A binational study was initiated to update statistical equations that are used to estimate the magnitude and frequency of peak flows on streams in Manitoba and Ontario, Canada, and Minnesota that are contained within the binational Lake of the Woods–Rainy River Basin upstream from Kenora, Ontario, Canada. Hydraulic engineers use peak streamflow data to inform designs of bridges, culverts, and dams, and water managers use peak streamflow data to inform regulation and planning activities. However, long-term streamflow measurements are available at few locations along the more than 20,000 miles of stream/ditch networks within the binational Lake of the Woods–Rainy River Basin upstream from Kenora, Ontario, Canada.
Estimates of peak-flow magnitudes for 66.7-, 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities equivalent to annual flood-frequency recurrence intervals of 1.5-, 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals, respectively, are presented for 49 streamgages in Minnesota and adjacent areas in the Province of Ontario, Canada, based on data collected through water year 2013. Peak-flow frequency information was subsequently used in regression analyses to develop equations relating peak flows for selected recurrence intervals to various basin and climatic characteristics.
The study area includes 49 streamgages located in the binational Lake of the Woods–Rainy River Basin upstream from Kenora, Ontario, Canada, and is represented by southern portions of the Canadian Provinces of Manitoba (2 percent) and Ontario (56 percent) and the northern portion of the U.S. State of Minnesota (42 percent). The study area was represented by three regions that were defined in previous studies in the U.S. State of Minnesota and another in the Canadian Province of Ontario. The two Minnesota regions A and B were developed using a multiple regression method and hydrologic landscape units were used to validate regions in Minnesota. The Ontario region A was developed using a multiple regression method and standardized residuals from the 100-year recurrence intervals.
Canadian maximum instantaneous peak-flow data were converted from a calendar year to a water year (October 1 to September 30) and where the annual maximum instantaneous peak-flow value was not available in HYDAT, the Sangal method was applied to known average daily flow values to estimate an annual maximum instantaneous peak-flow value. Geographic information system software was used to calculate eight characteristics investigated as potential explanatory variables in the regression analyses.
The procedure for estimating peak-flow frequency for selected exceedance probabilities for a specific ungaged site depends on whether the site is near a streamgage on the same stream or is on an ungaged stream. For an ungaged site near a streamgage on the same stream, the drainage-area ratio method can be used. For an ungaged site on an ungaged stream, the regional regression equations developed for this study should be used.
All equations presented in this study will be incorporated into StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey. StreamStats allows users to obtain streamflow statistics, basin characteristics, and other information for user-selected locations on streams through an interactive map.
Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
The dynamic, multiscale nature of stream systems makes it challenging to establish basic ecological principles to guide stream fish conservation and management. For example, finer-scale instream habitat is often constrained by coarser-scale characteristics driving observed species distributions. Additionally, instream environmental variability can result in patchy species distributions within general upstream–downstream occurrence patterns (i.e., variation around a common theme). Groundwater contribution, an often-overlooked habitat characteristic in warmwater systems, has numerous influences on the instream environment and can play a role in fish habitat-use patterns and assemblage structure. We identified multiscale instream habitat characteristics associated with the occurrence probability of 20 Ozark Highland stream fishes. Fishes were surveyed using tow-barge electrofishing in 76 channel unit complexes (i.e., riffle-to-riffle habitat sequences) nested in 20 reaches of northwest Oklahoma and southwest Missouri. We used a multiscale, multispecies generalized linear mixed model to identify relationships between fish occurrence and both channel unit complex- and reach-scale variables. Stream fishes were more likely to occur in larger or deeper channel unit complexes. Fish occurrence was also associated with different levels of reach-scale groundwater contribution, bankfull width-to-depth ratio, and percent instream cover. Ten fishes, typically associated with warmer water temperatures, had lower occurrence probabilities in reaches with higher groundwater contribution, whereas Banded Sculpin Cottus carolinae and Creek Chub Semotilus atromaculatus occurrence probabilities were higher. There was no relationship between occurrence probabilities and instream cover for 11 fishes. The occurrence probabilities in relation to varying amounts of instream cover for the other nine stream fishes was dependent on bankfull width-to-depth ratio, where the direction and magnitude of the relationships varied among stream fishes. The variation in occurrence relationships can be attributed to thermal preferences, environmental interactions, and the use of multiple habitat types. Our findings demonstrate the multiscale nature of fish occurrence relationships and how conservation and management may benefit from considering this complexity when developing holistic instream habitat enhancement strategies.
","language":"English","publisher":"American Society of Ichthyologists and Herpetologists","doi":"10.1643/CE-18-099","usgsCitation":"Mollenhauer, R., Zhou, Y., and Brewer, S.K., 2019, Multiscale habitat factors explain variability in stream fish occurrence in the Ozark Highlands ecoregion, USA: Copeia, v. 107, no. 2, p. 219-231, https://doi.org/10.1643/CE-18-099.","productDescription":"13 p.","startPage":"219","endPage":"231","ipdsId":"IP-099822","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Oklahoma","otherGeospatial":"Ozark Highlands ecoregion","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.1910400390625,\n 36.465471886798134\n ],\n [\n -93.9935302734375,\n 36.465471886798134\n ],\n [\n -93.9935302734375,\n 36.99816565700228\n ],\n [\n -95.1910400390625,\n 36.99816565700228\n ],\n [\n -95.1910400390625,\n 36.465471886798134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mollenhauer, Robert","contributorId":274327,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhou, Yan","contributorId":274328,"corporation":false,"usgs":false,"family":"Zhou","given":"Yan","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832909,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203128,"text":"70203128 - 2019 - Adaptive Management and Monitoring","interactions":[],"lastModifiedDate":"2019-04-25T08:33:30","indexId":"70203128","displayToPublicDate":"2019-04-22T10:19:14","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Adaptive Management and Monitoring","docAbstract":"This is a chapter in a technical report that is the second of two works describing longer-term actions to implement policies and strategies for preventing and suppressing rangeland fire and restoring rangeland landscapes affected by fire in the Western United States. The first part, Chambers et al 2017, \"Science Framework for conservation and restoration of the sagebrush biome: Linking the Department of the Interior’s Integrated Rangeland Fire Management Strategy to long-term strategic conservation actions. Part 1. Science basis and applications\" provides information and decision support tools. This part 2 describes application and use of part 1 to resource managers.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Science framework for conservation and restoration of the sagebrush biome: Linking the Department of the Interior’s Integrated Rangeland Fire Management Strategy to long-term strategic conservation actions. Part 2. Management applications","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Forest Service","usgsCitation":"Wiechman, L.A., Pyke, D.A., Crist, M., Munson, S., Brooks, M., Chambers, J.C., Rowland, M.M., Kachergis, E.J., and Davidson, Z., 2019, Adaptive Management and Monitoring, 13 p.","productDescription":"13 p.","startPage":"19","endPage":"31","ipdsId":"IP-096061","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":363178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363120,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.usda.gov/treesearch/pubs/57911"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wiechman, Lief A. 0000-0002-3804-4426","orcid":"https://orcid.org/0000-0002-3804-4426","contributorId":184047,"corporation":false,"usgs":true,"family":"Wiechman","given":"Lief","email":"","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","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":761295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crist, Michele R.","contributorId":178453,"corporation":false,"usgs":false,"family":"Crist","given":"Michele R.","affiliations":[],"preferred":false,"id":761296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth","contributorId":214953,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":761297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brooks, Matthew 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":214954,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":761298,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chambers, Jeanne C.","contributorId":178256,"corporation":false,"usgs":false,"family":"Chambers","given":"Jeanne","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":761299,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rowland, Mary M.","contributorId":173292,"corporation":false,"usgs":false,"family":"Rowland","given":"Mary","email":"","middleInitial":"M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":761300,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kachergis, Emily J","contributorId":214955,"corporation":false,"usgs":false,"family":"Kachergis","given":"Emily","email":"","middleInitial":"J","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":761301,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Davidson, Zoe","contributorId":214956,"corporation":false,"usgs":false,"family":"Davidson","given":"Zoe","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":761302,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70215404,"text":"70215404 - 2019 - Aluminum mobility in mildly acidic mine drainage: Interactions between hydrobasaluminite, silica and trace metals from the nano to the meso-scale","interactions":[],"lastModifiedDate":"2020-10-18T15:23:00.83267","indexId":"70215404","displayToPublicDate":"2019-04-22T10:15:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Aluminum mobility in mildly acidic mine drainage: Interactions between hydrobasaluminite, silica and trace metals from the nano to the meso-scale","docAbstract":"Aluminum precipitates control the hydrochemistry and mineralogy of a broad variety of environments on Earth (e.g., acid mine drainage, AMD, coastal wetlands, boreal and alpine streams, tropical acid sulfate soils, laterites and bauxites, …). However, the geochemical and mineralogical processes controlling Al (and other associated metals and metalloids) transport and removal in those environments are not fully understood. The geochemical system of Paradise Portal (Colorado, USA) comprises sulfate-rich mildly acidic waters, the hydrochemistry of which is directly controlled by the massive precipitation of hydrobasaluminite Al4(SO4)(OH)10·12-36H2O. Three connected but discernible aluminum precipitation stages were identified and described: 1) nanoparticle formation and size decrease along the creek, 2) hydrobasaluminite neoformation on the riverbed, and 3) precipitate accretion and accumulation on the riverbed leading to Al and Fe banded formations. The co-occurrence of Al and Si in the system was observed, recording significant amounts of Si accompanying the three different components of the system (i.e., nanoparticles and fresh and aged Al-precipitates). Also, abrupt and minor changes in the sedimentary record were described and proposed to be the response of the system to seasonal and interannual changes in AMD chemistry. Concerning the mobility of other metals and metalloids, P, Th, V, W, Ti and B showed a tendency to be preferentially incorporated into hydrobasaluminite, while others like Be, As, Se or Ba tend to remain dissolved in the water.
The quantity and character of dissolved organic matter (DOM) can change rapidly during storm events, affecting key biogeochemical processes, carbon bioavailability, metal pollutant transport, and disinfection byproduct formation during drinking water treatment. We used in situ ultraviolet–visible spectrophotometers to concurrently measure dissolved organic carbon (DOC) concentration and spectral slope ratio, a proxy for DOM molecular weight. Measurements were made at 15-minute intervals over three years in three streams draining primarily agricultural, urban, and forested watersheds. We describe storm event dynamics by calculating hysteresis indices for DOC concentration and spectral slope ratio for 220 storms and present a novel analytical framework that can be used to interpret these metrics together. DOC concentration and spectral slope ratio differed significantly among sites, and individual storm DOM dynamics were remarkably variable at each site and among the three sites. Distinct patterns emerged for storm DOM dynamics depending on land use/land cover (LULC) of each watershed. In agricultural and forested streams, DOC concentration increased after the time of peak discharge, and spectral slope ratio dynamics indicate that this delayed flux was of relatively higher molecular weight material compared to the beginning of each storm. In contrast, DOM character during storms at the urban stream generally shifted to lower molecular weight while DOC concentration increased on the falling limb, indicating either the introduction of lower molecular weight DOM, the exhaustion of a higher molecular weight DOM sources, or a combination of these factors. We show that the combination of high-frequency DOM character and quantity metrics have the potential to provide new insight into short-timescale DOM dynamics and can reveal previously unknown effects of LULC on the chemical nature, source, and timing of DOM export during storms.
Paleohydrologic reconstructions of water-year streamflow for 105 sites across the western United States (West) were used to compute the likelihood (risk) of regime (wet/dry state) shifts given the length of time in a specific regime and for a specified time in the future. The spatial variability of risks was examined and indicates that regime shift risks are variable across the West. The Pacific-Northwest region is associated with low risks of regime shifts, indicating persistence controlled by prevalent low frequency variability in flow (periods above 64 years). Other areas in the West indicate higher risks compared to the Pacific-Northwest due to flow variability in the mid-to-high frequencies (periods of 32 to 16 years). Understanding risks of regime shifts provides critical information for improved management of water supplies, particularly during periods of extended low flows. The method presented here has global applicability as a decision-making framework for risk-based planning and management.
The U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the European Association for Remote Sensing Companies, and the European Space Agency in coordination with the GEOValue Community hosted a side event to the Group on Earth Observations Plenary on October 23–24, 2017, in Washington, D.C. The workshop, entitled “Demonstrating the Value of Earth Observations: Methods, Practical Applications and Solutions,” brought together more than 60 international experts including economists, scientists, and engineers to consider the state of the science and applications of valuing Earth observations (EO).
This 2-day workshop built upon previous activities developed under the GEOValue initiative. This workshop brought together expert analysts from multiple disciplines and backgrounds who are developing methods to identify and measure the value of information generated from the use of satellite and in-situ data. The mix of government agencies, international financial institutions, and independent consultants who participated in the workshop blended to develop a rich mix of views, approaches, and outcomes.
During the first part of the workshop, the focus was on the latest science in valuing EO. A number of methodologies were described. Approaches generally assess the societal benefits of specific actions (for example, investments in EO). Some methods focus on broad measures of economic activity (for example, gross domestic product) or methods to assess total economic value such as contingent valuation surveys. Alternatively, use-case approaches (a use case is defined as an evaluation in which one or more decisions, applications, or other uses of data, information, and information products are specifically considered) start with the specific actions and how information is used to support decision making and affect outcomes.
The second part of the meeting was focused on the use and development of value chains and decision trees. A value chain can be defined as the set of value-adding activities that one or more organizations perform in creating and distributing goods and services. In terms of EO, the value chain approach can be applied to consider societal benefits of the data and assess the value of data and data features. The EO value chain considers the geospatial data sources and the processing of the data into value added information to be incorporated into decision-support systems, leading to decision makers’ actions. To understand the value of EO, one would also need to recognize the demand side of the equation or how EO benefits users. Extending the value chain concept and incorporating tenets of Bayesian decision making, a decision tree would include one or more use cases. The value provided by the marginal increase in information could flow from one or several parts of the supply side of the value chain. The decision tree is based on the premise that information has no value if it is not used in at least one decision. By connecting the value chain and the decision tree, a framework is created that allows for conceptualizing the value of EO in its many uses. One can then apply economic techniques to monetize the marginal benefit of an outcome with information versus one without.
A third part of the meeting applied the value chain and decision-tree frameworks to five specific thematic areas, each with the focus of using information for a decision point:
During the working session, five separate groups worked to define and delineate the value chains and decision trees associated with each topic, discussing the related challenges and data needs. The outcomes were reported back to the full group. Because of the complexity of the topics, most groups first identified a network of value chains and then narrowed the scope to develop a single value chain to address their group’s topic. Although they worked separately and on different topics, the groups came to similar conclusions, concurring that the value chain and decision-tree frameworks are very effective for informing quantitative impact assessments and developing a relatable narrative to assist the public in understanding the link between EO and citizens.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191033","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration, FourBridges, European Space Agency, and European Association of Remote Sensing Companies","usgsCitation":"Pearlman, F., Lawrence, C.B., Pindilli, E.J., Geppi, D., Shapiro, C.D., Grasso, M., Pearlman, J., Adkins, J., Sawyer, G., and Tassa, A., 2019, Demonstrating the value of Earth observations—Methods, practical applications, and solutions—Group on Earth Observations side event proceedings: U.S. Geological Survey Open-File Report 2019–1033, 33 p., https://doi.org/10.3133/ofr20191033.","productDescription":"vi, 33 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-102614","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":363044,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1033/coverthb.jpg"},{"id":363045,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1033/ofr20191033.pdf","text":"Report","size":"1.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1033"}],"contact":"Science and Decisions Center
U.S. Geological Survey
913 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Email: gs_emeh_sdc@usgs.gov
The tropics are a region encircling the equator, delineated to the north by the Tropic of Cancer (23°26′14.0″N) and to the south by the Tropic of Capricorn (23°26′14.0″S). While we often think of the tropics as consistently warm and wet throughout the year, in reality, the tropics maintain a myriad of climates. Of the 116 Holdridge life zones (a global bioclimatic classification scheme), the tropics contain more life zones than the sum of all the planet's other geographic regions combined (Holdridge, 1967). In addition to high climatic diversity, the tropics support a wide range of parent materials, landforms, geomorphic characteristics, and soil ages, and maintain all 12 soil types of the USDA soil taxonomy system (Palm et al., 2007; Porder et al., 2007; Quesada et al., 2010; Richter and Babbar, 1991; Sanchez, 1977; Soil Survey Staff, 2006; Townsend et al., 2008). Accordingly, there is no single representative tropical ecosystem. Given the diversity of tropical biomes, this chapter will focus specifically on tropical forested ecosystems and their responses to warming because of their global importance, potential sensitivity to change, and the fact that an improved understanding of how these ecosystems may respond to warmer climate conditions is of significant importance to ecology and society. Furthermore, while generally considering all tropical forest types, emphasis in this chapter is on the humid tropics for which we have most data.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecosystem consequences of soil warming: Microbes, vegetation, fauna and soil biogeochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-813493-1.00015-6","usgsCitation":"Wood, T.E., Cavaleri, M., Giardina, C.P., Khan, S., Mohan, J., Nottingham, A.T., Reed, S., and Slot, M., 2019, Soil warming effects on tropical forests with highly weathered soils, chap. 14 of Ecosystem consequences of soil warming: Microbes, vegetation, fauna and soil biogeochemistry, p. 385-439, https://doi.org/10.1016/B978-0-12-813493-1.00015-6.","productDescription":"55 p.","startPage":"385","endPage":"439","ipdsId":"IP-102016","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":389955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Tana E.","contributorId":197805,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","middleInitial":"E.","affiliations":[],"preferred":false,"id":824198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cavaleri, Molly A.","contributorId":67381,"corporation":false,"usgs":true,"family":"Cavaleri","given":"Molly A.","affiliations":[],"preferred":false,"id":824199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giardina, Christian P. 0000-0002-3431-5073","orcid":"https://orcid.org/0000-0002-3431-5073","contributorId":182695,"corporation":false,"usgs":false,"family":"Giardina","given":"Christian","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":824200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Khan, Shafkat","contributorId":266048,"corporation":false,"usgs":false,"family":"Khan","given":"Shafkat","email":"","affiliations":[],"preferred":false,"id":824201,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohan, Jacqueline","contributorId":62924,"corporation":false,"usgs":true,"family":"Mohan","given":"Jacqueline","email":"","affiliations":[],"preferred":false,"id":824202,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nottingham, Andrew T.","contributorId":266049,"corporation":false,"usgs":false,"family":"Nottingham","given":"Andrew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":824203,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824204,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Slot, Martijn","contributorId":266050,"corporation":false,"usgs":false,"family":"Slot","given":"Martijn","email":"","affiliations":[],"preferred":false,"id":824205,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203199,"text":"70203199 - 2019 - Evaluating and using existing models to map probable suitable habitat for rare plants to inform management of multiple-use public lands in the California desert","interactions":[],"lastModifiedDate":"2019-04-29T08:53:31","indexId":"70203199","displayToPublicDate":"2019-04-19T08:53:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating and using existing models to map probable suitable habitat for rare plants to inform management of multiple-use public lands in the California desert","docAbstract":"Multiple-use public lands require balancing diverse resource uses and values across landscapes. In the California desert, there is strong interest in renewable energy development and important conservation concerns. The Bureau of Land Management recently completed a land-use plan for the area that provides protection for modeled suitable habitat for multiple rare plants. Three sets of habitat models were commissioned for plants of conservation concern as part of the planning effort. The Bureau of Land Management then needed to determine which model or combination of models to use to implement plan requirements. Our goals were to: 1) develop a process for evaluating the existing habitat models and 2) use the evaluation results to map probable and potential suitable habitat. We developed a method for evaluating the construction (input data and methods) and performance of existing models and applied it to 88 habitat models for 43 rare plant species. We also developed a process for mapping probable and potential suitable habitat based on the existing models; potential habitat maps are intended only to guide future field surveys. We were able to map probable suitable habitat for 26 of the 43 species and potential suitable habitat for 41 species. Forty percent of the project area contains probable suitable habitat for at least one species (43,338 km2), with much of that habitat (43%) occurring on lands managed by the Bureau of Land Management. Lands prioritized for renewable energy development contain 3% of the habitat modeled as suitable for at least one species. Our products can be used by agencies to review proposed projects and plan future plant surveys and by developers to target sites likely to minimize conflicts with rare plant conservation goals. Our methods can be broadly applied to understand and quantify the defensibility of models used in conservation and regulatory contexts.","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0214099","usgsCitation":"Reese, G., Carter, S.K., Lunch, C., and Walterscheid, S., 2019, Evaluating and using existing models to map probable suitable habitat for rare plants to inform management of multiple-use public lands in the California desert: PLoS ONE, v. 14, no. 4, 26 p., https://doi.org/10.1371/journal.pone.0214099.","productDescription":"26 p.","ipdsId":"IP-099792","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467685,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0214099","text":"Publisher Index Page"},{"id":437493,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NDA9YC","text":"USGS data release","linkHelpText":"Probable and potential suitable habitat for 43 rare plant species in the California desert"},{"id":363287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.27783203125,\n 31.87755764334002\n ],\n [\n -113.88427734374999,\n 31.87755764334002\n ],\n [\n -113.88427734374999,\n 38.22091976683121\n ],\n [\n -122.27783203125,\n 38.22091976683121\n ],\n [\n -122.27783203125,\n 31.87755764334002\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Reese, Gordon 0000-0002-5191-7770 greese@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-7770","contributorId":215093,"corporation":false,"usgs":true,"family":"Reese","given":"Gordon","email":"greese@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":761612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lunch, Christina","contributorId":215094,"corporation":false,"usgs":false,"family":"Lunch","given":"Christina","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":761614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walterscheid, Steve","contributorId":215095,"corporation":false,"usgs":false,"family":"Walterscheid","given":"Steve","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":761615,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202389,"text":"sir20185170 - 2019 - Drinking water health standards comparison and chemical analysis of groundwater for 72 domestic wells in Bradford County, Pennsylvania, 2016","interactions":[],"lastModifiedDate":"2019-06-12T10:00:24","indexId":"sir20185170","displayToPublicDate":"2019-04-19T08:45:00","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":"2018-5170","displayTitle":"Drinking Water Health Standards Comparison and Chemical Analysis of Groundwater for 72 Domestic Wells in Bradford County, Pennsylvania, 2016","title":"Drinking water health standards comparison and chemical analysis of groundwater for 72 domestic wells in Bradford County, Pennsylvania, 2016","docAbstract":"Pennsylvania has the second highest number of residential wells of any state in the Nation with approximately 2.4 million residents that depend on groundwater for their domestic water supply. Despite the widespread reliance on groundwater in rural areas of the state, publicly available data to characterize the quality of private well water are limited. In Bradford County, more than half of the residents use groundwater from private domestic-supply wells as their primary drinking source. The quality of private well water is influenced by the regional and local setting, including the surrounding soil, geology, land use, household plumbing, and well construction. The groundwater used for domestic water supply in Bradford County is obtained primarily from shallow bedrock and from unconsolidated (glacial) deposits that overlie the bedrock. Historical land use has been predominately forested, agricultural, and residential, but more recently unconventional oil/gas development has been distributed throughout the landscape. Pennsylvania is one of only two states in the Nation without statewide water-well construction standards.
To better assess the quality of groundwater used for drinking water supply in Bradford County, data for 72 domestic wells were collected and analyzed for a wide range of constituents that could be evaluated in relation to drinking water health standards, geology, land use, and other environmental factors. Groundwater samples were collected from May through August 2016 and analyzed for physical and chemical properties, including major ions, nutrients, trace elements, volatile organic compounds, ethylene and propylene glycol, alcohols, gross-alpha/beta-particle activity, uranium, radon-222, and dissolved gases. A subset of samples was analyzed for radium isotopes (radium-226 and -228) and for the isotopic composition of methane. This study was conducted by the U.S. Geological Survey in cooperation with the Northern Tier Regional Planning and Development Commission and is part of a regional effort to characterize groundwater in rural areas of Pennsylvania.
Results of the 2016 study show that groundwater quality generally met most drinking-water standards. However, a percentage of samples failed to meet maximum contaminant levels (MCLs) for total coliform bacteria (49.3 percent), Escherichia coli (8.5 percent), barium (2.8 percent), and arsenic (2.8 percent); and secondary maximum contaminant levels (SMCL) for sodium (48.6 percent), manganese (30.6 percent), gross alpha and beta activity (16.7 percent), iron (11.1 percent), pH (8.3 percent), total dissolved solids (5.6 percent), chloride (1.4 percent), and aluminum (1.4 percent). Radon-222 activities exceeded the proposed drinking-water standard of 300 picocuries per liter (pCi/L) in 70.4 percent of the samples. There were no exceedances of drinking water health standards for any volatile organic compounds, and the only detections were for three trihalomethanes in one sample.
The pH of the groundwater had a large influence on chemical characteristics and ranged from 6.18 to 9.31. Generally, the higher pH samples had higher potential for elevated concentrations of several constituents, including total dissolved solids, sodium, lithium, chloride, fluoride, boron, arsenic, and methane. For the Bradford County well-water samples, calcium/bicarbonate type waters were most abundant, with others classified as sodium/bicarbonate or mixed water types including calcium-sodium/bicarbonate, calcium-sodium/bicarbonate-chloride, sodium/bicarbonate-chloride, sodium/bicarbonate-sulfate, or sodium/chloride types. Six principal components (pH, redox, hardness, chloride-bromide, strontium-barium, and molybdenum-arsenic) explained nearly 78.3 percent of the variance in the groundwater dataset.
Groundwater from 12.5 percent of the wells had concentrations of methane greater than the Pennsylvania action level of 7 milligrams per liter (mg/L); detectable methane concentrations ranged from 0.01 to 77 mg/L. In addition, low levels of ethane (as much as 0.13 mg/L) were present in seven samples with the highest methane concentrations. The isotopic composition of methane in five of these groundwater samples was consistent with the isotopic compositions reported for mud-gas logging samples from these geologic units and a thermogenic source. Isotopic composition from a sixth sample suggested the methane in that sample may be of microbial origin. Well-water samples with the higher methane concentrations also had higher pH values and elevated concentrations of sodium, lithium, boron, fluoride, arsenic, and bromide. Relatively elevated concentrations of some other constituents, such as barium and chloride, commonly were present in, but not limited to, those well-water samples with elevated methane.
Four of the six groundwater samples with the highest methane concentrations had chloride/bromide ratios that indicate mixing with a small amount of brine (0.02 percent or less) similar in composition to those reported for gas and oil well brines in Pennsylvania. In several other eastern Pennsylvania counties where gas drilling is absent, groundwater with comparable chloride/bromide ratios and chloride concentrations have been reported, implying a potential natural source of brine. Most of Bradford County well-water samples have chloride concentrations less than 20 mg/L, and those with higher chloride concentrations have chloride/bromide ratios that indicate anthropogenic sources (such as road-deicing salt and septic effluent) or brine. Brines that are naturally present may originate from deeper parts of the aquifer system, whereas anthropogenic sources are more likely to affect shallow groundwater because they occur on or near the land surface.
The available data for this study indicate that no one physical factor, such as the topographic setting, well depth, or altitude at the bottom of the well, was particularly useful for predicting those well locations with an elevated dissolved concentration of methane. The 2016 assessment of groundwater quality in Bradford County shows groundwater is generally of good quality, but methane and some constituents that occur in high concentration in naturally occurring brine and also in produced waters may be present at low to moderate concentrations in groundwater in various parts of the aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185170","collaboration":"Prepared in cooperation with the Northern Tier Regional Planning and Development Commission","usgsCitation":"Clune, J.W., and Cravotta, C.A., III, 2019, Drinking water health standards comparison and chemical analysis of groundwater for 72 domestic wells in Bradford County, Pennsylvania, 2016 (ver 1.2, May 30, 2019): U.S. Geological Survey Scientific Investigations Report 2018–5170, 66 p., https://doi.org/10.3133/sir20185170.","productDescription":"Report: vi, 66 p.; Data Release","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098593","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":363039,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5170/coverthb4.jpg"},{"id":363132,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5170/versionHist.txt","text":"Version History","size":"1.24 KB","linkFileType":{"id":2,"text":"txt"}},{"id":363047,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VRV6US","text":"USGS data release","description":"USGS data release","linkHelpText":"Compilation of Data Not Available in the National Water Information System for Domestic Wells Sampled by the U.S. Geological Survey in Bradford County, Pennsylvania, May-August 2016"},{"id":363040,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5170/sir20185170.pdf","text":"Report","size":"8.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5170"}],"country":"United States","state":"Pennsylvania","county":"Bradford County ","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-76.9291,42.0024],[-76.9095,42.0025],[-76.8966,42.0026],[-76.6476,42.0019],[-76.6334,42.0017],[-76.5964,42.0013],[-76.5618,42.0009],[-76.5531,42.0008],[-76.5229,42.0005],[-76.466,41.9999],[-76.3826,41.9989],[-76.1467,41.9991],[-76.1382,41.898],[-76.1336,41.8467],[-76.1285,41.7935],[-76.1258,41.773],[-76.1219,41.7217],[-76.1171,41.6531],[-76.1959,41.648],[-76.1996,41.6467],[-76.2015,41.6435],[-76.2015,41.6426],[-76.2015,41.6408],[-76.2016,41.6353],[-76.2016,41.6344],[-76.2023,41.6335],[-76.2029,41.6322],[-76.2063,41.6145],[-76.209,41.6004],[-76.2091,41.5982],[-76.2184,41.5579],[-76.2217,41.5447],[-76.2383,41.5458],[-76.2432,41.5463],[-76.2487,41.5468],[-76.3277,41.5526],[-76.4454,41.5608],[-76.5,41.5649],[-76.5975,41.5715],[-76.6367,41.5745],[-76.6478,41.5755],[-76.6619,41.5765],[-76.679,41.578],[-76.6938,41.579],[-76.6993,41.5795],[-76.7496,41.5834],[-76.7569,41.5839],[-76.787,41.5872],[-76.7949,41.5882],[-76.8005,41.5887],[-76.8103,41.5896],[-76.8133,41.5901],[-76.8219,41.5911],[-76.8379,41.593],[-76.8747,41.5968],[-76.8747,41.599],[-76.8805,41.6363],[-76.8833,41.6681],[-76.8838,41.6717],[-76.885,41.6781],[-76.8873,41.6999],[-76.8907,41.7267],[-76.8936,41.7503],[-76.8976,41.783],[-76.8987,41.8007],[-76.8993,41.808],[-76.9022,41.8248],[-76.9022,41.8257],[-76.9051,41.8466],[-76.9162,41.918],[-76.9209,41.9507],[-76.9238,41.9711],[-76.9291,42.0024]]]},\"properties\":{\"name\":\"Bradford\",\"state\":\"PA\"}}]}","edition":"Version 1.2: May 30, 2019; Version 1.1: April 23, 2019; Version 1.0: April 19, 2019","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Fire is a necessary ecosystem process in many biomes and is best viewed as a natural disturbance that is beneficial to ecosystem functioning. However, increasingly we are seeing human interference in fire regimes that alter the historical range of variability for most fire parameters and result in vegetation shifts. Such perturbations can affect all fire regime parameters. Here we provide a brief overview of examples where anthropogenically driven changes in fire frequency, fire pattern, fuels consumed and fire intensity constitute perturbations that greatly disrupt natural disturbance cycles. These changes are not due to fire per se but rather anthropogenic perturbations in the natural disturbance regime.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF18203","usgsCitation":"Keeley, J., and Pausas, J.G., 2019, Distinguishing disturbance from perturbations in fire-prone ecosystems: International Journal of Wildland Fire, v. 28, no. 4, p. 282-287, https://doi.org/10.1071/WF18203.","productDescription":"6 p.","startPage":"282","endPage":"287","ipdsId":"IP-101725","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467687,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf18203","text":"Publisher Index Page"},{"id":364966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keeley, Jon 0000-0002-4564-6521","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":208184,"corporation":false,"usgs":false,"family":"Keeley","given":"Jon","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":764962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pausas, Juli G.","contributorId":91347,"corporation":false,"usgs":true,"family":"Pausas","given":"Juli","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":764963,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202394,"text":"fs20193008 - 2019 - Landsat 9","interactions":[],"lastModifiedDate":"2022-08-03T22:06:00.386184","indexId":"fs20193008","displayToPublicDate":"2019-04-18T14:47:27","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-3008","displayTitle":"Landsat 9","title":"Landsat 9","docAbstract":"Landsat 9 is a partnership between the National Aeronautics and Space Administration and the U.S. Geological Survey that will continue the Landsat program’s critical role of repeat global observations for monitoring, understanding, and managing Earth’s natural resources. Since 1972, Landsat data have provided a unique resource for those who work in agriculture, geology, forestry, regional planning, education, mapping, and global-change research. Landsat images have also proved invaluable to the International Charter: Space and Major Disasters, supporting emergency response and disaster relief to save lives. With the addition of Landsat 9, the Landsat program’s record of land imaging will be extended to over half a century.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193008","usgsCitation":"U.S. Geological Survey, 2019, Landsat 9 (ver. 1.3, August 2022): U.S. Geological Survey Fact Sheet 2019–3008, 2 p., https://doi.org/10.3133/fs20193008.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-102185","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":363027,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3008/coverthb4.jpg"},{"id":404567,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3008/fs20193008.pdf","text":"Report","size":"2.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3008"},{"id":404568,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2019/3008/versionHist.txt","text":"Version History","size":"8.43 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"}],"edition":"Version 1.0: April 18, 2019; Version 1.1: May 1, 2019; Version 1.2: April 8, 2020; Version 1.3: August 3, 2022","contact":"Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Historical training and operational activities at Joint Base Cape Cod (JBCC) on western Cape Cod, Massachusetts, have resulted in the release of contaminants into an underlying glacial aquifer that is the sole source of water to the surrounding communities. Remedial systems have been installed to contain and remove contamination from the aquifer. Groundwater withdrawals for public supply are expected to increase as the region continues to urbanize. Increases in water-supply withdrawals and wastewater return flow likely will affect the hydrologic system around JBCC and could affect the transport of any contamination that may remain in the aquifer following remediation of contamination from the JBCC. The U.S. Geological Survey, in cooperation with the Air Force Civil Engineer Center, developed a numerical, steady-state regional model of the Sagamore flow lens on western Cape Cod and evaluated the potential effects of future (2030) groundwater withdrawals on water levels, streamflows, hydraulic gradients, and advective transport near the JBCC.
The aquifer consists generally of sandy sediments underlain by impermeable bedrock and is bounded laterally by a freshwater/saltwater interface. Data on the altitude of the bedrock surface, position of the freshwater/saltwater interface, lithology of the aquifer, spatial distribution of recharge, and hydrologic boundaries were incorporated into the three-dimensional, finite-difference groundwater flow model.
Some inputs into the numerical model—aquifer properties, leakances, and recharge—are represented as parameters to facilitate estimation of optimal parameter values in an inverse calibration. A hybrid parameterization scheme, with both zones of piecewise constancy and pilot points, is used to represent hydraulic conductivity; other adjustable parameters include recharge, boundary leakance, and porosity. Data on water levels, the distribution of subsurface contamination, and groundwater ages were compiled, evaluated, and used to develop observations of long-term average hydraulic gradients and advective-transport patterns. These observations of steady-state hydrologic conditions were combined with the parameterized groundwater model in an inverse calibration to estimate model parameters that best fit the observations.
Current (2010) and future (2030) conditions were simulated in the calibrated model to characterize the groundwater flow system and to determine potential effects of increased groundwater withdrawals on advective-transport patterns at the JBCC. Groundwater flow and advective transport are radially outward from a water-table divide in the northern part of the JBCC; flow diverges from the divide toward all points of the compass. Most groundwater flow and contaminant transport occur in shallow parts of the aquifer. On average, about one-half of the groundwater flux occurs in the shallowest 20 percent of the saturated thickness; shallow flow is even more predominant near streams and lakes. Projected (2030) increases in groundwater withdrawals decrease water levels by a maximum of about 1.2 feet in the northern part of the JBCC; drawdowns exceeding 1 foot generally are limited to areas near the largest increases in withdrawals, such as in the northern part of the JBCC, near Long Pond in Falmouth, and in eastern Barnstable. Streamflow decreases average about 6 percent; the largest decreases are in areas with the largest drawdowns. Changes in hydraulic-gradient directions at the water table exceed 1 degree in about 13 percent of the aquifer, generally near groundwater divides where gradient magnitudes are small and near large groundwater withdrawals. Predictions of advective transport from randomly selected locations at the water table are similar for current (2010) and future (2030) groundwater withdrawals. The results indicate that projected increases in groundwater withdrawals affect water levels and streamflows, but effects on hydraulic gradients and advective transport at the JBCC likely are small.
Several underlying assumptions inherent in the model, including observations and weights used in the calibration, representation of local-scale heterogeneity, and simulation of the freshwater/saltwater interface, could affect model calibration and predictions; these assumptions were evaluated with alternative models and alternative inverse calibrations. Eight alternative calibrations were performed in which different, but reasonable, observations and weights were used. The preferred calibrated model had the best overall fit to the observations.
Fine-grained silty sediments occur in many parts of the aquifer, and silt lenses can locally affect hydraulic gradients. A set of alternative models in which silts were represented with different correlation distances and hydraulic conductivities indicated that explicitly representing silt lenses could affect model calibration but that the implicit representation of local-scale heterogeneity may be sufficient at the regional scale to represent regional-scale hydraulic gradients. For the coastal boundary, two alternative models representing silty and sandy seabeds and their associated interface positions were developed to test the importance of the assumed coastal-boundary condition. The two alternative models resulted in different predictions of streamflow—streamflows increase with smaller (silty) seabed leakances. However, predictions of advective transport, particularly near the JBCC, generally were similar between the alternative and preferred calibrated models, indicating that the seabed leakance and associated interface position at the coastal boundary does not affect simulations of advective transport in inland parts of the aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185139","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center","usgsCitation":"Walter, D.A., McCobb, T.D., and Fienen, M.N., 2019, Use of a numerical model to simulate the hydrologic system and transport of contaminants near Joint Base Cape Cod, western Cape Cod, Massachusetts: U.S. Geological Survey Scientific Investigations Report 2018–5139, 98 p., https://doi.org/10.3133/sir20185139.","productDescription":"Report: xi, 98 p.; Data Release","numberOfPages":"114","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077209","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":362939,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77P8XCT ","text":"USGS data release ","description":"USGS data release ","linkHelpText":"MODFLOW–2005 and MODPATH Used to Simulate the Hydrologic System and Transport of Contaminants Near Joint Base Cape Cod, Western Cape Cod, Massachusetts"},{"id":437495,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77P8XCT","text":"USGS data release","linkHelpText":"MODFLOW2005 and MODPATH used to simulate the hydrologic system and transport contaminants near Joint Base Cape Cod, Western Cape Cod, Massachusetts"},{"id":362937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5139/coverthb2.jpg"},{"id":362938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5139/sir20185139.pdf","text":"Report","size":"43.8 MB ","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5139"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.026611328125,\n 41.21172151054787\n ],\n [\n -69.840087890625,\n 41.21172151054787\n ],\n [\n -69.840087890625,\n 42.21224516288584\n ],\n [\n -71.026611328125,\n 42.21224516288584\n ],\n [\n -71.026611328125,\n 41.21172151054787\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Public and domestic water supplies in Elbert County, Colorado, rely on groundwater withdrawals from five bedrock aquifers in the Denver Basin aquifer system (lower Dawson, upper Dawson, Denver, Arapahoe, and Laramie-Fox Hills) to meet water demands. Increased pumping in response to regional population growth and development has led to declining groundwater levels in neighboring Douglas County. The U.S. Geological Survey, in cooperation with the Elbert County Board of County Commissioners, began a study in 2015 to monitor groundwater levels within Elbert County. The purpose of this study is to report on groundwater levels measured between April 2015 and June 2018, and analyze trends and changes in groundwater-level elevations throughout the county.
Discrete groundwater levels were measured at 42 wells within Elbert County. Six of those wells contained equipment to make and record continuous groundwater-level measurements at hourly intervals. All five aquifers had wells with a rise in groundwater-level elevation and wells with a decline in groundwater-level elevation, based on a relative change in groundwater-level elevation between the April 2015 and April 2018 measurements. All aquifers except the upper Dawson had more wells with significant negative trends in discrete groundwater-level elevations than significant positive trends; however, at least one well within the upper Dawson, lower Dawson, Arapahoe, and Laramie-Fox Hills aquifers had a significant positive trend. Wells screened in the lower Dawson aquifer consistently had the most significant negative trends, with an average trend of −1.96 feet per year (ft/year). The upper Dawson, Denver, Arapahoe, and Laramie-Fox Hills aquifers had average trends of 0.03 ft/year, −1.04 ft/year, −0.46 ft/year, and −0.65 ft/year, respectively. Trends in continuous groundwater-level elevations were in agreement with significant trends in discrete groundwater-level elevations. Potentiometric-surface maps of the upper and lower Dawson aquifers for April 2015 and April 2018 show that differences in hydraulic head from the two measurement periods were greatest along the western part of Elbert County. Results of this study could guide future groundwater monitoring in the county and aid in long-term planning of water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195014","collaboration":"Prepared in cooperation with the Elbert County Board of County Commissioners","usgsCitation":"Penn, C.A., and Everett, R.R., 2019, Groundwater-level elevations in the Denver Basin bedrock aquifers of Elbert County, Colorado, 2015–18: U.S. Geological Survey Scientific Investigations Report 2019–5014, 50 p., \nhttps://doi.org/10.3133/sir20195014.","productDescription":"viii, 50 p.","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-100822","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":363023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5014/coverthb.jpg"},{"id":363024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5014/sir20195014.pdf","text":"Report","size":"11.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5014"}],"country":"United States","state":"Colorado","county":"Elbert County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-103.7126,39.5649],[-103.713,39.4761],[-103.7135,39.3876],[-103.7138,39.3011],[-103.7136,39.2136],[-103.7145,39.1265],[-103.7211,39.1266],[-103.722,39.0401],[-103.7201,38.9503],[-103.7186,38.8655],[-103.8315,38.867],[-103.9414,38.8666],[-104.0549,38.8666],[-104.0544,38.9528],[-104.0538,39.0407],[-104.0521,39.1264],[-104.166,39.1277],[-104.2733,39.1278],[-104.3854,39.1284],[-104.4958,39.1298],[-104.6072,39.1307],[-104.6642,39.1308],[-104.6638,39.2165],[-104.664,39.3026],[-104.663,39.3892],[-104.6626,39.4762],[-104.6627,39.5665],[-104.6054,39.5663],[-104.5374,39.5655],[-104.4927,39.5636],[-104.4891,39.5636],[-104.4742,39.5629],[-104.3841,39.5627],[-104.3763,39.5631],[-104.2695,39.5639],[-104.2647,39.5638],[-104.1602,39.5646],[-104.1543,39.565],[-104.0468,39.5652],[-104.0427,39.5651],[-103.9305,39.5646],[-103.9293,39.5646],[-103.8189,39.5646],[-103.8129,39.5649],[-103.7126,39.5649]]]},\"properties\":{\"name\":\"Elbert\",\"state\":\"CO\"}}]}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Identification of habitats responsible for the successful production and recruitment of rare migratory species is a challenge in conservation biology. Here, a tool was developed to assess life stage linkages for the threatened potamodromous cyprinid Clear Lake hitch Lavinia exilicauda chi. Clear Lake hitch undertake migrations from Clear Lake (Lake County, CA, USA) into ephemeral tributary streams for spawning. An aqueous isoscape of strontium isotopic ratios (87Sr/86Sr) was constructed for Clear Lake and its watershed to trace natal origins and migration histories of adult recruits. Aqueous 87Sr/86Sr differentiated Clear Lake from 8 of 10 key tributaries and clustered into 5 strontium isotope groups (SIGs) with 100% classification success. Otolith 87Sr/86Sr showed all five groups contributed variably to the population. The age at which juveniles migrated from natal streams to Clear Lake ranged from 11 to 152 days (mean ± s.d., 43 ± 34 days) and was positively associated with the permanency of natal habitat. This information can be used by resource managers to develop conservation actions for Clear Lake hitch. This study demonstrates the utility of strontium isotopes in otoliths as a tool to identify important freshwater habitats occupied over the lifespan of an individual that would otherwise be challenging or impossible to trace with other methods.