The Osage Nation lacks a comprehensive tribal water plan to describe the quality and quantity of water resources in the Osage Nation, a 2,304-square-mile (mi2) area of rolling pastures, tallgrass prairie, and mixed woodlands in northeastern Oklahoma. A tribal water plan can be used to help manage the sustainable development of surface and groundwater resources, thereby helping to provide a better future for the Osage Nation and their neighbors, while preserving water resources for the benefit of the surrounding environment and future generations. To help meet these goals and contribute to increased knowledge of the quantity and quality of water resources and the hydrologic processes and factors affecting those resources, the U.S. Geological Survey (USGS) in cooperation with the Osage Nation began studies to evaluate the surface-water and groundwater resources of the Osage Nation. An important component of these studies is the development and application of numerical models to improve quantification and understanding of the hydrologic system. These models are needed to estimate and quantify the effects of historical and potential future water resource development for the Osage Nation.
This report describes the development and application of a precipitation-runoff model, the Osage Nation watershed model (ONWM). The ONWM is needed as a component of the Osage Nation integrated hydrologic model (ONIHM). At the time of this study, the ONIHM was being developed using the USGS computer software MODFLOW-One Water Hydrologic Flow Model (MODFLOW-OWHM). The intended use of the ONIHM is to simulate all surface-water and groundwater components of the hydrologic system for a 2,905-mi2 study area centered on the Osage Nation. The ONWM was developed using the USGS Precipitation Runoff Modeling System, version 4 (PRMS-IV) computer software, also referred to as PRMS in this report, for an 8,343-mi2 study area in northeastern Oklahoma and southeastern Kansas, centered on and including the areas of the Osage Nation and the ONIHM. The ONWM is to be used as part of the ONIHM to provide a direct coupling with spatially and temporally varying daily climate conditions affecting the ONIHM study area. As an integral part of the ONIHM, the ONWM (1) simulates the inflow boundary conditions from tributary basins in the region outside and surrounding the ONIHM area; (2) provides estimates of spatially and temporally distributed precipitation, air temperature, potential evapotranspiration (PET), actual evapotranspiration (ET), soil moisture, recharge, and streamflow in the ONIHM area; and (3) provides a preliminary water budget for the ONIHM area and the surrounding region, including tributary drainage basins outside of and next to the ONIHM.
The specific objectives of this study were to use the ONWM to (1) provide a systematic inventory of the historical distribution of water inflows from precipitation (rain or snow) falling on the land surface and flowing through the surface-water network, (2) provide a historical context of the variability and spatial and temporal distribution of these waters, and (3) provide estimates of water inflows and potential observations to the ONIHM. The application of the ONWM as a component of the ONIHM is needed for planned simulations using the ONIHM to improve the understanding of the hydrologic system and to develop a fully comprehensive water budget, including the use and movement of water across the landscape, in the surface-water network, and in groundwater aquifers under historical and potential future conditions.
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Groundwater makes up a primary portion of the water supply in many parts of Utah, with annual withdrawals estimated at more than 1,000,000 acre-feet per year. Increases to groundwater withdrawal and land use may negatively impact water availability. Ensuring availability of clean water requires understanding how water quality has changed over time and how natural and human activities and processes influence water quality. Changes in arsenic, nitrate, and dissolved-solids concentrations in the groundwater in basins with high groundwater withdrawals were evaluated between 1975 and 2015 as indicators of basinwide water quality and the suitability of water for drinking. Data were used from the U.S. Geological Survey’s National Water Information System (NWIS) database and the Safe Drinking Water Information System (SDWIS) maintained by the Utah Department of Environmental Quality, Division of Drinking Water. Mann-Kendall trend tests were used to assess temporal trends in decadal and 5-year (sub-decadal) median analyte concentrations in basins. Trends also were assessed in smaller parts of larger basins to focus on changes occurring at a smaller spatial scale. To evaluate the relationship between land-use change and water-quality changes, trends also were evaluated for wells where land use has changed. Trends in decadal and sub-decadal median arsenic, nitrate, and dissolved-solids concentrations over time were identified throughout the basins and sub-basins in this study. For combined NWIS and SDWIS data, rates of median arsenic concentration change in basins and sub-basins ranged between decreases of –0.24 microgram per liter (μg/L) per year and increases of 0.48 μg/L per year. Rates of median nitrate-concentration change ranged between decreases of –0.08 milligram per liter (mg/L) per year and increases of 0.02 mg/L per year. Rates of median dissolved solids concentration change ranged between decreases of –5 mg/L per year and increases of 7 mg/L per year. The rates of change for nitrate and dissolved solids were similar to or less than rates of change observed in other parts of the country. Trends were not directly related to land-use change approximal to a well, although more data from wells where land use has changed would improve this evaluation. These findings highlight that water quality at a well is related to a range of factors including land, demographics, and water use over a larger area surrounding and up-gradient from the well; rates and direction of groundwater movement; and geologic and hydrologic conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205047","collaboration":"Prepared in Cooperation with the Utah Department of Environmental Quality","usgsCitation":"Miller, O.L., 2020, Quantifying trends in arsenic, nitrate, and dissolved solids from selected wells in Utah: U.S. Geological Survey Scientific Investigations Report 2020–5047, 80 p., https://doi.org/10.3133/sir20205047.","productDescription":"viii, 80 p.","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-108685","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":374936,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5047/sir20205047.pdf","text":"Report","size":"7.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":374937,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5047/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
801-908-5000
Model‐estimated monthly water balance components (i.e., potential evapotranspiration, actual evapotranspiration, and runoff (R)) for 146 United States (U.S.) Geological Survey 8‐digit hydrologic units located in the Colorado River Basin (CRB) are used to examine the temporal and spatial variability of the CRB water balance for water years 1901 through 2014 (a water year is the period from October 1 of one year through September 30 of the following year). Results indicate that the CRB can be divided into six subregions with similar temporal variability in monthly R. The water balance analyses indicated that approximately 75% of total water‐year R is generated by just one CRB subregion and that most of the R in the basin is derived from surplus (S) water generated during the months of October through April. Furthermore, the analyses show that temporal variability in S is largely controlled by the occurrence of negative atmospheric pressure anomalies over the northwestern conterminous U.S. (CONUS) and positive atmospheric pressure anomalies over the southeastern CONUS. This combination of atmospheric pressure anomalies results in an anomalous flow of moist air from the North Pacific Ocean into the CRB, particularly the Upper CRB. Additionally, the occurrence of extreme dry and wet periods in the CRB appears to be related to variability of the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation.
The sediment–water interfaces (SWI) of streams serve as important biogeochemical hotspots in watersheds and contribute to whole-catchment reactive nitrogen budgets and water-quality conditions. Recently, the SWI has been identified as an important source of nitrous oxide (N2O) produced in streams, with SWI residence time among the principal controls on its production. Here, we conducted a series of controlled manipulations of SWI exchange in an urban stream that has high dissolved N2O concentrations and where we concurrently evaluated less-mobile porosity dynamics. Our experiments took place within isolated portions of two sediment types: a coarse sandy stream bed resulting from excess road-sand application in the watershed, and a coarse sand mixed with clay and organic particles. In these manipulation experiments we systematically varied SWI vertical-flux rates and residence times to evaluate their effect on the fate of nitrate and production rates of N2O. Our experiments demonstrate that the fate and transport of nitrate and N2O production are influenced by hydrologic flux rates through SWI sediments and associated residence times. Specifically, we show that manipulations of hydrologic flux systematically shifted the depth of the bulk oxic–anoxic interface in the sediments, and that nitrate removal increased with residence time. Our results also support the emerging hypothesis of a ‘Goldilocks’ timescale for the production of nitrous oxide, when transport and reaction timescales favor incomplete denitrification. Areal N2O production rates were up to threefold higher during an intermediate residence-time experiment, compared to shorter or longer residence times. In our companion study we documented that the studied sediments were dominated by a long-residence-time less-mobile porosity domain, which could explain why we observed N2O production even in bulk-oxic sediments. Overall, we have experimentally demonstrated that changes to SWI hydrologic residence times and SWI substrate associated with urbanization can change the biogeochemical function of the river corridor.
","language":"English","publisher":"Wiley","doi":"10.1007/s10533-020-00674-7","usgsCitation":"Hampton, T., Zarnetske, J., Briggs, M., Dehkordy, F.M., Singha, K., Day-Lewis, F., Harvey, J., Chowdhury, S.R., and Lane, J.W., 2020, Experimental shifts of hydrologic residence time in a sandy urban stream sediment-water interface alter nitrate removal and nitrous oxide fluxes: Biogeochemistry, v. 149, p. 195-219, https://doi.org/10.1007/s10533-020-00674-7.","productDescription":"25 p.","startPage":"195","endPage":"219","ipdsId":"IP-116946","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":385331,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Sawmill Brook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.18739366531372,\n 42.52077860418496\n ],\n [\n -71.18534445762633,\n 42.52077860418496\n ],\n [\n -71.18534445762633,\n 42.52389408092782\n ],\n [\n -71.18739366531372,\n 42.52389408092782\n ],\n [\n -71.18739366531372,\n 42.52077860418496\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"149","noUsgsAuthors":false,"publicationDate":"2020-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Hampton, T.","contributorId":257642,"corporation":false,"usgs":false,"family":"Hampton","given":"T.","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":814793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zarnetske, J.","contributorId":222749,"corporation":false,"usgs":false,"family":"Zarnetske","given":"J.","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":814794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814795,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dehkordy, F. M. P.","contributorId":257643,"corporation":false,"usgs":false,"family":"Dehkordy","given":"F.","email":"","middleInitial":"M. P.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":814796,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singha, K.","contributorId":201025,"corporation":false,"usgs":false,"family":"Singha","given":"K.","email":"","affiliations":[],"preferred":false,"id":814797,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":814798,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":814799,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chowdhury, S. R.","contributorId":222748,"corporation":false,"usgs":false,"family":"Chowdhury","given":"S.","email":"","middleInitial":"R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":814800,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lane, John W. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":219742,"corporation":false,"usgs":true,"family":"Lane","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":814801,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70210776,"text":"70210776 - 2020 - Projecting spatiotemporally explicit effects of climate change on stream temperature: A model comparison and implications for coldwater fishes","interactions":[],"lastModifiedDate":"2020-06-24T13:35:31.700545","indexId":"70210776","displayToPublicDate":"2020-05-16T08:27:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Projecting spatiotemporally explicit effects of climate change on stream temperature: A model comparison and implications for coldwater fishes","docAbstract":"Conservation planners and resource managers seek information about how the availability and locations of cold-water habitats will change in the future and how these predictions vary among models. We used a physical process-based model to demonstrate the implications of climate change for streamflow and water temperature in two watersheds with distinctive flow regimes: the Snoqualmie watershed (WA) and Siletz watershed (OR), USA. Our model incorporated a downscaled ensemble of global climate model outputs and was calibrated with in situ and remotely sensed water temperatures. We compared predictions from our processed-based model to those from a publicly available and widely used statistical model. The process-based model projected greater changes in summer maximum water temperatures for the mixed-rain-snow Snoqualmie watershed than for the rain-dominated Siletz watershed as a result of the near-complete loss of winter snowpack and significant reduction in summer flow in the Snoqualmie watershed expected by the 2080s. Both models projected generally similar future spatial patterns of maximum water temperature in the two rivers, with cool reaches distributed farther upstream and fewer in number. However, the process-based model projected higher spatial heterogeneity in water temperature due to our spatially explicit simulation of streamflow and because we calibrated the model with spatially continuous remotely sensed water temperature data. We used stream temperature projections to assess the vulnerability of Pacific salmon and trout to changes in the spatial distribution of cold-water habitats during August by the 2080s. Results suggest that salmonids may have fewer summertime cold-water habitats in both watersheds. Projected stream warming may further limit particular species and life stages, especially in the Snoqualmie watershed. Our comparison of models highlights the importance of considering what might be gained by using a process-based model for evaluating and prioritizing management actions that mitigate climate impacts on cold-water habitats for stream fishes.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.125066","usgsCitation":"Lee, Y., Fullerton, A.H., Sun, N., and Torgersen, C.E., 2020, Projecting spatiotemporally explicit effects of climate change on stream temperature: A model comparison and implications for coldwater fishes: Journal of Hydrology, v. 588, 125066, 16 p., https://doi.org/10.1016/j.jhydrol.2020.125066.","productDescription":"125066, 16 p.","ipdsId":"IP-107958","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":456751,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1639159","text":"External Repository"},{"id":375848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Siletz River, Snoqualmie River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.07752990722655,\n 44.7384422020289\n ],\n [\n -123.85505676269531,\n 44.7384422020289\n ],\n [\n -123.85505676269531,\n 44.949735226126776\n ],\n [\n -124.07752990722655,\n 44.949735226126776\n ],\n [\n -124.07752990722655,\n 44.7384422020289\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.03750610351564,\n 47.45873704984453\n ],\n [\n -121.4208984375,\n 47.45873704984453\n ],\n [\n -121.4208984375,\n 47.755944512091666\n ],\n [\n -122.03750610351564,\n 47.755944512091666\n ],\n [\n -122.03750610351564,\n 47.45873704984453\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"588","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Yeun","contributorId":225503,"corporation":false,"usgs":false,"family":"Lee","given":"Yeun","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":791363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fullerton, Aimee H.","contributorId":146936,"corporation":false,"usgs":false,"family":"Fullerton","given":"Aimee","email":"","middleInitial":"H.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":791364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Ning","contributorId":225504,"corporation":false,"usgs":false,"family":"Sun","given":"Ning","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":791365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":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":791366,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70213698,"text":"70213698 - 2020 - Biological soil crusts in ecological restoration: Emerging research and perspectives","interactions":[],"lastModifiedDate":"2020-09-18T21:33:47.885725","indexId":"70213698","displayToPublicDate":"2020-05-14T16:31:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Biological soil crusts in ecological restoration: Emerging research and perspectives","docAbstract":"Drylands encompass over 40% of terrestrial ecosystems and face significant anthropogenic degradation causing a loss of ecosystem integrity, services, and deterioration of social‐ecological systems. To combat this degradation, some dryland restoration efforts have focused on the use of biological soil crusts (biocrusts): complex communities of cyanobacteria, algae, lichens, bryophytes, and other organisms living in association with the top millimeters of soil. Biocrusts are common in many ecosystems and especially drylands. They perform a suite of ecosystem functions: stabilizing soil surfaces to prevent erosion, contributing carbon through photosynthesis, fixing nitrogen, and mediating the hydrological cycle in drylands. Biocrusts have emerged as a potential tool in restoration; developing methods to implement effective biocrust restoration has the potential to return many ecosystem functions and services. Although culture‐based approaches have allowed researchers to learn about the biology, physiology, and cultivation of biocrusts, transferring this knowledge to field implementation has been more challenging. A large amount of research has amassed to improve our understanding of biocrust restoration, leaving us at an opportune time to learn from one another and to join approaches for maximum efficacy. The articles in this special issue improve the state of our current knowledge in biocrust restoration, highlighting efforts to effectively restore biocrusts through a variety of different ecosystems, across scales and utilizing a variety of lab and field methods. This collective work provides a useful resource for the scientific community as well as land managers.
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S2, p. s3-s8, https://doi.org/10.1111/rec.13201.","productDescription":"6 p.","startPage":"s3","endPage":"s8","ipdsId":"IP-117103","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":456772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13201","text":"Publisher Index Page"},{"id":378584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"S2","noUsgsAuthors":false,"publicationDate":"2020-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Antoninka, Anita","contributorId":166769,"corporation":false,"usgs":false,"family":"Antoninka","given":"Anita","affiliations":[{"id":24503,"text":"Northern Arizona University, School of Forestry, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":799232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faist, Akasha M.","contributorId":193038,"corporation":false,"usgs":false,"family":"Faist","given":"Akasha","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":799233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez-Caballero, Emilio 0000-0002-5934-3214","orcid":"https://orcid.org/0000-0002-5934-3214","contributorId":205639,"corporation":false,"usgs":false,"family":"Rodriguez-Caballero","given":"Emilio","email":"","affiliations":[{"id":37132,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":799234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Kristina E.","contributorId":195945,"corporation":false,"usgs":false,"family":"Young","given":"Kristina E.","affiliations":[],"preferred":false,"id":799235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chaudhary, V Bala","contributorId":240984,"corporation":false,"usgs":false,"family":"Chaudhary","given":"V Bala","affiliations":[{"id":36623,"text":"DePaul University","active":true,"usgs":false}],"preferred":false,"id":799236,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":799237,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":799238,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70210141,"text":"70210141 - 2020 - Evaluation of uncertainty intervals for daily, statistically derived streamflow estimates at ungaged basins across the continental U.S.","interactions":[],"lastModifiedDate":"2020-05-15T13:59:00.848318","indexId":"70210141","displayToPublicDate":"2020-05-14T08:54:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of uncertainty intervals for daily, statistically derived streamflow estimates at ungaged basins across the continental U.S.","docAbstract":"Streamflow estimation methods that transfer information from an index gage to an ungaged site are commonly used; however, uncertainty in daily streamflow estimates are often not adequately quantified. In this study, daily streamflow was simulated at 1,331 validation streamgages across the continental United States using four transfer-based streamflow estimation methods. Empirical 95 percent uncertainty intervals were computed for estimated daily streamflows. Uncertainty intervals were evaluated for reliability, sharpness, and overall ability to accurately quantify the uncertainty inherent in the estimated daily streamflow. Uncertainty intervals performed reliably in the Eastern U.S. and Pacific Northwest regions of the country, containing a median of 96 and 99 percent of the observed values respectively. Uncertainty intervals were less reliable in the Great Plains and arid Southwest regions, where uncertainty intervals contained a median of 83 and 94 percent of the observed streamflows respectively. Uncertainty interval performance was correlated with gage density and hydrologic similarity near the validation site, as well as the aridity and base-flow indices at the site.","language":"English","publisher":"MDPI","doi":"10.3390/w12051390","collaboration":"","usgsCitation":"Levin, S., and Farmer, W.H., 2020, Evaluation of uncertainty intervals for daily, statistically derived streamflow estimates at ungaged basins across the continental U.S.: Water, v. 12, no. 5, 1390, 20 p., https://doi.org/10.3390/w12051390.","productDescription":"1390, 20 p.","ipdsId":"IP-117236","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":456781,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12051390","text":"Publisher Index Page"},{"id":436988,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KCLD9W","text":"USGS data release","linkHelpText":"Performance of 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0000-0002-2448-3129","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":209947,"corporation":false,"usgs":true,"family":"Levin","given":"Sara B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":789281,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210092,"text":"ofr20201040 - 2020 - Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona","interactions":[],"lastModifiedDate":"2020-05-14T11:55:22.364325","indexId":"ofr20201040","displayToPublicDate":"2020-05-13T13:43:13","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1040","displayTitle":"Assessment of Rangeland Ecosystem Conditions in Grand Canyon-Parashant National Monument, Arizona","title":"Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona","docAbstract":"Sustainability of dryland ecosystems depends on the functionality of soil-vegetation feedbacks that affect ecosystem processes, such as nutrient cycling, water capture and retention, soil erosion and deposition, and plant establishment and reproduction. Useful, common indicators can provide information on soil and site stability, hydrologic function, and biotic integrity. Evaluation of rangeland health thus relies on describing the condition and sustainability of these individual, measurable, and observable indicators that are linked to important ecosystem processes. This report focuses on the ~200,000 acres of the Grand Canyon-Parashant National Monument that is administered by the National Park Service (NPS)—one of the largest NPS units where livestock grazing is a permitted land-use activity. Many ecosystems in the monument are characterized by a low degree of resilience to improper grazing because of low and variable precipitation. The monument is marked by a high degree of environmental heterogeneity, including a large elevation gradient, widely differing precipitation patterns, a diversity of geologic substrates, and unique combinations of plant species.
The objective of this report is to (1) increase our understanding of the underlying landscape, soil, and climate setting factors that affect Grand Canyon-Parashant National Monument dryland ecosystem structure and function (also referred to as land potential) and (2) characterize the condition of monument ecosystems in relation to management concepts, such as rangeland health.
Data were analyzed by elevation zone using both univariate and multivariate approaches. Survey results document the high level of diversity within the study area, including 15 unique soil taxa and 271 species of plants. We collected three new plant species for Grand Canyon-Parashant National Monument and 17 new species for the NPS portion of the monument. Results also document a strong association between rangeland health indicators and elevation, topographic setting, and soils. Soil factors found to explain important variation across plots include the amount of exposed bedrock, soil rockiness, soil texture (and associated hydrologic properties), and soil depth. We also found that dominant species turnover across elevation may represent species’ differences in adaptation to climates, including Larrea tridentata, Coleogyne ramosissima, and Artemisia spp. Bromus rubens is the most common invasive species of concern recorded in this study, but other common invasive species are Bromus tectorum, Erodium cicutarium, and Schismus arabicus. Correlations between an index of cattle use and indicators of rangeland health suggest that areas with high cattle use have increased bare ground, decreased ground cover, increased frequency of Schismus arabicus, decreased cover of Coleogyne ramosissima and Ephedra spp., and increased cover of Gutierrezia spp. The few strong correlations observed between indicators of vascular plant community cover or abundance and indicators of cattle activity support rangeland assessment and monitoring strategies that do not rely solely on plant-based indicators are needed.
This work supports management of dryland ecosystems, including Grand Canyon-Parashant National Monument, using concepts of land potential. We conclude the report with recommendations on improving existing land-potential-based classification systems, associated interpretations, and methods for moving forward with a Grand Canyon-Parashant National Monument rangeland monitoring program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201040","usgsCitation":"Duniway, M.C., and Palmquist, E.C., 2020, Assessment of rangeland ecosystem conditions in Grand Canyon-Parashant National Monument, Arizona: U.S. Geological Survey Open-File Report 2020–1040, 42 p., https://doi.org/10.3133/ofr20201040.","productDescription":"Report: viii, 42 p.; Data Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-106479","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":374803,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SJSJHT","linkHelpText":"Rangeland Ecosystem Data, Grand Canyon - Parashant National Monument, AZ, USA"},{"id":374801,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1040/coverthb.jpg"},{"id":374802,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1040/ofr20201040.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon-Parashant National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.005126953125,\n 35.679609609368576\n ],\n [\n -111.57714843749999,\n 35.679609609368576\n ],\n [\n -111.57714843749999,\n 36.97622678464096\n ],\n [\n -114.005126953125,\n 36.97622678464096\n ],\n [\n -114.005126953125,\n 35.679609609368576\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
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U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Manure and wastewater from large livestock operations have the potential to negatively affect surface water and groundwater, including the eutrophication of surface waters and harmful algal blooms. In the Western Lake Erie Basin, where there is a high density of animal agriculture, harmful algal blooms have been attributed, in part, to phosphorus loading from dairy manure and fertilizer applications. Liquid lagoon manure produced by dairy operations typically has low nutrient concentrations and high-water content, so transportation costs are high relative to the value of the nutrients when applied to fields. Treatment systems are needed to transform manure into a dewatered product that is more economical to transport greater distances and that slows and (or) reduces the release of nutrients in soil, allowing nutrients to remain available for crop growth.
This study was designed to pilot test a treatment solution in the Western Lake Erie Basin. The U.S. Geological Survey and Bowling Green State University field tested a dewatering treatment process (coagulant/polymer mixture) for dairy manure at pilot-scale test plots at The Ohio State University Agricultural Research and Development Center Northwest Agricultural Research Station. Automatic samplers were used to collect samples during 13 baseline and 9 post-manure application rainfall events that resulted in substantial surface runoff and (or) tile flow from October 2015 through early November 2017. Results are reported for three test plots that received liquid lagoon manure (raw manure) and three test plots that received polymer-treated manure (treated manure).
Nutrient concentrations and flow volumes in surface runoff and tile flow were determined in baseline and post-manure application rainfall events. Nutrient concentration ranges are reported for 9 baseline and 9 post-manure application events as follows: dissolved reactive phosphorus, less than (<) 0.013−2.16 milligrams per liter (mg/L); nitrate plus nitrite, filtered, 0.32−77 mg/L; ammonia, filtered, <0.05−2.6 mg/L; total phosphorus, <0.01−12.8 mg/L; and total nitrogen, 1.49−77.2 mg/L. Volumes are reported for 6 baseline and 9 post-manure application rainfall events. None of the post-manure application runoff volumes were significantly different by plot or by treatment type (raw manure versus treated manure).
Because concentrations alone do not reflect the true effects of different manure treatments, loads and flow-weighted mean concentrations of nutrients during post-manure application rainfall events were compared between plots with treated manure and those with raw manure. Loads of dissolved reactive phosphorus, total phosphorus, nitrate plus nitrite, and total nitrogen were calculated using the U.S. Geological Survey Graphical Constituent Loading and Analysis System. Loads of ammonia were not calculated because many of the ammonia concentrations were below the reporting limit.
During the post-manure application period, higher nitrogen loads resulted from tile flow than surface runoff. For phosphorus, the opposite was true in that higher loads resulted from surface runoff than tile flow. Combined loads (surface runoff and tile flow) of dissolved reactive phosphorus were significantly different between raw manure and treated manure plots, but there was no significant difference in combined loads of total phosphorus, nitrate plus nitrite, or total nitrogen between raw manure and treated manure plots. Flow-weighted mean concentrations were calculated for the combined loads for the post-manure application rainfall events. Flow-weighted mean concentrations of dissolved reactive phosphorus and, to a lesser extent, total phosphorus were significantly different between raw manure and treated manure plots. Flow-weighted mean concentrations of nitrate plus nitrite and total nitrogen were not significantly different between raw manure and treated manure plots. The differences in loads and flow-weighted mean concentrations between raw manure and treated manure plots indicate that dissolved reactive phosphorus was likely retained in the soil and hydrological transport was reduced for the plots amended with the treated manure as compared to raw manure. Although confirmation field testing needs to be done, these results indicate that the use of this coagulant/polymer mixture shows potential in helping to reduce flow of dissolved phosphorus from agricultural fields with applied manure.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205015","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Francy, D.S., Brady, A.M.G., Ash, B.L., and Midden, W.R., 2020, Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17: U.S. Geological Survey Scientific Investigations Report 2020–5015, 31 p., https://doi.org/10.3133/sir20205015.","productDescription":"Report: viii, 31 p.; Appendix Tables","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-095889","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":374487,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5015/sir20205015.pdf","text":"Report","size":"1.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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U.S. Geological Survey
6460 Busch Boulevard Suite 100
Columbus, OH 43229–1737
Global trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from climate-driven variability in wetland extent. We present an approach to concurrently track land cover disturbance and inundation extent across the Mid-Atlantic region, United States, using the Landsat archive in Google Earth Engine. Disturbance was identified as a change in greenness, using a harmonic linear regression approach, or as a change in growing season brightness. Inundation extent was mapped using a modified version of the U.S. Geological Survey’s Dynamic Surface Water Extent (DSWE) algorithm. Annual (2015–2018) disturbance averaged 0.32% (1095 km2 year-1) of the study area per year and was most common in forested areas. While inundation extent showed substantial interannual variability, the co-occurrence of disturbance and declines in inundation extent represented a minority of both change types, totaling 109 km2 over the four-year period, and 186 km2, using the National Wetland Inventory dataset in place of the Landsat-derived inundation extent. When the annual products were evaluated with permitted wetland and stream fill points, 95% of the fill points were detected, with most found by the disturbance product (89%) and fewer found by the inundation decline product (25%). The results suggest that mapping inundation alone is unlikely to be adequate to find and track anthropogenic wetland loss. Alternatively, remotely tracking both disturbance and inundation can potentially focus efforts to protect, manage, and restore wetlands.
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Central Branch","active":true,"usgs":true}],"preferred":true,"id":796080,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, Jay R.","contributorId":238115,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","middleInitial":"R.","affiliations":[],"preferred":false,"id":796081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beal, Yen-Ju G. 0000-0002-5538-5687 ygbeal@usgs.gov","orcid":"https://orcid.org/0000-0002-5538-5687","contributorId":5328,"corporation":false,"usgs":true,"family":"Beal","given":"Yen-Ju","email":"ygbeal@usgs.gov","middleInitial":"G.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":796082,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeVries, Ben 0000-0003-2136-3401","orcid":"https://orcid.org/0000-0003-2136-3401","contributorId":198971,"corporation":false,"usgs":false,"family":"DeVries","given":"Ben","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":796083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796084,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hwang, Nora","contributorId":238116,"corporation":false,"usgs":false,"family":"Hwang","given":"Nora","email":"","affiliations":[],"preferred":false,"id":796085,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mazzarella, Christine","contributorId":169818,"corporation":false,"usgs":false,"family":"Mazzarella","given":"Christine","email":"","affiliations":[],"preferred":false,"id":796086,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jones, John 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":796087,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70213227,"text":"70213227 - 2020 - Effect of spatial resolution of satellite images on estimating the greenness and evapotranspiration of urban green spaces","interactions":[],"lastModifiedDate":"2020-09-15T12:56:38.466452","indexId":"70213227","displayToPublicDate":"2020-05-02T07:41:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Effect of spatial resolution of satellite images on estimating the greenness and evapotranspiration of urban green spaces","docAbstract":"Urban green spaces (UGS), like most managed land covers, are getting progressively affected by water scarcity and drought. Preserving, restoring and expanding UGS require sustainable management of green and blue water resources to fulfil evapotranspiration (ET) demand for green plant cover. The heterogeneity of UGS with high variation in their microclimates and irrigation practices builds up the complexity of ET estimation. In oversized UGS, areas too large to be measured with in situ ET methods, remote sensing (RS) approaches of ET measurement have the potential to estimate the actual ET. Often in situ approaches are not feasible or too expensive. We studied the effects of spatial resolution using different satellite images, with high‐, medium‐ and coarse‐spatial resolutions, on the greenness and ET of UGS using Vegetation Indices (VIs) and VI‐based ET, over a 780‐ha urban park in Adelaide, Australia. We validated ET with the ground‐based ET method of Soil Water Balance. Three sets of imagery from WorldView2, Landsat and MODIS, and three VIs including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Enhanced Vegetation Index 2 (EVI2), were used to assess long‐term changes of VIs and ET calculated from the different imagery acquired for this study (2011–2018). We found high correspondence between ET‐MODIS and ET‐Landsat (R2 > 0.99 for all VIs). Landsat‐VIs captured the seasonal changes of greenness better than MODIS‐VIs. We used artificial neural network (ANN) to relate the RS‐ET and ground data, and ET‐MODIS (EVI2) showed the highest correlation (R2 = 0.95 and MSE =0.01 for validation). We found a strong relationship between RS‐ET and in situ measurements, even though it was not explicable by simple regressions; black box models helped us to explore their correlation. The methodology used in this research makes a strong case for the value of remote sensing in estimating and managing ET of green spaces in water‐limited cities.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13790","usgsCitation":"Nouri, H., Nagler, P.L., Borujeni, S.C., Munez, A.B., Alaghmand, S., Noori, B., Galindo, A., and Didan, K., 2020, Effect of spatial resolution of satellite images on estimating the greenness and evapotranspiration of urban green spaces: Hydrological Processes, v. 34, no. 15, p. 3183-3199, https://doi.org/10.1002/hyp.13790.","productDescription":"17 p.","startPage":"3183","endPage":"3199","ipdsId":"IP-110995","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":456880,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.13790","text":"Publisher Index Page"},{"id":378390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","city":"Adelaide","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 138.4716796875,\n -35.06597313798418\n ],\n [\n 138.955078125,\n -35.06597313798418\n ],\n [\n 138.955078125,\n -34.70549341022545\n ],\n [\n 138.4716796875,\n -34.70549341022545\n ],\n [\n 138.4716796875,\n -35.06597313798418\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"15","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nouri, Hamideh 0000-0002-7424-5030","orcid":"https://orcid.org/0000-0002-7424-5030","contributorId":16327,"corporation":false,"usgs":true,"family":"Nouri","given":"Hamideh","email":"","affiliations":[],"preferred":false,"id":798683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":798645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borujeni, Sattar Chavoshi","contributorId":240671,"corporation":false,"usgs":false,"family":"Borujeni","given":"Sattar","email":"","middleInitial":"Chavoshi","affiliations":[],"preferred":false,"id":798684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munez, Armando Barreto","contributorId":240672,"corporation":false,"usgs":false,"family":"Munez","given":"Armando","email":"","middleInitial":"Barreto","affiliations":[],"preferred":false,"id":798685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alaghmand, Sina","contributorId":172388,"corporation":false,"usgs":false,"family":"Alaghmand","given":"Sina","email":"","affiliations":[{"id":27031,"text":"School of Natural and Built Environments, U. So. Aus and Discipline of Civil Engineering, School Of Engineering, Monash University Malaysia","active":true,"usgs":false}],"preferred":false,"id":798686,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noori, Behnaz","contributorId":172392,"corporation":false,"usgs":false,"family":"Noori","given":"Behnaz","email":"","affiliations":[],"preferred":false,"id":798687,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Galindo, Alejandro","contributorId":240673,"corporation":false,"usgs":false,"family":"Galindo","given":"Alejandro","email":"","affiliations":[],"preferred":false,"id":798688,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":798689,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70212036,"text":"70212036 - 2020 - Effects of flow diversion on Snake Creek and its riparian cottonwood forest, Great Basin National Park","interactions":[],"lastModifiedDate":"2020-08-13T14:59:57.567569","indexId":"70212036","displayToPublicDate":"2020-04-30T09:53:53","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/GRBA/NRR-2020/2104","title":"Effects of flow diversion on Snake Creek and its riparian cottonwood forest, Great Basin National Park","docAbstract":"Snake Creek flows east from the southern Snake Range in Nevada over complex lithology before leaving Great Basin National Park. The river travels over a section of karst limestone where some surface water naturally recharges the groundwater flow system. In 1961 a water diversion pipeline was constructed by downstream water users to transport surface water through the groundwater recharge zone to reduce potential water losses. The diversion pipeline dewaters a 5-km reach for most of the year by transporting water past the recharge zone then returning it to the channel downstream. Snake Creek was incorporated into the newly established Great Basin National Park in 1986, and today park managers and visitors are concerned that the diversion has destabilized Snake Creek’s riparian ecosystem in this arid region where it has high ecological value. The objectives of this study were to 1) document riparian cottonwood forest conditions in the pipeline-dewatered (DW) reach, 2) evaluate Snake Creek water availability and whether it can support a healthy riparian ecosystem, and 3) determine if dewatering has shifted the fluvial system into an unnatural and poorly functioning state.
We pursued these ecohydrological study objectives in 11 research investigations of Snake Creek’s DW reach and nearby reference reaches. The research investigations analyzed: 1) riparian forest condition, tree age, growth, and death; 2) tree ring chronologies through time and space; 3) hydroclimatic drivers of tree growth; 4) stable carbon isotopes extracted from tree rings; 5) cottonwood ecophysiology related to water transport and water stress; 6) historical aerial photography; 7) stand-level riparian forest production; 8) groundwater availability as related to surface water and plant rooting zones; 9) near-surface geophysics using electrical resistivity imaging; 10) channel and valley geomorphology; and 11) in-channel wood jams caused by fallen trees. Integrating these diverse research topics provided a full perspective of historical and modern conditions along Snake Creek.
We found that modern hydrological conditions in Snake Creek’s DW reach could not maintain the drought-sensitive ecosystem. The riparian cottonwoods (Populus angustifolia and P. angustifolia x P. trichocarpa) have experienced significant dieback. Tree mortality was 2.4 times higher in the DW reach than in reference reaches, and surviving trees supported only 60% of the live canopy compared to trees in reference reaches. Changes in the DW reach forest began in the 1960s and became more severe during the last two decades. Stable carbon isotope ratios and branch dieback analyses both demonstrated initial forest adjustments related to water stress beginning in the early 1960s. Tree ring width chronologies indicated two periods of growth decline in the DW relative to control reaches. The first decline in the 1960s represented an immediate adjustment to the modified flow regime, and the second decline in the 2000s demonstrated reduced resilience to atmospheric drought. Aerial photos and stand-level forest production calculations indicated that substantial riparian forest decline occurred in the 1990s–2010s in the DW reach compared to reference reaches. Stable carbon isotope ratios and leaf water potentials revealed that trees in the DW reach experienced greater drought stress than those in reference reaches. Monitoring wells and electrical resistivity surveys both showed riparian water tables to be largely supported by in-channel surface water flow, indicating that the flow diversion removed water that recharges alluvial groundwater and sustains riparian plants. Areas of widespread tree mortality in the DW reach also corresponded to a larger and more unstable channel with a high instream wood load from fallen trees. Modern conditions of Snake Creek in the DW reach robustly suggest that dewatering the river and its associated riparian corridor adversely affected the riparian ecosystem. The degraded condition is likely to persist and intensify unless water is returned to the channel. As we documented during the wet 1980s and the scientific literature suggest, a partial recovery of the riparian ecosystem is likely possible with restored flows.
","language":"English","publisher":"National Park Service","usgsCitation":"Schook, D.M., Cooper, D.J., Friedman, J.M., Rice, S.E., Hoover, J.D., and Thaxton, R.D., 2020, Effects of flow diversion on Snake Creek and its riparian cottonwood forest, Great Basin National Park: Natural Resource Report NPS/GRBA/NRR-2020/2104, xv, 159 p.","productDescription":"xv, 159 p.","ipdsId":"IP-114048","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":377493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377489,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/DownloadFile/637892"}],"country":"United States","state":"Nevada","otherGeospatial":"Great Basin National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.3951416015625,\n 38.66406704456943\n ],\n [\n -114.114990234375,\n 38.66406704456943\n ],\n [\n -114.114990234375,\n 39.08956785484934\n ],\n [\n -114.3951416015625,\n 39.08956785484934\n ],\n [\n -114.3951416015625,\n 38.66406704456943\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schook, Derek M.","contributorId":178325,"corporation":false,"usgs":false,"family":"Schook","given":"Derek","email":"","middleInitial":"M.","affiliations":[{"id":13539,"text":"Department of Geosciences, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":796163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooper, David J.","contributorId":53309,"corporation":false,"usgs":true,"family":"Cooper","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":796164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663 friedmanj@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":2473,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","email":"friedmanj@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":796165,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rice, Steven E.","contributorId":238179,"corporation":false,"usgs":false,"family":"Rice","given":"Steven","email":"","middleInitial":"E.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":796166,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoover, Jamie D.","contributorId":238180,"corporation":false,"usgs":false,"family":"Hoover","given":"Jamie","email":"","middleInitial":"D.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":796167,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thaxton, Richard D.","contributorId":238181,"corporation":false,"usgs":false,"family":"Thaxton","given":"Richard","email":"","middleInitial":"D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":796168,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70210513,"text":"70210513 - 2020 - Stormwater control impacts on runoff volume and peak flow: A meta-analysis of watershed modelling studies","interactions":[],"lastModifiedDate":"2020-07-09T15:05:48.672194","indexId":"70210513","displayToPublicDate":"2020-04-28T10:01:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Stormwater control impacts on runoff volume and peak flow: A meta-analysis of watershed modelling studies","docAbstract":"Decades of research has concluded that the percent of impervious surface cover in a watershed is strongly linked to negative impacts on urban stream health. Recently, there has been a push by municipalities to offset these effects by installing structural stormwater control measures (SCMs), which are landscape features designed to retain and reduce runoff to mitigate the effects of urbanisation on event hydrology. The goal of this study is to build generalisable relationships between the level of SCM implementation in urban watersheds and resulting changes to hydrology. A literature review of 185 peer‐reviewed studies of watershed‐scale SCM implementation across the globe was used to identify 52 modelling studies suitable for a meta‐analysis to build statistical relationships between SCM implementation and hydrologic change. Hydrologic change is quantified as the percent reduction in storm event runoff volume and peak flow between a watershed with SCMs relative to a (near) identical control watershed without SCMs. Results show that for each additional 1% of SCM‐mitigated impervious area in a watershed, there is an additional 0.43% reduction in runoff and a 0.60% reduction in peak flow. Values of SCM implementation required to produce a change in water quantity metrics were identified at varying levels of probability. For example, there is a 90% probability (high confidence) of at least a 1% reduction in peak flow with mitigation of 33% of impervious surfaces. However, as the reduction target increases or mitigated impervious surface decreases, the probability of reaching the reduction target also decreases. These relationships can be used by managers to plan SCM implementation at the watershed scale.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13784","usgsCitation":"Bell, C.D., Wolfand, J.M., Panos, C.L., Bhaskar, A.S., Gilliom, R.L., Hogue, T.S., Hopkins, K.G., and Jefferson, A.J., 2020, Stormwater control impacts on runoff volume and peak flow: A meta-analysis of watershed modelling studies: Hydrological Processes, v. 34, no. 14, p. 3134-3152, https://doi.org/10.1002/hyp.13784.","productDescription":"19 p.","startPage":"3134","endPage":"3152","ipdsId":"IP-114115","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":456920,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.13784","text":"Publisher Index Page"},{"id":375409,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"14","noUsgsAuthors":false,"publicationDate":"2020-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Bell, Colin D.","contributorId":215502,"corporation":false,"usgs":false,"family":"Bell","given":"Colin","email":"","middleInitial":"D.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":790474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolfand, Jordyn M.","contributorId":225130,"corporation":false,"usgs":false,"family":"Wolfand","given":"Jordyn","email":"","middleInitial":"M.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":790475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Panos, Chelsea L.","contributorId":225131,"corporation":false,"usgs":false,"family":"Panos","given":"Chelsea","email":"","middleInitial":"L.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":790476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bhaskar, Aditi S.","contributorId":199824,"corporation":false,"usgs":false,"family":"Bhaskar","given":"Aditi","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":790477,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gilliom, Ryan L.","contributorId":225132,"corporation":false,"usgs":false,"family":"Gilliom","given":"Ryan","email":"","middleInitial":"L.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":790478,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":790479,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790480,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jefferson, Anne J.","contributorId":199823,"corporation":false,"usgs":false,"family":"Jefferson","given":"Anne","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":790481,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70209731,"text":"70209731 - 2020 - Mitigating land subsidence in the Coachella Valley, California, USA: An emerging success story","interactions":[],"lastModifiedDate":"2020-04-23T15:30:09.031759","indexId":"70209731","displayToPublicDate":"2020-04-22T10:23:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5272,"text":"Proceedings of the International Association of Hydrological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Mitigating land subsidence in the Coachella Valley, California, USA: An emerging success story","docAbstract":"Groundwater has been a major source of agricultural, municipal, and domestic water supply since the early 1920s in the Coachella Valley, California, USA. Land subsidence, resulting from aquifer-system compaction and groundwater-level declines, has been a concern of the Coachella Valley Water District (CVWD) since the mid-1990s. As a result, the CVWD has implemented several projects to address groundwater overdraft that fall under three categories – groundwater substitution, conservation, and managed aquifer-recharge (MAR). The implementation of three projects in particular – replacing groundwater extraction with surface water from the Colorado River and recycled water (Mid-Valley Pipeline project), reducing water usage by tiered-rate costs, and increasing groundwater recharge at the Thomas E. Levy Groundwater Replenishment Facility – are potentially linked to markedly improved groundwater levels and subsidence conditions, including in some of the historically most overdrafted areas in the southern Coachella Valley. Groundwater-level and subsidence monitoring have tracked the effect these projects have had on the aquifer system. Prior to about 2010, water levels persistently declined, and some had reached historically low levels by 2010. Since about 2010, however, groundwater levels have stabilized or partially recovered, and subsidence has stopped or slowed substantially almost everywhere it previously had been observed; uplift was observed in some areas. Furthermore, results of Interferometric Synthetic Aperture Radar analyses for 1995–2017 indicate that as much as about 0.6 m of subsidence occurred; nearly all of which occurred prior to 2010. Continued monitoring of water levels and subsidence is necessary to inform the CVWD about future mitigation measures. The water management strategies implemented by the CVWD can inform managers of other overdrafted and subsidence-prone basins as they seek solutions to reduce overdraft and subsidence.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/piahs-382-809-2020","collaboration":"","usgsCitation":"Sneed, M., and Brandt, J.T., 2020, Mitigating land subsidence in the Coachella Valley, California, USA: An emerging success story: Proceedings of the International Association of Hydrological Sciences, v. 382, p. 809-813, https://doi.org/10.5194/piahs-382-809-2020.","productDescription":"5 p.","startPage":"809","endPage":"813","ipdsId":"IP-111082","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":456979,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/piahs-382-809-2020","text":"Publisher Index Page"},{"id":374224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coachella Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.37954711914062,\n 33.53223722395908\n ],\n [\n -116.02523803710938,\n 33.53223722395908\n ],\n [\n -116.02523803710938,\n 33.82023008524739\n ],\n [\n -116.37954711914062,\n 33.82023008524739\n ],\n [\n -116.37954711914062,\n 33.53223722395908\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"382","noUsgsAuthors":false,"publicationDate":"2020-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Justin T. 0000-0002-9397-6824 jbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":157,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"jbrandt@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787697,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209787,"text":"70209787 - 2020 - Detection and measurement of land subsidence and uplift using interferometric synthetic aperture radar, San Diego, California, USA, 2016–2018","interactions":[],"lastModifiedDate":"2020-04-29T13:17:26.480601","indexId":"70209787","displayToPublicDate":"2020-04-22T08:16:45","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Detection and measurement of land subsidence and uplift using interferometric synthetic aperture radar, San Diego, California, USA, 2016–2018","docAbstract":"Land subsidence associated with groundwater-level declines is stipulated as an “undesirable effect” in California’s Sustainable Groundwater Management Act (SGMA), and has been identified as a potential issue in San Diego, California, USA. The United States Geological Survey (USGS), the Sweetwater Authority, and the City of San Diego, undertook a cooperative study to better understand the hydromechanical response of the coastal aquifer system using Interferometric Synthetic Aperture Radar (InSAR) techniques. Three periods of interest were analyzed for this study that correspond to the periods before and after two substantial changes were made to the location and volume of pumpage: (1) April–August 2016 when groundwater levels and land surface elevation were relatively stable during normal pumping, (2) September 2016–May 2017 when groundwater levels recovered and the land surface uplifted during a period of substantially reduced pumping, (3) June 2017–October 2018 when groundwater levels declined and land subsidence occurred when pumpage resumed and expanded to new wells. Spatial and temporal characterization of the hydromechanical response to changes in pumpage is important for managing land subsidence. 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Measured groundwater level values ranged from −22.8 to 185.4 feet above mean sea level. During the study period, cumulative rainfall of 0.65 inch was recorded in the study area. Measurements of instantaneous streamflow at 15 locations in streams and irrigation canals, and locations of irrigation ponds, provide additional information about the hydrologic setting. Results of the study indicate a cone of depression was present near the center and eastern parts of the Santa Isabel area of southern Puerto Rico, and a small, deeper cone of depression existed west of Santa Isabel and Rio Coamo. These cones of depression represent areas where the potentiometric surface was below mean sea level. The long-term persistence of such conditions could result in seawater intrusion and an increase in concentrations of total dissolved solids within the South Coast aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3455","collaboration":"Prepared in cooperation with the Puerto Rico Department of Natural and Environmental Resources","usgsCitation":"Ramos, F.A., and Santiago, A.A., 2020, Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014: U.S. Geological Survey Scientific Investigations Map 3455, 4 p., 1 sheet, https://doi.org/10.3133/sim3455.","productDescription":"Pamphlet: vi, 4 p.; Sheet: 35.68 inches x 28.17 inches; Data Release","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064406","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":374025,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NS0STQ","text":"USGS data release","linkHelpText":"Data and shapefiles for the potentiometric surface of the South Coast aquifer and hydrologic conditions in the Santa Isabel area, Puerto Rico, March–April 2014"},{"id":374019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3455/coverthb.jpg"},{"id":374021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3455/sim3455.pdf","text":"Pamphlet","size":"350 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Pamphlet"},{"id":374022,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3455/sim3455_sheet.pdf","text":"Sheet 1—","size":"4.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Sheet","linkHelpText":"Potentiometric Surface and Hydrologic Conditions of the South Coast Aquifer, Santa Isabel Area, Puerto Rico, March–April, 2014"}],"country":"United States","state":"Puerto Rico","otherGeospatial":"Santa Isabel Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.4779281616211,\n 17.932682319509986\n ],\n [\n -66.29854202270508,\n 17.932682319509986\n ],\n [\n -66.29854202270508,\n 18.029995361346103\n ],\n [\n -66.4779281616211,\n 18.029995361346103\n ],\n [\n -66.4779281616211,\n 17.932682319509986\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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Russell 0000-0002-5572-9064 rlotspei@usgs.gov","orcid":"https://orcid.org/0000-0002-5572-9064","contributorId":3388,"corporation":false,"usgs":true,"family":"Lotspeich","given":"R.","email":"rlotspei@usgs.gov","middleInitial":"Russell","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":791974,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Laveau, Christopher 0000-0002-4009-1889","orcid":"https://orcid.org/0000-0002-4009-1889","contributorId":206046,"corporation":false,"usgs":true,"family":"Laveau","given":"Christopher","email":"","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791975,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moramarco, Tommaso 0000-0002-9870-1694","orcid":"https://orcid.org/0000-0002-9870-1694","contributorId":225686,"corporation":false,"usgs":false,"family":"Moramarco","given":"Tommaso","email":"","affiliations":[{"id":41180,"text":"IRPI-Consiglio Nazionale delle Ricerche","active":true,"usgs":false}],"preferred":false,"id":791976,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Jones, Mark E. 0000-0002-9242-1528","orcid":"https://orcid.org/0000-0002-9242-1528","contributorId":225687,"corporation":false,"usgs":true,"family":"Jones","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791977,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gourley, Jonathan J 0000-0001-7363-3755","orcid":"https://orcid.org/0000-0001-7363-3755","contributorId":225540,"corporation":false,"usgs":false,"family":"Gourley","given":"Jonathan","email":"","middleInitial":"J","affiliations":[{"id":41158,"text":"NOAA/OAR/National Severe Storms Laboratory, Norman, OK, USA 73072","active":true,"usgs":false}],"preferred":false,"id":791978,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wasielewski, Danny","contributorId":225688,"corporation":false,"usgs":false,"family":"Wasielewski","given":"Danny","affiliations":[{"id":41181,"text":"NOAA National Severe Storms Laboratory","active":true,"usgs":false}],"preferred":false,"id":791979,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70222531,"text":"70222531 - 2020 - Hydrologically induced deformation in Long Valley Caldera and adjacent Sierra Nevada","interactions":[],"lastModifiedDate":"2021-08-03T12:45:57.564571","indexId":"70222531","displayToPublicDate":"2020-04-20T07:43:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologically induced deformation in Long Valley Caldera and adjacent Sierra Nevada","docAbstract":"Vertical and horizontal components of GNSS displacements in the Long Valley Caldera and adjacent Sierra Nevada range show a clear correlation with hydrological trends at both multiyear and seasonal time scales. We observe a clear vertical and horizontal seasonal deformation pattern primarily attributable to the solid earth response to hydrological surface loading at large-to-regional (Sierra Nevada range) scales. Several GNSS sites, located at the eastern edge of the Sierra Nevada along the southwestern rim of Long Valley Caldera, also show significant horizontal deformation that cannot be explained by elastic deformation from surface loading. Due to the location of these sites and the strong correlation between their horizontal displacements and spring discharge, we hypothesize that this deformation reflects poroelastic processes related to snowmelt runoff water infiltrating into the Sierra Nevada slopes around Long Valley Caldera. Interestingly, this is also an area where water infiltrates to feed the local hydrothermal system, and where snowmelt-induced earthquake swarms have been recently detected.
Manganese (Mn) plays a critical role in river-water quality because Mn-oxides serve as sorption sites for contaminant metals. The aim of this study is to understand the seasonal cycling of Mn in an alpine streambed that experiences large spring snowmelt events and the potential responses to changes in snowmelt timing and magnitude. To address this goal, annual variations in river-water/groundwater interaction and Mn(aq) transport were measured and modeled in the bed of East River, Colorado, USA. In observations and numerical models, oxygenated river water containing dissolved organic carbon (DOC) mixes with groundwater rich in Mn(aq) in the streambed. The mixing depth increases during spring snowmelt when river discharge increases, leading to a greater DOC supply to the hyporheic zone and net respiration of Mn-oxides, despite an enhanced supply of oxygen. As groundwater upwelling resumes during the subsequent baseflow period, Mn(aq)-rich groundwater mixes with oxygenated river water, resulting in net accumulation of Mn-oxides until the bed freezes in winter. To explore potential responses of Mn transport to different climate-induced hydrological regimes, three hydrograph scenarios were numerically modeled (historic, low-snow, and storm) for the Rocky Mountain region. In a warming climate, Mn(aq) export to the river decreases, and Mn(aq) oxidation is favored in the upper streambed sediments over more of the year. One important implication is that the streambed may have an increased sorption capacity for metals over more of the year, leading to potential changes in river-water quality.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-020-02146-6","usgsCitation":"Bryant, S., Sawyer, A., Briggs, M., Saup, C., Nelson, A.R., Wilkins, M.J., Christensen, J.R., and Williams, K.H., 2020, Seasonal manganese transport in the hyporheic zone of a snowmelt-dominated river (East River, Colorado): Hydrogeology Journal, v. 28, p. 1323-1341, https://doi.org/10.1007/s10040-020-02146-6.","productDescription":"19 p.","startPage":"1323","endPage":"1341","ipdsId":"IP-115069","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":385333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"East River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.95238709449768,\n 38.92190699243362\n ],\n [\n -106.94936156272888,\n 38.92190699243362\n ],\n [\n -106.94936156272888,\n 38.923893566458055\n ],\n [\n -106.95238709449768,\n 38.923893566458055\n ],\n [\n -106.95238709449768,\n 38.92190699243362\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Bryant, S.","contributorId":222764,"corporation":false,"usgs":false,"family":"Bryant","given":"S.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sawyer, A.","contributorId":222761,"corporation":false,"usgs":false,"family":"Sawyer","given":"A.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saup, C.","contributorId":222763,"corporation":false,"usgs":false,"family":"Saup","given":"C.","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":814780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, A. R","contributorId":193402,"corporation":false,"usgs":false,"family":"Nelson","given":"A.","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":814781,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilkins, M. J.","contributorId":176779,"corporation":false,"usgs":false,"family":"Wilkins","given":"M.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":814782,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christensen, J. R.","contributorId":204686,"corporation":false,"usgs":false,"family":"Christensen","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":36974,"text":"U.S. Environmental Protection Agency, National Exposure Research Laboratory, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":814783,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, K. H.","contributorId":176777,"corporation":false,"usgs":false,"family":"Williams","given":"K.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":814784,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70214078,"text":"70214078 - 2020 - HESS opinions: Beyond the long-term water balance: Evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds","interactions":[],"lastModifiedDate":"2020-09-22T16:00:25.192871","indexId":"70214078","displayToPublicDate":"2020-04-17T10:02:25","publicationYear":"2020","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":"HESS opinions: Beyond the long-term water balance: Evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds","docAbstract":"Global hydroclimatic conditions have been substantially altered over the past century by anthropogenic influences that arise from the warming global climate and from local/regional anthropogenic disturbances. Traditionally, studies have used coupling of multiple models to understand how land-surface water fluxes vary due to changes in global climatic patterns and local land-use changes. We argue that because the basis of the Budyko framework relies on the supply and demand concept, the framework could be effectively adapted and extended to quantify the role of drivers – both changing climate and local human disturbances – in altering the land-surface response across the globe. We review the Budyko framework, along with these potential extensions, with the intent of furthering the applicability of the framework to emerging hydrologic questions. Challenges in extending the Budyko framework over various spatio-temporal scales and the use of global datasets to evaluate the water balance at these various scales are also discussed.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-24-1975-2020","usgsCitation":"Sankarasubramanian, A., Wang, D., Archfield, S.A., Reitz, M., Vogel, R., Mazrooei, A., and Mukhopadhyaya, S., 2020, HESS opinions: Beyond the long-term water balance: Evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds: Hydrology and Earth System Sciences, v. 24, p. 1975-1984, https://doi.org/10.5194/hess-24-1975-2020.","productDescription":"10 p.","startPage":"1975","endPage":"1984","ipdsId":"IP-116284","costCenters":[{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":457044,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-24-1975-2020","text":"Publisher Index Page"},{"id":378673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Sankarasubramanian, A. 0000-0002-7668-1311","orcid":"https://orcid.org/0000-0002-7668-1311","contributorId":241034,"corporation":false,"usgs":false,"family":"Sankarasubramanian","given":"A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":799382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Dingbao","contributorId":166993,"corporation":false,"usgs":false,"family":"Wang","given":"Dingbao","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":799383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":799384,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reitz, Meredith 0000-0001-9519-6103 mreitz@usgs.gov","orcid":"https://orcid.org/0000-0001-9519-6103","contributorId":196694,"corporation":false,"usgs":true,"family":"Reitz","given":"Meredith","email":"mreitz@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":799385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vogel, Richard M","contributorId":241035,"corporation":false,"usgs":false,"family":"Vogel","given":"Richard M","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":799386,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mazrooei, Amirhossein","contributorId":241036,"corporation":false,"usgs":false,"family":"Mazrooei","given":"Amirhossein","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":799387,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mukhopadhyaya, Sudarshana","contributorId":241037,"corporation":false,"usgs":false,"family":"Mukhopadhyaya","given":"Sudarshana","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":799388,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70207122,"text":"tm1D8 - 2020 - Passive sampling of groundwater wells for determination of water chemistry","interactions":[],"lastModifiedDate":"2020-04-16T11:28:30.827687","indexId":"tm1D8","displayToPublicDate":"2020-04-15T15:05:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1-D8","chapter":"","displayTitle":"Passive Sampling of Groundwater Wells for Determination of Water Chemistry","title":"Passive sampling of groundwater wells for determination of water chemistry","docAbstract":"Passive groundwater sampling is defined as the collection of a water sample from a well without the use of purging by a pump or retrieval by a bailer (Interstate Technology and Regulatory Council [ITRC], 2006; American Society for Testing and Materials [ASTM], 2014). No purging means that advection of water is not involved in collecting the water sample from the well. Passive samplers rely on diffusion as the primary process that drives their collection of chemical constituents. Diffusion is the transport of chemicals caused by the presence of a chemical gradient. Chemicals tend to move or diffuse from areas of higher concentration to areas of lower concentration to reach an average or equilibrium concentration. Passive sampling of groundwater relies on the ambient exchange of groundwater in the formation with water in the screened or open interval of a well. In this report, the term formation is used to describe all saturated hydrogeologic units that yield water to a well. If the well opening is unclogged and free of a film of deposits from physical turbidity or chemical precipitation, then the exchange of groundwater is likely adequate, and the water in the open interval will be representative of water in the formation. In some cases, the passive sample from the well opening can be more representative of groundwater from the formation than a sample collected by pumping if pumping induces mixing of water in the open interval with stagnant casing water that has undergone chemical alteration (Harte and others, 2018). In most cases, passive sampling will better represent the ambient groundwater chemistry flowing through the open interval of a well because pumping may capture water of different chemistry from downgradient or lateral areas that would not normally pass through the well. Three basic types of passive samplers are discussed in this report. The first type of passive sampler is the equilibrium-membrane type, which includes a semi-permeable membrane through which chemicals diffuse or permeate. Permeation is simply the process of water or chemicals moving through openings in the membrane. The authors contend that permeation is dominated by diffusion for many of the passive samplers discussed in this report. Some passive equilibrium-membrane-type samplers allow most types of chemical constituents through, whereas others allow the diffusion of only selected groups of chemicals. Once the chemical constituents are inside the membrane, they are retained by the equilibration of concentrations inside the sampler with those outside the sampler. The second type of passive sampler is an equilibrium-thief type, which has no semi-permeable membrane. Chemical constituents simply move through the openings in the body of the sampler either initially through advection and dispersion or over time primarily by diffusion. Chemical constituents reach equilibrium between the water in the sampler and the water in the well and are captured in the sampler when the sampler is closed. The third type of passive sampler is an accumulation-type sampler that contains sorptive media. Selected chemical constituents are sorbed onto the media that the sampler contains for later extraction and analysis. Although passive samplers have been available for more than 15 years (from present [2020]), their use by U.S. Geological Survey (USGS) hydrologists and hydrologic technicians to monitor groundwater quality largely has been limited to selected research studies. The authors believe that this may be the result of (1) a lack of exposure of most USGS personnel to passive samplers and the uses of these samplers and (2) the lack of a USGS-approved protocol for the proper use of these samplers by USGS personnel. This report is an effort to fill those two needs. The focus of this report is on hydraulic, hydrologic, and chemical considerations in the application of passive samplers and interpretation of groundwater chemistry results obtained using passive samplers in wells. This report describes the differences between purging and passive sampling methods in groundwater and explains how and why passive samplers work. The report points out the advantages and limitations of passive samplers in general and for each particular type of passive sampler. Important considerations to be taken into account prior to the use of passive samplers are discussed, such as defining the data-quality objectives, the water-quality constituents to be sampled, sample volumes required for analysis, well construction of the sampling network, and the geologic formations that will be sampled. Potential applications of passive samplers also are discussed, such as chemical-vertical profiling of wells. A general field protocol for the deployment, recovery, and sample collection using these devices is described, and some overall guidance for the practitioner with application examples is given. Comparison methods used to evaluate results from passive sampling versus purge sampling also are discussed.
","largerWorkTitle":"","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm1D8","collaboration":"","usgsCitation":"Imbrigiotta, T.E., and Harte, P.T., 2020, Passive sampling of groundwater wells for determination of water chemistry: U.S. Geological Survey Techniques and Methods, chap. 8, section D, book 1, 80 p., https://doi.org/10.3133/tm1d8.\n","productDescription":"ix, 80 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-082895","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":373983,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/01/d8/coverthb.jpg"},{"id":373984,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/01/d8/tm1d8.pdf","text":"Report","size":"4.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 1-D8"}],"publicComments":"This report is Chapter 8 of Section D: Water quality in Book 1: Collection of water data by direct measurement","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648