Resident mussels are effective indicators of ecosystem health and have been utilized in national assessment and monitoring studies for over two decades. Mussels were chosen because contaminant concentrations in their tissues respond to changes in ambient environmental levels, accumulation occurs with little metabolic transformation and a substantial amount of historic data were available. Mussels were collected from 10 previously studied locations approximately a year after Hurricane Sandy. Regionally, concentrations of polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs) decreased significantly, while concentrations of organochlorine pesticides (OCPs) remained unchanged, and polybrominated diphenyl ethers (PBDEs) increased compared to historic concentrations. Although concentrations of PCBs, OCPs and PAHs were at or near record low concentrations, long-term trends did not change after Hurricane Sandy. To effectively measure storm-induced impacts it is necessary to understand the factors influencing changes in mussel body burdens and have a long-term monitoring network and an ability to mobilize post event.
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We used fiber-optic distributed temperature sensing (FO-DTS), seepage meters, and vertical temperature profiling to locate, quantify, and monitor areas of focused groundwater discharge in a geomorphically simple sand-bed stream. This combined approach allowed us to rapidly focus efforts at locations where prodigious amounts of groundwater discharged to the Quashnet River on Cape Cod, Massachusetts, northeastern USA. FO-DTS detected numerous anomalously cold reaches one to several m long that persisted over two summers. Seepage meters positioned upstream, within, and downstream of 7 anomalously cold reaches indicated that rapid groundwater discharge occurred precisely where the bed was cold; median upward seepage was nearly 5 times faster than seepage measured in streambed areas not identified as cold. Vertical temperature profilers deployed next to 8 seepage meters provided diurnal-signal-based seepage estimates that compared remarkably well with seepage-meter values. Regression slope and R2 values both were near 1 for seepage ranging from 0.05 to 3.0 m d−1. Temperature-based seepage model accuracy was improved with thermal diffusivity determined locally from diurnal signals. Similar calculations provided values for streambed sediment scour and deposition at subdaily resolution. Seepage was strongly heterogeneous even along a sand-bed river that flows over a relatively uniform sand and fine-gravel aquifer. FO-DTS was an efficient method for detecting areas of rapid groundwater discharge, even in a strongly gaining river, that can then be quantified over time with inexpensive streambed thermal methods.
","language":"English","publisher":"AGU","doi":"10.1002/2016WR018808","usgsCitation":"Rosenberry, D.O., Briggs, M.A., Delin, G.N., and Hare, D.K., 2016, Combined use of thermal methods and seepage meters to efficiently locate, quantify, and monitor focused groundwater discharge to a sand-bed stream: Water Resources Research, v. 52, no. 6, p. 4486-4503, https://doi.org/10.1002/2016WR018808.","productDescription":"18 p.","startPage":"4486","endPage":"4503","ipdsId":"IP-074377","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470931,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr018808","text":"Publisher Index Page"},{"id":346111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.5154037475586,\n 41.58810068130451\n ],\n [\n -70.499267578125,\n 41.58810068130451\n ],\n [\n -70.499267578125,\n 41.6154423246811\n ],\n [\n -70.5154037475586,\n 41.6154423246811\n ],\n [\n -70.5154037475586,\n 41.58810068130451\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"6","noUsgsAuthors":false,"publicationDate":"2016-06-12","publicationStatus":"PW","scienceBaseUri":"59cb6732e4b017cf3141c697","contributors":{"authors":[{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":711255,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711256,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delin, Geoffrey N. 0000-0001-7991-6158 delin@usgs.gov","orcid":"https://orcid.org/0000-0001-7991-6158","contributorId":2610,"corporation":false,"usgs":true,"family":"Delin","given":"Geoffrey","email":"delin@usgs.gov","middleInitial":"N.","affiliations":[{"id":5063,"text":"Central Water Science Field Team","active":true,"usgs":true}],"preferred":true,"id":711257,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hare, Danielle K.","contributorId":76222,"corporation":false,"usgs":true,"family":"Hare","given":"Danielle","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":711258,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171361,"text":"70171361 - 2016 - Cyanotoxins in inland lakes of the United States: Occurrence and potential recreational health risks in the EPA National Lakes Assessment 2007","interactions":[],"lastModifiedDate":"2018-08-07T12:33:30","indexId":"70171361","displayToPublicDate":"2016-05-26T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Cyanotoxins in inland lakes of the United States: Occurrence and potential recreational health risks in the EPA National Lakes Assessment 2007","docAbstract":"A large nation-wide survey of cyanotoxins (1161 lakes) in the United States (U.S.) was conducted during the EPA National Lakes Assessment 2007. Cyanotoxin data were compared with cyanobacteria abundance- and chlorophyll-based World Health Organization (WHO) thresholds and mouse toxicity data to evaluate potential recreational risks. Cylindrospermopsins, microcystins, and saxitoxins were detected (ELISA) in 4.0, 32, and 7.7% of samples with mean concentrations of 0.56, 3.0, and 0.061 mg/L, respectively (detections only). Co-occurrence of the three cyanotoxin classes was rare (0.32%) when at least one toxin was detected. Cyanobacteria were present and dominant in 98 and 76% of samples, respectively. Potential anatoxin-, cylindrospermopsin-, microcystin-, and saxitoxin-producing cyanobacteria occurred in 81, 67, 95, and 79% of samples, respectively. Anatoxin-a and nodularin-R were detected (LC/MS/MS) in 15 and 3.7% samples (n = 27). The WHO moderate and high risk thresholds for microcystins, cyanobacteria abundance, and total chlorophyll were exceeded in 1.1, 27, and 44% of samples, respectively. Complete agreement by all three WHO microcystin metrics occurred in 27% of samples. This suggests that WHO microcystin metrics based on total chlorophyll and cyanobacterial abundance can overestimate microcystin risk when compared to WHO microcystin thresholds. The lack of parity among the WHO thresholds was expected since chlorophyll is common amongst all phytoplankton and not all cyanobacteria produce microcystins.
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Portland, Oregon","interactions":[],"lastModifiedDate":"2016-05-25T16:01:15","indexId":"ofr20161079","displayToPublicDate":"2016-05-25T13:00:00","publicationYear":"2016","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":"2016-1079","title":"Evaluation of flood inundation in Crystal Springs Creek, Portland, Oregon","docAbstract":"Efforts to improve fish passage have resulted in the replacement of six culverts in Crystal Springs Creek in Portland, Oregon. Two more culverts are scheduled to be replaced at Glenwood Street and Bybee Boulevard (Glenwood/Bybee project) in 2016. Recently acquired data have allowed for a more comprehensive understanding of the hydrology of the creek and the topography of the watershed. To evaluate the impact of the culvert replacements and recent hydrologic data, a Hydrologic Engineering Center-River Analysis System hydraulic model was developed to estimate water-surface elevations during high-flow events. Longitudinal surface-water profiles were modeled to evaluate current conditions and future conditions using the design plans for the culverts to be installed in 2016. Additional profiles were created to compare with the results from the most recent flood model approved by the Federal Emergency Management Agency for Crystal Springs Creek and to evaluate model sensitivity.
Model simulation results show that water-surface elevations during high-flow events will be lower than estimates from previous models, primarily due to lower estimates of streamflow associated with the 0.01 and 0.002 annual exceedance probability (AEP) events. Additionally, recent culvert replacements have resulted in less ponding behind crossings. Similarly, model simulation results show that the proposed replacement culverts at Glenwood Street and Bybee Boulevard will result in lower water-surface elevations during high-flow events upstream of the proposed project. Wider culverts will allow more water to pass through crossings, resulting in slightly higher water-surface elevations downstream of the project during high-flows than water-surface elevations that would occur under current conditions. For the 0.01 AEP event, the water-surface elevations downstream of the Glenwood/Bybee project will be an average of 0.05 ft and a maximum of 0.07 ft higher than current conditions. Similarly, for the 0.002 AEP event, the water-surface elevations will be an average of 0.04 ft and a maximum of 0.19 ft higher than current conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161079","collaboration":"Prepared in cooperation with the City of Portland Bureau of Environmental Services","usgsCitation":"Stonewall, Adam, and Hess, Glen, 2016, Evaluation of flood inundation in Crystal Springs Creek, Portland, Oregon: U.S. Geological Survey Open-File Report 2016-1079, 33 p., https://dx.doi.org/10.3133/ofr20161079.","productDescription":"Report: iv, 33 p.; Plate: 24.00 x 36.00 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052885","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":321611,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1079/ofr20161079.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1079 Report PDF"},{"id":321612,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2016/1079/ofr20161079_plate1.pdf","text":"Plate 1","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1079 Plate 1 PDF"},{"id":321610,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1079/coverthb.jpg"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Crystal Springs Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62,\n 45.45\n ],\n [\n -122.62,\n 45.5\n ],\n [\n -122.65,\n 45.5\n ],\n [\n -122.65,\n 45.45\n ],\n [\n -122.62,\n 45.45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
Monomethyl mercury (MMHg) and total mercury (THg) concentrations and Hg stable isotope ratios (δ202Hg and Δ199Hg) were measured in sediment and aquatic organisms from Cache Creek (California Coast Range) and Yolo Bypass (Sacramento Valley). Cache Creek sediment had a large range in THg (87 to 3870 ng/g) and δ202Hg (−1.69 to −0.20‰) reflecting the heterogeneity of Hg mining sources in sediment. The δ202Hg of Yolo Bypass wetland sediment suggests a mixture of high and low THg sediment sources. Relationships between %MMHg (the percent ratio of MMHg to THg) and Hg isotope values (δ202Hg and Δ199Hg) in fish and macroinvertebrates were used to identify and estimate the isotopic composition of MMHg. Deviation from linear relationships was found between %MMHg and Hg isotope values, which is indicative of the bioaccumulation of isotopically distinct pools of MMHg. The isotopic composition of pre-photodegraded MMHg (i.e., subtracting fractionation from photochemical reactions) was estimated and contrasting relationships were observed between the estimated δ202Hg of pre-photodegraded MMHg and sediment IHg. Cache Creek had mass dependent fractionation (MDF; δ202Hg) of at least −0.4‰ whereas Yolo Bypass had MDF of +0.2 to +0.5‰. This result supports the hypothesis that Hg isotope fractionation between IHg and MMHg observed in rivers (−MDF) is unique compared to +MDF observed in non-flowing water environments such as wetlands, lakes, and the coastal ocean.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.04.139","usgsCitation":"Donovan, P.M., Blum, J.D., Singer, M.B., Marvin-DiPasquale, M.C., and Tsui, M.T., 2016, Methylmercury degradation and exposure pathways in streams and wetlands impacted by historical mining: Science of the Total Environment, v. 568, p. 1192-1203, https://doi.org/10.1016/j.scitotenv.2016.04.139.","productDescription":"12 p.","startPage":"1192","endPage":"1203","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072121","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470966,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.04.139","text":"Publisher Index Page"},{"id":328235,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cache Creek, Yolo Bypass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.64474487304686,\n 38.464611135935776\n ],\n [\n -121.64474487304686,\n 38.572327030541246\n ],\n [\n -121.57779693603517,\n 38.572327030541246\n ],\n [\n -121.57779693603517,\n 38.464611135935776\n ],\n [\n -121.64474487304686,\n 38.464611135935776\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.53292083740234,\n 38.927365763942475\n ],\n [\n -122.53292083740234,\n 39.00771295997199\n ],\n [\n -122.39559173583984,\n 39.00771295997199\n ],\n [\n -122.39559173583984,\n 38.927365763942475\n ],\n [\n -122.53292083740234,\n 38.927365763942475\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"568","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57cd45ace4b0f2f0cec4cb51","contributors":{"authors":[{"text":"Donovan, Patrick M.","contributorId":168368,"corporation":false,"usgs":false,"family":"Donovan","given":"Patrick","email":"","middleInitial":"M.","affiliations":[{"id":25267,"text":"Univ. of Michigan","active":true,"usgs":false}],"preferred":false,"id":647988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blum, Joel D.","contributorId":83657,"corporation":false,"usgs":true,"family":"Blum","given":"Joel","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":647989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singer, Michael B.","contributorId":168369,"corporation":false,"usgs":false,"family":"Singer","given":"Michael","email":"","middleInitial":"B.","affiliations":[{"id":25268,"text":"University of St Andrews, UK","active":true,"usgs":false}],"preferred":false,"id":647990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":647987,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tsui, Martin T.K.","contributorId":168370,"corporation":false,"usgs":false,"family":"Tsui","given":"Martin","email":"","middleInitial":"T.K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":647991,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170583,"text":"ofr20161065 - 2016 - Development of a decision support tool for water and resource management using biotic, abiotic, and hydrological assessments of Topock Marsh, Arizona","interactions":[],"lastModifiedDate":"2016-05-24T08:51:11","indexId":"ofr20161065","displayToPublicDate":"2016-05-23T16:30:00","publicationYear":"2016","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":"2016-1065","title":"Development of a decision support tool for water and resource management using biotic, abiotic, and hydrological assessments of Topock Marsh, Arizona","docAbstract":"Topock Marsh is a large wetland adjacent to the Colorado River and the main feature of Havasu National Wildlife Refuge (Havasu NWR) in southern Arizona. In 2010, the U.S. Fish and Wildlife Service (FWS) and Bureau of Reclamation began a project to improve water management capabilities at Topock Marsh and protect habitats and species. Initial construction required a drawdown, which caused below-average inflows and water depths in 2010–11. U.S. Geological Survey Fort Collins Science Center (FORT) scientists collected an assemblage of biotic, abiotic, and hydrologic data from Topock Marsh during the drawdown and immediately after, thus obtaining valuable information needed by FWS.
Building upon that work, FORT developed a decision support system (DSS) to better understand ecosystem health and function of Topock Marsh under various hydrologic conditions. The DSS was developed using a spatially explicit geographic information system package of historical data, habitat indices, and analytical tools to synthesize outputs for hydrologic time periods. Deliverables include high-resolution orthorectified imagery of Topock Marsh; a DSS tool that can be used by Havasu NWR to compare habitat availability associated with three hydrologic scenarios (dry, average, wet years); and this final report which details study results. This project, therefore, has addressed critical FWS management questions by integrating ecologic and hydrologic information into a DSS framework. This DSS will assist refuge management to make better informed decisions about refuge operations and better understand the ecological results of those decisions by providing tools to identify the effects of water operations on species-specific habitat and ecological processes. While this approach was developed to help FWS use the best available science to determine more effective water management strategies at Havasu NWR, technologies used in this study could be applied elsewhere within the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161065","collaboration":"In cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Holmquist-Johnson, Chris; Hanson, Leanne; Daniels, Joan; Talbert, Colin; and Haegele, Jeanette, 2016, Development of a decision support tool for water and resource management using biotic, abiotic, and hydrological assessments of Topock Marsh, Arizona: U.S. Geological Survey Open-File Report 2016–1065, 121 p., https://dx.doi.org/10.3133/ofr20161065.","productDescription":"viii, 121 p.","numberOfPages":"130","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070577","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":321529,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1065/ofr20161065.pdf","text":"Report","size":"55.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1065"},{"id":321528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1065/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Topock Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.57572937011719,\n 34.75233231513255\n ],\n [\n -114.57572937011719,\n 34.85015678001124\n ],\n [\n -114.46826934814453,\n 34.85015678001124\n ],\n [\n -114.46826934814453,\n 34.75233231513255\n ],\n [\n -114.57572937011719,\n 34.75233231513255\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Box 25046, MS-939
Fort Collins, CO 80526-8118
Biocrusts exert a strong influence on hydrological processes in drylands by modifying numerous soil properties that affect water retention and movement in soils. Yet, their role in these processes is not clearly understood due to the large number of factors that act simultaneously and can mask the biocrust effect. The influence of biocrusts on soil hydrology depends on biocrust intrinsic characteristics such as cover, composition, and external morphology, which differ greatly among climate regimes, but also on external factors as soil type, topography and vegetation distribution patterns, as well as interactions among these factors. This chapter reviews the most recent literature published on the role of biocrusts in infiltration and runoff, soil moisture, evaporation and non-rainfall water inputs (fog, dew, water absorption), in an attempt to elucidate the key factors that explain how biocrusts affect land hydrology. In addition to the crust type and site characteristics, recent studies point to the crucial importance of the type of rainfall and the spatial scale at which biocrust effects are analyzed to understand their role in hydrological processes. Future studies need to consider the temporal and spatial scale investigated to obtain more accurate generalizations on the role of biocrusts in land hydrology.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological studies","language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-30214-0_17","usgsCitation":"Chamizo, S., Belnap, J., Elridge, D.J., and Issa, O., 2016, Biological soil crusts: An organizing principle in dryland ecosystems (aka: the role of biocrusts in arid land hydrology), chap. of Ecological studies, p. 321-346, https://doi.org/10.1007/978-3-319-30214-0_17.","productDescription":"26 p.","startPage":"321","endPage":"346","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070333","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"57cfe8b0e4b04836416a0d2f","contributors":{"authors":[{"text":"Chamizo, Sonia 0000-0002-2980-1683","orcid":"https://orcid.org/0000-0002-2980-1683","contributorId":174264,"corporation":false,"usgs":false,"family":"Chamizo","given":"Sonia","email":"","affiliations":[{"id":27406,"text":"Department of Agronomy, University of Almeria, 04120 Almeria, Spain","active":true,"usgs":false}],"preferred":false,"id":647888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elridge, David J","contributorId":174265,"corporation":false,"usgs":false,"family":"Elridge","given":"David","email":"","middleInitial":"J","affiliations":[{"id":27407,"text":"Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia","active":true,"usgs":false}],"preferred":false,"id":647889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Issa, Oumarou M","contributorId":174266,"corporation":false,"usgs":false,"family":"Issa","given":"Oumarou M","affiliations":[{"id":27408,"text":"URCA, GEGENAA EA 3795, 51100 Reims – France / UMR 242 IEES-Paris, IRD representation au Niger BP11416 Niamey, Niger","active":true,"usgs":false}],"preferred":false,"id":647890,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176223,"text":"70176223 - 2016 - Synthesis on biological soil crust research","interactions":[],"lastModifiedDate":"2016-09-06T13:29:15","indexId":"70176223","displayToPublicDate":"2016-05-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Synthesis on biological soil crust research","docAbstract":"In this closing chapter, we summarize the advances in biocrust research made during the last 1.5 decades. In the first part of the chapter, we discuss how in some research fields, such as the microbial diversity of fungi, bacteria, and microfauna; the interaction between biocrusts and vascular plants; and in the rehabilitation of biocrusts; particularly large achievements have been made. In other fields, previously established knowledge of overall patterns has been corroborated and refined by additional studies, e.g., in the fields of soil stabilization and disturbance effects. In the second part of the chapter, we outline the research gaps and challenges foreseen by us. We identify multiple knowledge gaps, including many understudied geographic regions, the largely missing link between genetic and morphological species identification data, and the answers to some mechanistic questions, such as the overall role of biocrusts in hydrology and nutrient cycles. With some ideas on promising new research questions and approaches we close this chapter and the overall book.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological studies","language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-30214-0_25","usgsCitation":"Weber, B., Belnap, J., and Buedel, B., 2016, Synthesis on biological soil crust research, chap. of Ecological studies, p. 527-534, https://doi.org/10.1007/978-3-319-30214-0_25.","productDescription":"8 p.","startPage":"527","endPage":"534","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071476","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-22","publicationStatus":"PW","scienceBaseUri":"57cfe8bee4b04836416a0e3a","contributors":{"authors":[{"text":"Weber, Bettina","contributorId":21447,"corporation":false,"usgs":true,"family":"Weber","given":"Bettina","affiliations":[],"preferred":false,"id":647899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":647898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buedel, Burkhard","contributorId":172210,"corporation":false,"usgs":false,"family":"Buedel","given":"Burkhard","email":"","affiliations":[{"id":27000,"text":"Department of Biology, University of Kaiserslautern, Kaiserlautern, Germany","active":true,"usgs":false}],"preferred":false,"id":647900,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70171126,"text":"ofr20161080 - 2016 - Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management","interactions":[],"lastModifiedDate":"2016-06-23T16:23:54","indexId":"ofr20161080","displayToPublicDate":"2016-05-20T17:00:00","publicationYear":"2016","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":"2016-1080","title":"Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management","docAbstract":"Successful adaptive management hinges largely upon integrating new and improved sources of information as they become available. As a timely example of this tenet, we updated a management decision support tool that was previously developed for greater sage-grouse (Centrocercus urophasianus, hereinafter referred to as “sage-grouse”) populations in Nevada and California. Specifically, recently developed spatially explicit habitat maps derived from empirical data played a key role in the conservation of this species facing listing under the Endangered Species Act. This report provides an updated process for mapping relative habitat suitability and management categories for sage-grouse in Nevada and northeastern California (Coates and others, 2014, 2016). These updates include: (1) adding radio and GPS telemetry locations from sage-grouse monitored at multiple sites during 2014 to the original location dataset beginning in 1998; (2) integrating output from high resolution maps (1–2 m2) of sagebrush and pinyon-juniper cover as covariates in resource selection models; (3) modifying the spatial extent of the analyses to match newly available vegetation layers; (4) explicit modeling of relative habitat suitability during three seasons (spring, summer, winter) that corresponded to critical life history periods for sage-grouse (breeding, brood-rearing, over-wintering); (5) accounting for differences in habitat availability between more mesic sagebrush steppe communities in the northern part of the study area and drier Great Basin sagebrush in more southerly regions by categorizing continuous region-wide surfaces of habitat suitability index (HSI) with independent locations falling within two hydrological zones; (6) integrating the three seasonal maps into a composite map of annual relative habitat suitability; (7) deriving updated land management categories based on previously determined cut-points for intersections of habitat suitability and an updated index of sage-grouse abundance and space-use (AUI); and (8) masking urban footprints and major roadways out of the final map products.
Seasonal habitat maps were generated based on model-averaged resource selection functions (RSF) derived for 10 project areas (813 sage-grouse; 14,085 locations) during the spring season, 10 during the summer season (591 sage-grouse, 11,743 locations), and 7 during the winter season (288 sage-grouse, 4,862 locations). RSF surfaces were transformed to HSIs and averaged in a GIS framework for every pixel for each season. Validation analyses of categorized HSI surfaces using a suite of independent datasets resulted in an agreement of 93–97 percent for habitat versus non-habitat on an annual basis. Spring and summer maps validated similarly well at 94–97 percent, while winter maps validated slightly less accurately at 87–93 percent.
We then provide an updated example of how space use models can be integrated with habitat models to help inform conservation planning. We used updated lek count data to calculate a composite abundance and space use index (AUI) that comprised the combination of probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek. The AUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based on information about sage-grouse occupancy coupled with habitat suitability. Compared to Coates and others (2014, 2016), the amount of area classified as habitat across the region increased by 6.5 percent (approximately 1,700,000 acres). For management categories, core increased by 7.2 percent (approximately 865,000 acres), priority increased by 9.6 percent (approximately 855,000 acres), and general increased by 9.2 percent (approximately 768,000 acres), while non-habitat decreased (that is, classified non-habitat occurring outside of areas of concentrated use) by 11.9 percent (approximately 2,500,000 acres). Importantly, seasonal and annual maps represent habitat for all age and sex classes of sage-grouse (that is, sample sizes of marked grouse were insufficient to only construct models for reproductive females). This revised sage-grouse habitat mapping product helps improve adaptive application of conservation planning tools based on intersections of spatially explicit habitat suitability, abundance, and space use indices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161080","collaboration":"Prepared in cooperation with the State of Nevada Sagebrush Ecosystem Program, Bureau of Land Management, Nevada Department of Wildlife, California Department of Fish and Wildlife, and Idaho State University","usgsCitation":"Coates, P.S., Casazza, M.L., Brussee B.E., Ricca, M.A., Gustafson, K.B., Sanchez-Chopitea, E., Mauch, K., Niell, L., Gardner, S., Espinosa, S., and Delehanty, D.J., 2016, Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management: U.S. Geological Survey Open-File Report 2016-1080, 160 p., https://dx.doi.org/10.3133/ofr20161080.","productDescription":"Report: viii, 160 p.; Dataset","numberOfPages":"172","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072897","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":322138,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7CC0XRV","text":"USGS data release - Spatially Explicit Modeling of Annual and Seasonal Habitat for Greater Sage-Grouse (Centrocercus urophasianus) in Nevada and Northeastern California - an Updated Decision-Support Tool for Management"},{"id":321471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1080/coverthb.jpg"},{"id":321472,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1080/ofr20161080.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1080 Report PDF"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.87158203125,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 37.50972584293751\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://werc.usgs.gov/
A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called “isoscapes,” form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL068904","usgsCitation":"Brennan, S.R., Torgersen, C.E., Hollenbeck, J.P., Fernandez, D.P., Jensen, C.K., and Schindler, D.E., 2016, Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers: Geophysical Research Letters, v. 43, no. 10, p. 5043-5051, https://doi.org/10.1002/2016GL068904.","productDescription":"9 p.","startPage":"5043","endPage":"5051","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073082","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":470972,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068904","text":"Publisher Index Page"},{"id":321442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-18","publicationStatus":"PW","scienceBaseUri":"5740271be4b07e28b65dcfd4","contributors":{"authors":[{"text":"Brennan, Sean R.","contributorId":149334,"corporation":false,"usgs":false,"family":"Brennan","given":"Sean","email":"","middleInitial":"R.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":629872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":629871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hollenbeck, Jeff P. 0000-0001-6481-5354 jhollenbeck@usgs.gov","orcid":"https://orcid.org/0000-0001-6481-5354","contributorId":5130,"corporation":false,"usgs":true,"family":"Hollenbeck","given":"Jeff","email":"jhollenbeck@usgs.gov","middleInitial":"P.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":629873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fernandez, Diego P.","contributorId":138701,"corporation":false,"usgs":false,"family":"Fernandez","given":"Diego","email":"","middleInitial":"P.","affiliations":[{"id":12499,"text":"Univ. of Utah","active":true,"usgs":false}],"preferred":false,"id":629874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jensen, Carrie K","contributorId":169520,"corporation":false,"usgs":false,"family":"Jensen","given":"Carrie","email":"","middleInitial":"K","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":629876,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schindler, Daniel E.","contributorId":83485,"corporation":false,"usgs":true,"family":"Schindler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":629875,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171110,"text":"70171110 - 2016 - Toward improved simulation of river operations through integration with a hydrologic model","interactions":[],"lastModifiedDate":"2016-05-20T09:13:54","indexId":"70171110","displayToPublicDate":"2016-05-20T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Toward improved simulation of river operations through integration with a hydrologic model","docAbstract":"Advanced modeling tools are needed for informed water resources planning and management. Two classes of modeling tools are often used to this end–(1) distributed-parameter hydrologic models for quantifying supply and (2) river-operation models for sorting out demands under rule-based systems such as the prior-appropriation doctrine. Within each of these two broad classes of models, there are many software tools that excel at simulating the processes specific to each discipline, but have historically over-simplified, or at worse completely neglected, aspects of the other. As a result, water managers reliant on river-operation models for administering water resources need improved tools for representing spatially and temporally varying groundwater resources in conjunctive-use systems. A new tool is described that improves the representation of groundwater/surface-water (GW-SW) interaction within a river-operations modeling context and, in so doing, advances evaluation of system-wide hydrologic consequences of new or altered management regimes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2016.04.018","usgsCitation":"Morway, E.D., Niswonger, R.G., and Triana, E., 2016, Toward improved simulation of river operations through integration with a hydrologic model: Environmental Modelling and Software, no. 82, p. 255-274, https://doi.org/10.1016/j.envsoft.2016.04.018.","productDescription":"20 p.","startPage":"255","endPage":"274","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070519","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":470977,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2016.04.018","text":"Publisher Index Page"},{"id":321438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"82","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5740271de4b07e28b65dcfea","contributors":{"authors":[{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":152462,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":629911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Triana, Enrique","contributorId":169532,"corporation":false,"usgs":false,"family":"Triana","given":"Enrique","email":"","affiliations":[{"id":25556,"text":"MWH Global, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":629912,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70171081,"text":"70171081 - 2016 - Storm-event-transport of urban-use pesticides to streams likely impairs invertebrate assemblages","interactions":[],"lastModifiedDate":"2018-09-13T14:55:19","indexId":"70171081","displayToPublicDate":"2016-05-19T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Storm-event-transport of urban-use pesticides to streams likely impairs invertebrate assemblages","docAbstract":"Insecticide use in urban areas results in the detection of these compounds in streams following stormwater runoff at concentrations likely to cause toxicity for stream invertebrates. In this 2013 study, stormwater runoff and streambed sediments were analyzed for 91 pesticides dissolved in water and 118 pesticides on sediment. Detections included 33 pesticides, including insecticides, fungicides, herbicides, degradates, and a synergist. Patterns in pesticide occurrence reveal transport of dissolved and sediment-bound pesticides, including pyrethroids, from upland areas through stormwater outfalls to receiving streams. Nearly all streams contained at least one insecticide at levels exceeding an aquatic-life benchmark, most often for bifenthrin and (or) fipronil. Multiple U.S. EPA benchmark or criterion exceedances occurred in 40 % of urban streams sampled. Bed sediment concentrations of bifenthrin were highly correlated (p < 0.001) with benthic invertebrate assemblages. Non-insects and tolerant invertebrates such as amphipods, flatworms, nematodes, and oligochaetes dominated streams with relatively high concentrations of bifenthrin in bed sediments, whereas insects, sensitive invertebrates, and mayflies were much more abundant at sites with no or low bifenthrin concentrations. The abundance of sensitive invertebrates, % EPT, and select mayfly taxa were strongly negatively correlated with organic-carbon normalized bifenthrin concentrations in streambed sediments. Our findings from western Clackamas County, Oregon (USA), expand upon previous research demonstrating the transport of pesticides from urban landscapes and linking impaired benthic invertebrate assemblages in urban streams with exposure to pyrethroid insecticides.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-016-5215-5","usgsCitation":"Carpenter, K.D., Kuivila, K., Hladik, M., Haluska, T., and Cole, M.B., 2016, Storm-event-transport of urban-use pesticides to streams likely impairs invertebrate assemblages: Environmental Monitoring and Assessment, v. 188, art345: 18 p., https://doi.org/10.1007/s10661-016-5215-5.","productDescription":"art345: 18 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063257","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470982,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-016-5215-5","text":"Publisher Index 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partial exponential lumped parameter model (PEM) was derived to determine age distributions and nitrate trends in long-screened production wells. The PEM can simulate age distributions for wells screened over any finite interval of an aquifer that has an exponential distribution of age with depth. The PEM has 3 parameters – the ratio of saturated thickness to the top and bottom of the screen and mean age, but these can be reduced to 1 parameter (mean age) by using well construction information and estimates of the saturated thickness. The PEM was tested with data from 30 production wells in a heterogeneous alluvial fan aquifer in California, USA. Well construction data were used to guide parameterization of a PEM for each well and mean age was calibrated to measured environmental tracer data (3H, 3He, CFC-113, and 14C). Results were compared to age distributions generated for individual wells using advective particle tracking models (PTMs). Age distributions from PTMs were more complex than PEM distributions, but PEMs provided better fits to tracer data, partly because the PTMs did not simulate 14C accurately in wells that captured varying amounts of old groundwater recharged at lower rates prior to groundwater development and irrigation. Nitrate trends were simulated independently of the calibration process and the PEM provided good fits for at least 11 of 24 wells. This work shows that the PEM, and lumped parameter models (LPMs) in general, can often identify critical features of the age distributions in wells that are needed to explain observed tracer data and nonpoint source contaminant trends, even in systems where aquifer heterogeneity and water-use complicate distributions of age. While accurate PTMs are preferable for understanding and predicting aquifer-scale responses to water use and contaminant transport, LPMs can be sensitive to local conditions near individual wells that may be inaccurately represented or missing in an aquifer-scale flow model.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.05.011","usgsCitation":"Jurgens, B.C., Bohlke, J.K., Kauffman, L.J., Belitz, K., and Esser, B.K., 2016, A partial exponential lumped parameter model to evaluate groundwater age distributions and nitrate trends in long-screened wells: Journal of Hydrology, v. 543, no. A, p. 109-126, https://doi.org/10.1016/j.jhydrol.2016.05.011.","productDescription":"18 p.","startPage":"109","endPage":"126","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069107","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":325571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 37.9\n ],\n [\n -122,\n 37.2\n ],\n [\n -120.2,\n 37.2\n ],\n [\n -120.2,\n 37.9\n ],\n [\n -122,\n 37.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"543","issue":"A","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57934440e4b0eb1ce79e8bd2","contributors":{"authors":[{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, John Karl 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":127841,"corporation":false,"usgs":true,"family":"Bohlke","given":"John","email":"jkbohlke@usgs.gov","middleInitial":"Karl","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":643298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Leon J. 0000-0003-4564-0362 lkauff@usgs.gov","orcid":"https://orcid.org/0000-0003-4564-0362","contributorId":1094,"corporation":false,"usgs":true,"family":"Kauffman","given":"Leon","email":"lkauff@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esser, Bradley K.","contributorId":33161,"corporation":false,"usgs":true,"family":"Esser","given":"Bradley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":643301,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170990,"text":"70170990 - 2016 - Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA","interactions":[],"lastModifiedDate":"2018-09-18T10:01:55","indexId":"70170990","displayToPublicDate":"2016-05-17T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA","docAbstract":"Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O2 reduction and denitrification (NO3− reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF6, CFCs, 3H, He from 3H (tritiogenic He),14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO3− and dissolved gas data to estimate zero order and first order rates of O2 reduction and denitrification. Results indicated that O2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O2 and NO3− reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O2 reduction rates. Estimated historical NO3− trends were similar to historical measurements. Results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.
","language":"English","publisher":"European Geophysical Society","doi":"10.1016/j.jhydrol.2016.05.018","usgsCitation":"Green, C.T., Jurgens, B.C., Zhang, Y., Starn, J., Singleton, M.J., and Esser, B.K., 2016, Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA: Journal of Hydrology, v. 145, p. 47-55, https://doi.org/10.1016/j.jhydrol.2016.05.018.","productDescription":"9 p.","startPage":"47","endPage":"55","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067486","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2016.05.018","text":"Publisher Index Page"},{"id":321295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 37\n ],\n [\n -121.5,\n 38\n ],\n [\n -120,\n 38\n ],\n [\n -120,\n 37\n ],\n [\n -121.5,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d566fe4b07e28b667f7a0","contributors":{"authors":[{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":629354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Yong","contributorId":19029,"corporation":false,"usgs":true,"family":"Zhang","given":"Yong","affiliations":[],"preferred":false,"id":629356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starn, Jeffrey jjstarn@usgs.gov","contributorId":149231,"corporation":false,"usgs":true,"family":"Starn","given":"Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singleton, Michael J.","contributorId":44400,"corporation":false,"usgs":true,"family":"Singleton","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Esser, Bradley K.","contributorId":33161,"corporation":false,"usgs":true,"family":"Esser","given":"Bradley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":629359,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176281,"text":"70176281 - 2016 - Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns","interactions":[],"lastModifiedDate":"2016-09-07T12:00:19","indexId":"70176281","displayToPublicDate":"2016-05-14T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns","docAbstract":"The export of nitrogen (N), phosphorus (P), and suspended sediment (SS) is a long-standing management concern for the Chesapeake Bay watershed, USA. Here we present a comprehensive evaluation of nutrient and sediment loads over the last three decades at multiple locations in the Susquehanna River basin (SRB), Chesapeake's largest tributary watershed. Sediment and nutrient riverine loadings, including both dissolved and particulate fractions, have generally declined at all sites upstream of Conowingo Dam (non-tidal SRB outlet). Period-of-record declines in riverine yield are generally smaller than those in source input, suggesting the possibility of legacy contributions. Consistent with other watershed studies, these results reinforce the importance of considering lag time between the implementation of management actions and achievement of river quality improvement. Whereas flow-normalized loadings for particulate species have increased recently below Conowingo Reservoir, those for upstream sites have declined, thus substantiating conclusions from prior studies about decreased reservoir trapping efficiency. In regard to streamflow effects, statistically significant log-linear relationships between annual streamflow and annual constituent load suggest the dominance of hydrological control on the inter-annual variability of constituent export. Concentration-discharge relationships revealed general chemostasis and mobilization effects for dissolved and particulate species, respectively, both suggesting transport-limitation conditions. In addition to affecting annual export rates, streamflow has also modulated the relative importance of dissolved and particulate fractions, as reflected by its negative correlations with dissolved P/total P, dissolved N/total N, particulate P/SS, and total N/total P ratios. For land-use effects, period-of-record median annual yields of N, P, and SS all correlate positively with the area fraction of non-forested land but negatively with that of forested land under all hydrological conditions. Overall, this work has informed understanding with respect to four major factors affecting constituent export (i.e., source input, reservoir modulation, streamflow, and land use) and demonstrated the value of long-term river monitoring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.104","usgsCitation":"Zhang, Q., Ball, W.P., and Moyer, D.L., 2016, Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns: Science of the Total Environment, v. 563-564, p. 1016-1029, https://doi.org/10.1016/j.scitotenv.2016.03.104.","productDescription":"14 p.","startPage":"1016","endPage":"1029","ipdsId":"IP-070367","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":471000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.104","text":"Publisher Index Page"},{"id":328310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New York, Pennsylvania","otherGeospatial":"Chesapeake Bay, Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.51953125,\n 39.30029918615029\n ],\n [\n -77.51953125,\n 42.309815415686664\n ],\n [\n -75.73974609375,\n 42.309815415686664\n ],\n [\n -75.73974609375,\n 39.30029918615029\n ],\n [\n -77.51953125,\n 39.30029918615029\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"563-564","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a39e4b0571647cf8dbb","contributors":{"authors":[{"text":"Zhang, Qian 0000-0003-0500-5655","orcid":"https://orcid.org/0000-0003-0500-5655","contributorId":174393,"corporation":false,"usgs":false,"family":"Zhang","given":"Qian","email":"","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":648192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, William P.","contributorId":174394,"corporation":false,"usgs":false,"family":"Ball","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":27446,"text":"Johns Hopkins University, Department of Geography and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":648193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moyer, Douglas L. 0000-0001-6330-478X dlmoyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6330-478X","contributorId":174389,"corporation":false,"usgs":true,"family":"Moyer","given":"Douglas","email":"dlmoyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648191,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70161744,"text":"70161744 - 2016 - Tidal saline wetland regeneration of sentinel vegetation types in the Northern Gulf of Mexico: An overview","interactions":[],"lastModifiedDate":"2016-06-13T09:51:08","indexId":"70161744","displayToPublicDate":"2016-05-12T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Tidal saline wetland regeneration of sentinel vegetation types in the Northern Gulf of Mexico: An overview","docAbstract":"Tidal saline wetlands in the Northern Gulf of Mexico (NGoM) are dynamic and frequently disturbed systems that provide myriad ecosystem services. For these services to be sustained, dominant macrophytes must continuously recolonize and establish after disturbance. Macrophytes accomplish this regeneration through combinations of vegetative propagation and sexual reproduction, the relative importance of which varies by species. Concurrently, tidal saline wetland systems experience both anthropogenic and natural hydrologic alterations, such as levee construction, sea-level rise, storm impacts, and restoration activities. These hydrologic alterations can affect the success of plant regeneration, leading to large-scale, variable changes in ecosystem structure and function. This review describes the specific regeneration requirements of four dominant coastal wetland macrophytes along the NGoM (Spartina alterniflora, Avicennia germinans, Juncus roemerianus, and Batis maritima) and compares them with current hydrologic alterations to provide insights into potential future changes in dominant ecosystem structure and function and to highlight knowledge gaps in the current literature that need to be addressed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2016.02.010","usgsCitation":"Jones, S.F., Stagg, C.L., Krauss, K.W., and Hester, M.W., 2016, Tidal saline wetland regeneration of sentinel vegetation types in the Northern Gulf of Mexico: An overview: Estuarine, Coastal and Shelf Science, v. 174, p. A1-A10, https://doi.org/10.1016/j.ecss.2016.02.010.","productDescription":"10 p.","startPage":"A1","endPage":"A10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070031","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":321171,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.68115234375,\n 27.644606381943326\n ],\n [\n -90.68115234375,\n 30.883369321692268\n ],\n [\n -84.6826171875,\n 30.883369321692268\n ],\n [\n -84.6826171875,\n 27.644606381943326\n ],\n [\n -90.68115234375,\n 27.644606381943326\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"174","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57359b1ce4b0dae0d5dee786","contributors":{"authors":[{"text":"Jones, Scott F. 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":152041,"corporation":false,"usgs":true,"family":"Jones","given":"Scott","email":"","middleInitial":"F.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":18863,"text":"University of Louisiana, Lafayette, LA","active":true,"usgs":false}],"preferred":true,"id":587627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":587626,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":587628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hester, Mark W.","contributorId":9566,"corporation":false,"usgs":true,"family":"Hester","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":587629,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174265,"text":"70174265 - 2016 - Latest Miocene-earliest Pliocene evolution of the ancestral Rio Grande at the Española-San Luis Basin boundary, northern New Mexico","interactions":[],"lastModifiedDate":"2016-07-06T17:31:05","indexId":"70174265","displayToPublicDate":"2016-05-12T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2860,"text":"New Mexico Geology","active":true,"publicationSubtype":{"id":10}},"title":"Latest Miocene-earliest Pliocene evolution of the ancestral Rio Grande at the Española-San Luis Basin boundary, northern New Mexico","docAbstract":"High-elevation aquatic ecosystems are highly vulnerable to climate change, yet relatively few records are available to characterize shifts in ecosystem structure or their underlying mechanisms. Using a long-term dataset on seven alpine lakes (3126 to 3620 m) in Colorado, USA, we show that ice-off dates have shifted seven days earlier over the past 33 years and that spring weather conditions – especially snowfall – drive yearly variation in ice-off timing. In the most well-studied lake, earlier ice-off associated with increases in water residence times, thermal stratification, ion concentrations, dissolved nitrogen, pH, and chlorophyll-a. Mechanistically, low spring snowfall and warm temperatures reduce summer stream flow (increasing lake residence times) but enhance melting of glacial and permafrost ice (increasing lake solute inputs). The observed links among hydrological, chemical, and biological responses to climate factors highlight the potential for major shifts in the functioning of alpine lakes due to forecasted climate change.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL069036","usgsCitation":"Preston, D.L., Caine, N., McKnight, D.M., Williams, M.W., Hell, K., Miller, M.P., Hart, S.J., and Johnson, P.T., 2016, Climate regulates alpine lake ice cover phenology and aquatic ecosystem structure: Geophysical Research Letters, v. 43, no. 10, p. 5353-5360, https://doi.org/10.1002/2016GL069036.","productDescription":"8 p.","startPage":"5353","endPage":"5360","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065721","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":471008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/74a41412b86246d8b0d27b74c0bce459","text":"Publisher Index Page"},{"id":321123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","volume":"43","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-28","publicationStatus":"PW","scienceBaseUri":"5734499be4b0dae0d5dd68f4","contributors":{"authors":[{"text":"Preston, Daniel L.","contributorId":58581,"corporation":false,"usgs":true,"family":"Preston","given":"Daniel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":629149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caine, Nel","contributorId":169277,"corporation":false,"usgs":false,"family":"Caine","given":"Nel","email":"","affiliations":[],"preferred":false,"id":629150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKnight, Diane M.","contributorId":59773,"corporation":false,"usgs":false,"family":"McKnight","given":"Diane","email":"","middleInitial":"M.","affiliations":[{"id":16833,"text":"INSTAAR, University of Colorado","active":true,"usgs":false}],"preferred":false,"id":629151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Mark W.","contributorId":43046,"corporation":false,"usgs":true,"family":"Williams","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":629152,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hell, Katherina","contributorId":169278,"corporation":false,"usgs":false,"family":"Hell","given":"Katherina","email":"","affiliations":[],"preferred":false,"id":629153,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Sarah J.","contributorId":169279,"corporation":false,"usgs":false,"family":"Hart","given":"Sarah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629154,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Pieter T.J.","contributorId":28508,"corporation":false,"usgs":true,"family":"Johnson","given":"Pieter","email":"","middleInitial":"T.J.","affiliations":[],"preferred":false,"id":629155,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70170932,"text":"70170932 - 2016 - Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend","interactions":[],"lastModifiedDate":"2016-07-07T10:04:44","indexId":"70170932","displayToPublicDate":"2016-05-11T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend","docAbstract":"Compound meander bends with multiple lobes of maximum curvature are common in actively evolving lowland rivers. Interaction among spatial patterns of mean flow, turbulence, bed morphology, bank failures and channel migration in compound bends is poorly understood. In this paper, acoustic Doppler current profiler (ADCP) measurements of the three-dimensional (3D) flow velocities in a compound bend are examined to evaluate the influence of channel curvature and hydrologic variability on the structure of flow within the bend. Flow structure at various flow stages is related to changes in bed morphology over the study timeframe. Increases in local curvature within the upstream lobe of the bend reduce outer bank velocities at morphologically significant flows, creating a region that protects the bank from high momentum flow and high bed shear stresses. The dimensionless radius of curvature in the upstream lobe is one-third less than that of the downstream lobe, with average bank erosion rates less than half of the erosion rates for the downstream lobe. Higher bank erosion rates within the downstream lobe correspond to the shift in a core of high velocity and bed shear stresses toward the outer bank as flow moves through the two lobes. These erosion patterns provide a mechanism for continued migration of the downstream lobe in the near future. Bed material size distributions within the bend correspond to spatial patterns of bed shear stress magnitudes, indicating that bed material sorting within the bend is governed by bed shear stress. Results suggest that patterns of flow, sediment entrainment, and planform evolution in compound meander bends are more complex than in simple meander bends. Moreover, interactions among local influences on the flow, such as woody debris, local topographic steering, and locally high curvature, tend to cause compound bends to evolve toward increasing planform complexity over time rather than stable configurations.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/esp.3895","usgsCitation":"Engel, F.L., and Rhoads, B.L., 2016, Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend: Earth Surface Processes and Landforms, v. 41, no. 9, p. 1211-1226, https://doi.org/10.1002/esp.3895.","productDescription":"16 p.","startPage":"1211","endPage":"1226","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059802","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":321116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-15","publicationStatus":"PW","scienceBaseUri":"5734499ee4b0dae0d5dd691b","contributors":{"authors":[{"text":"Engel, Frank L. 0000-0002-4253-2625 fengel@usgs.gov","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":5463,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","email":"fengel@usgs.gov","middleInitial":"L.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rhoads, Bruce L.","contributorId":20248,"corporation":false,"usgs":true,"family":"Rhoads","given":"Bruce","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":629143,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170902,"text":"70170902 - 2016 - The ecology of methane in streams and rivers: Patterns, controls, and global significance","interactions":[],"lastModifiedDate":"2016-05-11T10:34:05","indexId":"70170902","displayToPublicDate":"2016-05-11T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"The ecology of methane in streams and rivers: Patterns, controls, and global significance","docAbstract":"Streams and rivers can substantially modify organic carbon (OC) inputs from terrestrial landscapes, and much of this processing is the result of microbial respiration. While carbon dioxide (CO2) is the major end-product of ecosystem respiration, methane (CH4) is also present in many fluvial environments even though methanogenesis typically requires anoxic conditions that may be scarce in these systems. Given recent recognition of the pervasiveness of this greenhouse gas in streams and rivers, we synthesized existing research and data to identify patterns and drivers of CH4, knowledge gaps, and research opportunities. This included examining the history of lotic CH4 research, creating a database of concentrations and fluxes (MethDB) to generate a global-scale estimate of fluvial CH4 efflux, and developing a conceptual framework and using this framework to consider how human activities may modify fluvial CH4 dynamics. Current understanding of CH4 in streams and rivers has been strongly influenced by goals of understanding OC processing and quantifying the contribution of CH4 to ecosystem C fluxes. Less effort has been directed towards investigating processes that dictate in situ CH4 production and loss. CH4 makes a meager contribution to watershed or landscape C budgets, but streams and rivers are often significant CH4 sources to the atmosphere across these same spatial extents. Most fluvial systems are supersaturated with CH4 and we estimate an annual global emission of 26.8 Tg CH4, equivalent to ~15-40% of wetland and lake effluxes, respectively. Less clear is the role of CH4 oxidation, methanogenesis, and total anaerobic respiration to whole ecosystem production and respiration. Controls on CH4 generation and persistence can be viewed in terms of proximate controls that influence methanogenesis (organic matter, temperature, alternative electron acceptors, nutrients) and distal geomorphic and hydrologic drivers. Multiple controls combined with its extreme redox status and low solubility result in high spatial and temporal variance of CH4 in fluvial environments, which presents a substantial challenge for understanding its larger-scale dynamics. Further understanding of CH4 production and consumption, anaerobic metabolism, and ecosystem energetics in streams and rivers can be achieved through more directed studies and comparison with knowledge from terrestrial, wetland, and aquatic disciplines.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-1027.1","usgsCitation":"Stanley, E.H., Casson, N.J., Christel, S.T., Crawford, J.T., Loken, L., and Oliver, S., 2016, The ecology of methane in streams and rivers: Patterns, controls, and global significance: Ecological Monographs, v. 86, no. 2, p. 146-171, https://doi.org/10.1890/15-1027.1.","productDescription":"16 p.","startPage":"146","endPage":"171","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066395","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471013,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10680/1574","text":"External Repository"},{"id":321111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-07","publicationStatus":"PW","scienceBaseUri":"5734499de4b0dae0d5dd690d","contributors":{"authors":[{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":629004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casson, Nora J.","contributorId":169271,"corporation":false,"usgs":false,"family":"Casson","given":"Nora","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christel, Samuel T.","contributorId":169272,"corporation":false,"usgs":false,"family":"Christel","given":"Samuel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":629006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":629003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loken, Luke C. lloken@usgs.gov","contributorId":169218,"corporation":false,"usgs":true,"family":"Loken","given":"Luke C.","email":"lloken@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":629008,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170912,"text":"70170912 - 2016 - POLARIS: A 30-meter probabilistic soil series map of the contiguous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:50:15","indexId":"70170912","displayToPublicDate":"2016-05-10T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"POLARIS: A 30-meter probabilistic soil series map of the contiguous United States","docAbstract":"A new complete map of soil series probabilities has been produced for the contiguous United States at a 30 m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~ 2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.
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,{"id":70171533,"text":"70171533 - 2016 - Extremes of heat, drought and precipitation depress reproductive performance in shortgrass prairie passerines","interactions":[],"lastModifiedDate":"2016-06-16T11:25:03","indexId":"70171533","displayToPublicDate":"2016-05-09T14:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"Extremes of heat, drought and precipitation depress reproductive performance in shortgrass prairie passerines","docAbstract":"Climate change elevates conservation concerns worldwide because it is likely to exacerbate many identified threats to animal populations. In recent decades, grassland birds have declined faster than other North American bird species, a loss thought to be due to habitat loss and fragmentation and changing agricultural practices. Climate change poses additional threats of unknown magnitude to these already declining populations. We examined how seasonal and daily weather conditions over 10 years influenced nest survival of five species of insectivorous passerines native to the shortgrass prairie and evaluate our findings relative to future climate predictions for this region. Daily nest survival (n = 870) was best predicted by a combination of daily and seasonal weather variables, age of nest, time in season and bird habitat guild. Within a season, survival rates were lower on very hot days (temperatures ≥ 35 °C), on dry days (with a lag of 1 day) and on stormy days (especially for those species nesting in shorter vegetation). Across years, survival rates were also lower during warmer and drier breeding seasons. Clutch sizes were larger when early spring temperatures were cool and the week prior to egg-laying was wetter and warming. Climate change is likely to exacerbate grassland bird population declines because projected climate conditions include rising temperatures, more prolonged drought and more intense storms as the hydrological cycle is altered. Under varying realistic scenarios, nest success estimates were halved compared to their current average value when models both increased the temperature (3 °C) and decreased precipitation (two additional dry days during a nesting period), thus underscoring a sense of urgency in identifying and addressing the current causes of range-wide declines.
","language":"English","publisher":"British Ornithologists' Union","publisherLocation":"Oxford","doi":"10.1111/ibi.12373","collaboration":"Reesa Conrey; Amy A. Yackel Adams; Arvind Panjabi","usgsCitation":"Conrey, R.Y., Skagen, S., Yackel, A., and Panjabi, A.O., 2016, Extremes of heat, drought and precipitation depress reproductive performance in shortgrass prairie passerines: Ibis, v. 158, no. 3, p. 614-629, https://doi.org/10.1111/ibi.12373.","productDescription":"16 p.","startPage":"614","endPage":"629","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070119","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":322103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"158","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"575158b1e4b053f0edd03c44","chorus":{"doi":"10.1111/ibi.12373","url":"http://dx.doi.org/10.1111/ibi.12373","publisher":"Wiley-Blackwell","authors":"Conrey Reesa Y., Skagen Susan K., Yackel Adams Amy A., Panjabi Arvind O.","journalName":"Ibis","publicationDate":"5/9/2016"},"contributors":{"authors":[{"text":"Conrey, Reesa Y.","contributorId":169966,"corporation":false,"usgs":false,"family":"Conrey","given":"Reesa","email":"","middleInitial":"Y.","affiliations":[{"id":16861,"text":"Colorado Parks and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":631635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skagen, Susan K. 0000-0002-6744-1244 skagens@usgs.gov","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":167829,"corporation":false,"usgs":true,"family":"Skagen","given":"Susan K.","email":"skagens@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":631634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackel, Amy 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":152310,"corporation":false,"usgs":true,"family":"Yackel","given":"Amy","email":"yackela@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":631636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Panjabi, Arvind O.","contributorId":169967,"corporation":false,"usgs":false,"family":"Panjabi","given":"Arvind","email":"","middleInitial":"O.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":631637,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169357,"text":"sir20165036 - 2016 - Flood-inundation maps for the East Fork White River at Shoals, Indiana","interactions":[],"lastModifiedDate":"2016-05-18T09:55:41","indexId":"sir20165036","displayToPublicDate":"2016-05-06T14:00:00","publicationYear":"2016","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":"2016-5036","title":"Flood-inundation maps for the East Fork White River at Shoals, Indiana","docAbstract":"Digital flood-inundation maps for a 5.9-mile reach of the East Fork White River at Shoals, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the East Fork White River at Shoals, Ind. (USGS station number 03373500). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS AHPS site SHLI3). NWS AHPS forecast peak stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
Flood profiles were computed for the East Fork White River reach by means of a one-dimensional, step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating no. 43.0) at USGS streamgage 03373500, East Fork White River at Shoals, Ind. The calibrated hydraulic model was then used to compute 26 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (10 ft) to the highest stage of the current stage-discharge rating curve (35 ft). The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM), derived from light detection and ranging (lidar) data, to delineate the area flooded at each water level. The areal extent of the 24-ft flood-inundation map was verified with photographs from a flood event on July 20, 2015.
The availability of these maps, along with information on the Internet regarding current stage from the USGS streamgage at East Fork White River at Shoals, Ind., and forecasted stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165036","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Boldt, J.A., 2016, Flood-inundation maps for the East Fork White River at Shoals, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5036, 22 p., https://dx.doi.org/10.3133/sir20165036.","productDescription":"Report: vi, 22 p.; Additional Report Piece: zipfile; Shapefile; Depth Grids; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069452","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":321015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5036/coverthb.jpg"},{"id":321016,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5036/sir20165036.pdf","text":"Report","size":"6.22 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U.S. Geological Survey
5957 Lakeside Blvd
Indianapolis, IN 46278
http://in.water.usgs.gov/
Hydrologic and hydraulic analyses were done for selected reaches of five streams in and near Shelby, Richland County, Ohio. The U.S. Geological Survey (USGS), in cooperation with the Muskingum Watershed Conservancy District, conducted these analyses on the Black Fork Mohican River and four tributaries: Seltzer Park Creek, Seltzer Park Tributary, Tuby Run, and West Branch. Drainage areas of the four stream reaches studied range from 0.51 to 60.3 square miles. The analyses included estimation of the 10-, 2-, 1-, and 0.2-percent annual-exceedance probability (AEP) flood-peak discharges using the USGS Ohio StreamStats application. Peak discharge estimates, along with cross-sectional and hydraulic structure geometries, and estimates of channel roughness coefficients were used as input to step-backwater models. The step-backwater water models were used to determine water-surface elevation profiles of four flood-peak discharges and a regulatory floodway. This study involved the installation of, and data collection at, a streamflow-gaging station (Black Fork Mohican River at Shelby, Ohio, 03129197), precipitation gage (Rain gage at Reservoir Number Two at Shelby, Ohio, 405209082393200), and seven submersible pressure transducers on six selected river reaches. Two precipitation-runoff models, one for the winter events and one for nonwinter events for the headwaters of the Black Fork Mohican River, were developed and calibrated using the data collected. With the exception of the runoff curve numbers, all other parameters used in the two precipitation-runoff models were identical. The Nash-Sutcliffe model efficiency coefficients were 0.737, 0.899, and 0.544 for the nonwinter events and 0.850 and 0.671 for the winter events. Both of the precipitation-runoff models underestimated the total volume of water, with residual runoff ranging from -0.27 inches to -1.53 inches. The results of this study can be used to assess possible mitigation options and define flood hazard areas that will contribute to the protection of life and property. This study could also assist emergency managers, community officials, and residents in determining when flooding may occur and planning evacuation routes during a flood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155187","collaboration":"Prepared in cooperation with the Muskingum Watershed Conservancy District","usgsCitation":"Huitger, C.A, Ostheimer, C.J., and Koltun, G.F., 2016, Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio: U.S. Geological Survey Scientific Investigations Report 2015–5187, 39 p., 2 appendixes, https://dx.doi.org/10.3133/sir20155187.","productDescription":"Report: vi, 39 p.; 5 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060945","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":320916,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-1.csv","text":"Appendix 1 - Table 1-1","size":"84.1 KB csv","description":"SIR 2015-5187"},{"id":320915,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5187/sir20155187.pdf","text":"Report","size":"1.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5187"},{"id":320917,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-2.csv","text":"Appendix 1 - Table 1-2","size":"62 KB csv","description":"SIR 2015-5187"},{"id":320914,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5187/coverthb.jpg"},{"id":320919,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-4.csv","text":"Appendix 1 - Table 1-4","size":"50 KB csv","description":"SIR 2015-5187"},{"id":320918,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-3.csv","text":"Appendix 1 - Table 1-3","size":"19 KB csv","description":"SIR 2015-5187"},{"id":320920,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-5.csv","text":"Appendix 1 - Table 1-5","size":"22 KB csv","description":"SIR 2015-5187"}],"country":"United States","state":"Ohio","city":"Shelby","otherGeospatial":"Black Fork Mohican River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.70902633666992,\n 40.83563216247778\n ],\n [\n -82.70902633666992,\n 40.91934991356069\n ],\n [\n -82.61959075927734,\n 40.91934991356069\n ],\n [\n -82.61959075927734,\n 40.83563216247778\n ],\n [\n -82.70902633666992,\n 40.83563216247778\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio Water Science Center
6480 Doubletree Ave
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http://oh.water.usgs.gov/
Hurricane Sandy made landfall in Barnegat Bay, October, 29, 2012, damaging shorelines and infrastructure. Estuarine sediment chemistry and toxicity were investigated before and after to evaluate potential environmental health impacts and to establish post-event baseline sediment-quality conditions. Trace element concentrations increased throughout Barnegat Bay up to two orders of magnitude, especially north of Barnegat Inlet, consistent with northward redistribution of silt. Loss of organic compounds, clay, and organic carbon is consistent with sediment winnowing and transport through the inlets and sediment transportmodeling results. The number of sites exceeding sediment quality guidance levels for trace elements tripled post-Sandy. Sediment toxicity post-Sandy was mostly unaffected relative to pre-Sandy conditions, but at the site with the greatest relative increase for trace elements, survival rate of the test amphipod decreased (indicating degradation). This study would not have been possible without comprehensive baseline data enabling the evaluation of storm-derived changes in sediment quality.
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