":"Cuffney","given":"Thomas","email":"","middleInitial":"F","affiliations":[],"preferred":false,"id":874467,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70224522,"text":"ofr20201138 - 2021 - Historical streamflow and stage data compilation for the Lower Columbia River, Pacific Northwest","interactions":[],"lastModifiedDate":"2021-09-27T12:07:04.69961","indexId":"ofr20201138","displayToPublicDate":"2021-09-24T07:39:36","publicationYear":"2021","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":"2020-1138","displayTitle":"Historical Streamflow and Stage Data Compilation for the Lower Columbia River, Pacific Northwest","title":"Historical streamflow and stage data compilation for the Lower Columbia River, Pacific Northwest","docAbstract":"The U.S. Geological Survey mined data from a variety of national and state agencies including USGS, Oregon Water Resources Department, National Oceanic and Atmospheric Administration, Washington Department of Ecology, Pacific Northwest National Laboratory, Portland State University, and U.S. Army Corps of Engineers. A comprehensive dataset of streamflow, stage, and tidal elevations for the Lower Columbia River basin was compiled. Data were compiled from gaging stations in Oregon and Washington along the Columbia River from Astoria to The Dalles and along the Willamette River from Salem to Portland. Tidal gages along the Washington, Oregon, and California coasts were also compiled. Seasonal maximum values were calculated for both streamflow and stage for the winter (November–March) and spring (April–July) flow seasons, as well as for the full water year when underlying data were available. The aggregated datasets are available at https://doi.org/10.5066/P9R6RT0Z.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201138","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers","usgsCitation":"Boudreau, C.L., Stewart, M.A., and Stonewall, A.J., 2021, Historical streamflow and stage data compilation for the Lower Columbia River, Pacific Northwest: U.S. Geological Survey Open-File Report 2020–1138, 50 p., https://doi.org/10.3133/ofr20201138.","productDescription":"Report: viii, 50 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-101122","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":389696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1138/coverthb.jpg"},{"id":389697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1138/ofr20201138.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1138"},{"id":389698,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R6RT0Z","text":"USGS data release","description":"USGS Data release","linkHelpText":"Historical streamflow and stage data for the lower Columbia River basin and the coasts of Washington, Oregon, and northern California"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Lower Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.63964843750001,\n 41.672911819602085\n ],\n [\n -120.80566406250001,\n 41.672911819602085\n ],\n [\n -120.80566406250001,\n 49.26780455063753\n ],\n [\n -125.63964843750001,\n 49.26780455063753\n ],\n [\n -125.63964843750001,\n 41.672911819602085\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
For species with variable phenology, it is often challenging to produce reliable estimates of population dynamics or changes in occupancy. The Arizona Toad (Anaxyrus microscaphus) is a southwestern USA endemic that has been petitioned for legal protection, but status assessments are limited by a lack of information on population trends. Also, timing and consistency of Arizona Toad breeding varies greatly, making it difficult to predict optimal survey times or effort required for detection. To help fill these information gaps, we conducted breeding season call surveys during 2013–2016 and 2019 at 86 historically occupied sites and 59 control sites across the species' range in New Mexico. We estimated variation in mean dates of arrival and departure from breeding sites, changes in occupancy, and site-level extinction since 1959 with recently developed multi-season staggered-entry models, which relax the within-season closure assumption common to most occupancy models. Optimal timing of surveys in our study areas was approximately 5–30 March. Averaged across years, estimated probability of occupancy was 0.58 (SE = 0.09) for historical sites and 0.19 (SE = 0.08) for control sites. Occupancy increased from 2013 through 2019. Notably, even though observer error was trivial, annual detection probabilities varied from 0.23 to 0.75 and declined during the study; this means naïve occupancy values would have been misleading, indicating apparent declines in toad occupancy. Occupancy was lowest during the first year of the study, possibly due to changes in stream flows and conditions in many waterbodies following extended drought and recent wildfires. Although within-season closure was violated by variable calling phenology, simple multi-season models provided nearly identical estimates as staggered-entry models. Surprisingly, extinction probability was unrelated to the number of years since the first or last record at historically occupied sites. Collectively, our results suggest a lack of large, recent declines in occupancy by Arizona Toads in New Mexico, but we still lack population information from most of the species' range.
Discoveries in the 1980s greatly expanded speleologists’ understanding of the role that hypogenic groundwater flow can play in developing caves at depth. Ascending groundwater charged with carbon dioxide and, especially, hydrogen sulfide can readily dissolve carbonate bedrock just below and above the water table. Sulfuric acid speleogenesis, in which anoxic, rising, sulfidic groundwater mixes with oxygenated cave atmosphere to form aggressive sulfuric acid (H2SO4) formed spectacular caves in Carlsbad Caverns National Park, USA. Cueva de Villa Luz in Mexico provides an aggressively active example of sulfuric acid speleogenesis processes, and the Frasassi Caves in Italy preserve the results of sulfuric acid speleogenesis in its upper levels while sulfidic groundwater currently enlarges cave passages in the lower levels.
Many caves in east-central Nevada and western Utah (USA) are products of hypogenic speleogenesis and formed before the current topography fully developed. Wet climate during the late Neogene and Pleistocene brought extensive meteoric infiltration into the caves, and calcite speleothems (e.g., stalactites, stalagmites, shields) coat the walls and floors of the caves, concealing evidence of the earlier hypogenic stage. However, by studying the speleogenetic features in well-established sulfuric acid speleogenesis caves, evidence of hypogenic, probably sulfidic, speleogenesis in many Great Basin caves can be teased out. Compelling evidence of hypogenic speleogenesis in these caves include folia, mammillaries, bubble trails, cupolas, and metatyuyamunite. Sulfuric acid speleogenesis signs include hollow coralloid stalagmites, trays, gypsum crust, pseudoscallops, rills, and acid pool notches. Lehman Caves in Great Basin National Park is particularly informative because a low-permeability capstone protected about half of the cave from significant meteoric infiltration, preserving early speleogenetic features.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Field Excursions from the 2021 GSA Section Meetings","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2020.0061(05)","usgsCitation":"Hose, L.D., DuChene, H.R., Jones, D., Baker, G.M., Havlena, Z., Sweetkind, D.S., and Powell, D., 2021, Hypogenic karst of the Great Basin, chap. of Field Excursions from the 2021 GSA Section Meetings, v. 61, p. 77-114, https://doi.org/10.1130/2020.0061(05).","productDescription":"38 p.","startPage":"77","endPage":"114","ipdsId":"IP-124815","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":450693,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1130/fld.s.16620391.v1","text":"External Repository"},{"id":392721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"New Mexico, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.172119140625,\n 31.952162238024975\n ],\n [\n -104.161376953125,\n 31.952162238024975\n ],\n [\n -104.161376953125,\n 32.59310597426537\n ],\n [\n -105.172119140625,\n 32.59310597426537\n ],\n [\n -105.172119140625,\n 31.952162238024975\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.79589843749999,\n 39.027718840211605\n ],\n [\n -114.169921875,\n 39.027718840211605\n ],\n [\n -114.169921875,\n 40.88029480552824\n ],\n [\n -115.79589843749999,\n 40.88029480552824\n ],\n [\n -115.79589843749999,\n 39.027718840211605\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.59277343749999,\n 17.97873309555617\n ],\n [\n -90.7470703125,\n 17.97873309555617\n ],\n [\n -90.7470703125,\n 18.979025953255267\n ],\n [\n -92.59277343749999,\n 18.979025953255267\n ],\n [\n -92.59277343749999,\n 17.97873309555617\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"61","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hose, Louise D.","contributorId":269963,"corporation":false,"usgs":false,"family":"Hose","given":"Louise","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":828185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DuChene, Harvey R.","contributorId":269964,"corporation":false,"usgs":false,"family":"DuChene","given":"Harvey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":828186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Daniel","contributorId":269965,"corporation":false,"usgs":false,"family":"Jones","given":"Daniel","affiliations":[],"preferred":false,"id":828187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, Gretchen M.","contributorId":54894,"corporation":false,"usgs":true,"family":"Baker","given":"Gretchen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":828188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Havlena, Zoe","contributorId":269966,"corporation":false,"usgs":false,"family":"Havlena","given":"Zoe","email":"","affiliations":[],"preferred":false,"id":828189,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sweetkind, Donald S. 0000-0003-0892-4796 dsweetkind@usgs.gov","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":139913,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald","email":"dsweetkind@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":828190,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Powell, Doug","contributorId":269967,"corporation":false,"usgs":false,"family":"Powell","given":"Doug","email":"","affiliations":[],"preferred":false,"id":828191,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70226736,"text":"70226736 - 2021 - Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a","interactions":[],"lastModifiedDate":"2021-12-08T12:36:34.644353","indexId":"70226736","displayToPublicDate":"2021-09-24T06:32:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9944,"text":"Remote Sensing of the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a","docAbstract":"Lakes and other surface fresh waterbodies provide drinking water, recreational and economic opportunities, food, and other critical support for humans, aquatic life, and ecosystem health. Lakes are also productive ecosystems that provide habitats and influence global cycles. Chlorophyll concentration provides a common metric of water quality, and is frequently used as a proxy for lake trophic state. Here, we document the generation and distribution of the complete MEdium Resolution Imaging Spectrometer (MERIS; Appendix A provides a complete list of abbreviations) radiometric time series for over 2300 satellite resolvable inland bodies of water across the contiguous United States (CONUS) and more than 5,000 in Alaska. This contribution greatly increases the ease of use of satellite remote sensing data for inland water quality monitoring, as well as highlights new horizons in inland water remote sensing algorithm development. We evaluate the performance of satellite remote sensing Cyanobacteria Index (CI)-based chlorophyll algorithms, the retrievals for which provide surrogate estimates of phytoplankton concentrations in cyanobacteria dominated lakes. Our analysis quantifies the algorithms' abilities to assess lake trophic state across the CONUS. As a case study, we apply a bootstrapping approach to derive a new CI-to-chlorophyll relationship, ChlBS, which performs relatively well with a multiplicative bias of 1.11 (11%) and mean absolute error of 1.60 (60%). While the primary contribution of this work is the distribution of the MERIS radiometric timeseries, we provide this case study as a roadmap for future stakeholders' algorithm development activities, as well as a tool to assess the strengths and weaknesses of applying a single algorithm across CONUS.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2021.112685","usgsCitation":"Seegers, B., Werdell, P., Vandermeulen, R., Salls, W., Stumpf, R., Schaeffer, B., Owens, T., Bailey, S., Scott, J., and Loftin, K.A., 2021, Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a: Remote Sensing of the Environment, v. 266, 112685, 14 p., https://doi.org/10.1016/j.rse.2021.112685.","productDescription":"112685, 14 p.","ipdsId":"IP-129074","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":450699,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2021.112685","text":"Publisher Index Page"},{"id":392623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.42675781249999,\n 43.229195113965005\n ],\n [\n -89.2529296875,\n 43.229195113965005\n ],\n [\n -89.2529296875,\n 49.15296965617042\n ],\n [\n -97.42675781249999,\n 49.15296965617042\n ],\n [\n -97.42675781249999,\n 43.229195113965005\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.078125,\n 53.74871079689897\n ],\n [\n -128.32031249999997,\n 55.677584411089526\n ],\n [\n -134.82421875,\n 60.75915950226991\n ],\n [\n -139.5703125,\n 61.438767493682825\n ],\n [\n -140.09765625,\n 69.71810669906763\n ],\n [\n -156.09375,\n 71.85622888185527\n ],\n [\n -166.2890625,\n 68.84766505841037\n ],\n [\n -167.6953125,\n 65.29346780107583\n ],\n [\n -166.2890625,\n 59.44507509904714\n ],\n [\n -161.89453125,\n 54.36775852406841\n ],\n [\n -153.80859375,\n 55.87531083569679\n ],\n [\n -145.01953124999997,\n 59.80063426102869\n ],\n [\n -134.47265625,\n 55.07836723201515\n ],\n [\n -132.36328125,\n 51.83577752045248\n ],\n [\n -131.1328125,\n 52.05249047600099\n ],\n [\n -130.078125,\n 53.74871079689897\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"266","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Seegers, Bridget","contributorId":269867,"corporation":false,"usgs":false,"family":"Seegers","given":"Bridget","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":828030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werdell, P. 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The Colorado River Salinity Control Act of 1974 (Public Law 93–320) authorized “the construction, operation, and maintenance of certain works in the Colorado River Basin to control the salinity of water delivered to users in the United States and Mexico.” Water-quality standards for salinity in the lower Colorado River Basin were adopted in 1975. To help meet these standards, the Bureau of Reclamation, Natural Resource Conservation Service, and States within the Colorado River Basin have implemented salinity control projects that focus on reducing salt loading associated with irrigated agriculture by improving water delivery systems and water management practices. The term salinity is synonymous with dissolved solids in this report.
The Bureau of Reclamation, in conjunction with the Colorado River Basin Salinity Control Forum, was interested in determining the contribution of dissolved solids from Blacks Fork above Smiths Fork to the Colorado River and initiated a study of Blacks Fork above Smiths Fork in 2018. In early 2018, the U.S. Geological Survey installed a streamgage at the most downstream location on the Blacks Fork, upstream from the convergence with Smiths Fork, to characterize the stream. The Blacks Fork above Smiths Fork, near Lyman, Wyoming, streamgage (U.S. Geological Survey identifier 09219200) was operated from April 4, 2018, through September 30, 2019, collecting continuous stream stage and specific-conductance data, from which continuous discharge, dissolved-solids concentrations, and dissolved-solids loads were calculated. Seven sites were selected on Blacks Fork and a tributary to describe a snapshot of the discharge and dissolved-solids characteristics. These sites were sampled during July, August, and September 2018 and June, July, August, and September 2019 report.
Discharge at the Blacks Fork above Smiths Fork, near Lyman, Wyo., streamgage (09219200) from April through September in 2018 was lower and less variable than during the same period in 2019. The mean daily (mean of the daily means) discharge during those 6 months in 2018 (15.1 cubic feet per second [ft3/s]) was about one-tenth of the discharge during the same period in 2019 (152 ft3/s). The cumulative monthly discharge during April through September in 2018 was 5,360 acre-feet, about one-tenth of the discharge during the same period in 2019 which was 54,700 acre-feet. Similar differences in discharge between the 2018 and 2019 periods also are noted at other Blacks Fork streamgages in the area.
Continuous specific conductance data and the statistical relation between specific conductance and dissolved-solids concentrations were used to calculate the daily mean dissolved-solids concentrations. Dissolved solids often have an inverse relation with discharge because higher discharges typically have a diluting effect that lowers the dissolved-solids concentrations. In general, when discharges at the Blacks Fork above Smiths Fork streamgage (09219200) are higher, dissolved-solids concentrations are generally lower. However, the high dissolved-solids concentrations that are measured during high discharges indicate that the system has natural variability and the dissolved-solids concentrations are determined by more factors than just discharge. The mean daily dissolved-solids concentration during April through September 2018 was 1,630 milligrams per liter and during the same period in 2019 was 1,100 milligrams per liter.
Dissolved-solids loads were calculated as the product of the discharge and dissolved-solids concentration. The daily mean dissolved-solids loads during 2018 were typically lower than during 2019. This result is primarily because the discharge was much lower in 2018 than in 2019. Therefore, although the daily mean dissolved-solids concentrations tended to be higher in 2018, the substantially higher discharges in 2019 had more of an effect on the dissolved-solids loads than the dissolved-solids concentrations.
The cumulative dissolved-solids load at the Blacks Fork above Smiths Fork, near Lyman, Wyo., streamgage (09219200) during the 18-month study was 81,200 tons, with a mean daily load of 149 tons per day. During the 6-month period from April through September 2018, the cumulative dissolved-solids load at the streamgage was estimated to be 8,740 tons and, during the same 6 months in 2019, the cumulative dissolved-solids load was estimated to be 60,900 tons. During the fall and winter between the two periods, the cumulative dissolved-solids load was 11,600 tons.
Discharge and dissolved-solids concentrations from samples collected during the synoptic sampling events were highly variable among most sites during most synoptic sampling events and also highly variable at most sites among different sampling events. The two sites upstream from the tributary input from Threemile Creek had lower dissolved-solids concentrations than sites including and downstream from the tributary. Sites including and downstream from the tributary had similar values and variability of dissolved-solids loads, with the exception of the farthest downstream site at the Blacks Fork above Smiths Fork, near Lyman, Wyo., streamgage (09219200) that tended to have larger dissolved-solids loads and higher variability among synoptic sampling events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215095","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Eddy-Miller, C.A., Wheeler, J.D., Law, R.M., and Moran, S.W., 2021, Discharge and dissolved-solids characteristics of Blacks Fork above Smiths Fork, Wyoming, April 2018 through September 2019: U.S. Geological Survey Scientific Investigations Report 2021–5095, 32 p., https://doi.org/10.3133/sir20215095.","productDescription":"vii, 32 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-125542","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":389699,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5095/sir20215095.xml","size":"220 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5095 xml"},{"id":389653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5095/sir20215095.pdf","text":"Report","size":"2.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5095"},{"id":389652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5095/coverthb3.jpg"}],"contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
521 Progress Circle, Suite 6
Cheyenne, WY 82007
Surface-water and groundwater resources in the Big Lost River Basin of south-central Idaho are extensively interconnected; this interchange affects and is affected by water-resource management for irrigated agriculture and other uses in the basin. Concerns from water users regarding declining groundwater levels, declining streamflows, and drought helped motivate an updated evaluation of water resources in the Big Lost River Basin. The hydrogeologic framework presented in this report provides a conceptual basis for understanding groundwater resources in the Big Lost River Basin and comprises three major parts: (1) conceptual description of four hydrogeologic units, (2) development of a three-dimensional hydrogeologic framework model representing the spatial distribution of the hydrogeologic units, and (3) a description of groundwater occurrence and movement. This hydrogeologic framework represents the first of three planned reports describing water resources in the Big Lost River Basin; subsequent reports are intended to present a groundwater budget for the basin and to describe the results of a series of events measuring gains to and losses from streamflow in the Big Lost River. This report was prepared by the U.S. Geological Survey in cooperation with the Idaho Department of Water Resources.
The Big Lost River Basin has four hydrogeologic units. First, the Quaternary unconsolidated sediments unit comprises the basin-fill alluvial aquifer and generally is used within 250 feet of the land surface. The Quaternary unconsolidated sediments unit is spatially heterogeneous, with locally confining conditions in some areas, and is the most heavily used hydrogeologic unit in the basin. Second, the Paleozoic sedimentary rocks unit, composed primarily of carbonates with some siliciclastic rocks, represents the major bedrock aquifer and contributes subsurface recharge at the margins of the alluvial aquifer. Third, the Tertiary volcanic rocks unit, composed primarily of andesite and dacite with lesser tuff, is locally important to water production, particularly in faulted and fractured zones. The Paleozoic sedimentary rocks hydrogeologic unit occurs at the valley margins and underlies tributaries throughout the basin, whereas the Tertiary volcanic rocks hydrogeologic unit primarily occurs in uplands in the western one-half of the basin. Fourth, the Quaternary basalt rocks unit consists of multiple basalt flows that are interbedded with the Quaternary unconsolidated sediments unit in the southern end of the Big Lost River Basin and contains at least three water-bearing zones. Insights gained from this updated hydrogeologic framework will help inform current water-resource management in the Big Lost River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215078A","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Zinsser, L.M., 2021, Hydrogeologic framework of the Big Lost River Basin, south-central Idaho, chap. A of Zinsser, L.M., ed., Characterization of water resources in the Big Lost River Basin, south-central Idaho: U.S. Geological Survey Scientific Investigations Report 2021–5078–A, 42 p., https://doi.org/10.3133/sir20215078A.","productDescription":"Report: viii, 42 p.; Appendix; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-125228","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":396956,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/sir20215078A.XML"},{"id":396955,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/images"},{"id":389624,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P911S9LF","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic framework of the Big Lost River Basin, south-central Idaho—Hydrogeologic framework model and well data"},{"id":389623,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/sir20215078A_app1.pdf","text":"Appendix 1","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5078A Appendix 1"},{"id":389622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/sir20215078A.pdf","text":"Report","size":"8.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5078A"},{"id":389621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/coverthb.jpg"},{"id":409279,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2021-5078A Version History"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Lost River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.169921875,\n 43.229195113965005\n ],\n [\n -112.2802734375,\n 43.229195113965005\n ],\n [\n -112.2802734375,\n 44.15068115978094\n ],\n [\n -114.169921875,\n 44.15068115978094\n ],\n [\n -114.169921875,\n 43.229195113965005\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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230 Collins Road
Boise, Idaho 83702-4520
Warming of lake surface waters has become a concern to limnologists and water managers because air temperatures, which directly affect near-surface water temperatures, are projected to increase in Wisconsin (WICCI 2011) as well as globally (IPCC 2018). This projected increase is in addition to the changes in air temperatures that have already occurred in recent decades(WICCI 2011, NOAA 2017).The deleterious effects of increased temperatures in lake surface waters have been extensively reviewed (e.g., Blenckner 2005, Keller 2007, Adrian et al. 2009, George 2010). Briefly, the exceedance of thermal preferences or tolerances of aquatic biota can cause altered food webs and loss of biodiversity in lakes (DeStasio et al. 1996, Chu et al. 2005, Graham and Harrod 2009, Woodward et al. 2010, Comte et al. 2013). Warmer surface water temperature scan result in stronger and longer thermal stratification in deep lakes(Robertson and Ragotzkie1990, Hondzo and Stefan 1993, Livingstone 2003, Butcher et al. 2015). This process in turn can cause the duration and extent of hypolimnetic anoxia to increase, thus reducing hypolimnetic refugia needed for cold-and cool-water fish (De Stasio et al. 1996, Magnuson et al. 1997, Jeppesen et al. 2012, Missaghi et al. 2017). Longer duration of hypolimnetic anoxia can enhance eutrophication because of more internal loading of phosphorus from bottom sediments (Blenckner et al. 2002, North et al. 2014). Of particular concern, warmer water temperatures favor the growth of toxic cyanobacteria in eutrophic systems (Paerl and Huisman 2008, Wagner and Adrian 2009, Kosten et al. 2012).Another effect of warmer lake surface temperatures is increased evaporation that can result in lower water levels(Spence et al. 2013, Gronewold and Stow 2014).
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Center","active":true,"usgs":true}],"preferred":true,"id":839931,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70224325,"text":"ofr20211087 - 2021 - Economic assessment of surface water in the Harney Basin, Oregon","interactions":[],"lastModifiedDate":"2021-09-23T16:56:33.117288","indexId":"ofr20211087","displayToPublicDate":"2021-09-23T09:15:54","publicationYear":"2021","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":"2021-1087","displayTitle":"Economic Assessment of Surface Water in the Harney Basin, Oregon","title":"Economic assessment of surface water in the Harney Basin, Oregon","docAbstract":"The Harney Basin is a closed river basin in southeastern Oregon. Surface water in the basin is used for a variety of social, economic, and ecological benefits. While some surface water uses compete with one another, others are complementary or jointly produce multiple beneficial outcomes. The objective of this study is to conduct an economic assessment of surface water in the basin as it relates to wet meadow pasture production and outdoor recreation. Given the complex interactions between surface water management on public and private land and the various goods and services that are derived from adequate water resources, an economic assessment of surface water management can be used to assist future decision making in the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211087","usgsCitation":"Bair, L.S., Flyr, M., and Huber, C., 2021, Economic assessment of surface water in the Harney Basin, Oregon: U.S. Geological Survey Open-File Report 2021-1087, 43 p., https://doi.org/10.3133/ofr20211087.","productDescription":"vii, 43 p.","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-122032","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":389611,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1087/covrthb.jpg"},{"id":389612,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1087/ofr20211087.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Harney Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.05859375,\n 42.24478535602799\n ],\n [\n -117.454833984375,\n 42.24478535602799\n ],\n [\n -117.454833984375,\n 44.38669150215206\n ],\n [\n -120.05859375,\n 44.38669150215206\n ],\n [\n -120.05859375,\n 42.24478535602799\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"This project evaluated habitat conditions for two species found in the imperiled pine rockland ecosystem—the Rim Rock Crowned Snake (Tantilla oolitica) and the Key Ring-Necked Snake (Diadophis punctatus acricus). The Rim Rock Crowned Snake historically occurred in eastern Miami-Dade County (hereafter, mainland) as well as throughout the Florida Keys, whereas the Key Ring-Necked Snake occurs only in lower Florida Keys (Enge et al. 2004; Mays and Enge 2016). Both species are very elusive, small (< 20 cm in length) and primarily fossorial. Pine rockland habitat is rapidly disappearing in South Florida, with < 3 percent of its original extent remaining. Saltwater intrusion from hurricanes and sea-level rise (SLR), and human development pose the greatest threats to the longevity of this ecosystem which, in turn, places species that are endemic to this unique habitat at risk of extinction.
The Rim Rock Crowned Snake and the Key Ringed-Necked Snake are being considered for listing by the U.S. Fish and Wildlife Service (USFWS). To aid the agency’s decision, it must be able to forecast species’ responses to potential future environmental conditions, as well as to different conservation and management actions. Yet, the information needed to complete these forecasts—such as population trends, life history traits, habitat use, and future land use and climate conditions—is often lacking for most rare species. This is especially problematic for assessments of species resiliency to changes in climate and land use.
When these types of data are lacking, information on habitat quality can be used to help determine how a species will respond to change. First, this project gathered current and historical records for both species from various sources such as museum specimens, inventories, and other personal account. Then, we identified potential future changes in habitat that could result from different management actions, such as habitat acquisition or restoration, and environmental conditions, such as changes in the frequency and intensity of tropical storms and rates of SLR. Researchers then explored the potential impacts of these habitat condition changes on the Rim Rock Crowned Snake and Key Ring-Necked Snake.
This information can be used by the USFWS to help make decisions about the need to protect these species under the Endangered Species Act and could inform the conservation, management, and recovery of other at-risk species found in the pine rockland ecosystem. This work supports the Secretary of Interior’s priority to create a conservation stewardship legacy by using science to identify best practices to manage land and water resource and adapt to changes in the environment.
","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Walls, S.C., 2021, Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida: Final Report, 18 p.","productDescription":"18 p.","ipdsId":"IP-129367","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":398537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398518,"type":{"id":15,"text":"Index Page"},"url":"https://secasc.ncsu.edu/science/pine-rocklands/"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.0458984375,\n 24.287026865376436\n ],\n [\n -79.9365234375,\n 24.287026865376436\n ],\n [\n -79.9365234375,\n 26.244156283890756\n ],\n [\n -82.0458984375,\n 26.244156283890756\n ],\n [\n -82.0458984375,\n 24.287026865376436\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":840331,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70227126,"text":"70227126 - 2021 - Evaluating streamwater dissolved organic carbon dynamics in context of variable flowpath contributions with a tracer-based mixing model","interactions":[],"lastModifiedDate":"2022-01-03T15:32:26.574984","indexId":"70227126","displayToPublicDate":"2021-09-23T08:09:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating streamwater dissolved organic carbon dynamics in context of variable flowpath contributions with a tracer-based mixing model","docAbstract":"This study focuses on characterizing the contributions of key terrestrial pathways that deliver dissolved organic carbon (DOC) to streams during hydrological events and on elucidating factors governing variation in water and DOC fluxes from these pathways. We made high-frequency measurements of discharge, specific conductance (SC), and fluorescent dissolved organic matter (FDOM) during 221 events recorded over 2 years within four Vermont (USA) watersheds that range in area from 0.4 to 139 km2. Using the SC measurements, together with statistical information on discharge, we separated the event hydrographs into contributions from three terrestrial pathways, which we refer to as riparian quickflow, subsurface quickflow, and slow-flow groundwater. The pathway discharges were used as input to a mixing model that closely approximated sub-hourly streamwater DOC concentrations as measured with the FDOM sensors. Subsurface quickflow, comprised of pre-event water, was the leading contributor to streamwater DOC fluxes, while riparian quickflow, comprised of event water, was the second-leading contributor to streamwater DOC fluxes, despite comprising the smallest proportion of streamflow yield among the three end-member pathways. Fixed-effects regression analysis revealed that the relationship between DOC fluxes from the end-member pathways and event magnitude was consistent across the four watersheds. This analysis also showed that DOC fluxes from the quickflow pathways increased significantly with temperature and varied inversely, but weakly, with catchment antecedent wetness. We believe that our approach, which leverages in-stream sensors that enable high-frequency measurements over extended periods, may be applicable for evaluating controls on DOC export from other watersheds within and beyond our study region.
Scale circuli yield valuable information about the life history, age, and growth of a fish. However, because circuli formation is influenced by somatic growth, the rate at which circuli are formed and the factors influencing these rates must be taken into account for the given life stage of the study species. Scales were collected from Atlantic salmon raised in marine net pens off of the coast of Maine in order to characterize the formation of scale circuli and the growth of scales during the ocean phase, and to relate circulus deposition and scale growth rate to water temperature. Fish were sampled 13 times over a period of 25 months. Neither circulus deposition rate nor growth rate were constant through time and the same trend held when circulus deposition and growth were related to thermal experience. Both rates decreased over the course of the study, presumably related to the fish reaching sexual maturity. The results of this study indicate that the pattern of circulus deposition and scale growth of Atlantic salmon vary greatly during the early marine phase, and this dynamic should be taken into account when assessing growth, especially over short time periods.
","language":"English","publisher":"Northwest Atlantic Fisheries Organization","doi":"10.2960/J.v52.m733","usgsCitation":"Peterson, E., Sheehan, T., and Zydlewski, J.D., 2021, Scale growth rates and scale circulus deposition rates of marine-stage Atlantic salmon Salmo salar raised under semi-natural conditions: Journal of Northwest Atlantic Fishery Science, v. 52, p. 19-27, https://doi.org/10.2960/J.v52.m733.","productDescription":"9 p.","startPage":"19","endPage":"27","ipdsId":"IP-110206","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2960/j.v52.m733","text":"Publisher Index Page"},{"id":481464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Newfoundland","otherGeospatial":"Placentia Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -53.5,\n 47.5\n ],\n [\n -54.5,\n 47.5\n ],\n [\n -54.5,\n 46.667\n ],\n [\n -53.5,\n 46.667\n ],\n [\n -53.5,\n 47.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","noUsgsAuthors":false,"publicationDate":"2021-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Erin","contributorId":287522,"corporation":false,"usgs":false,"family":"Peterson","given":"Erin","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":925429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, Timothy F.","contributorId":272581,"corporation":false,"usgs":false,"family":"Sheehan","given":"Timothy F.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":925430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":925428,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224584,"text":"70224584 - 2021 - Migration stopover ecology of Cinnamon Teal in western North America","interactions":[],"lastModifiedDate":"2023-03-27T16:48:28.401034","indexId":"70224584","displayToPublicDate":"2021-09-21T08:17:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Migration stopover ecology of Cinnamon Teal in western North America","docAbstract":"Identifying migration routes and fall stopover sites of Cinnamon Teal (Spatula cyanoptera septentrionalium) can provide a spatial guide to management and conservation efforts, and address vulnerabilities in wetland networks that support migratory waterbirds. Using high spatiotemporal resolution GPS-GSM transmitters, we analyzed 61 fall migration tracks across western North America during our three-year study (2017–2019). We marked Cinnamon Teal primarily during spring/summer in important breeding and molting regions across seven states (California, Oregon, Washington, Idaho, Utah, Colorado, and Nevada). We assessed fall migration routes and timing, detected 186 fall stopover sites, and identified specific North American ecoregions where sites were located. We classified underlying land cover for each stopover site and measured habitat selection for 12 land cover types within each ecoregion. Cinnamon Teal selected a variety of flooded habitats including natural, riparian, tidal, and managed wetlands; wet agriculture (including irrigation ditches, flooded fields, and stock ponds); wastewater sites; and golf and urban ponds. Wet agriculture was the most used habitat type (29.8% of stopover locations), and over 72% of stopover locations were on private land. Relatively scarce habitats such as wastewater ponds, tidal marsh, and golf and urban ponds were highly selected in specific ecoregions. In contrast, dry non-habitat across all ecoregions, and dry agriculture in the Cold Deserts and Mediterranean California ecoregions, was consistently avoided. Resources used by Cinnamon Teal often reflected wetland availability across the west and emphasize their adaptability to dynamic resource conditions in arid landscapes. Our results provide much needed information on spatial and temporal resource use by Cinnamon Teal during migration and indicate important wetland habitats for migrating waterfowl in the western United States.
Storm-driven nutrient loading from tributaries can fuel eutrophication in nearshore and open water areas of lentic ecosystems. However, nutrient processing in river-to-lake transitional zones can substantially alter the amount and composition of nutrients transported to lakes from upstream surface waters. We measured the removal of nutrients and dissolved organic carbon (DOC) from the water column in the Fox rivermouth (Green Bay, Lake Michigan) to evaluate the response of rivermouth plankton to episodic nutrient enrichment. Light and dark water column incubations (8–12 hr) were conducted on four occasions from April through September to measure changes in dissolved nitrogen (N), phosphorus (P), and DOC concentrations in three locations along the Fox rivermouth. Two incubation experiments were conducted on consecutive days, (a) under ambient nutrient concentrations, and (b) under experimentally enriched N and P concentrations. Spatial and temporal variation was observed in nutrient uptake rates, but light incubations consistently had higher nutrient uptake rates than dark incubations. Nutrient enrichment increased total dissolved P and total dissolved N uptake and DOC release in light incubations, but only increased total dissolved P uptake in dark incubations. Moreover, nutrient uptake ratios (N:P) decreased from ambient to nutrient enriched conditions and indicated preferential P uptake by phytoplankton communities in light conditions. Our study substantiates that rivermouths can process nutrients bound for downstream ecosystems and demonstrates the potential of plankton communities to dynamically increase net uptake rates in response to episodic nutrient enrichment.
RRestoring degraded rivers requires initial assessment of the fluvial landscape to identify stressors and riverine features that can be enhanced. We associated local-scale river habitat data collected using standardized national monitoring tools with modeled regional water temperature and flow data on mid-sized northwest U.S. rivers (30–60 m wide). We grouped these rivers according to quartiles of their modeled mean August water temperature and examined their physical habitat structure and flow. We then used principal components analysis to summarize the variation in several dimensions of physical habitat. We also compared local conditions in the Priest River, a river targeted for restoration of native salmonid habitat in northern Idaho, with those in other rivers of the region to infer potential drivers controlling water temperature. The warmest rivers had physical structure and fluvial characteristics typical of thermally degraded rivers, whereas the coldest rivers had higher mean summer flows and greater channel planform complexity. The Priest River sites had approximately twice as many deep residual pools (>50, >75, and >100 cm) and incision that averaged approximately twice that in the coldest rivers. Percentage fines and natural cover in the Priest were also more typical of the higher-temperature river groups. We found generally low instream cover and low levels of large wood both across the region and within the Priest River. Our approach enabled us to consider the local habitat conditions of a river in the context of other similarly sized rivers in the surrounding region. Understanding this context is important for identifying potential influences on river water temperature within the focal basin and for defining attainable goals for management and restoration of thermal and habitat conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.108213","usgsCitation":"Mejia, F.H., Connor, J.M., Kaufmann, P.R., Torgersen, C.E., Berntsen, E.K., and Andersen, T., 2021, Integrating regional and local monitoring data and assessment tools to evaluate habitat conditions and inform river restoration: Ecological Indicators, no. 131, 108213, 14 p., https://doi.org/10.1016/j.ecolind.2021.108213.","productDescription":"108213, 14 p.","ipdsId":"IP-119748","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":450752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.108213","text":"Publisher Index Page"},{"id":390391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Washington","otherGeospatial":"Priest River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.158203125,\n 48.191725575618726\n ],\n [\n -116.861572265625,\n 48.191725575618726\n ],\n [\n -116.861572265625,\n 48.49840764096433\n ],\n [\n -117.158203125,\n 48.49840764096433\n ],\n [\n -117.158203125,\n 48.191725575618726\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"131","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mejia, Francine H. 0000-0003-4447-231X","orcid":"https://orcid.org/0000-0003-4447-231X","contributorId":214345,"corporation":false,"usgs":true,"family":"Mejia","given":"Francine","email":"","middleInitial":"H.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":824849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connor, Jason M","contributorId":267258,"corporation":false,"usgs":false,"family":"Connor","given":"Jason","email":"","middleInitial":"M","affiliations":[{"id":40867,"text":"Kalispel Tribe Natural Resources Department","active":true,"usgs":false}],"preferred":false,"id":824850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaufmann, Phil R","contributorId":267259,"corporation":false,"usgs":false,"family":"Kaufmann","given":"Phil","email":"","middleInitial":"R","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":824851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":824852,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berntsen, Eric K","contributorId":214885,"corporation":false,"usgs":false,"family":"Berntsen","given":"Eric","email":"","middleInitial":"K","affiliations":[{"id":39131,"text":"Kalispel Tribe of Indians","active":true,"usgs":false}],"preferred":false,"id":824853,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andersen, Todd","contributorId":243418,"corporation":false,"usgs":false,"family":"Andersen","given":"Todd","email":"","affiliations":[{"id":40867,"text":"Kalispel Tribe Natural Resources Department","active":true,"usgs":false}],"preferred":false,"id":824854,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70224266,"text":"sir20215062 - 2021 - Development of regression equations for the estimation of the magnitude and frequency of floods at rural, unregulated gaged and ungaged streams in Puerto Rico through water year 2017","interactions":[],"lastModifiedDate":"2021-09-21T11:32:14.387182","indexId":"sir20215062","displayToPublicDate":"2021-09-20T09:49:44","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5062","displayTitle":"Development of Regression Equations for the Estimation of the Magnitude and Frequency of Floods at Rural, Unregulated Gaged and Ungaged Streams in Puerto Rico Through Water Year 2017","title":"Development of regression equations for the estimation of the magnitude and frequency of floods at rural, unregulated gaged and ungaged streams in Puerto Rico through water year 2017","docAbstract":"The methods of computation and estimates of the magnitude of flood flows were updated for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance levels for 91 streamgages on the main island of Puerto Rico by using annual peak-flow data through 2017. Since the previous flood frequency study in 1994, the U.S. Geological Survey has collected additional peak flows at additional streamgages, and Puerto Rico has experienced numerous flood events. This updated study was performed using longer annual peak-flow datasets from more stations to provide more representative equations to predict flood flows. Screening criteria for these streamgages included 10 or more years of annual peak-flow data, unregulated flow, and less than 10 percent impervious drainage area.
The magnitude and frequency of floods at selected streamgages in Puerto Rico were estimated using updated methods outlined in Bulletin 17C. The new procedures include a regional skew analysis that incorporates Bayesian regression techniques, the Expected Moments Algorithm to better represent missing record and estimate parameters of the log-Pearson Type III distribution, and the Multiple Grubbs-Beck test for low outlier detection.
Regional regression equations were developed to estimate peak-flow statistics at ungaged locations by using selected basin and climatic characteristics as explanatory variables. These variables were determined from digital spatial datasets and geographic information systems by using the most recent data available. Ordinary least-squares regression techniques were used to filter the basin characteristics and determine two separate regions, region 1 (west) and region 2 (east), based on residuals. A generalized least-squares procedure was used to account for cross-correlation of sites and develop the final set of equations that have drainage area as the only explanatory variable. The average standard errors of prediction ranged from 18.7 to 46.7 percent in region 1 and 33.4 to 57.6 percent in region 2 for all annual exceedance probabilities (AEPs) examined. The updated statistics showed a greater accuracy of prediction when compared to those from the previous study using drainage area as the only explanatory variable for all AEPs examined in region 1 and the 0.01 and 0.002 AEP flows for region 2. When compared to equations developed in the previous study that have drainage area, mean annual rainfall, and (or) depth-to-rock as explanatory variables, the updated statistics show a greater accuracy of prediction in region 1 at AEP flows of 0.02 and lower (that is, higher flows). Those developed for region 2 do not show a greater accuracy of prediction for any AEP flows when compared to the equations having multiple explanatory variables in the previous study.
The calculated regression equations, basin characteristics, and at-site statistics will be incorporated into the U.S. Geological Survey web application, StreamStats (https://streamstats.usgs.gov/ss/). This application allows users to select a location on a stream, whether gaged or ungaged, to obtain estimates of basin characteristics and flow statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215062","usgsCitation":"Ryan, P.J., Gotvald, A.J., Hazelbaker, C.L., Veilleux, A.G., and Wagner, D.M., 2021, Development of regression equations for the estimation of the magnitude and frequency of floods at rural, unregulated gaged and ungaged streams in Puerto Rico through water year 2017: U.S. Geological Survey Scientific Investigations Report 2021–5062, 37 p., https://doi.org/10.3133/sir20215062.","productDescription":"Report: v, 37 p.; Appendix Tables: 3; Data Release","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-123614","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":389343,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91XT14B","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data files for the development of regression equations for estimation of the magnitude and frequency of floods at rural, unregulated gaged and ungaged streams in Puerto Rico through water year 2017"},{"id":389335,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5062/coverthb.jpg"},{"id":389336,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062.pdf","text":"Report","size":"4.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5062"},{"id":389337,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_2.1.csv","text":"Appendix Table 2.1 (.csv format)","size":"5.89 kB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"— Streamgages operated by the U.S. Geological Survey (USGS) in Puerto Rico that were used in the regional skew analysis"},{"id":389340,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_1.xlsx","text":"Appendix 1 (.xlsx format)","size":"30.9 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"— Streamgages considered for development of regional regression equations in Puerto Rico and details of at-site statistic inputs"},{"id":389338,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_2.1.xlsx","text":"Appendix Table 2.1 (.xlsx format)","size":"19.6 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"— Streamgages operated by the U.S. Geological Survey (USGS) in Puerto Rico that were used in the regional skew analysis"},{"id":389339,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_1.csv","text":"Appendix 1 (.csv format)","size":"20.7 kB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"— Streamgages considered for development of regional regression equations in Puerto Rico and details of at-site statistic inputs"},{"id":389341,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_3.csv","text":"Appendix 3 (.csv format)","size":"80.4 kB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"— At-site, regression equation, and weighted magnitude, variance, and prediction intervals of annual exceedance probability floods for select unregulated streamgages in Puerto Rico"},{"id":389342,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_3.xlsx","text":"Appendix 3 (.xlsx format)","size":"134 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"— At-site, regression equation, and weighted magnitude, variance, and prediction intervals of annual exceedance probability floods for select unregulated streamgages in Puerto Rico"}],"country":"United States","otherGeospatial":"Puerto 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U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Evaluating resource use patterns for imperiled species is critical for understanding what supports their populations. Here we established stable isotope (