Landfills are the final repository for most of the discarded material from human society and its “built environments.” Microorganisms subsequently degrade this discarded material in the landfill, releasing gases (largely CH4 and CO2) and a complex mixture of soluble chemical compounds in leachate. Characterization of “landfill microbiomes” and their comparison across several landfills should allow the identification of environmental or operational properties that influence the composition of these microbiomes and potentially their biodegradation capabilities. To this end, the composition of landfill microbiomes was characterized as part of an ongoing USGS national survey studying the chemical composition of leachates from 19 non-hazardous landfills across 16 states in the continental U.S. The landfills varied in parameters such as size, waste composition, management strategy, geography, and climate zone. The diversity and composition of bacterial and archaeal populations in leachate samples were characterized by 16S rRNA gene sequence analysis, and compared against a variety of physical and chemical parameters in an attempt to identify their impact on selection. Members of the Epsilonproteobacteria, Gammaproteobacteria, Clostridia, and candidate division OP3 were the most abundant. The distribution of the observed phylogenetic diversity could best be explained by a combination of variables and was correlated most strongly with the concentrations of chloride and barium, rate of evapotranspiration, age of waste, and the number of detected household chemicals. This study illustrates how leachate microbiomes are distinct from those of other natural or built environments, and sheds light on the major selective forces responsible for this microbial diversity.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmicb.2016.00534","usgsCitation":"Stamps, B.W., Lyles, C.N., Suflita, J.M., Masoner, J.R., Cozzarelli, I.M., Kolpin, D.W., and Stevenson, B.S., 2016, Municipal solid waste landfills harbor distinct microbiomes: Frontiers in Microbiology, v. 7, p. 1-11, https://doi.org/10.3389/fmicb.2016.00534.","productDescription":"Article 534; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-062988","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2016.00534","text":"Publisher Index Page"},{"id":330574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-20","publicationStatus":"PW","scienceBaseUri":"5818582fe4b0bb36a4c6fa13","contributors":{"authors":[{"text":"Stamps, Blake W.","contributorId":176485,"corporation":false,"usgs":false,"family":"Stamps","given":"Blake","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":652503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyles, Christopher N.","contributorId":176484,"corporation":false,"usgs":false,"family":"Lyles","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":652504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Suflita, Joseph M.","contributorId":82997,"corporation":false,"usgs":true,"family":"Suflita","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":652507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652508,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stevenson, Bradley S.","contributorId":176491,"corporation":false,"usgs":false,"family":"Stevenson","given":"Bradley","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":652509,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70179445,"text":"70179445 - 2016 - Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity","interactions":[],"lastModifiedDate":"2017-01-03T11:21:55","indexId":"70179445","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity","docAbstract":"The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are much weaker than anticipated and may be too subtle for detection given the widespread use of sparse water temperature datasets or imprecise surrogates like elevation and air temperature. Through application of large water-temperature databases evaluated for sensitivity to historical air-temperature variability and computationally interpolated to provide high-resolution thermal habitat information for a 222,000-km network, we estimate a less dire thermal plight for cold-water species within mountains of the northwestern United States. Stream warming rates and climate velocities were both relatively low for 1968–2011 (average warming rate = 0.101 °C/decade; median velocity = 1.07 km/decade) when air temperatures warmed at 0.21 °C/decade. Many cold-water vertebrate species occurred in a subset of the network characterized by low climate velocities, and three native species of conservation concern occurred in extremely cold, slow velocity environments (0.33–0.48 km/decade). Examination of aggressive warming scenarios indicated that although network climate velocities could increase, they remain low in headwaters because of strong local temperature gradients associated with topographic controls. Better information about changing hydrology and disturbance regimes is needed to complement these results, but rather than being climatic cul-de-sacs, many mountain streams appear poised to be redoubts for cold-water biodiversity this century.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1522429113","usgsCitation":"Isaak, D.J., Young, M.K., Luce, C.H., Hostetler, S.W., Wenger, S., Peterson, E.E., Ver Hoef, J., Groce, M.C., Horan, D.L., and Nagel, D.E., 2016, Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity: Proceedings of the National Academy of Sciences of the United States of America, v. 113, no. 16, p. 4374-4379, https://doi.org/10.1073/pnas.1522429113.","productDescription":"6 p.","startPage":"4374","endPage":"4379","ipdsId":"IP-072844","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471098,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4843441","text":"External Repository"},{"id":332732,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"16","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-04","publicationStatus":"PW","scienceBaseUri":"586cc697e4b0f5ce109fa957","contributors":{"authors":[{"text":"Isaak, Daniel J.","contributorId":177835,"corporation":false,"usgs":false,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":657245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Michael K.","contributorId":177836,"corporation":false,"usgs":false,"family":"Young","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":657246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luce, Charles H.","contributorId":177837,"corporation":false,"usgs":false,"family":"Luce","given":"Charles","email":"","middleInitial":"H.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":657247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":657244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":657248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Erin E.","contributorId":177839,"corporation":false,"usgs":false,"family":"Peterson","given":"Erin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":657249,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ver Hoef, Jay","contributorId":177840,"corporation":false,"usgs":false,"family":"Ver Hoef","given":"Jay","affiliations":[],"preferred":false,"id":657250,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Groce, Matthew C.","contributorId":177841,"corporation":false,"usgs":false,"family":"Groce","given":"Matthew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":657251,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Horan, Dona L.","contributorId":36672,"corporation":false,"usgs":true,"family":"Horan","given":"Dona","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":657252,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nagel, David E.","contributorId":86887,"corporation":false,"usgs":true,"family":"Nagel","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":657253,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70193182,"text":"70193182 - 2016 - NHDPlus as a geospatial framework for SPARROW modeling","interactions":[],"lastModifiedDate":"2018-03-15T10:26:24","indexId":"70193182","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1975,"text":"Impact Assessment Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"NHDPlus as a geospatial framework for SPARROW modeling","docAbstract":"Successful water-resource management requires thorough knowledge and understanding of the relations among water-quality contaminate sources and the factors that affect the transport throughout a hydrologic system. Surface-water modeling is a valuable tool that can be applied to help advance and achieve the understanding of these dynamic relations. Spatially Referenced Regressions on Watershed Attributes (SPARROW) is one such model that uses nonlinear statistical methods to define conceptual and spatial relations among quantities of contaminant sources, monitored contaminant load, aquatic transport processes. NHDPlus Version 2 (V2) is a digital representation of a hydrologic network of streams and associated catchments. The dataset provides the fundamental spatial framework for SPARROW modeling.","language":"English","publisher":"American Water Resources Association","usgsCitation":"Brakebill, J.W., and Schwarz, G., 2016, NHDPlus as a geospatial framework for SPARROW modeling: Impact Assessment Bulletin, v. 18, no. 3.","ipdsId":"IP-073650","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":348610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347782,"type":{"id":15,"text":"Index Page"},"url":"https://www.awra.org/impact/"}],"volume":"18","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07ea50e4b09af898c8cc73","contributors":{"authors":[{"text":"Brakebill, John W. 0000-0001-9235-6810 jwbrakeb@usgs.gov","orcid":"https://orcid.org/0000-0001-9235-6810","contributorId":1061,"corporation":false,"usgs":true,"family":"Brakebill","given":"John","email":"jwbrakeb@usgs.gov","middleInitial":"W.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":718136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":718137,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192938,"text":"70192938 - 2016 - Role of large- and fine-scale variables in predicting catch rates of larval Pacific lamprey in the Willamette Basin, Oregon","interactions":[],"lastModifiedDate":"2017-11-07T12:50:32","indexId":"70192938","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Role of large- and fine-scale variables in predicting catch rates of larval Pacific lamprey in the Willamette Basin, Oregon","docAbstract":"Pacific lamprey Entosphenus tridentatus is an anadromous fish native to the Pacific Northwest of the USA. That has declined substantially over the last 40 years. Effective conservation of this species will require an understanding of the habitat requirements for each life history stage. Because its life cycle contains extended freshwater rearing (3–8 years), the larval stage may be a critical factor limiting abundance of Pacific lamprey. The objective of our study was to estimate the influence of barriers and habitat characteristics on the catch-per-unit-effort (CPUE) of larval Pacific lamprey in the Willamette River Basin, Oregon, USA. We sampled lampreys at multiple locations in wadeable streams throughout the basin in 2011–13 and used an information theoretic approach to examine the relative influence of fine- and large-scale predictors of CPUE. Pacific lamprey was observed across the basin, but its relative abundance appeared to be limited by the presence of natural and artificial barriers in some sub-basins. Lower velocity habitats such as off-channel areas and pools contained higher densities of larval lamprey; mean Pacific lamprey CPUE in off-channel habitats was 4 and 32 times greater than in pools and riffles respectively. Restoration and conservation strategies that improve fish passage, enhance natural hydrologic and depositional processes and increase habitat heterogeneity will likely benefit larval Pacific lamprey.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12207","usgsCitation":"Schultz, L., Mayfield, M.P., Sheoships, G.T., Wyss, L.A., Clemens, B.J., Whitlock, S.L., and Schreck, C.B., 2016, Role of large- and fine-scale variables in predicting catch rates of larval Pacific lamprey in the Willamette Basin, Oregon: Ecology of Freshwater Fish, v. 25, no. 2, p. 261-271, https://doi.org/10.1111/eff.12207.","productDescription":"11 p.","startPage":"261","endPage":"271","ipdsId":"IP-056803","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.50280761718751,\n 43.97700467496408\n ],\n [\n -122.01416015625,\n 43.97700467496408\n ],\n [\n -122.01416015625,\n 45.7176863579072\n ],\n [\n -123.50280761718751,\n 45.7176863579072\n ],\n [\n -123.50280761718751,\n 43.97700467496408\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-19","publicationStatus":"PW","scienceBaseUri":"5a07ea50e4b09af898c8cc75","contributors":{"authors":[{"text":"Schultz, Luke 0000-0002-6751-4626 lschultz@usgs.gov","orcid":"https://orcid.org/0000-0002-6751-4626","contributorId":193171,"corporation":false,"usgs":true,"family":"Schultz","given":"Luke","email":"lschultz@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":720937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mayfield, Mariah P.","contributorId":200089,"corporation":false,"usgs":false,"family":"Mayfield","given":"Mariah","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":720938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheoships, Gabe T.","contributorId":200090,"corporation":false,"usgs":false,"family":"Sheoships","given":"Gabe","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":720939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wyss, Lance A.","contributorId":195114,"corporation":false,"usgs":false,"family":"Wyss","given":"Lance","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720940,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clemens, Benjamin J.","contributorId":195098,"corporation":false,"usgs":false,"family":"Clemens","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":720941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitlock, Steven L.","contributorId":171705,"corporation":false,"usgs":false,"family":"Whitlock","given":"Steven","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":720942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":717382,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169948,"text":"ofr20161056 - 2016 - Construction, calibration, and validation of the RBM10 water temperature model for the Trinity River, northern California","interactions":[],"lastModifiedDate":"2016-04-01T08:35:51","indexId":"ofr20161056","displayToPublicDate":"2016-03-31T17:00:00","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":"2016-1056","title":"Construction, calibration, and validation of the RBM10 water temperature model for the Trinity River, northern California","docAbstract":"We constructed a one-dimensional daily averaged water-temperature model to simulate Trinity River temperatures for 1980–2013. The purpose of this model is to assess effects of water-management actions on water temperature and to provide water temperature inputs for a salmon population dynamics model. Simulated meteorological data, observed streamflow data, and observed water temperatures were used as model inputs to simulate a continuous 34-year time series of historical daily mean water temperature at eight locations along 112.2 river miles from Lewiston Dam near Weaverville, California, downstream to the Klamath River confluence. To demonstrate the utility of the model to inform management actions, we simulated three management alternatives to assess the effects of bypass flow augmentation in a drought year, 1994, and compared those results to the simulated historical baseline, referred to as the “No Action” alternative scenario. Augmentation flows from the Lewiston Dam bypass consist of temperature-controlled releases capable of cooling downstream water temperatures in hot times of the year, which can reduce the probability of disease outbreaks in fish populations. Outputs from the Trinity River water-temperature model were then used as inputs to an existing water-temperature model of the Klamath River to evaluate the effect of augmentation flow releases on water temperatures in the lower Klamath River.
\nWe structured the Trinity River water-temperature model in River Basin Model-10 (RBM10), which uses a simple equilibrium flow model, assuming discharge in each river segment on each day is transmitted downstream instantaneously. The model uses a heat-budget formulation to quantify heat flux at the air-water interface. Inputs for the heat budget are calculated from daily mean meteorological data, including net shortwave solar radiation, net longwave atmospheric radiation, air temperature, wind speed, vapor pressure, and a psychrometric constant needed to calculate the Bowen ratio. The modeling domain was divided into eight reaches ranging in length from 8.8 to 20.6 miles, which were calibrated and validated separately with observed water temperature data collected irregularly from 1980 to 2013. Root mean square errors of observed and simulated water temperatures for the eight reaches ranged from 0.25 to 1.12 degrees Celsius (°C). Mean absolute errors ranged from 0.18 to 0.89 °C. For model validation, a k-fold cross-validation technique was used. Validation root mean square error and mean absolute error for the eight reaches ranged from 0.24 to 1.11 °C and from 0.18 to 0.89 °C, respectively.
\nAugmentation scenarios were based on historical hydrological and meteorological data, combined with prescribed flow and temperature releases from Lewiston Dam provided by the Bureau of Reclamation. Water releases were scheduled to achieve targeted flows of 2,500, 2,800, and 3,200 cubic feet per second in the lower Klamath River from mid-August through late September, coinciding with the upstream migration of adult fall-run Chinook salmon (Oncorhynchus tshawytscha). Water temperatures simulated at river mile 5.7 on the Klamath River showed a 5 °C decrease from the No Action historical baseline, which was near or greater than 23 °C when augmentation began in mid-August. Thereafter, an approximate 1 °C difference among augmentation scenarios emerged, with the decrease in water temperature commensurate to the level of augmentation. All augmentation scenarios simulated water temperatures equal to or less than 21 °C from mid-August through late September. Water temperatures equal to or greater than 23 °C are of particular interest because of a thermal threshold known to inhibit upstream migration of salmon. When temperatures exceed this approximate 23 °C threshold, Chinook salmon are known to congregate in high densities in thermal refugias and show extended residence times, which can potentially trigger epizootic outbreaks such as of Ichthyophthirius multifiliis (“Ich”) and Flavobacterium columnare (“Columnaris”) that were the causative factors of the Klamath River fish kill in 2002. A model with the ability to simulate water temperatures in response to management actions at the basin scale is a valuable asset for water managers who must make decisions about how best to use limited water resources, which directly affect the state of fisheries in the Klamath Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161056","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Bureau of Reclamation","usgsCitation":"Jones, E.C., Perry, R.W., Risley, J.C., Som, N.A., and Hetrick, N.J., 2016, Construction, calibration, and validation of the RBM10 water temperature model for the Trinity River, northern California: U.S. Geological Survey Open-File Report 2016–1056, 46 p., https://dx.doi.org/10.3133/ofr20161056.","productDescription":"vi, 46 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070848","costCenters":[{"id":654,"text":"Western Fisheries Research 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U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
The U.S. Geological Survey (USGS) South Atlantic Water Science Center (SAWSC) Georgia office, in cooperation with local, State, and other Federal agencies, maintains a long-term hydrologic monitoring network of more than 350 real-time, continuous-record, streamflow-gaging stations (streamgages). The network includes 14 real-time lake-level monitoring stations, 72 real-time surface-water-quality monitors, and several water-quality sampling programs. Additionally, the SAWSC Georgia office operates more than 204 groundwater monitoring wells, 39 of which are real-time. The wide-ranging coverage of streamflow, reservoir, and groundwater monitoring sites allows for a comprehensive view of hydrologic conditions across the State. One of the many benefits this monitoring network provides is a spatially distributed overview of the hydrologic conditions of creeks, rivers, reservoirs, and aquifers in Georgia.
Streamflow and groundwater data are verified throughout the year by USGS hydrographers and made available to water-resource managers, recreationists, and Federal, State, and local agencies. Hydrologic conditions are determined by comparing the statistical analyses of data collected during the current water year to historical data. Changing hydrologic conditions underscore the need for accurate, timely data to allow informed decisions about the management and conservation of Georgia’s water resources for agricultural, recreational, ecological, and water-supply needs and in protecting life and property.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163016","usgsCitation":"Knaak, A.E., Ankcorn, P.D., and Peck, M.F., 2016, Normal streamflows and water levels continue—Summary of hydrologic conditions in Georgia, 2014: U.S. Geological Survey Fact Sheet 2016–3016, 4 p., https://dx.doi.org/10.3133/fs20163016.","productDescription":"4 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070931","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":319376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3016/fs20163016.pdf","text":"Report","size":"4.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3016"},{"id":319375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3016/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Atlantic coastal bays of the US are essential habitat for young of year bluefish (Pomatomus saltatrix). Their residence in these estuaries during critical life stages, high lipid content, and piscivory make bluefish an ideal bioindicator species for evaluating estuarine health. Individual whole fish from four estuaries impacted by Hurricane Sandy were collected in August 2013, analyzed for a suite of persistent organic pollutants (POPs) including polychlorinated biphenyls, polybrominated diphenyl ethers and organochlorine pesticides and evaluated using health metrics. Concentrations in whole bluefish differed by estuary; however, concentrations for many POPs decreased or were similar to those observed prior to the hurricane. Prevalence of the ectoparasitic gill isopod (Lironeca ovalis) varied by estuary and no relationships between contaminants and lesions were observed. Bluefish should be considered for monitoring programs and, if sampled frequently, could be an effective bioindicator of incremental and episodic changes in contaminants within aquatic food webs.
","language":"English","publisher":"Elsevier Science","doi":"10.1016/j.marpolbul.2016.03.019","usgsCitation":"Smalling, K., Deshpande, A.D., Blazer, V., Bruce W Dockum, DeMond Timmons, Beth L. 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In 2015, the network included about 200 real-time streamgages (hereafter referred to as “gages”), 12 real-time reservoir-level monitoring stations, and 30 groundwater-level monitoring wells. These data and associated analyses provide a unique overview of hydrologic conditions and help improve the understanding of Kansas’s water resources.
Real-time data are verified by the USGS throughout the year with regular measurements of streamflow, lake levels, and groundwater levels. These data are used in protecting life and property; and managing water resources for agricultural, industrial, public supply, ecological, and recreational purposes. Yearly hydrologic conditions are characterized by comparing statistical analyses of current and historical water year (WY) data for the period of record. A WY is the 12-month period from October 1 through September 30 and is designated by the year in which it ends.
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\"}}]}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, Kansas 66049
The permafrost component of the cryosphere is changing dramatically, but the permafrost region is not well monitored and the consequences of change are not well understood. Changing permafrost interacts with ecosystems and climate on various spatial and temporal scales. The feedbacks resulting from these interactions range from local impacts on topography, hydrology, and biology to complex influences on global scale biogeochemical cycling. This review contributes to this focus issue by synthesizing its 28 multidisciplinary studies which provide field evidence, remote sensing observations, and modeling results on various scales. We synthesize study results from a diverse range of permafrost landscapes and ecosystems by reporting key observations and modeling outcomes for permafrost thaw dynamics, identifying feedbacks between permafrost and ecosystem processes, and highlighting biogeochemical feedbacks from permafrost thaw. We complete our synthesis by discussing the progress made, stressing remaining challenges and knowledge gaps, and providing an outlook on future needs and research opportunities in the study of permafrost–ecosystem–climate interactions.
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Relatively few of these assessments, however, have involved the use of process-based simulations of contaminant transport and fate in the subsurface, or compared the predictions from such models with measured data—especially over regional to national scales. To address this need, a process-based groundwater vulnerability assessment (P-GWAVA) system was constructed to use transport-and-fate simulations to predict the concentration of any surface-derived compound at a specified depth in the vadose zone anywhere in the conterminous United States. The system was then used to simulate the concentrations of selected agrichemicals in the vadose zone beneath agricultural areas in multiple locations across the conterminous United States. The simulated concentrations were compared with measured concentrations of the compounds detected in shallow groundwater (that is, groundwater drawn from within a depth of 6.3 ± 0.5 meters [mean ± 95 percent confidence interval] below the water table) in more than 1,400 locations across the United States. The results from these comparisons were used to select the simulation approaches that led to the closest agreement between the simulated and the measured concentrations.
The P-GWAVA system uses computer simulations that account for a broader range of the hydrologic, physical, biological and chemical phenomena known to control the transport and fate of solutes in the subsurface than has been accounted for by any other vulnerability assessment over regional to national scales. Such phenomena include preferential transport and the influences of temperature, soil properties, and depth on the partitioning, transport, and transformation of pesticides in the subsurface. Published methods and detailed soil property data are used to estimate a wide range of model input parameters for each site, including surface albedo, surface crust permeability, soil water content, Brooks-Corey parameters, saturated hydraulic conductivity, macroporosity and sizes of microbial populations, as well as solute partition coefficients, reaction rates, and meso-micropore diffusion rates. To ensure geographic consistency among the predictions, the only site-specific input data that are used are those that are available for all of the 48 conterminous states.
","language":"English","publisher":"U.S Geological Survey","publisherLocation":"Reston, V.A","doi":"10.3133/sir20145189","collaboration":"Prepared in cooperation with National Water-Quality Assessment Program","usgsCitation":"Barbash, J.E., and Voss, F.D., 2016, Design and testing of a process-based groundwater vulnerability assessment (P-GWAVA) system for predicting concentrations of agrichemicals in groundwater across the United States: U.S. Geological Survey Scientific Investigations Report 2014–5189, 210 p., https://dx.doi.org/10.3133/sir20145189.","productDescription":"xvi, 210 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044178","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":316519,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5189/sir20145189.pdf","text":"Report","size":"7.9 MB","description":"SIR 2014-5189 Report 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U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre-1970] and contemporary [post-2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet–dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2092","usgsCitation":"Post van der Burg, M., Anteau, M.J., McCauley, L.A., and Wiltermuth, M.T., 2016, A Bayesian approach for temporally scaling climate for modeling ecological systems: Ecology and Evolution, v. 6, no. 9, p. 2978-2987, https://doi.org/10.1002/ece3.2092.","productDescription":"10 p.","startPage":"2978","endPage":"2987","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063141","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471122,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2092","text":"Publisher Index Page"},{"id":319621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"9","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-28","publicationStatus":"PW","scienceBaseUri":"56fceaabe4b0a6037df29c96","contributors":{"authors":[{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":625616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":625618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCauley, Lisa A. lmccauley@usgs.gov","contributorId":5048,"corporation":false,"usgs":true,"family":"McCauley","given":"Lisa","email":"lmccauley@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":625617,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":625619,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170378,"text":"70170378 - 2016 - Trophic magnification of organic chemicals: A global synthesis","interactions":[],"lastModifiedDate":"2018-08-07T12:11:16","indexId":"70170378","displayToPublicDate":"2016-03-25T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Trophic magnification of organic chemicals: A global synthesis","docAbstract":"Production of organic chemicals (OCs) is increasing exponentially, and some OCs biomagnify through food webs to potentially toxic levels. Biomagnification under field conditions is best described by trophic magnification factors (TMFs; per trophic level change in log-concentration of a chemical) which have been measured for more than two decades. Syntheses of TMF behavior relative to chemical traits and ecosystem properties are lacking. We analyzed >1500 TMFs to identify OCs predisposed to biomagnify and to assess ecosystem vulnerability. The highest TMFs were for OCs that are slowly metabolized by animals (metabolic rate kM < 0.01 day–1) and are moderately hydrophobic (log KOW 6–8). TMFs were more variable in marine than freshwaters, unrelated to latitude, and highest in food webs containing endotherms. We modeled the probability that any OC would biomagnify as a combined function of KOW and kM. Probability is greatest (∼100%) for slowly metabolized compounds, regardless of KOW, and lowest for chemicals with rapid transformation rates (kM > 0.2 day–1). This probabilistic model provides a new global tool for screening existing and new OCs for their biomagnification potential.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.6b00201","usgsCitation":"Walters, D., Jardine, T., Cade, B.S., Kidd, K., Muir, D., and Leipzig-Scott, P.C., 2016, Trophic magnification of organic chemicals: A global synthesis: Environmental Science & Technology, v. 50, no. 9, p. 4650-4658, https://doi.org/10.1021/acs.est.6b00201.","productDescription":"9 p.","startPage":"4650","endPage":"4658","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071917","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":320332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-20","publicationStatus":"PW","scienceBaseUri":"5718a852e4b0ef3b7caba67d","contributors":{"authors":[{"text":"Walters, David 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":147135,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":627031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jardine, T.D.","contributorId":168698,"corporation":false,"usgs":false,"family":"Jardine","given":"T.D.","email":"","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":627032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cade, Brian S. 0000-0001-9623-9849 cadeb@usgs.gov","orcid":"https://orcid.org/0000-0001-9623-9849","contributorId":1278,"corporation":false,"usgs":true,"family":"Cade","given":"Brian","email":"cadeb@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":627033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kidd, K.A.","contributorId":168699,"corporation":false,"usgs":false,"family":"Kidd","given":"K.A.","email":"","affiliations":[{"id":18889,"text":"University of New Brunswick","active":true,"usgs":false}],"preferred":false,"id":627034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muir, D.C.G.","contributorId":168700,"corporation":false,"usgs":false,"family":"Muir","given":"D.C.G.","email":"","affiliations":[{"id":6779,"text":"Environment Canada, Burlington, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":627035,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leipzig-Scott, Peter C. pleipzig-scott@usgs.gov","contributorId":5661,"corporation":false,"usgs":true,"family":"Leipzig-Scott","given":"Peter","email":"pleipzig-scott@usgs.gov","middleInitial":"C.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":627036,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174999,"text":"70174999 - 2016 - Crude oil metabolites in groundwater at two spill sites","interactions":[],"lastModifiedDate":"2018-08-06T13:12:27","indexId":"70174999","displayToPublicDate":"2016-03-24T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Crude oil metabolites in groundwater at two spill sites","docAbstract":"Two groundwater plumes in north central Minnesota with residual crude oil sources have 20 to 50 mg/L of nonvolatile dissolved organic carbon (NVDOC). These values are over 10 times higher than benzene and two to three times higher than Diesel Range Organics in the same wells. On the basis of previous work, most of the NVDOC consists of partial transformation products from the crude oil. Monitoring data from 1988 to 2015 at one of the sites located near Bemidji, MN show that the plume of metabolites is expanding toward a lakeshore located 335 m from the source zone. Other mass balance studies of the site have demonstrated that the plume expansion is driven by the combined effect of continued presence of the residual crude oil source and depletion of the electron accepting capacity of solid phase iron oxide and hydroxides on the aquifer sediments. These plumes of metabolites are not covered by regulatory monitoring and reporting requirements in Minnesota and other states. Yet, a review of toxicology studies indicates that polar metabolites of crude oil may pose a risk to aquatic and mammalian species. Together the results suggest that at sites where residual sources are present, monitoring of NVDOC may be warranted to evaluate the fates of plumes of hydrocarbon transformation products.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12419","usgsCitation":"Bekins, B.A., Cozzarelli, I.M., Erickson, M., Steenson, R., and Thorn, K.A., 2016, Crude oil metabolites in groundwater at two spill sites: Groundwater, v. 54, no. 5, p. 681-691, https://doi.org/10.1111/gwat.12419.","productDescription":"11 p.","startPage":"681","endPage":"691","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072648","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":325698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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• Hydrologic and hydraulic flood modeling
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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
The U.S. Geological Survey (USGS) has many ongoing and recent water-related natural hazard activities in New England that can be used to help mitigate the effects of natural hazards in cooperation with other agencies. The themes related to potential hazards and the tools and science to better understand and address them include the following:
\nErosion and landslides
• Fluvial erosion (sediment transport, bridge scour, and bankfull channel geometry characterization)
• Current and historic landslide mapping
Flood documentation and assessment
• Flood high-water marks
• Flood modeling and frequency analysis
• Flood inundation mapping
• Peak-flow regression equations
Drought documentation and assessment
• Drought frequency analysis
• Low-flow frequency and flow duration statistics
• Water use and availability during drought
Hydrologic monitoring
• Streamflow monitoring network
• Groundwater monitoring network
• Tidal monitoring network
• Snow surveys and ice jam monitoring
Tools for natural hazard assessment and mitigation
• Light detection and ranging (lidar) remote sensing technology
• StreamStats Web-based tool for streamflow statistics
• Flood inundation mapper
Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
The U.S. Geological Survey (USGS) has actively pursued research in the effects of climate change on the hydrology of New England. Ongoing focus areas of climate change science activities of the USGS in New England include the following:
\n• Hydrologic climate-response data (initiating or expanding long-term hydrologic climate-response data collection networks to detect and monitor climate-related changes in hydrology)
• Relations between historical climatic and hydrologic variation (investigating historic relations between long-term climatic variation and hydrologic variation and connecting these relations to future conditions as forecasted by the Interagency Panel on Climate Change (Nakićenović and others, 2000)
• Hydrologic change on natural and human (incorporating climate change scenarios into assessments of how flows in streams or water levels in aquifers may change)
• Relations between climatic and hydrologic variation (characterizing impacts of climate change on floods and droughts, the long-term availability of water supplies for societal and natural uses in response to climate changes)
• Developing tools to forecast ecosystem change and water resources management (developing regionally consistent tools for forecasting ecosystem change and resource management)
This fact sheet presents recent climate change investigations of the USGS in New England using selected recent publications. These publications highlight the broad spectrum of expertise and commitment to understanding the relations of climate change and water resources in New England.
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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
Habitat has changed unfavorably during the past 150 y for the desert tortoise Gopherus agassizii, a federally threatened species with declining populations in the Mojave Desert and western Sonoran Desert. To support recovery efforts, we synthesized published information on relationships of desert tortoises with three habitat features (cover sites, forage, and soil) and candidate management practices for improving these features for tortoises. In addition to their role in soil health and facilitating recruitment of annual forage plants, shrubs are used by desert tortoises for cover and as sites for burrows. Outplanting greenhouse-grown seedlings, protected from herbivory, has successfully restored (>50% survival) a variety of shrubs on disturbed desert soils. Additionally, salvaging and reapplying topsoil using effective techniques is among the more ecologically beneficial ways to initiate plant recovery after severe disturbance. Through differences in biochemical composition and digestibility, some plant species provide better-quality forage than others. Desert tortoises selectively forage on particular annual and herbaceous perennial species (e.g., legumes), and forage selection shifts during the year as different plants grow or mature. Nonnative grasses provide low-quality forage and contribute fuel to spreading wildfires, which damage or kill shrubs that tortoises use for cover. Maintaining a diverse “menu” of native annual forbs and decreasing nonnative grasses are priorities for restoring most desert tortoise habitats. Reducing herbivory by nonnative animals, carefully timing herbicide applications, and strategically augmenting annual forage plants via seeding show promise for improving tortoise forage quality. Roads, another disturbance, negatively affect habitat in numerous ways (e.g., compacting soil, altering hydrology). Techniques such as recontouring road berms to reestablish drainage patterns, vertical mulching (“planting” dead plant material), and creating barriers to prevent trespasses can assist natural recovery on decommissioned backcountry roads. Most habitat enhancement efforts to date have focused on only one factor at a time (e.g., providing fencing) and have not included proactive restoration activities (e.g., planting native species on disturbed soils). A research and management priority in recovering desert tortoise habitats is implementing an integrated set of restorative habitat enhancements (e.g., reducing nonnative plants, improving forage quality, augmenting native perennial plants, and ameliorating altered hydrology) and monitoring short- and long-term indicators of habitat condition and the responses of desert tortoises to habitat restoration.
","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington, D.C.","doi":"10.3996/052015-JFWM-046","usgsCitation":"Abella, S.R., and Berry, K.H., 2016, Enhancing and restoring habitat for the desert tortoise: Journal of Fish and Wildlife Management, v. 7, no. 1, p. 255-279, https://doi.org/10.3996/052015-JFWM-046.","productDescription":"25 p.","startPage":"255","endPage":"279","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066485","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488430,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/052015-jfwm-046","text":"Publisher Index Page"},{"id":319189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.027099609375,\n 37.32648861334206\n ],\n [\n -113.75244140624999,\n 37.42252593456307\n ],\n [\n -113.521728515625,\n 37.33522435930641\n ],\n [\n -113.48876953125,\n 37.055177106660814\n ],\n [\n -113.5986328125,\n 36.4566360115962\n ],\n [\n -113.73046875,\n 36.1822249804225\n ],\n [\n -113.79638671875,\n 35.951329861522666\n ],\n [\n -113.895263671875,\n 35.60371874069731\n ],\n [\n -113.675537109375,\n 35.23664622093195\n ],\n [\n -113.51074218749999,\n 35.074964853989556\n ],\n [\n -113.44482421875,\n 34.97600151317591\n ],\n [\n -113.18115234375,\n 34.66032236481892\n ],\n [\n -113.203125,\n 34.379712580462204\n ],\n [\n -113.466796875,\n 34.19817309627726\n ],\n [\n -113.88427734374999,\n 34.125447565116126\n ],\n [\n -114.36767578124999,\n 34.03445260967645\n ],\n [\n -115.13671875,\n 34.17090836352573\n ],\n [\n -115.15869140624999,\n 33.8430453147447\n ],\n [\n -114.664306640625,\n 33.486435450999885\n ],\n [\n -114.81811523437501,\n 33.14675022877648\n ],\n [\n -115.04882812499999,\n 32.94414888814148\n ],\n [\n -115.3564453125,\n 33.119150226768866\n ],\n [\n -115.521240234375,\n 33.330528249028085\n ],\n [\n -116.114501953125,\n 33.779147331286474\n ],\n [\n -116.38916015624999,\n 33.90689555128866\n ],\n [\n -117.22412109375,\n 34.19817309627726\n ],\n [\n -117.630615234375,\n 34.15272698011818\n ],\n [\n -118.02612304687499,\n 34.14363482031264\n ],\n [\n -118.38867187500001,\n 34.288991865037524\n ],\n [\n -118.65234374999999,\n 34.52466147177172\n ],\n [\n -118.80615234374999,\n 34.75966612466248\n ],\n [\n -118.223876953125,\n 35.16482750605027\n ],\n [\n -118.487548828125,\n 35.39800594715108\n ],\n [\n -118.443603515625,\n 35.6126508187567\n ],\n [\n -118.14697265625,\n 35.7286770448517\n ],\n [\n -117.98217773437499,\n 35.639441068973916\n ],\n [\n -117.850341796875,\n 35.64836915737426\n ],\n [\n -117.98217773437499,\n 36.05798104702501\n ],\n [\n -118.048095703125,\n 36.38591277287651\n ],\n [\n -118.21289062499999,\n 36.5978891330702\n ],\n [\n -118.333740234375,\n 37.02886944696474\n ],\n [\n -118.35571289062499,\n 37.25656608611523\n ],\n [\n -118.0810546875,\n 37.23907530202184\n ],\n [\n -117.938232421875,\n 37.448696585910376\n ],\n [\n -117.740478515625,\n 37.56199695314352\n ],\n [\n -117.57568359374999,\n 37.49229399862877\n ],\n [\n -117.2900390625,\n 37.26530995561875\n ],\n [\n -116.79565429687499,\n 37.274052809979054\n ],\n [\n -116.5869140625,\n 37.25656608611523\n ],\n [\n -116.49902343749999,\n 37.204081555898526\n ],\n [\n -116.15844726562501,\n 37.16907157713011\n ],\n [\n -115.927734375,\n 37.142803443716836\n ],\n [\n -115.51025390625,\n 37.38761749978395\n ],\n [\n -114.993896484375,\n 37.24782120155428\n ],\n [\n -114.54345703125,\n 37.25656608611523\n ],\n [\n -114.3017578125,\n 37.212831514455964\n ],\n [\n -114.027099609375,\n 37.32648861334206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-01","publicationStatus":"PW","scienceBaseUri":"56f25e98e4b0f59b85de6ff1","contributors":{"authors":[{"text":"Abella, Scott R.","contributorId":103940,"corporation":false,"usgs":true,"family":"Abella","given":"Scott","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":623207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":623206,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159388,"text":"sir20155152 - 2016 - Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska","interactions":[],"lastModifiedDate":"2016-03-22T10:17:15","indexId":"sir20155152","displayToPublicDate":"2016-03-22T00:00:00","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":"2015-5152","title":"Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska","docAbstract":"Digital flood-inundation maps for a 12.5-mile reach of the Big Papillion Creek from 0.6 mile upstream from the State Street Bridge to the 72nd Street Bridge in Omaha, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the Papio-Missouri River Natural Resources District. 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 Big Papillion Creek at Fort Street at Omaha, Nebraska (station 06610732). 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 Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at this site.
\nFlood profiles were computed for the 12.5-mile reach by means of a one-dimensional step-backwater model. The model was calibrated by using the current (2015) stage-discharge relation at streamgages for the Big Papillion Creek at Fort Street at Omaha, Nebraska, and the Big Papillion Creek at Q Street at Omaha, Nebraska. The hydraulic model was then used to compute 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum for the Big Papillion Creek at Fort Street and ranging from 18 ft (or near bankfull) to 32 ft, which exceeds the “major flood stage” as defined by the National Weather Service. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging data having a 1.18-ft vertical accuracy and 3.28-ft horizontal resolution) to delineate the area flooded at each flood stage (water level).
\nThe availability of these flood-inundation maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155152","collaboration":"Prepared in cooperation with the Papio-Missouri River Natural Resources District","usgsCitation":"Strauch, K.R., Dietsch, B.J., and Anderson, K.J., 2016, Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska: U.S. Geological Survey Scientific Investigations Report 2015–5152, 11 p., https://dx.doi.org/10.3133/sir20155152.","productDescription":"Report: v, 11 p.; Datasets; Metadata","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066029","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":314625,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_river_areas_GRIDS.zip","text":"River area GRIDS","size":"52.9 MB","description":"SIR 2015–5152 River area GRIDS"},{"id":314626,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_river_areas_shapefiles.zip","text":"River area shapefiles","size":"2.2 MB","description":"SIR 2015–5152 River area shapefiles"},{"id":314628,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_metadata_BigPapio_at_Fort_FIM_GRID.txt","text":"GRID metadata","size":"20.0 kb","description":"SIR 2015–5152 GRID metadata"},{"id":314629,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_metadata_BigPapio_at_Fort_FIM_shapefile.txt","text":"Shapefile metadata","size":"20.0 kb","description":"SIR 2015–5152 Shapefile metadata"},{"id":314466,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152.pdf","text":"Report","size":"2.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5152"},{"id":314622,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_levee_areas_GRIDS.zip","text":"Levee area GRIDS","size":"1.6 MB","description":"SIR 2015–5152 Levee area GRIDS"},{"id":314623,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_levee_areas_shapefiles.zip","text":"Levee area shapefiles","size":"144 kb","description":"SIR 2015–5152 Levee area shapefiles"},{"id":314465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5152/coverthb.jpg"}],"country":"United States","state":"Nebraska","city":"Omaha","otherGeospatial":"Big Papillion Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.16676330566406,\n 41.23702755320388\n ],\n [\n -96.16676330566406,\n 41.35052580597025\n ],\n [\n -96.01020812988281,\n 41.35052580597025\n ],\n [\n -96.01020812988281,\n 41.23702755320388\n ],\n [\n -96.16676330566406,\n 41.23702755320388\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Urbanization substantially changes the physicochemical and biological characteristics of streams. The trajectory of negative effect is broadly similar around the world, but the nature and magnitude of ecological responses to urban growth differ among locations. Some heterogeneity in response arises from differences in the level of urban development and attributes of urban water management. However, the heterogeneity also may arise from variation in hydrologic, biological, and physicochemical templates that shaped stream ecosystems before urban development. We present a framework to develop hypotheses that predict how natural watershed and channel attributes in the pre-urban-development state may confer ecological resistance to urbanization. We present 6 testable hypotheses that explore the expression of such attributes under our framework: 1) greater water storage capacity mitigates hydrologic regime shifts, 2) coarse substrates and a balance between erosive forces and sediment supply buffer morphological changes, 3) naturally high ionic concentrations and pH pre-adapt biota to water-quality stress, 4) metapopulation connectivity results in retention of species richness, 5) high functional redundancy buffers trophic function from species loss, and 6) landuse history mutes or reverses the expected trajectory of eutrophication. Data from past comparative analyses support these hypotheses, but rigorous testing will require targeted investigations that account for confounding or interacting factors, such as diversity in urban infrastructure attributes. Improved understanding of the susceptibility or resistance of stream ecosystems could substantially strengthen conservation, management, and monitoring efforts in urban streams. We hope that these preliminary, conceptual hypotheses will encourage others to explore these ideas further and generate additional explanations for the heterogeneity observed in urban streams.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/684839","usgsCitation":"Utz, R.M., Hopkins, K., Beesley, L., Booth, D.B., Hawley, R.J., Baker, M.E., Freeman, M., and Jones, K.L., 2016, Ecological resistance in urban streams: the role of natural and legacy attributes: Freshwater Science, v. 35, no. 1, p. 380-397, https://doi.org/10.1086/684839.","productDescription":"18 p.","startPage":"380","endPage":"397","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066391","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":318934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56ebc71be4b0f59b85d99410","contributors":{"authors":[{"text":"Utz, Ryan M.","contributorId":167572,"corporation":false,"usgs":false,"family":"Utz","given":"Ryan","email":"","middleInitial":"M.","affiliations":[{"id":24756,"text":"Chatham University, Pittsburg PA","active":true,"usgs":false}],"preferred":false,"id":622742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hopkins, Kristina G.","contributorId":167573,"corporation":false,"usgs":false,"family":"Hopkins","given":"Kristina G.","affiliations":[{"id":24757,"text":"University of Maryland, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":622743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beesley, Leah","contributorId":146250,"corporation":false,"usgs":false,"family":"Beesley","given":"Leah","email":"","affiliations":[{"id":16644,"text":"Centre of Excellence in Natural Resource Management, University of Western Australia,","active":true,"usgs":false}],"preferred":false,"id":622744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Booth, Derek B.","contributorId":100873,"corporation":false,"usgs":false,"family":"Booth","given":"Derek","email":"","middleInitial":"B.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":622745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hawley, Robert J.","contributorId":167574,"corporation":false,"usgs":false,"family":"Hawley","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":24758,"text":"Sustainable Streams, LLC, Louisville, KY","active":true,"usgs":false}],"preferred":false,"id":622746,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baker, Matthew E.","contributorId":149189,"corporation":false,"usgs":false,"family":"Baker","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":17665,"text":"Department of Geography and Environmental Systems, University of Maryland, Baltimore County, Baltimore, Maryland, US","active":true,"usgs":false}],"preferred":false,"id":622747,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":622741,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jones, Krista L. 0000-0002-0301-4497 kljones@usgs.gov","orcid":"https://orcid.org/0000-0002-0301-4497","contributorId":4550,"corporation":false,"usgs":true,"family":"Jones","given":"Krista","email":"kljones@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622748,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70168418,"text":"sir20165021 - 2016 - Groundwater hydrology and estimation of horizontal groundwater flux from the Rio Grande at selected locations in Albuquerque, New Mexico, 2009–10","interactions":[],"lastModifiedDate":"2016-03-18T08:13:50","indexId":"sir20165021","displayToPublicDate":"2016-03-17T00:00:00","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":"2016-5021","title":"Groundwater hydrology and estimation of horizontal groundwater flux from the Rio Grande at selected locations in Albuquerque, New Mexico, 2009–10","docAbstract":"The Albuquerque area of New Mexico has two principal sources of water: (1) groundwater from the Santa Fe Group aquifer system, and (2) surface water from the Rio Grande. From 1960 to 2002, pumping from the Santa Fe Group aquifer system caused groundwater levels to decline more than 120 feet while water-level declines along the Rio Grande in Albuquerque were generally less than 40 feet. These differences in water-level declines in the Albuquerque area have resulted in a great deal of interest in quantifying the river-aquifer interaction associated with the Rio Grande.
In 2003, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, acting as fiscal agent for the Middle Rio Grande Endangered Species Collaborative Program, and the U.S. Army Corps of Engineers, began a study to characterize the hydrogeology of the Rio Grande inner valley alluvial aquifer in the Albuquerque area of New Mexico. The study provides hydrologic data in order to enhance the understanding of rates of water leakage from the Rio Grande to the alluvial aquifer, groundwater flow through the aquifer, and discharge of water from the aquifer to riverside drains. The study area extends about 20 miles along the Rio Grande in the Albuquerque area. Piezometers and surface-water gages were installed in paired transects at eight locations. Nested piezometers, completed at various depths in the alluvial aquifer, and surface-water gages, installed in the Rio Grande and riverside drains, were instrumented with pressure transducers. Water-level and water-temperature data were collected from 2009 to 2010.
Water levels from the piezometers indicated that groundwater movement was usually away from the river towards the riverside drains. Annual mean horizontal groundwater gradients in the inner valley alluvial aquifer ranged from 0.0024 (I-25 East) to 0.0144 (Pajarito East). The median hydraulic conductivity values of the inner valley alluvial aquifer, determined from slug tests, ranged from 30 feet per day (ft/d) (Montaño) to 120 ft/d (Central) for paired transects, with a median hydraulic conductivity for all transects of 50 ft/d. Daily mean groundwater fluxes from the river through the inner valley alluvial aquifer computed using Darcy’s Law and the slug test results ranged from about 0.01 ft/d (Montaño West) to between 1.0 and 2.0 ft/d (Central East). Median annual groundwater fluxes from the river through the inner valley alluvial aquifer determined using the Suzuki-Stallman method was greatest at Alameda East (0.50 ft/d) and lowest at Alameda West (0.25 ft/d). The results from both methods agreed reasonably well.
Seepage investigations conducted by measuring discharge in the east and west riverside drains provided information for computing changes in flow within the drains and for evaluating results from Darcy’s Law and Suzuki-Stallman method flux calculations. Discharge measured in the east riverside drain between the Barelas Bridge and the I-25 bridge indicated that the flow in the east riverside drain increased by an average of 56.5 cubic feet per day per linear foot (ft3/d/ft) of drain. Discharge measured in the west riverside drain between the Central bridge and the I-25 bridge indicated that flow increased between west drain miles 0 and 4, an average of 53.8 ft3/d/ft of drain, and that flow increased between west drain miles 7 and 10, an average of 44.9 ft3/d/ft of drain. In comparison to the seepage measurement results, the groundwater fluxes from the river through the inner valley alluvial aquifer calculated from Darcy’s Law (qslug) and by the Suzuki-Stallman method (qheat) would account for 20–36 percent or 53–95 percent, respectively, of the total flow in the east riverside drain and 22–31 percent or 19–26 percent, respectively, of the total flow in the west drain. These results indicate that the drains likely also receive water from outside the inner valley.
The spatial variability of horizontal hydraulic gradients and groundwater fluxes can be primarily attributed to variability in the distances between the river and riverside drains throughout the study area and geologic heterogeneities in the alluvial aquifer. Temporal variability in the water levels, which control the horizontal hydraulic gradients and fluxes between the Rio Grande and the riverside drains, can be primarily attributed to seasonal fluctuations in river stage and irrigation practices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165021","collaboration":"Prepared in cooperation with Bureau of Reclamation acting as fiscal agent for the Middle Rio Grande Endangered Species Collaborative Program","usgsCitation":"Rankin, D.R., Oelsner, G.P., McCoy, K.J., Moret, G.J.M., Worthington, J.A., and Bandy-Baldwin, K.M., 2016, Groundwater hydrology and estimation of horizontal groundwater flux from the Rio Grande at selected locations in Albuquerque, New Mexico, 2009–10: U.S. Geological Survey Scientific Investigations Report 2016–5021, 89 p., https://dx.doi.org/10.3133/sir20165021.","productDescription":"viii, 89 p.","numberOfPages":"101","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-033038","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":318926,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5021/sir20165021.pdf","text":"Report","size":"5.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5021"},{"id":318925,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5021/coverthb.jpg"}],"country":"United States","state":"New Mexico","city":"Albuquerque","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.7266845703125,\n 34.95011635301367\n ],\n [\n -106.7266845703125,\n 35.290468565908775\n ],\n [\n -106.56051635742188,\n 35.290468565908775\n ],\n [\n -106.56051635742188,\n 34.95011635301367\n ],\n [\n -106.7266845703125,\n 34.95011635301367\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montogmery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
The biogeochemical cycling of metals and other contaminants in river-floodplain corridors is controlled by microbial activity responding to dynamic redox conditions. Riverine flooding thus has the potential to affect speciation of redox-sensitive metals such as mercury (Hg). Therefore, inundation history over a period of decades potentially holds information on past production of bioavailable Hg. We investigate this within a Northern California river system with a legacy of landscape-scale 19th century hydraulic gold mining. We combine hydraulic modeling, Hg measurements in sediment and biota, and first-order calculations of mercury transformation to assess the potential role of river floodplains in producing monomethylmercury (MMHg), a neurotoxin which accumulates in local and migratory food webs. We identify frequently inundated floodplain areas, as well as floodplain areas inundated for long periods. We quantify the probability of MMHg production potential (MPP) associated with hydrology in each sector of the river system as a function of the spatial patterns of overbank inundation and drainage, which affect long-term redox history of contaminated sediments. Our findings identify river floodplains as periodic, temporary, yet potentially important, loci of biogeochemical transformation in which contaminants may undergo change during limited periods of the hydrologic record. We suggest that inundation is an important driver of MPP in river corridors and that the entire flow history must be analyzed retrospectively in terms of inundation magnitude and frequency in order to accurately assess biogeochemical risks, rather than merely highlighting the largest floods or low-flow periods. MMHg bioaccumulation within the aquatic food web in this system may pose a major risk to humans and waterfowl that eat migratory salmonids, which are being encouraged to come up these rivers to spawn. There is a long-term pattern of MPP under the current flow regime that is likely to be accentuated by increasingly common large floods with extended duration.
","language":"English","publisher":"ScienceDirect","doi":"10.1016/j.scitotenv.2016.03.005","usgsCitation":"Singer, M.B., Harrison, L.R., Donovan, P.M., Blum, J.D., and Marvin-DiPasquale, M.C., 2016, Hydrologic indicators of hot spots and hot moments of mercury methylation potential along river corridors: Science of the Total Environment, v. 568, p. 697-711, https://doi.org/10.1016/j.scitotenv.2016.03.005.","productDescription":"15 p.","startPage":"697","endPage":"711","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071066","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":471145,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.005","text":"Publisher Index Page"},{"id":328234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bear River, Feather River, Sacramento River, Yuba River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.01965332031249,\n 38.13887716726548\n ],\n [\n -122.01965332031249,\n 39.317300373271024\n ],\n [\n -121.2451171875,\n 39.317300373271024\n ],\n [\n -121.2451171875,\n 38.13887716726548\n ],\n [\n -122.01965332031249,\n 38.13887716726548\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"568","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57cd45abe4b0f2f0cec4cb4e","contributors":{"authors":[{"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":647993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Lee R.","contributorId":174322,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":647994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":647995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blum, Joel D.","contributorId":83657,"corporation":false,"usgs":true,"family":"Blum","given":"Joel","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":647996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":647992,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168374,"text":"sir20165024 - 2016 - Estimating flood magnitude and frequency at gaged and ungaged sites on streams in Alaska and conterminous basins in Canada, based on data through water year 2012","interactions":[],"lastModifiedDate":"2022-09-15T18:41:32.475293","indexId":"sir20165024","displayToPublicDate":"2016-03-16T14:00:00","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":"2016-5024","title":"Estimating flood magnitude and frequency at gaged and ungaged sites on streams in Alaska and conterminous basins in Canada, based on data through water year 2012","docAbstract":"Estimates of the magnitude and frequency of floods are needed across Alaska for engineering design of transportation and water-conveyance structures, flood-insurance studies, flood-plain management, and other water-resource purposes. This report updates methods for estimating flood magnitude and frequency in Alaska and conterminous basins in Canada. Annual peak-flow data through water year 2012 were compiled from 387 streamgages on unregulated streams with at least 10 years of record. Flood-frequency estimates were computed for each streamgage using the Expected Moments Algorithm to fit a Pearson Type III distribution to the logarithms of annual peak flows. A multiple Grubbs-Beck test was used to identify potentially influential low floods in the time series of peak flows for censoring in the flood frequency analysis.
For two new regional skew areas, flood-frequency estimates using station skew were computed for stations with at least 25 years of record for use in a Bayesian least-squares regression analysis to determine a regional skew value. The consideration of basin characteristics as explanatory variables for regional skew resulted in improvements in precision too small to warrant the additional model complexity, and a constant model was adopted. Regional Skew Area 1 in eastern-central Alaska had a regional skew of 0.54 and an average variance of prediction of 0.45, corresponding to an effective record length of 22 years. Regional Skew Area 2, encompassing coastal areas bordering the Gulf of Alaska, had a regional skew of 0.18 and an average variance of prediction of 0.12, corresponding to an effective record length of 59 years. Station flood-frequency estimates for study sites in regional skew areas were then recomputed using a weighted skew incorporating the station skew and regional skew. In a new regional skew exclusion area outside the regional skew areas, the density of long-record streamgages was too sparse for regional analysis and station skew was used for all estimates. Final station flood frequency estimates for all study streamgages are presented for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities.
Regional multiple-regression analysis was used to produce equations for estimating flood frequency statistics from explanatory basin characteristics. Basin characteristics, including physical and climatic variables, were updated for all study streamgages using a geographical information system and geospatial source data. Screening for similar-sized nested basins eliminated hydrologically redundant sites, and screening for eligibility for analysis of explanatory variables eliminated regulated peaks, outburst peaks, and sites with indeterminate basin characteristics. An ordinary least‑squares regression used flood-frequency statistics and basin characteristics for 341 streamgages (284 in Alaska and 57 in Canada) to determine the most suitable combination of basin characteristics for a flood-frequency regression model and to explore regional grouping of streamgages for explaining variability in flood-frequency statistics across the study area. The most suitable model for explaining flood frequency used drainage area and mean annual precipitation as explanatory variables for the entire study area as a region. Final regression equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability discharge in Alaska and conterminous basins in Canada were developed using a generalized least-squares regression. The average standard error of prediction for the regression equations for the various annual exceedance probabilities ranged from 69 to 82 percent, and the pseudo-coefficient of determination (pseudo-R2) ranged from 85 to 91 percent.
The regional regression equations from this study were incorporated into the U.S. Geological Survey StreamStats program for a limited area of the State—the Cook Inlet Basin. StreamStats is a national web-based geographic information system application that facilitates retrieval of streamflow statistics and associated information. StreamStats retrieves published data for gaged sites and, for user-selected ungaged sites, delineates drainage areas from topographic and hydrographic data, computes basin characteristics, and computes flood frequency estimates using the regional regression equations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165024","collaboration":"Prepared in cooperation with the Alaska Department of Transportation and Public Facilities, Alaska Department of Natural Resources, and U.S. Army Corps of Engineers","usgsCitation":"Curran, J.H., Barth, N.A., Veilleux, A.G., and Ourso, R.T., 2016, Estimating flood magnitude and frequency at gaged and ungaged sites on streams in Alaska and conterminous basins in Canada, based on data through water year 2012: U.S. Geological Survey Scientific Investigations Report 2016–5024, 47 p., https://dx.doi.org/10.3133/sir20165024.","productDescription":"Report: vi, 47 p.; 3 Tables; 1 Appendix; Companion File; Database","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-10-01","ipdsId":"IP-068358","costCenters":[{"id":114,"text":"Alaska Science 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2011-2021"},{"id":438632,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JEL0UU","text":"USGS data release","linkHelpText":"Flood Frequency Data and 2020 Observed Flood Probability for Selected Streamgages in the Fortymile River Basin, Alaska, 1911-2020"},{"id":318921,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5024/sir20165024_table09.xlsx","text":"Table 9","size":"78 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":318920,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5024/sir20165024_appendixa.xlsx","text":"Appendix A","size":"99 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":318919,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5024/sir20165024_table04.xlsx","text":"Table 4","size":"88 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U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508-4560
http://alaska.usgs.gov
The Comprehensive Sturgeon Research Project is a multiyear, multiagency collaborative research framework developed to provide information to support pallid sturgeon recovery and Missouri River management decisions. The project strategy integrates field and laboratory studies of sturgeon reproductive ecology, early life history, habitat requirements, and physiology. The project scope of work is developed annually with collaborating research partners and in cooperation with the U.S. Army Corps of Engineers, Missouri River Recovery Program–Integrated Science Program. The project research consists of several interdependent and complementary tasks that involve multiple disciplines.
The project research tasks in the 2014 scope of work emphasized understanding of reproductive migrations and spawning of adult pallid sturgeon and hatch and drift of larvae. These tasks were addressed in three hydrologically and geomorphologically distinct parts of the Missouri River Basin: the Lower Missouri River downstream from Gavins Point Dam, the Upper Missouri River downstream from Fort Peck Dam and downstream reaches of the Milk River, and the Lower Yellowstone River. The project research is designed to inform management decisions related to channel re-engineering, flow modification, and pallid sturgeon population augmentation on the Missouri River and throughout the range of the species. Research and progress made through this project are reported to the U.S. Army Corps of Engineers annually. This annual report details the research effort and progress made by the Comprehensive Sturgeon Research Project during 2014.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161013","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Missouri River Recovery—Integrated Science Program","usgsCitation":"DeLonay, A.J., Chojnacki, K.A., Jacobson, R.B., Braaten, P.J., Buhl, K.J., Elliott, C.M., Erwin, S.O., Faulkner, J.D.A., Candrl, J.S., Fuller, D.B., Backes, K.M., Haddix, T.M., Rugg, M.L., Wesolek, C.J., Eder, B.L., and Mestl, G.E., 2016,\nEcological requirements for pallid sturgeon reproduction and recruitment in the Missouri River—Annual report 2014: U.S. Geological Survey Open-File Report 2016–1013, 131 p., https://dx.doi.org/10.3133/ofr20161013.","productDescription":"xv, 131 p.","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065464","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":318883,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1013/coverthb.jpg"},{"id":318884,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1013/ofr20161013.pdf","text":"Report","size":"24.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1013"}],"country":"United States","state":"Missouri, Montana, Nebraska","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.57812499999999,\n 47.956823800497475\n ],\n [\n -107.57812499999999,\n 48.629278127969414\n ],\n [\n -104.029541015625,\n 48.629278127969414\n ],\n [\n -104.029541015625,\n 47.956823800497475\n ],\n [\n -107.57812499999999,\n 47.956823800497475\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.84423828125,\n 41.054501963290505\n ],\n [\n -97.84423828125,\n 42.956422511073335\n ],\n [\n -95.78979492187499,\n 42.956422511073335\n ],\n [\n -95.78979492187499,\n 41.054501963290505\n ],\n [\n -97.84423828125,\n 41.054501963290505\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.08441162109374,\n 38.52668162061619\n ],\n [\n -93.08441162109374,\n 39.3024245604149\n ],\n [\n -91.67816162109375,\n 39.3024245604149\n ],\n [\n -91.67816162109375,\n 38.52668162061619\n ],\n [\n -93.08441162109374,\n 38.52668162061619\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
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To address concerns about the effects of water-resource management practices and rising sea level on saltwater intrusion, the U.S. Geological Survey in cooperation with the Broward County Environmental Planning and Community Resilience Division, initiated a study to examine causes of saltwater intrusion and predict the effects of future alterations to the hydrologic system on salinity distribution in eastern Broward County, Florida. A three-dimensional, variable-density solute-transport model was calibrated to conditions from 1970 to 2012, the period for which data are most complete and reliable, and was used to simulate historical conditions from 1950 to 2012. These types of models are typically difficult to calibrate by matching to observed groundwater salinities because of spatial variability in aquifer properties that are unknown, and natural and anthropogenic processes that are complex and unknown; therefore, the primary goal was to reproduce major trends and locally generalized distributions of salinity in the Biscayne aquifer. The methods used in this study are relatively new, and results will provide transferable techniques for protecting groundwater resources and maximizing groundwater availability in coastal areas. The model was used to (1) evaluate the sensitivity of the salinity distribution in groundwater to sea-level rise and groundwater pumping, and (2) simulate the potential effects of increases in pumping, variable rates of sea-level rise, movement of a salinity control structure, and use of drainage recharge wells on the future distribution of salinity in the aquifer.
\nResults from the simulation of historical conditions indicate that the model generally represents the observed greater westward extent of elevated salinity in the central part of the intruded area relative to the northern and southernmost parts of the intruded area. Results of sensitivity testing indicate that the extent of elevated salinity is most sensitive to pumping in areas where the source of saltwater is largely offshore, from the Atlantic Ocean, and is most sensitive to sea-level rise in areas where the source of salinity is downward leakage of brackish water from canals.
\nSimulations of future scenarios indicate that increases in pumping near the existing interface may cause the interface to advance and decreases in pumping may cause it to retreat. Climatic effects, such as periods of prolonged drought or high precipitation, may augment or counteract long-term effects of changes in pumping on aquifer salinity at well fields. With increasing rates of sea-level rise, the freshwater-saltwater interface advances progressively inland, and flow-averaged salinities at well fields near the existing interface increase commensurately. Hypothetical southeastward (downstream) re-positioning of the existing G–54 salinity-control structure may prevent the interface from moving northwestward along and near the North New River canal, but beneficial effects are localized. Implementation of freshwater recharge wells in the city of Hallandale Beach may also have only a localized freshening effect in the aquifer and little appreciable effect on the freshwater-saltwater interface or on concentrations of salinity at well fields.
\nModel accuracy and use are limited by uncertainty in the physical properties and boundary conditions of the system, uncertainty in historical and future conditions, and generalizations made in the mathematical relationships used to describe the physical processes of groundwater flow and transport. Because of these limitations, model results should be considered in relative rather than absolute terms. Nonetheless, model results do provide useful information on the relative scale of response of the system to changes in pumping distribution, sea-level rise, and mitigation activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165022","collaboration":"Prepared in cooperation with the Broward County Environmental Planning and Community Resilience Division","usgsCitation":"Hughes, J.D., Sifuentes, D.F., and White, J.T., 2016, Potential effects of alterations to the hydrologic system on the distribution of salinity in the Biscayne aquifer in Broward County, Florida: U.S. Geological Survey Scientific Investigations Report 2016–5022, 114 p., https://dx.doi.org/10.3133/sir20165022.","productDescription":"Report: x, 114 p.; Data Release","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056536","costCenters":[{"id":269,"text":"FLWSC-Ft. 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Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
http://fl.water.usgs.gov/
The U.S. Geological Survey (USGS) collected data and simulated groundwater flow to increase understanding of the hydrology and the effects of drainage alterations on the water table in the vicinity of Great Marsh, near Beverly Shores and Town of Pines, Indiana. Prior land-management practices have modified drainage and caused changes in the distribution of open water, streams and ditches, and groundwater abundance and flow paths.
\nCollected hydrologic data indicate that the majority of water entering Great Marsh flows from the southern dune ridge beneath Town of Pines, Indiana. Groundwater flow is intercepted by Brown Ditch in the eastern portion of the study area and Derby Ditch in the western portion of the study area. A smaller amount of groundwater from the northern dune ridge beneath Beverly Shores also contributed water to Great Marsh. Continuous groundwater-level data collected indicate that the predominant north-south groundwater-flow gradients vary during the course of the year due to increased levels of precipitation or during periods of drainage obstructions. Continuous surface-water discharge and surface-water elevation were measured at three USGS streamgages, one each on Brown, Kintzele and Derby Ditches. The monthly mean discharge statistics indicate that during the period of record— June 2012 to September 2013—streamflow in Kintzele Ditch was lowest during July 2012 and highest during April 2013. In Derby Ditch, streamflow also was lowest during July 2012 and highest during April 2013.
\nPeriods of relatively high and low groundwater levels during August 1982, March 2013, and April 2014 were examined and simulated by using MODFLOW and companion software. Results from the simulation of conditions during March 2013 include that nearly 100 percent of all water entering the area simulating Town of Pines is from recharge. Of all the water simulated to enter the eastern and western portions of Great Marsh, nearly 20 and 18 percent, respectively, flows from Town of Pines to the western and eastern portions of Great Marsh. The dune ridges beneath Town of Pines and to a lesser extent beneath Beverly Shores are a major source of recharge to the surficial aquifer and Great Marsh.
\nResults from the simulation of the conditions of April 2014 include that, despite increases in the amount of water entering Great Marsh due to a beaver-dam-modified hydrologic condition, there is still virtually zero simulated groundwater flow from Great Marsh to Town of Pines. The volume of water simulated to be entering the zone representing Beverly Shores decreased by 0.43 cubic foot per second from the results of the March 2013 simulation. This simulated difference in water budgets can be attributed to increased simulated recharge in Great Marsh and Town of Pines. Effects of the inclusion of the beaver dam included the increase of the simulated water table and simulated inundated area upstream of the beaver dam due to the effects of ponding surface water.
\nResults from the simulation scenario that includes six proposed pool-riffle control structures in Brown Ditch under the hydrologic conditions of March 2013 indicate areas inundated by water are larger, including areas just to the north of the entrance of Brown Ditch into Great Marsh, and areas north of the confluence of Brown and Kintzele Ditches.
\nResults from the scenario simulating the increase of the Lake Michigan water level to the historical high of May 31, 1998, showed inundated areas of Great Marsh south of Beverly Shores enlarged on both sides of Lakeshore County Road with the greatest enlargement simulated to be southeast of the intersection of Lakeshore County Road and Beverly Drive. For the scenario simulating the decrease of the Lake Michigan water level to the historical low of December 23, 2007, results show little change from the original March 2013 inundated area.
\nThe results of this study can be used by water-resource managers to understand how surrounding ditches affect water levels in Great Marsh and other inland wetlands and residential areas. The groundwater model developed can be applied to answer questions about how alterations to the drainage system in the area affects water levels in the public and residential areas surrounding Great Marsh. The modeling methods developed in this study provide a template for other studies of groundwater flow and groundwater/surface-water interactions within the shallow surficial aquifer in northern Indiana, and in similar hydrologic settings that include surficial sand aquifers in coastal areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155141","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Lampe, D.C., 2015, Hydrologic data and groundwater-flow simulations in the Brown Ditch Watershed, Indiana Dunes National Lakeshore, near Beverly Shores and Town of Pines, Indiana: U.S. Geological Survey Scientific Investigations Report 2015– 5141, 97 p., https://dx.doi.org/10.3133/sir20155141.","productDescription":"xi, 97 p.","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055857","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":318807,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5141/coverthb.jpg"},{"id":318808,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5141/sir20155141.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5141"}],"country":"United States","state":"Indiana","otherGeospatial":"Brown Ditch Watershed, Indiana Dunes National Lakeshore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1,\n 41.65\n ],\n [\n -87.1,\n 41.73\n ],\n [\n -86.9,\n 41.73\n ],\n [\n -86.9,\n 41.65\n ],\n [\n -87.1,\n 41.65\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd
Indianapolis, IN 46278
Phone: (317) 290-3333
http://in.water.usgs.gov/