The Organ Mountains-Desert Peaks National Monument (Monument) in southern New Mexico was established in 2014. Given anticipated future demands in the Monument for recreation, livestock grazing, and maintenance of rights-of-way (for example, pipelines and powerlines), the Bureau of Land Management (BLM) needs a better understanding of the current soil and water resources and how infrastructure improvements could affect these resources and the watershed. Specifically, the BLM is concerned with infiltration and erosion and their relations to existing or planned infrastructure, such as roads, campgrounds, location of livestock grazing, and rights-of-way. Alternatives to the current land-use conditions, land-management practices, and infrastructure will be assessed by BLM to best protect Monument resources. The U.S. Geological Survey, in cooperation with the BLM, conducted a study to assess the soil and water resources within the Monument to provide an inventory and compilation of natural-resource information needed by resource managers for the BLM’s land-use planning process for this new national monument. The overall objectives of this study were to (1) compile and interpret existing soil- and water-resource data for the Monument and (2) provide a basic assessment of the surface hydrological effects of selected alternatives to current land use and infrastructure. Data were compiled by using geographic information system software and evaluated for hydrologic and landscape properties that influence infiltration, runoff, and erosion. The effects of changing vegetation were simulated by using different scenarios in the Rangeland Hydrology and Erosion Model. Results of this model indicate areas where soil loss or runoff may occur.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195142","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Blake, J.M., Mitchell, A.C., Shephard, Z., Ball, G., Chavarria, S., and Douglas-Mankin, K.R., 2020, Assessment of soil and water resources in the Organ Mountains-Desert Peaks National Monument, New Mexico: U.S. Geological Survey Scientific Investigations Report 2019–5142, 64 p., https://doi.org/10.3133/sir20195142.","productDescription":"Report: x, 64 p.; Data Release","numberOfPages":"78","onlineOnly":"Y","ipdsId":"IP-098054","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":372464,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5142/sir20195142.pdf","text":"Report","size":"87.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5142"},{"id":399617,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109724.htm"},{"id":372465,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JVHA4Z","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Database associated with the assessment of soil and water resources in the Organ Mountains-Desert Peaks National Monument"},{"id":372463,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5142/coverthb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Organ Mountains-Desert Peaks National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.3,\n 31.8511\n ],\n [\n -106.4639,\n 31.8511\n ],\n [\n -106.4639,\n 32.6628\n ],\n [\n -107.3,\n 32.6628\n ],\n [\n -107.3,\n 31.8511\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd NE
Albuquerque, New Mexico 87113
The U.S. Geological Survey (USGS), in cooperation with the California State Water Resources Control Board, is evaluating several questions about oil and gas development and groundwater resources in California, including (1) the location of groundwater resources; (2) the proximity of oil and gas operations and groundwater and the geologic materials between them; (3) the location of evidence (or no evidence) of fluids from oil and gas sources in groundwater; and (4) the pathways or processes responsible when fluids from oil and gas sources are present in groundwater (U.S. Geological Survey, 2019). As part of this evaluation, the USGS installed a multiple-well monitoring site in the southern San Joaquin Valley near Lost Hills, California, adjacent to the Lost Hills oil field. Data collected at the Lost Hills multiple-well monitoring site (LHSP) provide information about the geology, hydrology, geophysics, and geochemistry of the aquifer system, thus enhancing understanding of relations between adjacent groundwater and the Lost Hills oil field in an area where there is little groundwater data. This report presents construction information for the LHSP and initial geohydrologic data collected from the site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191114","collaboration":"Prepared in cooperation with California State Water Resources Control Board","usgsCitation":"Everett, R.R., Kjos, A., Brown, A.A., Gillespie, J.M., and McMahon, P.B., 2020, Multiple-well monitoring site adjacent to the Lost Hills oil field, Kern County, California: U.S. Geological Survey Open-File Report 2019–1114, 8 p., https://doi.org/10.3133/ofr20191114.","productDescription":"8 p.","numberOfPages":"8","onlineOnly":"Y","ipdsId":"IP-104714","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437100,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LGXIN8","text":"USGS data release","linkHelpText":"Aquifer test data for multiple-well monitoring site LHSP, Kern County, California"},{"id":399418,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109721.htm"},{"id":372427,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1114/coverthb.jpg"},{"id":372428,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1114/ofr20191114.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Lost Hills Oil Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.0167,\n 35.5294\n ],\n [\n -119.4833,\n 35.5294\n ],\n [\n -119.4833,\n 35.7667\n ],\n [\n -120.0167,\n 35.7667\n ],\n [\n -120.0167,\n 35.5294\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
As runoff flows over the land or impervious surfaces (paved streets, parking lots, and building roofs), it accumulates debris, chemicals, sediment, and other contaminants that can adversely affect water quality if the runoff discharge remains untreated. Pathogens, commonly measured using fecal indicator bacteria such as Escherichia coli, enterococci, or fecal coliform, are the most-frequent cause of water-quality impairment in rivers and streams in the United States. Rapid Creek originates in the western Black Hills area and flows east through Rapid City, South Dakota, to its mouth at the Cheyenne River. The water quality of Rapid Creek is important because the reach that flows through Rapid City is a valuable spawning area for a self-sustaining trout fishery, is actively used for recreation, and is a seasonal municipal water supply for the City of Rapid City. These uses (fishery, recreation, and water supply) are considered beneficial uses by the South Dakota Department of Environment and Natural Resources. Numerical criteria have been established for total suspended solids and Escherichia coli concentrations, among other water-quality constituents, for these beneficial uses. The objectives of this study were to improve the method by which fecal indicator bacteria and total suspended solids are quantified in the urban drainages within Rapid City and to provide information that helps identify origins of fecal indicator bacteria and total suspended solids. This information can be used in hydrologic models to estimate fecal indicator bacteria and total suspended solid loading from certain infrastructure elements in urban environments.
Stormwater samples analyzed for Escherichia coli, total suspended solids, specific conductance, and pH were collected in three drainage basin flowpaths within Rapid City: Jackson, Wildwood, and the Eco Prayer Park. Data-collection activities for this study focused on upgradient urban flowpath elements during rainfall events. This approach builds upon previous stormwater assessments that characterized the water quality in urban basin outlets near the downstream end of the stormwater flowpaths. Within each flowpath group, 4–6 sites were selected to represent the various infrastructure elements of the runoff process. These elements included roof downspouts, parking lots, street curbs and gutters, open channels, underground storm sewers, and stormwater ponds or best-management practice facilities.
In general, the concentrations of Escherichia coli and total suspended solids increased in the downstream direction for all flowpath sites. The wash-off process after the first flush is evident for total suspended solids and specific conductance; however, Escherichia coli concentrations did not necessarily follow the same pattern. Escherichia coli concentrations in the latter part of the runoff period were similar to or greater than the initial concentrations of the first set of samples. Stormwater-quality data were summarized by infrastructure type (roof downspout, parking lot, street curb, and channel/storm sewer) to provide information about approximate water-quality concentrations originating at the upper end of urban flowpaths. Escherichia coli and total suspended solid concentrations were lowest in samples collected from locations most isolated from human influence (roof downspouts); the median concentrations at these sites were 4 most probable number per 100 milliliters and 15 milligrams per liter, respectively. The delivery potential of fecal indicator bacteria and sediment from parking lots and street curbs was similar; median concentrations of Escherichia coli and total suspended solids were around 150–220 most probable number per 100 milliliters and 56–86 milligrams per liter, respectively. The downstream receiving channels and storm sewers where stormwater was aggregated typically contained the highest Escherichia coli concentrations (median was 1,800 most probable number per 100 milliliters), but the total suspended solid concentrations were similar to upstream elements in the flowpath (median was 69 milligrams per liter). The data collected from this study demonstrate that stormwater is contaminated with fecal indicator bacteria upon initial contact with impervious surfaces and highlight the importance of controlling the volume of stormwater discharges into receiving waterbodies via storage structures and pervious elements. Diluting stormwater with high concentrations of Escherichia coli with the receiving water’s (Rapid Creek) lower concentration of Escherichia coli is likely the primary mechanism for meeting the beneficial-use criterion threshold of 235 most probable number per 100 milliliters. Although total suspended solid concentrations in the upper parts of the basin (parking lots and street curbs) also begin at concentrations (56 to 86 milligrams per liter) above the beneficial-use criterion for Rapid Creek (53 milligrams per liter), current stormwater-control practices (storage ponds, swales, and wetlands) may be able to reduce suspended-sediment concentrations to meet this threshold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205004","collaboration":"Prepared in cooperation with the City of Rapid City","usgsCitation":"Hoogestraat, G.K., 2020, Stormwater quality of infrastructure elements in Rapid City, South Dakota, 2016–18: U.S. Geological Survey Scientific Investigations Report 2020–5004, 24 p., https://doi.org/10.3133/sir20205004.","productDescription":"Report: vii, 24 p.; Appendix; Dataset","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108184","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":399627,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109723.htm"},{"id":372437,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System database","linkHelpText":"– USGS water data for the Nation"},{"id":372436,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5004/sir20205004_appendix1.csv","text":"Appendix 1","size":"12.8 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5004 Appendix 1"},{"id":372434,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5004/coverthb.jpg"},{"id":372435,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5004/sir20205004.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5004"}],"country":"United States","state":"South Dakota","city":"Rapid City","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.32,\n 44.0111\n ],\n [\n -103.1364,\n 44.0111\n ],\n [\n -103.1364,\n 44.125\n ],\n [\n -103.32,\n 44.125\n ],\n [\n -103.32,\n 44.0111\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
Subsurface drainage is used to efficiently drain saturated soils to support productive agriculture in poorly drained terrains. Although subsurface drainage alters the water balance for agricultural fields, its effect on groundwater resources and groundwater recharge is poorly understood. In Minnesota, subsurface drainage has begun to increase in southeastern Minnesota, even though this part of the State is underlain by permeable karstic bedrock aquifers with only a thin layer of glacial sediments separating these aquifers from land surface.
To gain a better understanding of groundwater recharge effects from subsurface drainage, the U.S. Geological Survey (USGS), in cooperation with the Legislative-Citizen Commission on Minnesota Resources, led a 2-year hydrologic study to investigate this connection for two agricultural fields in southeastern Minnesota with subsurface drainage. A total of three monitoring plots were used between the two agricultural fields: two monitoring plots that included an actively drained area with peripheral, undrained areas, and a third monitoring plot without any subsurface drainage. Multiple piezometer transects were set up across the three monitoring plots to characterize the unsaturated zone and shallow water-table flow using pressure transducers and soil moisture probes. From these piezometers, groundwater recharge rates were derived using two different methods: the RISE Water-Table Fluctuation (WTF) method and the DRAINMOD model. In addition to these two methods, the USGS Soil-Water-Balance (SWB) model was used to estimate potential recharge rates for three different monitoring plots.
In addition to deriving groundwater recharge rates, the hydrologic budget was analyzed to interpret the water-table surface elevation and soil volumetric water content time series. At one of the two drained plots, the transects exhibited varying water-table surface elevation patterns. Frequent backflow from the adjacent ditch caused subsurface drainage flow to slow down or stop drainage through the main collector drain and cause pipe pressurization, so the closest transect appeared to be mostly controlled by the drain pressurization, whereas the farthest transect was more efficiently drained. Both of the drained monitoring plots had an elevation gradient parallel to the pattern tiles, sloping downward towards the collector drain that aggregated the parallel lines into a single drain. Because the transects were set at different gradients in the field, some of the water-table surface elevation differences were also attributed to lateral flow towards the lowest parts of the field.
Three methods were used to derive potential groundwater recharge rates: the RISE WTF method, the USGS SWB model, and DRAINMOD-derived deep seepage rates. Potential groundwater recharge rates, using the RISE WTF method, across all piezometers were 1.55 and 1.94 inches per year, respectively, for water years 2017 and 2018. More differentiation of potential recharge rates between different piezometer types occurred for water year 2018. Although the difference was slightly more than 1 inch between the drained and nondrained piezometers for water year 2018, this difference was statistically significant based on a t-test with a p-value of 0.036 (α=0.05). When looking at recharge based on distance from the drain, the subsurface drain did not affect potential recharge, although other factors such as variability in screen depths, well construction, and specific yield variability cannot be eliminated. The SWB model was also used to estimate potential recharge rates for water years 2017–18, with rates between 2.44 and 5.92 inches per year for the two drained sites, generally higher than the RISE WTF estimates. DRAINMOD-derived potential recharge rates were generally the highest of the three methods, with potential recharge rates varying from 2.07 to 9.49 inches per year.
Overall, there was a lack of agreement between the three methods. These results were not remarkable, considering the fundamental differences in the methodology for each method. However, all methods did show a fundamental difference between piezometers within the drained area and piezometers outside the drained area, including the third undrained monitoring plot. The drained areas show a lower overall potential groundwater recharge compared to the nondrained areas for all three estimates. The difference for the 2018 recharge estimates was slightly higher than 1 inch for the RISE WTF method, the difference was almost double for the nine sites for the DRAINMOD model, and the difference between the drain and undrained plots was even more significant for the SWB model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205006","collaboration":"Prepared in cooperation with the Legislative-Citizen Commission on Minnesota Resources","usgsCitation":"Smith, E.A., and Berg, A.M., 2020, Potential groundwater recharge rates for two subsurface-drained agricultural fields, southeastern Minnesota, 2016–18: U.S. Geological Survey Scientific Investigations Report 2020–5006, 57 p., https://doi.org/10.3133/sir20205006.","productDescription":"Report: ix, 54 p.; 5 Appendixes; 3 Data Releases; Dataset","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112919","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":372354,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5006/sir20205006_appendixes.xlsx","text":"Appendix 1 and 2","size":"3.55 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5006 Appendixes"},{"id":372353,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5006/sir20205006.pdf","text":"Report","size":"4.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5006"},{"id":372352,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5006/coverthb.jpg"},{"id":372355,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5006/sir20205006_appendix_table1.1.csv","text":"Appendix 1.1","size":"1.55 MB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5006 Appendix 1.1"},{"id":372356,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5006/sir20205006_appendix_table1.2.csv","text":"Appendix 1.2","size":"1.66 MB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5006 Appendix 1.2"},{"id":372357,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5006/sir20205006_appendix_table2.1.csv","text":"Appendix 2.1","size":"13.0 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5006 Appendix 2.1"},{"id":372358,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5006/sir20205006_appendix_table2.2.csv","text":"Appendix 2.2","size":"13.3 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5006 Appendix 2.2"},{"id":372359,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P987N30U","text":"USGS data release","linkHelpText":"DRAINMOD simulations for two agricultural drainage sites in western Fillmore County, southeastern Minnesota"},{"id":372360,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90N4AWG","text":"USGS data release","linkHelpText":"Soil-Water Balance model datasets used to estimate recharge for southeastern Minnesota, 2014–2018"},{"id":372361,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94LMOPP","text":"USGS data release","linkHelpText":"Potential groundwater recharge estimates based on a groundwater rise analysis technique for two agricultural sites in southeastern Minnesota, 2016–2018"},{"id":372362,"rank":11,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS dataset","linkHelpText":"– USGS groundwater data for Minnesota in USGS water data for the Nation"},{"id":399628,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109687.htm"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.4167,\n 43.595\n ],\n [\n -92.45,\n 43.595\n ],\n [\n -92.45,\n 43.5444\n ],\n [\n -92.4167,\n 43.5444\n ],\n [\n -92.4167,\n 43.595\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
5840 Enterprise Drive
Lansing, MI 48911
Cattail (Typha) is an iconic emergent wetland plant found worldwide. By producing an abundance of wind-dispersed seeds, cattail can colonize wetlands across great distances, and its rapid growth rate, large size, and aggressive expansion result in dense stands in a variety of aquatic ecosystems such as marshes, ponds, lakes, and riparian areas. Cattail can also quickly dominate disturbed areas with waterlogged soils such as roadside ditches, retention areas, and fringes of stormwater ponds. These dense stands impact local plant and animal life, biogeochemical cycling, and wetland hydrology, which in turn alter wetland functions. Over recent decades, the distribution and abundance of cattail in North America has increased as a result of human disturbances to natural water cycles and increased nutrient loads. In addition, highly competitive nonnative and hybrid taxa have worsened the rapid spread of cattail. Because cattail invasion and expansion often change wetlands in undesirable ways, wetland managers often respond with widespread management efforts, though these efforts may have short-lived or weak effects. Notwithstanding the negative impacts, cattail provides beneficial ecosystem services including the reduction of pollution through bioremediation and the production of biofuel material.
Despite the widespread distribution and invasive characteristics of cattail, a comprehensive review and synthesis of past and current research on cattail was lacking. To address this gap, a diverse team of researchers produced a paper that details the spread and management of cattail throughout North America, summarizing 4 decades of research from more than 650 references (Bansal and others, 2019). This fact sheet highlights the primary topics covered in the paper.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193076","usgsCitation":"Bansal, S., Tangen, B., Lishawa, S., Newman, S., and Wilcox, D., 2020, A review of Cattail (Typha) invasion in North American wetlands: U.S. Geological Survey Fact Sheet 2019-3076, 6 p., https://doi.org/10.3133/fs20193076.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-112132","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":371754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3076/coverthb.jpg"},{"id":372286,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3076/fs20193076.pdf","text":"Report","size":"15.3 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3076"}],"contact":"Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401-7317
Northern high‐latitude lakes are undergoing climate‐induced changes including shifts in their hydrologic connectivity with terrestrial ecosystems. How this will impact dissolved organic matter (DOM) biogeochemistry remains uncertain. We examined the drivers of DOM composition for lakes in the Yukon Flats Basin in Alaska, an arid region of low relief that is characteristic of over one‐quarter of circumpolar lake area. Utilizing the vascular plant biomarker lignin, chromophoric dissolved organic matter (CDOM), and ultrahigh‐resolution mass spectrometry, we interpreted DOM compositional changes using lake‐water stable isotope (δ18O‐H2O) composition as a proxy for lake hydrologic connectivity with the landscape. We observed a relative decrease in CDOM in more hydrologically isolated lakes (enriched δ18O‐H2O) without a corresponding decrease in dissolved organic carbon (DOC) concentration. Although DOC and CDOM were weakly correlated, a significant positive relationship between lignin and CDOM (r2 = 0.67) demonstrates that optical parameters are useful for estimating lignin concentration and thus vascular plant contribution to lake DOM. Indicators of allochthonous DOM, including lignin carbon normalized yields, CDOM aromaticity proxies, and relative abundances of polyphenolic and condensed aromatic compound classes, were negatively correlated with δ18O‐H2O (r2 > 0.45), suggesting there is little allochthonous DOM supplied to many of these hydrologically isolated lakes. We conclude that decreased lake hydrologic connectivity, driven by ongoing climate change (i.e., decreased precipitation, warming temperatures), will reduce allochthonous DOM contributions and shift lakes toward lower CDOM systems with ecosystem‐scale ramifications for heat transfer, photochemical reactions, productivity, and ultimately their biogeochemical function.
","language":"English","publisher":"Wiley","doi":"10.1002/lno.11417","usgsCitation":"Johnston, S.E., Striegl, R.G., Bogard, M.J., Dornblaser, M.M., Butman, D.E., Kellerman, A.M., Wickland, K.P., Podgorski, D.C., and Spencer, R., 2020, Hydrologic connectivity determines dissolved organic matter biogeochemistry in northern high-latitude lakes: Limnology and Oceanography, v. 65, no. 8, p. 1764-1780, https://doi.org/10.1002/lno.11417.","productDescription":"17 p.","startPage":"1764","endPage":"1780","ipdsId":"IP-114991","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":373035,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.40136718749997,\n 66.53076810915225\n ],\n [\n -142.49267578125,\n 66.53076810915225\n ],\n [\n -142.49267578125,\n 69.4960701797534\n ],\n [\n -156.40136718749997,\n 69.4960701797534\n ],\n [\n -156.40136718749997,\n 66.53076810915225\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnston, Sarah Ellen","contributorId":213256,"corporation":false,"usgs":false,"family":"Johnston","given":"Sarah","email":"","middleInitial":"Ellen","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":784249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - 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This study uses paleoflood hydrology to examine a small portion the underutilized, but very extensive natural record of Holocene extreme floods in the UCRB. We perform a meta-analysis of 77 extreme paleofloods from seven slackwater deposit sites in the UCRB to show linkages between Holocene climate patterns and extreme floods. The analysis demonstrates several clusters of extreme flood activity: 8040-7790, 3600-3460, 2880-2740, 2330-700, and 620-0 years BP. The extreme paleofloods were found to occur during both dry and wet periods in the paleoclimate record. When compared with independent paleoclimatic records across the Rocky Mountains and the southwestern U.S., the observed temporal clustering pattern of UCRB extreme paleofloods shows associations with periods of abruptly intensified North Pacific-derived storms connected with enhanced El Niño variability.","language":"English","publisher":"SAGE Journals","doi":"10.1177/0309133320904038","usgsCitation":"Liu, T., Ji, L., Baker, V.R., Harden, T.M., and Cline, M.L., 2020, Holocene paleofloods and their climatological context, Upper Colorado River Basin, USA: Progress in Physical Geography: Earth and Environment, v. 44, no. 5, p. 727-745, https://doi.org/10.1177/0309133320904038.","productDescription":"19 p.","startPage":"727","endPage":"745","ipdsId":"IP-114520","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":372335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.0703125,\n 36.56260003738545\n ],\n [\n -114.521484375,\n 34.77771580360469\n ],\n [\n -107.05078125,\n 34.59704151614417\n ],\n [\n -105.2490234375,\n 36.24427318493909\n ],\n [\n -104.4140625,\n 39.095962936305476\n ],\n [\n -105.380859375,\n 41.64007838467894\n ],\n [\n -106.962890625,\n 42.16340342422401\n ],\n [\n -112.8955078125,\n 42.74701217318067\n ],\n [\n -116.27929687499999,\n 42.61779143282346\n ],\n [\n -118.5205078125,\n 40.81380923056958\n ],\n [\n -118.3447265625,\n 38.37611542403604\n ],\n [\n -117.0703125,\n 36.56260003738545\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Taojun","contributorId":201798,"corporation":false,"usgs":false,"family":"Liu","given":"Taojun","email":"","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":782311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ji, Lin","contributorId":222495,"corporation":false,"usgs":false,"family":"Ji","given":"Lin","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":782314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, Victor R.","contributorId":201141,"corporation":false,"usgs":false,"family":"Baker","given":"Victor","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":782312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harden, Tessa M. 0000-0001-9854-1347 tharden@usgs.gov","orcid":"https://orcid.org/0000-0001-9854-1347","contributorId":192153,"corporation":false,"usgs":true,"family":"Harden","given":"Tessa","email":"tharden@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cline, Michael L.","contributorId":222494,"corporation":false,"usgs":false,"family":"Cline","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":40551,"text":"Rizzo and Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":782313,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207558,"text":"pp1864 - 2020 - Groundwater availability of the Northern High Plains aquifer in Colorado, Kansas, Nebraska, South Dakota, and Wyoming","interactions":[],"lastModifiedDate":"2022-04-22T19:15:11.066381","indexId":"pp1864","displayToPublicDate":"2020-02-04T11:37:46","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1864","displayTitle":"Groundwater Availability of the Northern High Plains Aquifer in Colorado, Kansas, Nebraska, South Dakota, and Wyoming","title":"Groundwater availability of the Northern High Plains aquifer in Colorado, Kansas, Nebraska, South Dakota, and Wyoming","docAbstract":"The Northern High Plains aquifer underlies about 93,000 square miles of Colorado, Kansas, Nebraska, South Dakota, and Wyoming and is the largest subregion of the nationally important High Plains aquifer. Irrigation, primarily using groundwater, has supported agricultural production since before 1940, resulting in nearly $50 billion in sales in 2012. In 2010, the High Plains aquifer had the largest groundwater withdrawals of any major aquifer system in the United States. Nearly one-half of those withdrawals were from the Northern High Plains aquifer, which has little hydrologic interaction with parts of the aquifer farther south. Land-surface elevation ranges from more than 7,400 feet (ft) near the western edge to less than 1,100 ft near the eastern edge. Major stream primarily flow west to east and include the Big Blue River, Elkhorn River, Loup River, Niobrara River, Republican River and Platte River with its two forks—the North Platte River and South Platte River. Population in the Northern High Plain aquifer area is sparse with only 2 cities having a population greater than 30,000.
Droughts across much of the area from 2001 to 2007, combined with recent (2004–18) legislation, have heightened concerns regarding future groundwater availability and highlighted the need for science-based water-resource management. Groundwater models with the capability to provide forecasts of groundwater availability and related stream base flows from the Northern High Plains aquifer were published recently (2016) and were used to analyze groundwater availability. Stream base flows are generally the dominant component of total streamflow in the Northern High Plains aquifer, and total streamflows or shortages thereof define conjunctive management triggers, at least in Nebraska. Groundwater availability was evaluated through comparison of aquifer-scale water budgets compared for periods before and after major groundwater development and across selected future forecasts. Groundwater-level declines and the forecast amount of groundwater in storage in the aquifer also were examined.
Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Streamflow controls many freshwater and marine processes, including salinity profiles, sediment composition, fluxes of nutrients, and the timing of animal migrations. Watersheds that border the Gulf of Alaska (GOA) comprise over 400,000 km2 of largely pristine freshwater habitats and provide ecosystem services such as reliable fisheries for local and global food production. Yet no comprehensive watershed-scale description of current temporal and spatial patterns of streamflow exists within the coastal GOA. This is an immediate need because the spatial distribution of future streamflow patterns may shift dramatically due to warming air temperature, increased rainfall, diminishing snowpack, and rapid glacial recession. Our primary goal was to describe variation in streamflow patterns across the coastal GOA using an objective set of descriptors derived from flow predictions at the downstream-most point within each watershed. We leveraged an existing hydrologic runoff model and Bayesian mixture model to classify 4,140 watersheds into 13 classes based on seven streamflow statistics. Maximum discharge timing (annual phase shift) and magnitude relative to mean discharge (amplitude) were the most influential attributes. Seventy-six percent of watersheds by number showed patterns consistent with rain or snow as dominant runoff sources, while the remaining watersheds were driven by rain-snow, glacier, or low-elevation wetland runoff. Streamflow classes exhibited clear mechanistic links to elevation, ice coverage, and other landscape features. Our classification identifies watersheds that might shift streamflow patterns in the near future and, importantly, will help guide the design of studies that evaluate how hydrologic change will influence coastal GOA ecosystems.
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Ryan","email":"jbellmore@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":833916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crumley, Ryan L.","contributorId":275278,"corporation":false,"usgs":false,"family":"Crumley","given":"Ryan","email":"","middleInitial":"L.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":833917,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208453,"text":"70208453 - 2020 - Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models","interactions":[],"lastModifiedDate":"2020-02-11T07:40:36","indexId":"70208453","displayToPublicDate":"2020-01-31T07:37:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models","docAbstract":"Determining hydrologic conditions prior to instrumental records is a challenge for restoration of freshwater ecosystems worldwide. Paleoecologic data provide this information on past conditions and when these data are used to adjust hydrologic models, allow conditions to be hindcast that may not be directly estimated from the paleo-data alone. In this context, the paleo-data provide real-world estimates as input to the models. Restoration of the Greater Everglades Ecosystem requires this understanding of the hydrology of the natural system prior to significant alterations due to water management and land use. Large scale models such as the Natural Systems Model (NSM 4.6.2) have been used by the South Florida Water Management District and other agencies responsible for restoration to estimate past hydrologic conditions; however, these models typically portray a drier natural system for the beginning of the 20th century than what is indicated by paleoecologic analyses and historical data. The purpose of this study is to estimate pre-20th century water levels, hydroperiods and flow in the freshwater wetlands of the Everglades by using pollen assemblage data in three sediment cores to adjust the Natural Systems Model. This study is designed to further test estimates of flow through the Everglades derived from analysis of sediment cores collected in Florida Bay. The results demonstrate that the NSM 4.6.2 underestimates water levels and hydroperiods in the Everglades compared to the paleo-adjusted NSM 4.6.2 model outputs. Flow models that use the paleo-adjusted water levels as input indicate flow through Shark River Slough in the late 19th century was approximately two times flow between 1990 and 2000, and flow through Taylor Slough was approximately three times flow between 1990 and 2000. The flow estimates derived from this study agree with the estimates derived from earlier studies using estuarine cores. This integration of paleoecologic information and hydrologic models provides resource managers with the best available estimates of past conditions and allows them to set realistic targets for restoration of freshwater ecosystems.","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2020.00003","usgsCitation":"Marshall, F.E., Bernhardt, C.E., and Wingard, G.L., 2020, Estimating late 19th century hydrology in the Greater Everglades Ecosystem: An integration of paleoecologic data and models: Frontiers in Environmental Science, v. 8, no. 3, 21 p., https://doi.org/10.3389/fenvs.2020.00003.","productDescription":"21 p.","ipdsId":"IP-099728","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":457934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2020.00003","text":"Publisher Index Page"},{"id":372206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.58447265624999,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 25.903703303407667\n ],\n [\n -81.58447265624999,\n 25.903703303407667\n ],\n [\n -81.58447265624999,\n 25.110471486223346\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, Frank E.","contributorId":222355,"corporation":false,"usgs":false,"family":"Marshall","given":"Frank","email":"","middleInitial":"E.","affiliations":[{"id":40533,"text":"Cetacean Logic Foundation","active":true,"usgs":false}],"preferred":false,"id":781946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":781947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":781945,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208526,"text":"70208526 - 2020 - Climate change vulnerability assessment for Pacific Lamprey in rivers of the Western United States","interactions":[],"lastModifiedDate":"2020-02-14T06:51:19","indexId":"70208526","displayToPublicDate":"2020-01-31T06:48:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2299,"text":"Journal of Freshwater Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Climate change vulnerability assessment for Pacific Lamprey in rivers of the Western United States","docAbstract":"Pacific Lamprey (Entosphenus tridentatus) are a native anadromous species that, like salmon, historically returned to spawn in large numbers in watersheds along the west coast of the United States (U.S.). Lamprey play a vital role in river ecosystems and are one of the oldest vertebrates that have persisted over time likely influencing the evolution of many aquatic species. Pacific Lamprey have declined in abundance and are restricted in distribution throughout Washington, Oregon, Idaho and California. A key uncertainty influencing Pacific Lamprey status is the impact of climate change. We modified the NatureServe Climate Change Vulnerability Index (CCVI) to accommodate climate predictions from the International Panel on Climate Change. Using downscaled information, we characterized changes in 15 rivers occupied by Pacific Lamprey in the western U.S. We evaluated this risk under Representative Concentration Pathways (RCP) 4.5 and 8.5 for two time periods (mid-century 2040–2069 and end-century 2070–2099). The CCVI scores generally increased when going from RCP 4.5 to RCP 8.5 in three Global Climate Models for both mid-century and end-century, which our analyses forecasts degraded stream temperature and hydrologic conditions under increasing greenhouse gas emissions. The geographically assessed results suggest that climate change impacts to Pacific Lamprey vulnerability are magnified in highly altered rivers. If we continue to observe greenhouse gas emission levels associated with the RCP 8.5, Pacific Lamprey will be at greater risk to climate change impacts. In order to mitigate the risk from climate change toward the end of the century, additional actions will need to be prioritized to rapidly reduce the impact of these threats such as increasing flow, creating backwater habitat, restoring riparian vegetation and reducing stream disturbances. The findings revealed the patterns of vulnerability for Pacific Lamprey across their U.S. range are informative for prioritizing river restoration actions when paired with regional implementation plans.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02705060.2019.1706652","usgsCitation":"Wang, C., Shaller, H.A., Coates, K.C., Hayes, M.C., and Rose, R.K., 2020, Climate change vulnerability assessment for Pacific Lamprey in rivers of the Western United States: Journal of Freshwater Ecology, v. 35, no. 1, p. 29-55, https://doi.org/10.1080/02705060.2019.1706652.","productDescription":"27 p.","startPage":"29","endPage":"55","ipdsId":"IP-113962","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":457941,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2019.1706652","text":"Publisher Index Page"},{"id":372336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Washington, Oregon, Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.0244140625,\n 48.04870994288686\n ],\n [\n -124.49707031249999,\n 44.77793589631623\n ],\n [\n -124.49707031249999,\n 41.934976500546604\n ],\n [\n -124.49707031249999,\n 40.38002840251183\n ],\n [\n -123.96972656249999,\n 39.232253141714885\n ],\n [\n -122.9150390625,\n 39.842286020743394\n ],\n [\n -120.9814453125,\n 41.0130657870063\n ],\n [\n -119.44335937499999,\n 42.35854391749705\n ],\n [\n -116.19140625,\n 43.004647127794435\n ],\n [\n -114.12597656249999,\n 43.67581809328341\n ],\n [\n -113.9501953125,\n 45.73685954736049\n ],\n [\n -115.3564453125,\n 46.619261036171515\n ],\n [\n -116.4111328125,\n 47.724544549099676\n ],\n [\n -118.125,\n 48.86471476180277\n ],\n [\n -121.1572265625,\n 49.210420445650286\n ],\n [\n -123.26660156249999,\n 48.980216985374994\n ],\n [\n -124.8486328125,\n 48.25394114463431\n ],\n [\n -125.0244140625,\n 48.04870994288686\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Christina J","contributorId":222489,"corporation":false,"usgs":false,"family":"Wang","given":"Christina J","affiliations":[{"id":40548,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, Vancouver, WA","active":true,"usgs":false}],"preferred":false,"id":782296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaller, Howard A","contributorId":222490,"corporation":false,"usgs":false,"family":"Shaller","given":"Howard","email":"","middleInitial":"A","affiliations":[{"id":40549,"text":"U.S. Fish and Wildlife Service, Retired","active":true,"usgs":false}],"preferred":false,"id":782297,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coates, Kelly C.","contributorId":193504,"corporation":false,"usgs":false,"family":"Coates","given":"Kelly","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":782298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, Michael C. 0000-0002-9060-0565 mhayes@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0565","contributorId":3017,"corporation":false,"usgs":true,"family":"Hayes","given":"Michael","email":"mhayes@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":782299,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rose, Robert K","contributorId":222492,"corporation":false,"usgs":false,"family":"Rose","given":"Robert","email":"","middleInitial":"K","affiliations":[{"id":40550,"text":"Yakama Nation Fisheries, Toppenish, WA","active":true,"usgs":false}],"preferred":false,"id":782300,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207582,"text":"sir20195150 - 2020 - Numerical simulation of groundwater availability in central Moloka‘i, Hawai‘i","interactions":[],"lastModifiedDate":"2022-04-25T20:32:20.678493","indexId":"sir20195150","displayToPublicDate":"2020-01-30T12:22:46","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5150","displayTitle":"Numerical Simulation of Groundwater Availability in Central Moloka‘i, Hawai‘i","title":"Numerical simulation of groundwater availability in central Moloka‘i, Hawai‘i","docAbstract":"Since the 1990s, increased chloride concentrations of water pumped from wells (much of which is used for drinking water) and the effects of withdrawals on groundwater-dependent ecosystems have led to concerns over groundwater availability on the island of Molokaʻi, Hawaiʻi. An improved understanding of the hydrologic effects of proposed groundwater withdrawals is needed to ensure effective management of the groundwater resources of Molokaʻi, plan for possible growth, and accommodate cultural, social, and economic concerns. To address the information needs of managers and community stakeholders on Molokaʻi, the U.S. Geological Survey developed a numerical groundwater model capable of simulating salinity change and reduction in groundwater discharge in coastal areas of central and southern Molokaʻi. Estimates of groundwater recharge needed as input to the numerical groundwater model were made using a daily water budget for each decade during 1940−2012 (the period 2000−12 spanned 13 years) and the most current available data, including the distributions of monthly rainfall and potential evapotranspiration. Total island recharge during the decadal periods ranged from a low of about 189 Mgal/d during the 1970s to a high of 278 Mgal/d during the 1960s. These recharge estimates were used to develop an island-wide numerical groundwater model with simplifying assumptions (sharp interface between freshwater and saltwater; two-dimensional flow). The island-wide model provided estimates of groundwater inflows to the main area of interest simulated with a three-dimensional numerical groundwater model. Simulated withdrawal scenarios were selected in consultation with water managers and stakeholders and consisted of: (1) a baseline scenario using average recharge (1978−2007 rainfall and 2010 land cover) and average 2016−17 withdrawals; (2) a scenario using average recharge and withdrawals from existing wells at pending (as of January 2019) water-use permit rates; (3) six scenarios using average recharge and selected withdrawals from existing and proposed wells; and (4) a scenario using reduced recharge and selected withdrawals from existing and proposed wells. Results of the simulated withdrawal scenarios indicate that wells may be capable of producing groundwater with chloride concentrations below 250 mg/L at withdrawal rates exceeding average 2016−17 rates. However, the quality of water withdrawn from production wells is dependent on the rate and distribution of the withdrawals. For all nonbaseline scenarios, simulated groundwater discharge to the nearshore environment is reduced relative to the baseline scenario. Areas of discharge reduction may correspond to areas used for cultural or subsistence purposes. The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the hydrologic effects of additional groundwater withdrawals in central Molokaʻi. The model has several limitations, including its nonuniqueness and inability to account for local-scale heterogeneities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195150","collaboration":"Prepared in cooperation with the State of Hawai‘i Department of Hawaiian Home Lands, State of Hawai‘i Office of Hawaiian Affairs, and County of Maui Department of Water Supply","usgsCitation":"Oki, D.S., Engott, J.A., and Rotzoll, K., 2020, Numerical simulation of groundwater availability in central Moloka‘i, Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2019–5150, 95 p., https://doi.org/10.3133/sir20195150.","productDescription":"Report: ix, 95 p.; Data Release","numberOfPages":"95","onlineOnly":"Y","ipdsId":"IP-032683","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":399622,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109628.htm"},{"id":371721,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HRQASS","linkHelpText":"Central Molokaʻi, Hawaiʻi, SUTRA model"},{"id":371719,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5150/coverthb.jpg"},{"id":371720,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5150/sir20195150.pdf","text":"Report","size":"40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5150"}],"country":"United States","state":"Hawaii","otherGeospatial":"Moloka‘i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.77352905273438,\n 21.179289725795993\n ],\n [\n -156.8572998046875,\n 21.163922551671376\n ],\n [\n -156.92184448242188,\n 21.167764494849468\n ],\n [\n -156.97265625,\n 21.211299542246586\n ],\n [\n -156.99737548828125,\n 21.189533621502626\n ],\n [\n -157.1429443359375,\n 21.199776807250093\n ],\n [\n -157.21298217773435,\n 21.220261047755002\n ],\n [\n -157.25830078125,\n 21.218980865996457\n ],\n [\n -157.25555419921875,\n 21.17672864097083\n ],\n [\n -157.2967529296875,\n 21.14599216495789\n ],\n [\n -157.30499267578125,\n 21.097313035028538\n ],\n [\n -157.18826293945312,\n 21.090906697412837\n ],\n [\n -157.08801269531247,\n 21.103719096296263\n ],\n [\n -157.03582763671875,\n 21.090906697412837\n ],\n [\n -156.90811157226562,\n 21.051181240269393\n ],\n [\n -156.84906005859375,\n 21.047336278183312\n ],\n [\n -156.77215576171875,\n 21.08450008351735\n ],\n [\n -156.70074462890625,\n 21.15879980561845\n ],\n [\n -156.77352905273438,\n 21.179289725795993\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
Migrating waterbirds moving between upper and lower latitudinal breeding and wintering grounds rely on a limited network of endorheic lakes and wetlands when crossing arid continental interiors. Recent drying of global endorheic water stores raises concerns over deteriorating migratory pathways, yet few studies have considered these effects at the scale of continental flyways. Here, we investigate the resiliency of waterbird migration networks across western North America by reconstructing long-term patterns (1984–2018) of terminal lake and wetland surface water area in 26 endorheic watersheds. Findings were partitioned regionally by snowmelt- and monsoon-driven hydrologies and combined with climate and human water-use data to determine their importance in predicting surface water trends. Nonlinear patterns of lake and wetland drying were apparent along latitudinal flyway gradients. Pervasive surface water declines were prevalent in northern snowmelt watersheds (lakes −27%, wetlands −47%) while largely stable in monsoonal watersheds to the south (lakes −13%, wetlands +8%). Monsoonal watersheds represented a smaller proportion of total lake and wetland area, but their distribution and frequency of change within highly arid regions of the continental flyway increased their value to migratory waterbirds. Irrigated agriculture and increasing evaporative demands were the most important drivers of surface water declines. Underlying agricultural and wetland relationships however were more complex. Approximately 7% of irrigated lands linked to flood irrigation and water storage practices supported 61% of all wetland inundation in snowmelt watersheds. In monsoonal watersheds, small earthen dams, meant to capture surface runoff for livestock watering, were a major component of wetland resources (67%) that supported networks of isolated wetlands surrounding endorheic lakes. Ecological trends and human impacts identified herein underscore the importance of assessing flyway-scale change as our model depictions likely reflect new and emerging bottlenecks to continental migration.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15010","usgsCitation":"Donnelly, J., King, S.L., Silverman, N., Collins, D., Carrera-Gonzalez, E., Lafon-Terrazas, A., and Moore, J., 2020, Climate and human water use diminish wetland networks supporting continental waterbird migration: Global Change Biology, v. 26, no. 4, p. 2042-2059, https://doi.org/10.1111/gcb.15010.","productDescription":"18 p.","startPage":"2042","endPage":"2059","ipdsId":"IP-112789","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":457990,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.15010","text":"Publisher Index Page"},{"id":395897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","volume":"26","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Donnelly, J.P.","contributorId":276300,"corporation":false,"usgs":false,"family":"Donnelly","given":"J.P.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":834724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silverman, N.L.","contributorId":276301,"corporation":false,"usgs":false,"family":"Silverman","given":"N.L.","email":"","affiliations":[{"id":56951,"text":"Adaptive Hydrology, LLC","active":true,"usgs":false}],"preferred":false,"id":834726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collins, D. P.","contributorId":276303,"corporation":false,"usgs":false,"family":"Collins","given":"D. P.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":834727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carrera-Gonzalez, E.M.","contributorId":276304,"corporation":false,"usgs":false,"family":"Carrera-Gonzalez","given":"E.M.","affiliations":[{"id":56953,"text":"Ducks Unlimited - Mexico","active":true,"usgs":false}],"preferred":false,"id":834728,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lafon-Terrazas, A.","contributorId":276305,"corporation":false,"usgs":false,"family":"Lafon-Terrazas","given":"A.","email":"","affiliations":[{"id":56954,"text":"PROFAUNA","active":true,"usgs":false}],"preferred":false,"id":834729,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, J.N.","contributorId":276306,"corporation":false,"usgs":false,"family":"Moore","given":"J.N.","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":834730,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208960,"text":"70208960 - 2020 - Water tracks enhance water flow above permafrost in upland Arctic Alaska hillslopes","interactions":[],"lastModifiedDate":"2020-03-10T08:25:31","indexId":"70208960","displayToPublicDate":"2020-01-24T08:24:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Water tracks enhance water flow above permafrost in upland Arctic Alaska hillslopes","docAbstract":"Upland permafrost regions occupy approximately one third of the Arctic landscape. In upland regions, hydrologic fluxes are influenced by water tracks, curvilinear features on hillslopes that preferentially fill with and route water in response to snowmelt and rainfall when the soil above continuous permafrost thaws in the summer. As continued warming of the Arctic may alter hydrologic cycling leading to increased frequency of extreme hydrologic events like drought and flooding as well as modification of biogeochemical cycling, it is imperative to untangle the interplay between precipitation, runoff, and subsurface flow as water is routed from upland Arctic regions to the Arctic Ocean. This study quantifies how ground surface temperatures affect groundwater discharge from hillslopes with water tracks in the upland Arctic by employing a three-dimensional, physically based subsurface flow model with variable saturation and freeze and thaw capabilities that is calibrated to field measurements from the Upper Kuparuk River watershed on the North Slope of Alaska, USA. Model analysis indicates that higher ground surface temperatures along water track hillslopes promote increases in groundwater discharge where water tracks act as conduits for large recharge events and continue to discharge groundwater into the autumn after the adjacent hillslope has frozen. Simulating the conditions that distinguish water tracks from their hillslope watersheds changes subsurface water storage and ground thermal responses but does not alter the total magnitude of groundwater discharge outside of parameter uncertainty. These findings suggest that water tracks play a complex and critical role in hydrologic cycles of the upland Arctic.","language":"English","publisher":"Wiley","doi":"10.1029/2019JF005256","usgsCitation":"Evans, S.G., Godsey, S., Rushlow, C.R., and Voss, C., 2020, Water tracks enhance water flow above permafrost in upland Arctic Alaska hillslopes: Journal of Geophysical Research F: Earth Surface, v. 125, no. 2, e2019JF005256, https://doi.org/10.1029/2019JF005256.","productDescription":"e2019JF005256","ipdsId":"IP-114552","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458014,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jf005256","text":"Publisher Index Page"},{"id":373038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -161.015625,\n 66.6181218846659\n ],\n [\n -140.80078125,\n 66.68778386116203\n ],\n [\n -141.328125,\n 70.05059634999759\n ],\n [\n -157.1484375,\n 71.71888229713917\n ],\n [\n -162.509765625,\n 70.95969716686398\n ],\n [\n -167.34375,\n 68.8159271333607\n ],\n [\n -166.2890625,\n 68.0404612590484\n ],\n [\n -162.509765625,\n 66.40795547978848\n ],\n [\n -161.015625,\n 66.6181218846659\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Sarah G.","contributorId":203464,"corporation":false,"usgs":false,"family":"Evans","given":"Sarah","email":"","middleInitial":"G.","affiliations":[{"id":36626,"text":"Appalachian State University","active":true,"usgs":false}],"preferred":false,"id":784202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Godsey, Sarah E","contributorId":223120,"corporation":false,"usgs":false,"family":"Godsey","given":"Sarah E","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":784203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rushlow, Caitlin R","contributorId":223121,"corporation":false,"usgs":false,"family":"Rushlow","given":"Caitlin","email":"","middleInitial":"R","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":784204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voss, Clifford I. 0000-0001-5923-2752","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":211844,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":784201,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208272,"text":"70208272 - 2020 - Soil shear strength losses in two fresh marshes with variable increases in N and P loading","interactions":[],"lastModifiedDate":"2020-10-28T15:13:27.375074","indexId":"70208272","displayToPublicDate":"2020-01-24T07:01:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Soil shear strength losses in two fresh marshes with variable increases in N and P loading","docAbstract":"We measured soil shear strength (SSS) from 2009 to 2018 in two hydrologically distinct freshwater marshes dominated by Panicum hemitomon after nitrogen (N) and phosphorous (P) were applied to the surface in spring. The average SSS averaged over 100 cm depth in the floating and anchored marshes declined up to 30% throughout the profiles and with no apparent differences in the effects of the low, medium, and high N+P dosing. Plots with only N or P additions exhibited significant changes in SSS at individual depths below 40 cm for the anchored marsh, but not the floating marsh. The average SSS for the anchored marsh over the entire 100 cm profile declined when N and P were added separately or together. At the floating marsh, however, the SSS decreased when N and P were added in combination, or P alone, but not for the N addition. Increasing nutrient availability to these freshwater marsh soils makes them weaker, and perhaps lost if eroded or uplifted by buoyant forces during storms. These results are consistent with results from multi-year experiments demonstrating higher decomposition rates, greenhouse gas emissions, and carbon losses in wetlands following increased nutrient availability.","language":"English","publisher":"Springer","doi":"10.1007/s13157-020-01265-w","usgsCitation":"Turner, R.E., Swarzenski, C.M., and Bodker, J.E., 2020, Soil shear strength losses in two fresh marshes with variable increases in N and P loading: Wetlands, v. 40, p. 1189-1199, https://doi.org/10.1007/s13157-020-01265-w.","productDescription":"11 p.","startPage":"1189","endPage":"1199","ipdsId":"IP-102316","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":458022,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13157-020-01265-w","text":"Publisher Index Page"},{"id":371899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.362060546875,\n 29.22889003019423\n ],\n [\n -89.2529296875,\n 29.22889003019423\n ],\n [\n -89.2529296875,\n 30.192618218499273\n ],\n [\n -92.362060546875,\n 30.192618218499273\n ],\n [\n -92.362060546875,\n 29.22889003019423\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Turner, R. Eugene","contributorId":172726,"corporation":false,"usgs":false,"family":"Turner","given":"R.","email":"","middleInitial":"Eugene","affiliations":[],"preferred":false,"id":781210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swarzenski, Christopher M. 0000-0001-9843-1471 cswarzen@usgs.gov","orcid":"https://orcid.org/0000-0001-9843-1471","contributorId":656,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Christopher","email":"cswarzen@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":781209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodker, James E.","contributorId":152482,"corporation":false,"usgs":false,"family":"Bodker","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":13050,"text":"Department of Oceanography and Coastal Sciences, Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":781211,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208490,"text":"70208490 - 2020 - Effects of John Martin Reservoir on water quality and quantity: Assessment by chemical, isotopic, and mass-balance methods","interactions":[],"lastModifiedDate":"2020-02-12T06:49:45","indexId":"70208490","displayToPublicDate":"2020-01-23T06:45:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5836,"text":"Journal of Hydrology X","onlineIssn":"2589-9155","active":true,"publicationSubtype":{"id":10}},"title":"Effects of John Martin Reservoir on water quality and quantity: Assessment by chemical, isotopic, and mass-balance methods","docAbstract":"Water quality and quantity can be influenced by transit through and storage in reservoirs. Assessing such effects can be challenging, however, because of mixing and residence times, and inter-annual net storage and release from both the reservoir itself and surrounding porosity. Here, different methodologies were used to assess the effect of John Martin Reservoir (JMR), located on the Arkansas River, on water volumes and the problematic constituents salinity (total dissolved solids, TDS), selenium (Se), and uranium (U). Methodologies addressed short-term (16 months) and long-term (31 years) effects depending upon data availability. Evaporation was assessed by using isotopes of water to determine 12% short-term evaporation, and by pan evaporation and changes in storage to determine 11% long-term evaporation. Salinity, Se, and U mass balance were assessed by using chloride (Cl−) as an index by which to measure short-term gains or losses between inflows and outflows in the short term. Chloride gain from ungaged inflows skewed those results to overestimate retention. Continuous monitoring of discharge and specific conductance for inflows and outflows, along with discrete sampling for dissolved constituents were used to compute long-term, load-based mass balance. Mild gains of TDS (34,000 ± 15,000 Mg/yr) and U (0.1 ± 0.5 Mg/yr) in JMR were detected. Although the additions are small relative to uncertainty, they indicate little to no retention of TDS and U and likely additions from ungaged inflows. In contrast, an average of 0.6 ± 0.2 Mg/yr or 23% of gaged inflow Se was removed in JMR. The study illustrates the benefit of long-term records for assessing the influence of reservoirs for which net storage and release keep them from approaching steady-state conditions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.hydroa.2020.100051","usgsCitation":"Bern, C.R., Holmberg, M.J., and Kisfalusi, Z.D., 2020, Effects of John Martin Reservoir on water quality and quantity: Assessment by chemical, isotopic, and mass-balance methods: Journal of Hydrology X, v. 7, https://doi.org/10.1016/j.hydroa.2020.100051.","productDescription":"100051, 13 p.","startPage":"100051","ipdsId":"IP-105016","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":458045,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hydroa.2020.100051","text":"Publisher Index Page"},{"id":372253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"John Martin Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.03218841552733,\n 38.048361431471385\n ],\n [\n -102.92404174804688,\n 38.048361431471385\n ],\n [\n -102.92404174804688,\n 38.08593231319764\n ],\n [\n -103.03218841552733,\n 38.08593231319764\n ],\n [\n -103.03218841552733,\n 38.048361431471385\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bern, Carleton R. 0000-0002-8980-1781 cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":201152,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holmberg, Michael J. 0000-0002-1316-0412 mholmber@usgs.gov","orcid":"https://orcid.org/0000-0002-1316-0412","contributorId":190084,"corporation":false,"usgs":true,"family":"Holmberg","given":"Michael","email":"mholmber@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kisfalusi, Zachary D. 0000-0001-6016-3213","orcid":"https://orcid.org/0000-0001-6016-3213","contributorId":222422,"corporation":false,"usgs":true,"family":"Kisfalusi","given":"Zachary","email":"","middleInitial":"D.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":782119,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208311,"text":"70208311 - 2020 - Evaluation of hydrologic impact of an irrigation curtailment program in the Upper Klamath Lake Basin using Landsat satellite data","interactions":[],"lastModifiedDate":"2020-05-05T16:44:59.832545","indexId":"70208311","displayToPublicDate":"2020-01-22T07:27:42","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":"Evaluation of hydrologic impact of an irrigation curtailment program in the Upper Klamath Lake Basin using Landsat satellite data","docAbstract":"Upper Klamath Lake (UKL) is the source of the Klamath river that flows through southern Oregon and northern California. The UKL basin is home to two endangered species and provides water for 81,000+ ha (200,000+ acres) of irrigation on the United States Bureau of Reclamation (USBR) Klamath Project located downstream of the UKL basin. Irrigated agriculture also occurs along the tributaries to UKL. During 2013–2016, water right calls resulted in various levels of curtailment of irrigation diversions from the tributaries to UKL. However, information on the extent of curtailment, how much irrigation water was saved, and its impact on the UKL is unknown. In this study, we combined Landsat-based actual evapotranspiration (ETa) data obtained from the Operational Simplified Surface Energy Balance (SSEBop) model with gridded precipitation and USGS station discharge data to evaluate the hydrologic impact of the curtailment program. Analysis was performed for five base years (2004, 2006, 2008-2010) and four target years (2013-2016) over irrigated areas above UKL. Our results indicated that the impact of the curtailment program over the June to September time-period was highest during 2013 and declined in each of the following years. The total on-field water savings were approximately 60 hm3 in 2013 and 2014, 44 hm3 in 2015, and 32 hm3 in 2016. The instream water flow change or extra water available (EWA) were found at 92, 68, 45, and 26 hm3 respectively for 2013, 2014, 2015 and 2016. Most water savings came from pasture and wetlands. Alfalfa showed the most decline in water use among grain crops. The resulting EWA from the curtailment contributed to a maximum of 19% of the lake inflows and 50% of the lake volume. This study presents the use of Landsat-based ETa and other remote sensing datasets for evaluating water-related impacts of the irrigation curtailment program.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13708","usgsCitation":"Velpuri, N., Senay, G., Schauer, M., Garcia, C.A., Singh, R., Friedrichs, M., Bohms, S., Haynes, J.V., and Conlon, T.D., 2020, Evaluation of hydrologic impact of an irrigation curtailment program in the Upper Klamath Lake Basin using Landsat satellite data: Hydrological Processes, v. 34, no. 8, p. 1697-1713, https://doi.org/10.1002/hyp.13708.","productDescription":"17 p.","startPage":"1697","endPage":"1713","ipdsId":"IP-111134","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":458053,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.13708","text":"Publisher Index Page"},{"id":437147,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BC38CL","text":"USGS data release","linkHelpText":"Assessing the impact of irrigation curtailment using Landsat satellite data: A case study in the Upper Klamath Lake basin"},{"id":371987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"California, Oregon","otherGeospatial":"Upper Klamath Lake Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.42041015624999,\n 40.76806170936614\n ],\n [\n -119.94323730468749,\n 40.76806170936614\n ],\n [\n -119.94323730468749,\n 43.205175817237304\n ],\n [\n -123.42041015624999,\n 43.205175817237304\n ],\n [\n -123.42041015624999,\n 40.76806170936614\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"8","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":216911,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga Manohar ","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":781360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel 0000-0002-8810-8539","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":216910,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":781361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schauer, Matthew 0000-0002-4198-3379","orcid":"https://orcid.org/0000-0002-4198-3379","contributorId":216909,"corporation":false,"usgs":true,"family":"Schauer","given":"Matthew","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":781362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia, C. Amanda 0000-0003-3776-3565 cgarcia@usgs.gov","orcid":"https://orcid.org/0000-0003-3776-3565","contributorId":1899,"corporation":false,"usgs":true,"family":"Garcia","given":"C.","email":"cgarcia@usgs.gov","middleInitial":"Amanda","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singh, Ramesh 0000-0002-8164-3483","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":216912,"corporation":false,"usgs":false,"family":"Singh","given":"Ramesh ","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":781364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Friedrichs, MacKenzie 0000-0002-9602-321X","orcid":"https://orcid.org/0000-0002-9602-321X","contributorId":216914,"corporation":false,"usgs":true,"family":"Friedrichs","given":"MacKenzie","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":781365,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bohms, Stefanie 0000-0002-2979-4655 sbohms@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":3148,"corporation":false,"usgs":true,"family":"Bohms","given":"Stefanie","email":"sbohms@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":781359,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haynes, Jonathan V. 0000-0001-6530-6252 jhaynes@usgs.gov","orcid":"https://orcid.org/0000-0001-6530-6252","contributorId":3113,"corporation":false,"usgs":true,"family":"Haynes","given":"Jonathan","email":"jhaynes@usgs.gov","middleInitial":"V.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781366,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conlon, Terrence D. 0000-0002-5899-7187 tdconlon@usgs.gov","orcid":"https://orcid.org/0000-0002-5899-7187","contributorId":819,"corporation":false,"usgs":true,"family":"Conlon","given":"Terrence","email":"tdconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781367,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70228899,"text":"70228899 - 2020 - An agricultural water use package for MODFLOW and GSFLOW","interactions":[],"lastModifiedDate":"2022-02-23T12:45:47.212533","indexId":"70228899","displayToPublicDate":"2020-01-16T06:43:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7599,"text":"Environmental Modeling and Software","active":true,"publicationSubtype":{"id":10}},"title":"An agricultural water use package for MODFLOW and GSFLOW","docAbstract":"The Agricultural Water Use (AG) Package was developed for simulating demand-driven and supply-constrained agricultural water use in MODFLOW and GSFLOW models. The AG Package uses pre-existing hydrologic simulation provided by MODFLOW and GSFLOW. Three options are available for simulating water use for agriculture: (1) user-specified demands, (2) demands determined by a user-specified irrigation trigger value that is compared to the ratio of the simulated actual to potential evapotranspiration (ET), and (3) demands determined by minimizing the difference between potential and actual ET. The latter two approaches use energy and soil-water balance to determine crop-water demands. Irrigation withdrawals are diverted into canals and routed to fields using the MODFLOW SFR Package, or irrigation water is provided/supplemented by groundwater. Combined with MODFLOW or GSFLOW, the AG Package can simulate dynamic water use by agriculture in developed basins while providing flexibility to represent a range of irrigation practices.
Infiltration-based green infrastructure has become a popular means of reducing stormwater hazards in urban areas. However, the long-term effects of green infrastructure on the geochemistry of roadside environments are poorly defined, particularly given the considerable roadside legacy metal contamination from historic industrial activity and vehicle emissions (e.g., Pb). Most current research on green infrastructure geochemistry is restricted to time periods of less than a year or limited sets of chemical species. This further limits our understanding of systems that evolve over time and are subject to seasonal variability. Between 2016 and 2018, two infiltration trenches in Pittsburgh, PA, were monitored to determine infiltration rates and dissolved nutrient and metal content. The trench water was analyzed to characterize seasonal patterns in both trench function and chemistry. Shifting patterns in infiltration rate and geochemical activity show trends corresponding with seasonal changes. Trench function is dependent on the local water table, with the highest infiltration rates occurring when evapotranspiration is active and groundwater elevation is low. Two seasonal chemical patterns were identified. The first is driven by road salt application in the winter and interaction of the salt pulse increase Pb and Cu concentrations. The second is driven by the formation of summer reducing environments that increase dissolved Fe and Mn. These findings suggest that chemical and hydrological activity in infiltration-based green infrastructure varies seasonally and may remobilize legacy contamination.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.136503","usgsCitation":"Mullins, A.R., Bain, D.J., Pfeil McCullough, E., Hopkins, K.G., Lavin, S., and Copeland, E., 2020, Seasonal drivers of chemical and hydrological patterns in roadside infiltration-based green infrastructure: Science of the Total Environment, v. 714, 136503, 9 p., https://doi.org/10.1016/j.scitotenv.2020.136503.","productDescription":"136503, 9 p.","ipdsId":"IP-107782","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":372502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","city":"Pittsburgh","otherGeospatial":"Schenley Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.95034217834473,\n 40.428067577817366\n ],\n [\n -79.93197441101074,\n 40.428067577817366\n ],\n [\n -79.93197441101074,\n 40.4415907903353\n ],\n [\n -79.95034217834473,\n 40.4415907903353\n ],\n [\n -79.95034217834473,\n 40.428067577817366\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"714","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mullins, Angela R.","contributorId":222657,"corporation":false,"usgs":false,"family":"Mullins","given":"Angela","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":782814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bain, Daniel J 0000-0003-1979-7016","orcid":"https://orcid.org/0000-0003-1979-7016","contributorId":197634,"corporation":false,"usgs":true,"family":"Bain","given":"Daniel","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":782815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pfeil McCullough, Erin","contributorId":222658,"corporation":false,"usgs":false,"family":"Pfeil McCullough","given":"Erin","email":"","affiliations":[],"preferred":false,"id":782816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":782817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lavin, S.","contributorId":107127,"corporation":false,"usgs":true,"family":"Lavin","given":"S.","email":"","affiliations":[],"preferred":false,"id":782818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Copeland, Erin","contributorId":222659,"corporation":false,"usgs":false,"family":"Copeland","given":"Erin","email":"","affiliations":[],"preferred":false,"id":782819,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208607,"text":"70208607 - 2020 - Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States","interactions":[],"lastModifiedDate":"2020-02-21T11:50:49","indexId":"70208607","displayToPublicDate":"2020-01-08T06:45:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States","docAbstract":"This study uses the explores the viability of a proxy model calibration strategy through assessment of the spatiotemporal variability of surface-depression storage and runoff generated with the U.S. Geological Survey’s National Hydrologic Model (NHM) infrastructure for hydrologic response units (HRUs; n=109,951) across the conterminous United States (CONUS). Simulated values for each HRU of daily surface-depression storage (treated as a decimal fraction of total possible volume) and monthly normalized runoff (0 to 1) values were calculated using Spearman’s rho at monthly and annual aggregations. Locations where values are correlated show where previously-developed proxy calibration strategies are likely to be effective. In addition, differences in the correlation for monthly and annual time scale aggregations show which time scale drives surface-depression storage processes in the NHM. Results show overall long-term (annual) correlation is more common than short-term (monthly) correlation over the CONUS; however, summary statistics for eighty-six ecoregions show five with higher ranges of monthly relative to annual Spearman’s rank coefficient values. This landscape-scale analysis shows simulations aggregated to an annual time scale are generally more dominant for the CONUS; however, simulations aggregated to monthly, short-term time scales are more dominant in focused areas where surface-depression storage processes are investigated.","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12826","usgsCitation":"Driscoll, J.M., Hay, L., Vanderhoof, M.K., and Viger, R.J., 2020, Spatiotemporal variability of modeled watershed scale surface-depression storage and runoff for the conterminous United States: Journal of the American Water Resources Association, v. 56, no. 1, p. 16-29, https://doi.org/10.1111/1752-1688.12826.","productDescription":"14 p.","startPage":"16","endPage":"29","ipdsId":"IP-093569","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction 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