The Anderson Ranch property (study area), located in Taos County, north-central New Mexico, was transferred from Chevron Mining, Inc. (CMI) to the Bureau of Land Management (BLM) as part of a Natural Resource Damage Assessment and Restoration (NRDAR) court-ordered settlement. The study area supports freshwater emergent wetlands and freshwater ponds. The settlement states that CMI will provide the land and a monetary settlement to support the restoration of the wetlands on the property. To best manage the study area, the BLM requires an understanding of potential effects of climate variability and groundwater withdrawals on the wetland function. This study, completed by the U.S. Geological Survey in cooperation with the BLM, provides an initial hydrologic characterization of the study area, which included literature review, collection of groundwater-level and aqueous-chemistry data, completion of a vegetation survey, and preliminary data analysis. The data compiled, collected, and analyzed as part of this study indicate that the wetlands within the study area are groundwater fed and that the water maintaining the wetlands is modern. Surface-water levels in the pond and groundwater levels in the surrounding wetland fluctuate seasonally. The hydraulic gradient in the study area is from northeast to southwest. Evapotranspiration is a main driver of water demand within the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191100","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Galanter, A.E., Shephard, Z.M., and Herrera-Olivas, P., 2019, Anderson Ranch wetlands hydrologic characterization in Taos County, New Mexico: U.S. Geological Survey Open-File Report 2019–1100, 42 p., https://doi.org/10.3133/ofr20191100. ","productDescription":"iii, 42 p. 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New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE, Suite B
Albuquerque, NM 87113
This study explores the feasibility and utility of integrating environmental DNA (eDNA) assessments of species occurrences into the United States (U.S.) Geological Survey’s national streamgage network. We used an existing network of five gages in southwest Idaho to explore the type of information that could be gained as well as the associated costs and limitations. Hydrologic technicians were trained in eDNA sampling protocols and they collected samples during routine monthly visits to streamgages over an entire water year (2016). We analyzed the eDNA in the filtered water samples to determine the presence of two fish species: bull trout and rainbow trout. We then modeled the spatiotemporal distribution of each species using discharge and temperature data. To assess the influence of the spatial distribution of the gages on the biological information obtained, we also collected eDNA samples from locations between the gages three times during the water year. We found eDNA monitoring at the five gages provided meaningful information about the distribution of both species, especially when detection probabilities accounted for variations in temperature and discharge. Sampling between the gages provided additional information about bull trout distribution — the rarer of the two species. Our study suggests the integration of eDNA sampling into a streamgage network is feasible and could provide a novel and powerful source of biological information for riverine ecosystems in the U.S.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12800","usgsCitation":"Pilliod, D.S., Laramie, M., McCoy, D., and Maclean, S., 2019, Integration of eDNA-based biological monitoring within the US Geological Survey’s national streamgage network: Journal of the American Water Resources Association, v. 55, no. 6, p. 1505-1518, https://doi.org/10.1111/1752-1688.12800.","productDescription":"14 p.","startPage":"1505","endPage":"1518","numberOfPages":"14","ipdsId":"IP-104039","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":459688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12800","text":"Publisher Index Page"},{"id":367934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Nebraska ","otherGeospatial":"Bruneau–Jarbidge Rivers watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.26281738281249,\n 41.32732632036622\n ],\n [\n -114.87854003906249,\n 41.32732632036622\n ],\n [\n -114.87854003906249,\n 42.46399280017058\n ],\n [\n -116.26281738281249,\n 42.46399280017058\n ],\n [\n -116.26281738281249,\n 41.32732632036622\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":216342,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":772287,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laramie, Matthew 0000-0001-7820-2583 mlaramie@usgs.gov","orcid":"https://orcid.org/0000-0001-7820-2583","contributorId":152532,"corporation":false,"usgs":true,"family":"Laramie","given":"Matthew","email":"mlaramie@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":772288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Dorene","contributorId":219452,"corporation":false,"usgs":false,"family":"McCoy","given":"Dorene","email":"","affiliations":[{"id":39997,"text":"Idaho Water Science Center (retired)","active":true,"usgs":false}],"preferred":false,"id":772289,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maclean, Scott","contributorId":219453,"corporation":false,"usgs":false,"family":"Maclean","given":"Scott","email":"","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":772290,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205084,"text":"sir20195095 - 2019 - Water resources on Guam—Potential impacts of and adaptive response to climate change","interactions":[],"lastModifiedDate":"2019-12-30T11:39:08","indexId":"sir20195095","displayToPublicDate":"2019-09-30T12:48:06","publicationYear":"2019","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":"2019-5095","displayTitle":"Water resources on Guam—Potential impacts of and adaptive response to climate change","title":"Water resources on Guam—Potential impacts of and adaptive response to climate change","docAbstract":"The goals of this joint U.S. Geological Survey, University of Hawaiʻi, University of Guam, University of Texas, and East-West Center study were to (1) provide basic understanding about water resources for U.S. Department of Defense installations on Guam and (2) assess the resulting effect of sea-level rise and a changing climate on freshwater availability, on the basis of historic information, sea-level rise projections, and global-climate model temperature and rainfall projections. Downscaled regional climate models, informed by a multimodel ensemble of global climate models provided projections of future climate conditions for Guam. These projected climate conditions provided input to surface-water and groundwater models developed for Guam’s hydrology. Guam’s water resources in a future climate condition (2080–99) are projected to diminish relative to the recent climate condition. Projected average temperature increases, and average rainfall decreases will lead to reduced streamflow in southern Guam and reduced groundwater recharge to the Northern Guam Lens Aquifer (NGLA). Projected average temperatures in southern Guam will increase about 5.8 °F (3.22 °C), overall rainfall will decrease about 7 percent, and streamflow will consequently decrease 18 percent in important areas of southern Guam. Similarly, across the NGLA, future groundwater recharge will be 19 percent less than estimated recharge from 2012. Reduced future streamflow will decrease water availability from the Fena Valley Reservoir; however, the reservoir is expected to be able to supply water at recent demand rates without lowering the reservoir level to the elevation of the water-supply intakes throughout the simulated period of a future climate. A twelve-year simulation indicates that the reservoir can supply about twice the 2018 demand without lowering the reservoir level to the water-supply intakes. By following mitigation strategies to increase reservoir water availability, the withdrawal rate can be increased by 1.7 percent if the water-supply intakes are lowered 5 ft, by 3.5 percent if the spillway height is raised 5 ft, and by 5.3 percent if both strategies are combined. Higher sea level and reduced future recharge will decrease water availability from the NGLA. An index of composite chloride concentration from production wells increases to 300 milligrams per liter (mg/L) for future climate conditions and at 2010 withdrawal rates, compared with 130 mg/L under historic climate conditions. Most of this increase is due to reduced recharge as higher (+3.2 ft) sea level only has a small role in increasing withdrawn water salinity. A redistributed withdrawal scenario in which the composite chloride concentration is 290 mg/L offers only slight improvement. Should future droughts reduce recharge proportionally to the decreases observed during historic droughts, the composite concentration would be about 900 mg/L, and more than 70 percent of Guam’s production wells would produce water with a composite concentration greater than 500 mg/L. Potential mitigation strategies for increasing the potable yield of the NGLA in a future climate include reducing depths of deep production wells and reducing the withdrawal rates in selected wells projected to have higher chloride concentrations. Simulations show both strategies are effective in lowering the composite concentration of the withdrawn water.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195095","collaboration":"Prepared in cooperation with the Strategic Environmental Research and Development Program, U.S. Department of Defense","usgsCitation":"Gingerich, S.B., Johnson, A.G., Rosa, S.N., Marineau, M.D., Wright, S.A., Hay, L.E., Widlansky, M.J., Jenson, J.W., Wong, C.I., Banner, J.L., Keener, V.W., and Finucane, M.L., 2019, Water resources on Guam—Potential impacts of and adaptive response to climate change: U.S. Geological Survey Scientific Investigations Report 2019–5095, 55 p., https://doi.org/10.3133/sir20195095.","productDescription":"Report: viii, 55 p.: 3 Data Releases ","numberOfPages":"55","onlineOnly":"Y","ipdsId":"IP-099440","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":367769,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A64801","linkHelpText":"Mean annual water-budget components for Guam for historic (1990–2009) and future (2080–2099) climate conditions"},{"id":367768,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5095/sir20195095.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5095"},{"id":367770,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U34ACT","linkHelpText":"SUTRA model used to evaluate the freshwater flow system for a future (2080–2099) climate on Guam"},{"id":367771,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90S1CSX","linkHelpText":"Southern Guam watershed model and Fena Valley Reservoir water-balance model input files for historic (1990–2099) climate conditions"},{"id":367767,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5095/coverthb.jpg"}],"country":"Guam ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.53613281249997,\n 13.090179355733738\n ],\n [\n 145.01953124999997,\n 13.090179355733738\n ],\n [\n 145.01953124999997,\n 13.870080100685891\n ],\n [\n 144.53613281249997,\n 13.870080100685891\n ],\n [\n 144.53613281249997,\n 13.090179355733738\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
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U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
In cooperation with the New Mexico County of Bernalillo, the U.S. Geological Survey characterized potential polychlorinated biphenyl (PCB) concentration and estimated loading into the Rio Grande from watersheds that are under the county’s jurisdiction. Water and sediment samples were collected in 2017–18 from six sites within four stormwater drainage basins in the Albuquerque, New Mexico, urbanized area for the analysis of PCB congeners and other water-quality constituents during dry and wet seasons. Also, the rainfall-runoff model Arid Lands Hydrologic Model (AHYMO) was used to estimate stormwater discharge at the two sample collection sites not affected by pump station operation. Along with the PCB analysis, the discharge data were used to estimate total PCB stormflow event loads for eight events in these urban Rio Grande tributaries. PCBs were detected in 34 of 36 water samples at concentrations as high as 65.8 nanograms per liter and in 12 of 13 sediment samples at concentrations as high as 163,000 nanograms per kilogram dry weight. Six of the 36 water samples exceeded the New Mexico surface-water quality standard for protection of wildlife habitat and aquatic life of 14 nanograms per liter for PCBs. None of the water samples exceeded the U.S. Environmental Protection Agency’s National Pollutant Discharge Elimination System permit level limit of 200 nanograms per liter for PCBs in stormwater systems discharging into the Rio Grande. PCB concentrations in water samples in this study were not linearly related to antecedent precipitation or measured water-quality parameters, but PCB concentrations had a statistically significant positive Kendall’s tau correlation with total suspended solids for water samples and with total organic carbon for sediment samples. The PCB congener profiles indicate that sources to stormwater drainage basins in Bernalillo County originate both from legacy sources, such as Aroclors (for example, in landfills and old building materials), and from current-use sources, such as yellow pigments (for example, in printed materials and packaging in urban litter or refuse). Total PCB stormflow event loads were calculated with average potential minimum and maximum event loads of 0.73 and 4.32 milligrams per storm event, respectively, at the Adobe Acres pump station site and 56.78 and 315.13 milligrams per storm event at the Sanchez Farms inflow at Albuquerque, N. Mex., site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191106","collaboration":"Prepared in cooperation with Bernalillo County","usgsCitation":"Shephard, Z.M., Conn, K.E., Beisner, K.R., Jornigan, A.D., and Bryant, C.F., 2019, Characterization and load estimation of polychlorinated biphenyls (PCBs) from selected Rio Grande tributary stormwater channels in the Albuquerque urbanized area, New Mexico, 2017–18: U.S. Geological Survey Open-File Report 2019–1106, 48 p., https://doi.org/10.3133/of20191106.","productDescription":"x, 48 p.","numberOfPages":"61","onlineOnly":"Y","ipdsId":"IP-109136","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":367784,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1106/coverthb.jpg"},{"id":367785,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1106/ofr20191106.pdf","size":"4.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1106"}],"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 -106.8255615234375,\n 34.9371707067839\n ],\n [\n -106.48223876953125,\n 34.9371707067839\n ],\n [\n -106.48223876953125,\n 35.20579439829525\n ],\n [\n -106.8255615234375,\n 35.20579439829525\n ],\n [\n -106.8255615234375,\n 34.9371707067839\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
6700 Edith Blvd.
Albuquerque, NM 87113
The Biscayne and Southern Everglades Coastal Transport (BISECT) model was developed by the U.S. Geological Survey under the Greater Everglades Priority Ecosystem Studies Initiative to evaluate, both separately and in conjunction, the likely effects on surface-water stages and flows, hydroperiod, and groundwater levels and salinity in south Florida of (1) a vertical Biscayne aquifer barrier to maintain higher wetland levels, (2) possible future changes to current water-management practices, and (3) sea-level rise. The BISECT model is a combination of the Tides and Inflows to the Mangrove Everglades (TIME) and Biscayne models of the western and eastern parts of south Florida including Everglades National Park, the southern Miami-Dade urban area, and the Biscayne Bay coast and simulates hydrodynamic surface-water flow and three-dimensional groundwater conditions dynamically for the period 1996–2004 by using the Flow and Transport in a Linked Overland/Aquifer Density-Dependent System (FTLOADDS) simulator. BISECT includes a number of parameter and algorithmic refinements that improve simulation results relative to the TIME and Biscayne models and represents the hydrologic system more explicitly, including (1) improved topographic representations, (2) refined Manning’s friction coefficients, (3) improved evapotranspiration computation through spatially variable albedo, (4) increased vertical aquifer discretization, and (5) extension of the western boundary farther offshore.
Sensitivity analyses demonstrate that simulated flows into Long Sound have a different pattern of response to tidal amplitude, wind, and frictional resistance changes than do other coastal streams in the model; flows at Broad River and Lostmans River are most sensitive to tidal amplitude, wind, and frictional resistance changes; and flow to the Everglades coastal streams is substantially affected by surface-water/groundwater interactions in the eastern urban areas. Insight into the hydrologic system came from scenario simulations that represent proposed management actions, such as grouting of the aquifer to prevent seepage from the wetlands and changes to water deliveries proposed by the Comprehensive Everglades Restoration Plan (CERP), and projected sea-level rise. These scenario management changes are considered separately to isolate their specific effects and also in conjunction with sea-level rise. Scenario simulations show that (1) attempts to prevent seepage from the wetlands by grouting the aquifer along the L 31N levee produce minimal effects on surface-water levels; (2) the increased water deliveries proposed in the CERP redistribute flow to the northwestern coastal part of the study area with a minimal reduction to the southeast and a more substantial reduction in flows in the intervening coastal zones, mitigating some sea-level rise effects; (3) sea-level rise has a larger effect on the hydrology (water levels, flow, and salinity) than does CERP restoration; and (4) support for ecological models and hydrologic studies can be provided by applying BISECT to scenarios influenced by climatic and anthropogenic changes or by meteorological variability, such as extreme wet or dry periods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195045","collaboration":"USGS Greater Everglades Priority Ecosystem Studies Initiative","usgsCitation":"Swain, E.D., Lohmann, M.A., and Goodwin, C.R., 2019, The hydrologic system of the south Florida peninsula—Development and application of the Biscayne and Southern Everglades Coastal Transport (BISECT) model: U.S. Geological Survey Scientific Investigations Report 2019–5045, 114 p., https://doi.org/10.3133/sir20195045.","productDescription":"Report: viii, 114 p.; Data Release","numberOfPages":"126","onlineOnly":"Y","ipdsId":"IP-062750","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":367710,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/P9MDUQPK","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"FTLOADDS (combined SWIFT2D surface-water model and SEAWAT groundwater model) simulator used to assess proposed sea-level rise response and water-resource management plans for the hydrologic system of the south Florida peninsula for the Biscayne and Southern Everglades Coastal Transport (BISECT) model"},{"id":367709,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5045/sir20195045.pdf","text":"Report","size":"24.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5045"},{"id":367708,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5045/coverthb2.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.49795532226562,\n 25.11544539706194\n ],\n [\n -80.15213012695312,\n 25.11544539706194\n ],\n [\n -80.15213012695312,\n 25.856751966503136\n ],\n [\n -81.49795532226562,\n 25.856751966503136\n ],\n [\n -81.49795532226562,\n 25.11544539706194\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Although streamflow is widely recognized as a controlling factor in stream health, empirical relations between indicators of anthropogenic modification of streamflow and ecological indicators have been elusive. The objective of this report is to build upon specific findings reported in recent publications by providing a library of empirical models that describe the relations between streamflow modification and indicators of biological integrity. Biological monitoring data from 812 streams and rivers across the United States were matched with sites where daily streamflow was also monitored by the U.S. Geological Survey. Of these sites, 118 were sampled by the U.S. Geological Survey along gradients of streamflow modification within 3 regional focus studies. The integrity of invertebrate and fish communities was expressed as a binary variable, “impaired” or “unimpaired,” signifying whether or not the composition and structure of the biological community was statistically reduced relative to regional reference sites. Streamflow modification at each gaged site was quantified with 509 streamflow statistics scaled to express the ratio of observed streamflow conditions to site-specific expected conditions in the absence of human influences on watershed hydrology. For each region, generalized additive modeling was used to examine relations between each indicator of streamflow modification and indicators of biological integrity (response variable). In every region examined, statistically defensible and ecologically realistic relations were found between indicators of streamflow modification and indicators of biological integrity. These findings can aid practitioners and managers seeking to (1) propose empirically based hypotheses about the specific components of streamflow regimes that are critical to aquatic communities, which can subsequently be explored in detail in a region or river basin of interest; and (2) predict biological responses to anthropogenic modification of specific components of the streamflow regime.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191088","usgsCitation":"Carlisle, D.M., Grantham, T.E., Eng, K., Wolock, D.M., 2019, Regional-scale associations between indicators of biological integrity and indicators of streamflow modification: U.S. Geological Survey Open-File Report 2019–1088, 10 p., https://doi.org/10.3133/ofr20191088.\n","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-097828","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":367467,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O2ZV0M","linkHelpText":"Regional-scale Model Predictions of the Relation Between Biological Integrity and Streamflow Modification"},{"id":367452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1088/ofr20191088.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1088"},{"id":367451,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1088/coverthb.jpg"}],"contact":"Director, USGS Kansas Water Science Center
1217 Biltmore Drive
Lawrence, KS 66049
785-842-9909
The Rio Grande is the fourth longest river in North America extending over 3,000 km from the Rocky Mountains to the Gulf of Mexico. The Pleistocene evolution of this river from individual subbasins into a coalesced fluvial system has been long debated. Herein, we constrain the middle Pleistocene evolution of the northernmost and largest Rio Grande basin, the San Luis basin, and the timing of incision of the Rio Grande Gorge, based on new geologic mapping, 3He surface exposure dating, and U-series dating on pedogenic carbonates. 3He dating of shoreline deposits of closed basin Lake Alamosa and fluvially scoured bedrock along the Rio Grande gorge rim indicate the San Luis basin was connected with southerly Rio Grande basins and progressively incised since ∼400 ka. Waning tectonic activity, coupled with the hydrologic response to intensified middle Pleistocene glaciation, drove southward spillover of Lake Alamosa ∼400 ka, expanding the river's drainage basin by nearly 24,000 km2, and adding recharge areas in the high-altitude, glaciated San Juan, Tusas, and Sangre de Cristo Mountains. Geologic barriers to streamflow on the Taos Plateau were breached and basin tributary drainages were integrated and inset into their present canyons ∼250-200 ka, with approximately 120 m of incision during ∼400-200 ka. Previous work demonstrates that southerly streamflow through basins south of the SLB terminated into a large, rift-related bolson complex until the middle Pleistocene, and most axial Rio Grande river incision has occurred since 630 ka. We propose that middle Pleistocene integration of the SLB was the major geomorphic event that eroded Plio-Pleistocene tectonic and volcanic barriers and re-established flow of the Rio Grande from the Rocky Mountains to the Gulf of Mexico.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2019.07.028","collaboration":"Tulane University, Oregon State University (Corvallis)","usgsCitation":"Ruleman, C.A., Hudson, A.M., Thompson, R., Miggins, D.P., Paces, J.B., and Goehring, B.M., 2019, Middle Pleistocene formation of the Rio Grande Gorge, San Luis Valley, south-central Colorado and north-central New Mexico, USA: Process, timing, and downstream implications: Quaternary Science Reviews, v. 223, 105946, 30 p., https://doi.org/10.1016/j.quascirev.2019.07.028.","productDescription":"105946, 30 p.","ipdsId":"IP-104916","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":459766,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2019.07.028","text":"Publisher Index Page"},{"id":437332,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9966N16","text":"USGS data release","linkHelpText":"Data release for Middle Pleistocene formation of the Rio Grande Gorge, San Luis Valley, south-central Colorado and north-central New Mexico, USA: Process, timing, and downstream implications"},{"id":380469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"Rio Grande Gorge, San Luis Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.1494140625,\n 31.85889704445453\n ],\n [\n -104.34814453125,\n 31.85889704445453\n ],\n [\n -104.34814453125,\n 38.048091067457236\n ],\n [\n -108.1494140625,\n 38.048091067457236\n ],\n [\n -108.1494140625,\n 31.85889704445453\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"223","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":804766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":804767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":804768,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miggins, Daniel P.","contributorId":199027,"corporation":false,"usgs":false,"family":"Miggins","given":"Daniel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":804769,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":215864,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":804770,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goehring, Brent M. 0000-0001-6405-5156","orcid":"https://orcid.org/0000-0001-6405-5156","contributorId":203321,"corporation":false,"usgs":false,"family":"Goehring","given":"Brent","email":"","middleInitial":"M.","affiliations":[{"id":36600,"text":"Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA","active":true,"usgs":false}],"preferred":false,"id":804771,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70207301,"text":"70207301 - 2019 - Monitoring plans for Louisiana’s system-wide assessment and monitoring program (SWAMP). Version IV","interactions":[],"lastModifiedDate":"2019-12-16T12:34:16","indexId":"70207301","displayToPublicDate":"2019-09-16T11:54:07","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5883,"text":"Cooperator Report","active":true,"publicationSubtype":{"id":1}},"title":"Monitoring plans for Louisiana’s system-wide assessment and monitoring program (SWAMP). Version IV","docAbstract":"The System-Wide Assessment and Monitoring Program (SWAMP) has been envisioned as a long-term monitoring program to ensure a comprehensive network of coastal data collection activities is in place to support the development, implementation, and adaptive management of the coastal protection and restoration program within coastal Louisiana. The Coastwide Reference Monitoring System (CRMS) and Barrier Island Comprehensive Monitoring (BICM) programs have been implemented under SWAMP, while other aspects of system dynamics, including offshore and inland water-body boundary conditions, nontidal freshwater habitats, riverine conditions, risk status, and protection performance, are not presently the subject of CPRA-coordinated (Coastal Protection and Restoration Authority) monitoring. In order to implement these additional aspects of SWAMP, CPRA partnered with The Water Institute of the Gulf and others to develop 1) a programmatic monitoring plan for evaluating the effectiveness of the coastal protection and restoration program on a coastwide scale, and 2) basinwide monitoring plans that will incorporate the elements of the programmatic plan with specific data collection activities designed to capture effects within the basin. Monitoring plans were developed for Barataria Basin, Pontchartrain Region (includes Breton Sound, Pontchartrain and Mississippi River Delta Basins), and the western basins (Calcasieu-Sabine, Mermentau, Teche-Vermilion, Atchafalaya, and Terrebonne) for both the natural and human systems using a process to identify the monitoring variables, objectives, and sampling design. The monitoring variables and objectives identified fall under the general categories of weather and climate, biotic integrity, water quality, hydrology, physical terrain, population and demographics, housing and community characteristics, economy and employment, ecosystem dependency, residential properties protection, and critical infrastructure and essential services protection. A rigorous statistical analysis, examination of modeling needs, and thorough reviews of previous planning and monitoring efforts were conducted to develop the sampling designs for the natural and human system monitoring plans. The plan relies heavily on the use of existing data, thus, coordination with other agencies (e.g., LDEQ , LDWF) and CPRA’s existing monitoring programs (e.g., BICM, CRMS) is critical to the plan’s success. Implementation of the plans will require development of quality control and quality assurance protocols, specific standardized operating procedures for each of the data collection efforts, a data management plan, and a reporting framework to contribute to decision making and reducing uncertainty in management actions.
","language":"English","publisher":"Water Institute of the Gulf","usgsCitation":"Hemmerling, S., Baustian, M., Bienn, H., Dausman, A., Grace, A., Grimley, L., McInnis, A., Vingiello, M., Vu, H., Sable, S., Gentile, B., Lafargue, P., Hijuelos, A., Piazza, S., Stagg, C., Raynie, R., Haywood, E., and Khalid, S., 2019, Monitoring plans for Louisiana’s system-wide assessment and monitoring program (SWAMP). Version IV: Cooperator Report, xiii, 235 p.","productDescription":"xiii, 235 p.","ipdsId":"IP-109812","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":370311,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cims.coastal.louisiana.gov/RecordDetail.aspx?Root=0&sid=23567"},{"id":370312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.71337890625,\n 30.282788098216884\n ],\n [\n -93.702392578125,\n 30.12612436422458\n ],\n [\n -93.75732421875,\n 30.0262995822237\n ],\n [\n -93.91113281249999,\n 29.79298413547051\n ],\n [\n -93.8177490234375,\n 29.6880527498568\n ],\n [\n -93.22448730468749,\n 29.754839972510933\n ],\n [\n 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Scott","contributorId":221274,"corporation":false,"usgs":false,"family":"Hemmerling","given":"Scott","affiliations":[],"preferred":false,"id":777614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baustian, Melissa M.","contributorId":189569,"corporation":false,"usgs":false,"family":"Baustian","given":"Melissa M.","affiliations":[],"preferred":false,"id":777615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bienn, Harris","contributorId":221275,"corporation":false,"usgs":false,"family":"Bienn","given":"Harris","affiliations":[],"preferred":false,"id":777616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dausman, Alyssa adausman@usgs.gov","contributorId":177407,"corporation":false,"usgs":true,"family":"Dausman","given":"Alyssa","email":"adausman@usgs.gov","affiliations":[],"preferred":true,"id":777617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grace, 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0000-0003-0922-6754","orcid":"https://orcid.org/0000-0003-0922-6754","contributorId":201525,"corporation":false,"usgs":true,"family":"Hijuelos","given":"Ann","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":777626,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Piazza, Sarai 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":169024,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":777627,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":206064,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":777628,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Raynie, Richard C","contributorId":140898,"corporation":false,"usgs":false,"family":"Raynie","given":"Richard C","affiliations":[{"id":13608,"text":"Louisiana Coastal Protection and Restoration Authority","active":true,"usgs":false}],"preferred":false,"id":777629,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Haywood, Edward","contributorId":194452,"corporation":false,"usgs":false,"family":"Haywood","given":"Edward","email":"","affiliations":[],"preferred":false,"id":777630,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Khalid, Syed","contributorId":221283,"corporation":false,"usgs":false,"family":"Khalid","given":"Syed","email":"","affiliations":[],"preferred":false,"id":777631,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70205360,"text":"70205360 - 2019 - Characterization and evaluation of controls on post-fire streamflow response across western U.S. watersheds","interactions":[],"lastModifiedDate":"2019-09-16T09:14:57","indexId":"70205360","displayToPublicDate":"2019-09-15T23:03:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Characterization and evaluation of controls on post-fire streamflow response across western U.S. watersheds","docAbstract":"This research investigates the impact of wildfires on watershed flow regimes, specifically focusing on evaluation of fire events within specified hydroclimatic regions in the western United States, and evaluating the impact of climate and geophysical variables on response. Eighty-two watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. Percent change in annual runoff ratio, low flows, high flows, peak flows, number of zero flow days, baseflow index, and Richards–Baker flashiness index were calculated for each watershed using pre- and post-fire periods. Independent variables were identified for each watershed and fire event, including topographic, vegetation, climate, burn severity, percent area burned, and soils data. \n\nResults show that low flows, high flows, and peak flows increase in the first 2 years following a wildfire and decrease over time. Relative response was used to scale response variables with the respective percent area of watershed burned in order to compare regional differences in watershed response. To account for variability in precipitation events, runoff ratio was used to compare runoff directly to PRISM precipitation estimates. To account for regional differences in climate patterns, watersheds were divided into nine regions, or clusters, through k-means clustering using climate data, and regression models were produced for watersheds grouped by total area burned. Watersheds in Cluster 9 (eastern California, western Nevada, Oregon) demonstrate a small negative response to observed flow regimes after fire. Cluster 8 watersheds (coastal California) display the greatest flow responses, typically within the first year following wildfire. Most other watersheds show a positive mean relative response. In addition, simple regression models show low correlation between percent watershed burned and streamflow response, implying that other watershed factors strongly influence response. \n\nSpearman correlation identified NDVI, aridity index, percent of a watershed's precipitation that falls as rain, and slope as being positively correlated with post-fire streamflow response. This metric also suggested a negative correlation between response and the soil erodibility factor, watershed area, and percent low burn severity. Regression models identified only moderate burn severity and watershed area as being consistently positively/negatively correlated, respectively, with response. The random forest model identified only slope and percent area burned as significant watershed parameters controlling response. \n\nResults will help inform post-fire runoff management decisions by helping to identify expected changes to flow regimes, as well as facilitate parameterization for model application in burned watersheds.","language":"English","publisher":"Copernicus Publications","doi":"10.5194/hess-22-1221-2018","usgsCitation":"Saxe, S., Hogue, T.S., and Hay, L., 2019, Characterization and evaluation of controls on post-fire streamflow response across western U.S. watersheds: Hydrology and Earth System Sciences, v. 22, no. 2, p. 1221-1237, https://doi.org/10.5194/hess-22-1221-2018.","productDescription":"17 p.","startPage":"1221","endPage":"1237","numberOfPages":"17","ipdsId":"IP-090164","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":459812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-1221-2018","text":"Publisher Index Page"},{"id":367422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"22","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Saxe, Samuel 0000-0003-1151-8908","orcid":"https://orcid.org/0000-0003-1151-8908","contributorId":215753,"corporation":false,"usgs":true,"family":"Saxe","given":"Samuel","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":770931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":770932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren E. 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":211478,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":770930,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205385,"text":"70205385 - 2019 - Physically based estimation of rainfall thresholds triggering shallow landslides in volcanic slopes of southern Italy","interactions":[],"lastModifiedDate":"2019-09-17T08:50:30","indexId":"70205385","displayToPublicDate":"2019-09-14T08:49:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Physically based estimation of rainfall thresholds triggering shallow landslides in volcanic slopes of southern Italy","docAbstract":"On the 4th and 5th of March 2005, about 100 rainfall-induced landslides occurred along volcanic slopes of Camaldoli Hill in Naples, Italy. These started as soil slips in the upper substratum of incoherent and welded volcaniclastic deposits, then evolved downslope according to debris avalanche and debris flow mechanisms. This specific case of slope instability on complex volcaniclastic deposits remains poorly characterized and understood, although similar shallow landsliding phenomena have largely been studied in other peri-volcanic areas of the Campania region underlain by carbonate bedrock. Considering the landslide hazard in this urbanized area, this study focused on quantitatively advancing the understanding of the predisposing factors and hydrological conditions contributing to the initial landslide triggering. Borehole drilling, trial pits, dynamic penetrometer tests, topographic surveys, and infiltration tests were conducted on a slope sector of Camaldoli Hill to develop a geological framework model. Undisturbed soil samples were collected for laboratory testing to further characterize hydraulic and geotechnical properties of the soil units identified. In situ soil pressure head monitoring probes were also installed. A numerical model of two-dimensional variably saturated subsurface water flow was parameterized for the monitored hillslope using field and laboratory data. Based on the observed soil pressure head dynamics, the model was calibrated by adjusting the evapotranspiration parameters. This physically based hydrologic model was combined with an infinite-slope stability analysis to reconstruct the critical unsaturated/saturated conditions leading to slope failure. This coupled hydromechanical numerical model was then used to determine intensity–duration (I-D) thresholds for landslide initiation over a range of plausible rainfall intensities and topographic slope angles for the region. The proposed approach can be conceived as a practicable method for defining a warning criterion in urbanized areas threatened by rainfall-induced shallow landslides, given the unavailability of a consistent inventory of past landslide events that prevents a rigorous empirical analysis.","language":"English","publisher":"MDPI","doi":"10.3390/w11091915","usgsCitation":"Fusco, F., De Vita, P., Mirus, B.B., Baum, R.L., Allocca, V., Tufano, R., and Calcaterra, D., 2019, Physically based estimation of rainfall thresholds triggering shallow landslides in volcanic slopes of southern Italy: Water, v. 11, no. 9, Article 1915, https://doi.org/10.3390/w11091915.","productDescription":"Article 1915","ipdsId":"IP-102857","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":459825,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11091915","text":"Publisher Index Page"},{"id":367450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[15.52038,38.23116],[15.16024,37.44405],[15.3099,37.13422],[15.09999,36.61999],[14.33523,36.99663],[13.82673,37.10453],[12.431,37.61295],[12.57094,38.12638],[13.74116,38.03497],[14.76125,38.14387],[15.52038,38.23116]]],[[[9.21001,41.20999],[9.80998,40.50001],[9.66952,39.17738],[9.21482,39.24047],[8.80694,38.90662],[8.4283,39.17185],[8.38825,40.37831],[8.16,40.95001],[8.70999,40.89998],[9.21001,41.20999]]],[[[12.37649,46.76756],[13.80648,46.50931],[13.69811,46.01678],[13.93763,45.59102],[13.14161,45.73669],[12.32858,45.38178],[12.38387,44.88537],[12.26145,44.60048],[12.58924,44.09137],[13.52691,43.58773],[14.02982,42.76101],[15.14257,41.95514],[15.92619,41.96132],[16.1699,41.74029],[15.88935,41.54108],[16.785,41.17961],[17.51917,40.87714],[18.37669,40.35562],[18.48025,40.16887],[18.29339,39.81077],[17.73838,40.27767],[16.8696,40.44223],[16.44874,39.7954],[17.17149,39.4247],[17.05284,38.90287],[16.63509,38.84357],[16.10096,37.9859],[15.68409,37.90885],[15.68796,38.21459],[15.89198,38.75094],[16.10933,38.96455],[15.71881,39.54407],[15.41361,40.04836],[14.9985,40.17295],[14.70327,40.60455],[14.06067,40.78635],[13.62799,41.18829],[12.88808,41.25309],[12.10668,41.70453],[11.19191,42.35543],[10.51195,42.93146],[10.20003,43.92001],[9.70249,44.03628],[8.88895,44.36634],[8.42856,44.23123],[7.85077,43.76715],[7.43518,43.69384],[7.5496,44.1279],[7.00756,44.25477],[6.74996,45.02852],[7.09665,45.3331],[6.80236,45.70858],[6.84359,45.99115],[7.27385,45.77695],[7.75599,45.82449],[8.31663,46.16364],[8.48995,46.00515],[8.96631,46.03693],[9.18288,46.44021],[9.92284,46.3149],[10.36338,46.48357],[10.4427,46.89355],[11.04856,46.75136],[11.16483,46.94158],[12.15309,47.11539],[12.37649,46.76756]]]]},\"properties\":{\"name\":\"Italy\"}}]}","volume":"11","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Fusco, F. 0000-0002-6271-2228","orcid":"https://orcid.org/0000-0002-6271-2228","contributorId":219005,"corporation":false,"usgs":false,"family":"Fusco","given":"F.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":770977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Vita, P.","contributorId":219006,"corporation":false,"usgs":false,"family":"De Vita","given":"P.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":770978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":770979,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":770980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allocca, V.","contributorId":149077,"corporation":false,"usgs":false,"family":"Allocca","given":"V.","email":"","affiliations":[{"id":17631,"text":"Department of Earth, Environment and Resources Sciences, University of Naples “Federico II”, Naples, Italy.","active":true,"usgs":false}],"preferred":false,"id":770981,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tufano, R.","contributorId":219007,"corporation":false,"usgs":false,"family":"Tufano","given":"R.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":770982,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Calcaterra, D. 0000-0002-3480-3667","orcid":"https://orcid.org/0000-0002-3480-3667","contributorId":219008,"corporation":false,"usgs":false,"family":"Calcaterra","given":"D.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":770983,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70227523,"text":"70227523 - 2019 - Energetic status and bioelectrical impedance modeling of Arctic grayling Thymallus arcticus in interior Alaska Rivers","interactions":[],"lastModifiedDate":"2022-01-20T12:58:29.761524","indexId":"70227523","displayToPublicDate":"2019-09-14T06:53:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Energetic status and bioelectrical impedance modeling of Arctic grayling Thymallus arcticus in interior Alaska Rivers","docAbstract":"The energetic status of fishes represents energy stored as protein and lipids and reflects the ability of an individual to reproduce, migrate, and transition through life stages, ultimately influencing survival. However, traditional measurement methods, while highly accurate, are time consuming, expensive, and lethal, and nonlethal methods such as condition factor may not adequately characterize energetic status. We collected 161 Arctic grayling (Thymallus arcticus) from four interior Alaska river basins with varying hydrologic regimes during early summer and autumn seasons, and used multiple regression and model selection to evaluate the efficacy of bioelectrical impedance analysis (BIA), a nonlethal condition assessment method, to predict percent dry mass and percent lipid content estimated from proximate analysis. We found that Arctic grayling energetic status varied across seasons, by sex, and fish from sites with spawning runs of Pacific salmon had higher energy content than those from sites without salmon, potentially due to the influence of salmon-derived food subsidies. Electrical measurements explained 82% and 80% of the variability in percent dry mass and percent total lipids, respectively, and top models showed high predictive performance (observed vs. predicted root mean squared error ≤2.2%). Overall, we found the BIA approach to provide rapid, precise, and non-lethal estimates of Arctic grayling body condition. Such an approach may be useful for future work to characterize Arctic grayling bioenergetics and monitor fish condition under a rapidly changing Arctic environment.
The greater Everglades region in Florida (USA) is an area of wetlands that has been altered and reduced to 50% of its original area and faces multiple threats. Spatial landscape analysis can help guide a large and complex ecosystem restoration process, involving billions of dollars and multiple groups of stakeholders.
To guide Everglades restoration efforts, we evaluated ecological performance of different hydrologic restoration scenarios using a novel technique, the structural similarity index (SSIM), which quantitatively compares similarity between pairs of gridded maps in terms of mean, variance, and covariance.
Using the SSIM, we evaluated system-wide performance of apple snails, American alligators, Great egrets, and long- and short-hydroperiod vegetation types under multiple restoration scenarios that varied in water management strategies, amounts of water storage, removal of levees and canals (decompartmentalization), and seepage control barriers. We then compared species and habitat responses under each restoration scenario to a target scenario simulating the historical, natural system.
The SSIM approach provides a reliable means of scenario comparison, accounting for both the local magnitude and spatial structure of the underlying data. Our results demonstrated that decompartmentalization benefits the indicator species. In general, scenarios with increased water storage were closer to the target scenario.
This spatial comparison technique is useful for evaluating restoration efforts at multiple spatial scales, ranging from the entire ecosystem down to individual compartments or sub-compartments. The results can be used to inform management and restoration efforts and to guide policy for the greater Everglades area.
• Globally, spring phenology and abiotic processes are shifting earlier with warming. Differences in the magnitudes of these shifts may decouple the timing of plant resource requirements from resource availability. In riparian forests across the northern hemisphere, warming could decouple seed dispersal from snowmelt peak streamflow, thus reducing moisture and safe-sites for dominant tree recruitment.
• We combined field observations with climate, hydrology, and phenology models to simulate future change in synchrony of seed dispersal and snowmelt peaks in the upper South Platte River Basin, Colorado, for three Salicaceae species that dominate western USA riparian forests.
• Chilling requirements for overcoming winter endodormancy were strongest in Salix exigua, moderately supported for Populus deltoides, and indiscernible in Salix amygdaloides. Ensemble mean projected warming of 3.5ºC shifted snowmelt peaks 10-19 d earlier relative to S. exigua and P. deltoides dispersal, because decreased winter chilling combined with increased spring forcing limited change in their dispersal phenology. In contrast, warming shifted both snowmelt peaks and S. amygdaloides dispersal 21 d earlier, maintaining their synchrony.
• Decoupling of snowmelt from seed dispersal for Salicaceae with strong chilling requirements is likely to reduce resources critical for recruitment of these foundational riparian forests, although the magnitude of future decoupling remains uncertain.
","language":"English","publisher":"Wiley","doi":"10.1111/nph.16191","usgsCitation":"Perry, L.G., Shafroth, P.B., Hay, L., Markstrom, S.L., and Bock, A.R., 2019, Projected warming disrupts the synchrony of riparian seed dispersal and snowmelt streamflow: New Phytologist, v. 225, no. 2, p. 693-712, https://doi.org/10.1111/nph.16191.","productDescription":"20 p.","startPage":"693","endPage":"712","ipdsId":"IP-110069","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":459842,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.16191","text":"Publisher Index Page"},{"id":437340,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P994V9LI","text":"USGS data release","linkHelpText":"Riparian seed dispersal phenology and snowmelt streamflow timing in the upper South Platte River Basin, observed in 2010-2011 and simulated for 1962-2098"},{"id":373275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.16015624999999,\n 37.020098201368114\n ],\n [\n -102.041015625,\n 37.020098201368114\n ],\n [\n -102.041015625,\n 40.74725696280421\n ],\n [\n -109.16015624999999,\n 40.74725696280421\n ],\n [\n -109.16015624999999,\n 37.020098201368114\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"225","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Laura G.","contributorId":220048,"corporation":false,"usgs":false,"family":"Perry","given":"Laura","email":"","middleInitial":"G.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":784861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":784860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren","contributorId":209452,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","affiliations":[],"preferred":true,"id":784904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":784905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784906,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203470,"text":"pp1837B - 2019 - Evaluation of chemical and hydrologic processes in the eastern Snake River Plain Aquifer based on results from geochemical modeling, Idaho National Laboratory, eastern Idaho","interactions":[],"lastModifiedDate":"2023-04-14T16:58:11.822101","indexId":"pp1837B","displayToPublicDate":"2019-09-11T15:03:14","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1837-B","displayTitle":"Evaluation of Chemical and Hydrologic Processes in the Eastern Snake River Plain Aquifer Based on Results from Geochemical Modeling, Idaho National Laboratory, Eastern Idaho","title":"Evaluation of chemical and hydrologic processes in the eastern Snake River Plain Aquifer based on results from geochemical modeling, Idaho National Laboratory, eastern Idaho","docAbstract":"Nuclear research activities at the U.S. Department of Energy (DOE) Idaho National Laboratory (INL) produced liquid and solid chemical and radiochemical wastes that were disposed to the subsurface resulting in detectable concentrations of some waste constituents in the eastern Snake River Plain (ESRP) aquifer. These waste constituents may affect the water quality of the aquifer and may pose risks to the eventual users of the aquifer water. To understand these risks to water quality the U.S. Geological Survey, in cooperation with the DOE, conducted geochemical mass-balance modeling of the ESRP aquifer to improve the understanding of chemical reactions, sources of recharge, mixing of water, and groundwater flow directions in the shallow (upper 250 feet) aquifer at the INL.
Modeling was conducted using the water chemistry of 127 water samples collected from sites at and near the INL. Water samples were collected between 1952 and 2017 with most of the samples collected during the mid-1990s. Geochemistry and isotopic data used in geochemical modeling consisted of dissolved oxygen, carbon dioxide, major ions, silica, aluminum, iron, and the stable isotope ratios of hydrogen, oxygen, and carbon.
Geochemical modeling results indicated that the primary chemical reactions in the aquifer were precipitation of calcite and dissolution of plagioclase (An60) and basalt volcanic glass. Secondary minerals other than calcite included calcium montmorillonite and goethite. Reverse cation exchange, consisting of sodium exchanging for calcium on clay minerals, occurred near site facilities where large amounts of sodium were released to the ESRP aquifer in wastewater discharge. Reverse cation exchange acted to retard the movement of wastewater-derived sodium in the aquifer.
Regional groundwater inflow was the primary source of recharge to the aquifer underlying the Northeast and Southeast INL Areas. Birch Creek (BC), the Big Lost River (BLR), and groundwater from BC valley provided recharge to the North INL Area, and the BLR and groundwater from BC and Little Lost River (LLR) valleys provided recharge to the Central INL Area. The BLR, groundwater from the BLR and LLR valleys and the Lost River Range, and precipitation provided recharge to the Northwest and Southwest INL Areas. The primary source of recharge west and southwest of the INL was groundwater inflow from BLR valley. Upwelling geothermal water was a small source of recharge at two wells. Aquifer recharge from surface water in the northern, central, and western parts of the INL indicated that the aquifer in these areas was a dynamic, open system, whereas the aquifer in the eastern part of the INL, which receives little recharge from surface water, was a relatively static and closed system.
Sources of recharge identified from isotope ratios and geochemical modeling (major ion concentrations) were nearly identical for the North, Northeast, Southeast, and Central INL Areas, which indicated that both methods probably accurately identified the sources of recharge in these areas. Conversely, isotope ratios indicated that the BLR and groundwater from the LLR valley provided most recharge to the western parts of the Northwest and Southwest INL Areas, whereas geochemical modeling results indicated a smaller area of recharge from the BLR and groundwater from the LLR valley, a larger area of recharge from the Lost River Range, and recharge of groundwater from the BLR valley that extended to the west INL boundary. The results from geochemical modeling probably were more accurate because major ion concentrations, but not isotope ratios, were available to characterize groundwater from the BLR valley and the Lost River Range.
Sources of recharge identified with a groundwater flow model (using particle tracking) and geochemical modeling were similar for the Northeast and Southeast INL Areas. However, differences between the models were that the geochemical model represented (1) recharge of groundwater from the Lost River Range in the western part of the INL, whereas the flow model did not, (2) recharge of groundwater from the BC and BLR valleys extending farther south and east, respectively, than the flow model, and (3) more recharge from the BLR in the Southwest INL Area than the flow model.
Mixing of aquifer water beneath the INL included (1) mixing of regional groundwater and water from the BC valley in the Northeast and Southeast INL Areas and (2) mixing of surface water (primarily from the BLR) and groundwater across much of the North, Central, Northwest, and Southwest INL Areas. Localized recharge from precipitation mixed with groundwater in the Northwest and Southwest INL Areas, and localized upwelling geothermal water mixed with groundwater in the Central and Northeast INL Areas. Flow directions of regional groundwater were south in the eastern part of the INL and south-southwest at downgradient locations. Groundwater from the BC and LLR valleys initially flowed southeast before changing to south-southwest flow directions that paralleled regional groundwater, and groundwater from the BLR valley initially flowed south before changing to a southsouthwest direction.
Wastewater-contaminated groundwater flowed south from the Idaho Nuclear Technology and Engineering Center (INTEC) infiltration ponds in a narrow plume, with the percentage of wastewater in groundwater decreasing due to dilution, dispersion, and (or) degradation from about 60‒80 percent wastewater 0.7‒0.8 mile (mi) south of the INTEC infiltration ponds to about 1.4 percent wastewater about 15.5 mi south of the INTEC infiltration ponds. Wastewater contaminated groundwater flowed southeast and then southwest from the Naval Reactors Facility industrial waste ditch, with the percentage of wastewater in groundwater decreasing from about 100 percent wastewater adjacent to the waste ditch to about 2 percent wastewater about 0.6 mi south of the waste ditch.
Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
Floodplain ponds and wetlands are productive and biodiverse ecosystems, yet they face multiple threats including altered hydrology, land use change, and non‐native species. Protecting and restoring important floodplain ecosystems requires understanding how organisms use these habitats and respond to altered environmental conditions. We developed Bayesian models to evaluate occupancy of six amphibian species across 103 off‐channel aquatic habitats in the Chehalis River floodplain, Washington State, USA. The basin has been altered by changes in land use, reduced river–wetland connections, and the establishment of non‐native American bullfrogs (Rana catesbeiana = Lithobates catesbeianus) and centrarchid fishes, all of which we hypothesized could influence native amphibian occupancy. Despite potential threats, the floodplain habitats had relatively high rates of native amphibian occupancy, particularly when compared to studies from non‐floodplain habitats within the species’ native ranges. The biggest challenge for native amphibians appears to be non‐native centrarchid fishes, which strongly reduced occupancy of two native amphibians: the northern red‐legged frog (Rana aurora) and the northwestern salamander (Ambystoma gracile). Emergent vegetative cover increased occupancy probability for all five native amphibian species, indicating that plant management may offer a strategy to counter the negative effect of centrarchids by providing refuge from predation. We found that temporary and permanent hydroperiod sites supported different species; hence, both should be conserved on the landscape. Lastly, human‐created and natural ponds had similar amphibian occupancy patterns, suggesting that pond construction offers a viable strategy for adding habitats to the floodplain landscape. Overall, floodplain ponds and wetlands provide important amphibian habitat, and we offer management strategies that will bolster amphibian occupancy in an altered floodplain landscape.
","language":"English","publisher":"ESA","doi":"10.1002/ecs2.2853","usgsCitation":"Holgerson, M., Duarte, A., Hayes, M., Adams, M.J., Tyson, J.A., Douville, K., and Strecker, A., 2019, Floodplains provide important amphibian habitat despite multiple ecological threats: Ecosphere, v. 10, no. 9, e02853, 18 p., https://doi.org/10.1002/ecs2.2853.","productDescription":"e02853, 18 p.","ipdsId":"IP-106837","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":459938,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2853","text":"Publisher Index Page"},{"id":367248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Chehalis River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.17297363281251,\n 47.09069560264967\n ],\n [\n -124.17297363281251,\n 46.9465122958623\n ],\n [\n -124.07958984375001,\n 46.77184961467733\n ],\n [\n -123.33251953125,\n 46.77749276376827\n ],\n [\n -123.43414306640625,\n 46.60982785835103\n ],\n [\n -122.9754638671875,\n 46.219752144776876\n ],\n [\n -122.25585937500001,\n 46.543749602738565\n ],\n [\n -123.5687255859375,\n 47.344406158662125\n ],\n [\n -124.17297363281251,\n 47.09069560264967\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Holgerson, Meredith","contributorId":218790,"corporation":false,"usgs":false,"family":"Holgerson","given":"Meredith","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":770278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duarte, Adam","contributorId":28492,"corporation":false,"usgs":false,"family":"Duarte","given":"Adam","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":770279,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Marc","contributorId":218791,"corporation":false,"usgs":false,"family":"Hayes","given":"Marc","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":770280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":770282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tyson, Julie A.","contributorId":218792,"corporation":false,"usgs":false,"family":"Tyson","given":"Julie","email":"","middleInitial":"A.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":770281,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Douville, Keith","contributorId":218793,"corporation":false,"usgs":false,"family":"Douville","given":"Keith","email":"","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":770283,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Strecker, Angela","contributorId":218794,"corporation":false,"usgs":false,"family":"Strecker","given":"Angela","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":770284,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70215341,"text":"70215341 - 2019 - Updating estimates of low-streamflow statistics to account for possible trends","interactions":[],"lastModifiedDate":"2020-10-15T18:52:38.595974","indexId":"70215341","displayToPublicDate":"2019-09-02T13:46:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7162,"text":"Hydrologic Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Updating estimates of low-streamflow statistics to account for possible trends","docAbstract":"Accurate estimators of streamflow statistics are critical to the design, planning, and management of water resources. Given increasing evidence of trends in low-streamflow, new approaches to estimating low-streamflow statistics are needed. Here we investigate simple approaches to select a recent subset of the low-flow record to update the commonly used statistic of 7Q10, the annual minimum 7-day streamflow exceeded in 9 out of 10 years on average. Informed by low-streamflow records at 174 US Geological Survey streamgages, Monte Carlo simulation experiments evaluate competing approaches. We find that a strategy which estimates 7Q10 using the most recent 30 years of record when a trend is detected, reduces error and bias in 7Q10 estimators compared to use of the full record. This simple rule-based approach has potential as the basis for a framework for updating frequency-based statistics in the context of possible trends.
Hyperalkaline (pH greater than 12) ponds and groundwater exist at Big Marsh near Lake Calumet, Chicago, Illinois, a site used by the steel industry during the mid-1900s to deposit steel- and iron-making waste, in particular, slag. The hyperalkaline ponds may pose a hazard to human health and the environment. The U.S. Geological Survey (USGS), in cooperation with the Environmental Protection Agency (EPA) and in collaboration with the City of Chicago’s Park District, completed a study to evaluate the hydrologic balance, water quality, and chemical-mass balance of hyperalkaline ponds at Big Marsh and geochemical modeling used to evaluate remediation options for water quality at the site based on data collected in 2016–17.
Synoptic measurements of surface-water and groundwater elevations were used to determine flow directions and to enable a preliminary estimate of the hydrologic balance for the ponds. Water-quality samples also were collected and analyzed for selected constituents including major anions and cations, nutrients, metals, and trace elements. The results of the water-quality analyses were used to develop a geochemical model to evaluate concentrations, factors affecting pH, and the state of equilibrium between surface waters and atmospheric carbon dioxide. The geochemical model was used to evaluate remediation scenarios using riprap, spillways, or active aeration. The results indicate that active aeration will decrease the pH to near 7.5 in about 8 hours, the fastest rate of the scenarios. Passive aeration, such as riprap or spillways, also can be effective at decreasing the pH in about 45 hours, but spatial obstacles limit their implementation. Seasonal variations in temperature also affect the rate of equilibration, where colder temperatures may have a lower pH than warmer temperatures and may affect the timing and frequency of remediation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195078","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Brownfields Program, and in collaboration with the City of Chicago’s Park District","usgsCitation":"Gahala, A.M., Seal, R.R., and Piatak, N.M., 2019, Hydrologic balance, water quality, chemical-mass balance, and geochemical modeling of hyperalkaline ponds at Big Marsh, Chicago, Illinois, 2016–17: U.S. Geological Survey Scientific Investigations Report 2019–5078, 31 p., https://doi.org/10.3133/sir20195078.","productDescription":"Report: vi, 31 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-091826","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":366917,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5078/sir20195078.pdf","text":"SIR 2019–5078","size":"3.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5078"},{"id":366918,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VUAQ35","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Water level data from single-well (slug) tests at a monitoring well in Big Marsh, Chicago, Illinois"},{"id":366916,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5078/coverthb.jpg"}],"country":"United States","state":"Illinois","county":"Cook 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Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
In 2018, the U.S. Geological Survey (USGS), in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board, studied floods through the period of record to create a library of flood-inundation maps for the Medina River at Bandera, Texas. Digital flood-inundation maps for a 23-mile reach of the Medina River at and near Bandera, from the confluence with Winans Creek to English Crossing Road, were developed. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to a range of different gage heights (gage height is commonly referred to as “stage,” or the water-surface elevation at a streamflow-gaging station) at USGS streamflow-gaging station 08178880 Medina River at Bandera, Tex. (hereinafter referred to as the “Bandera station”). Water-surface profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The stage-discharge (streamflow) relation effective in 2018 was used to calibrate the model, and stages from four recent flood events were used to independently validate the model. The calibrated hydraulic model was then used to compute 29 water-surface profiles for stages at 1-foot (ft) increments referenced to the station datum and ranging from 10 ft (near bankfull) to 38 ft, which exceeds the major flood stage of the National Weather Service Advanced Hydrologic Prediction Service of 24 ft. 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 0.4-ft vertical accuracy and 1.6-ft horizontal resolution) to delineate the area flooded for stages ranging from 10 to 38 ft.
The digital flood-inundation maps are delivered through the USGS Flood Inundation Mapper application that presents map libraries and provides detailed information on flood-inundation extents and stages for modeled sites. The flood-inundation maps developed in this study, in conjunction with the real-time stage data from the Bandera station, are intended to help guide the public in taking individual safety precautions and provide emergency management personnel with a tool to efficiently manage emergency flood operations and post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195067","collaboration":"Prepared in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board","usgsCitation":"Choi, N., and Engel, F.L., 2019, Flood-inundation maps for a 23-mile reach of the Medina River at Bandera, Texas, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5067, 15 p., https://doi.org/10.3133/sir20195067.","productDescription":"Report: viii, 15 p.; Fact Sheet: 2 p.; Data Release","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-104084","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":366755,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/fs20193043","text":"FS 2019–3043","size":"895 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3043","linkHelpText":" Flood Warning Toolset for the Medina River in Bandera County, Texas"},{"id":366756,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WYD6LS","text":"USGS data release ","linkHelpText":"Geospatial and survey data for flood-inundation maps in a 23-mile reach of the Medina River at Bandera, Texas, 2018"},{"id":366666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5067/coverthb.jpg"},{"id":366667,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5067/sir20195067.pdf","text":"Report","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5067"}],"contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501