Regional regression is a common tool used to estimate daily flow-duration curves (FDCs) at ungaged locations. In this report, several refinements to a particular implementation of the regional regression method for estimating FDCs are evaluated by consideration of different methodological options through a leave-one-out cross-validation procedure in the 19 major river basins of the conterminous United States. Regression analyses in this report are based on streamflow data from water years 1981–2013 (October 1, 1980 to September 30, 2013) from 1,378 mostly undisturbed watersheds. Linear regression using selected basin characteristics at 27 quantiles with nonexceedance probabilities ranging from 0.02 to 99.98 percent was applied. The regression computations were primarily by weighted least squares, with left-censored Gaussian regression solved by maximum likelihood in the presence of zero-valued quantiles.
The regional regression method as applied to the FDC estimation problem includes several methodological options that require determination of the better of two or more choices. The options considered in this report include (1) the setting of the maximum number of basin characteristics considered in the regression models for each region, (2) the method of placing the quantiles into groups (“flow regimes”) having the same basin characteristics used as independent variables, (3) the maximum number of candidate models retained from regressions at the single-quantile level that are retained for testing of the best model at the flow-regime scale, and (4) whether drainage area should be forced into the models. In all, 5 binary options were considered for most regions, resulting in 32 methodological combinations. Leave-one-out cross-validation predictions of FDC quantiles at each streamgage used in the study were used to evaluate compared options. Various performance measures were computed based on the predicted quantiles; these were combined by region and the methods were ranked for each measure.
Based on examination of the ranked methods compared across the measures, the following treatments produced the more accurate results: (1) using fewer basin characteristics (of the two options considered), (2) utilizing a variance of the unit FDC-based method of determining the flow regimes rather than fixed regimes, (3) retaining more models from the quantile-level regressions regime-wide consideration, and (4) forcing drainage area into the regression models. Results of analyses also indicate that performance varies more by region than by methodological option, with FDCs in arid regions and those with a large value of a measure of intraregional FDC heterogeneity being harder to predict, particularly with respect to the low-flow quantiles.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185072","collaboration":"Water Availability and Use Science Program","usgsCitation":"Over, T.M., Farmer, W.H., and Russell, A.M., 2018, Refinement of a regression-based method for prediction of flow-duration curves of daily streamflow in the conterminous United States: U.S. Geological Survey Scientific Investigations Report 2018–5072, 34 p., https://doi.org/10.3133/sir20185072.","productDescription":"Report: vi, 34 p.; Appendixes 1–3; Data Release","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085859","costCenters":[{"id":344,"text":"Illinois Water Science 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\"}}]}\n\n\n","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 N. Goodwin Ave.
Urbana, Illinois 61801
Two Donax obesulus and two Protothaca asperrima shells collected prior to the nuclear testing of the 1950's were micromilled at sub-seasonal resolution to yield new reservoir effect (ΔR) estimates for the coast of Peru. Shells from northern (4°40′S to 8°14′S) and central (13°52′S) Peru produced ΔR values of 123 ± 50 and 110 ± 49 years respectively. We found such values statistically indistinguishable from each other while reporting intra-annual ΔR variability along shells ontogeny in agreement with previously published regional ΔR values. This similarity suggests radiocarbon dating of short-lived (<1.5 years) mollusks shells is a useful tool for comparing marine radiocarbon signals. Additionally, our analysis of ΔR and δ18O changes along shells' ontogeny found a tenuous relationship between them. We are not the first one to report these phenomena in Peruvian upwelling, but we are the first to suggest that fast Lagrangian water mixing as a mechanism behind it.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2018.07.001","usgsCitation":"Etayo-Cadavid, M.F., Andrus, C.F., Jones, K.B., and Hodgins, G.W., 2018, Subseasonal variations in marine reservoir age from pre-bomb Donax obesulus and Protothaca asperrima shell carbonate: Chemical Geology, v. 526, p. 110-116, https://doi.org/10.1016/j.chemgeo.2018.07.001.","productDescription":"7 p.","startPage":"110","endPage":"116","ipdsId":"IP-022729","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468570,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2018.07.001","text":"Publisher Index Page"},{"id":357866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"526","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02fcbe4b0fc368eb53982","contributors":{"authors":[{"text":"Etayo-Cadavid, Miguel F.","contributorId":16296,"corporation":false,"usgs":true,"family":"Etayo-Cadavid","given":"Miguel","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":746574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrus, C. Fred T.","contributorId":80568,"corporation":false,"usgs":true,"family":"Andrus","given":"C.","email":"","middleInitial":"Fred T.","affiliations":[],"preferred":false,"id":746575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Kevin B. 0000-0002-6386-2623 kevinjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6386-2623","contributorId":565,"corporation":false,"usgs":true,"family":"Jones","given":"Kevin","email":"kevinjones@usgs.gov","middleInitial":"B.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":746576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hodgins, Gregory W. L.","contributorId":67787,"corporation":false,"usgs":false,"family":"Hodgins","given":"Gregory","email":"","middleInitial":"W. L.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":746577,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197289,"text":"sir20185065 - 2018 - Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources","interactions":[],"lastModifiedDate":"2021-07-23T16:32:31.463125","indexId":"sir20185065","displayToPublicDate":"2018-07-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5065","title":"Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources","docAbstract":"The California State Water Resources Control Board initiated a regional monitoring program in July 2015 to determine where and to what degree groundwater quality may be adversely impacted by oil and gas development activities. A key issue in the implementation of the regional groundwater monitoring program is that each year, detailed characterization work can be done in only a few of California’s 487 onshore oil and gas fields. The first step in monitoring groundwater near petroleum development is to prioritize oil and gas fields using consistent statewide analysis of available data that indicate potential risk of groundwater to oil and gas development.
The U.S. Geological Survey compiled data for four factors that characterize the intensity of petroleum resource development and proximity to groundwater resources: petroleum-well density, volume of water injected in oil fields, vertical proximity of groundwater resources to oil and gas resource development, and water-well density. An overall priority ranking for each field was determined by computing summary metrics, analyzing statewide distributions of summary metrics for all oil and gas fields, using those distributions to define relative categories of potential risk for each factor, and combining relative risk rankings for different factors into an overall priority ranking. This preliminary assessment does not represent an evaluation of groundwater risk to oil and gas development, which needs to be based on detailed analysis and data related to development activities including well stimulation, well integrity issues, produced water ponds, and underground injection.
Based on the prioritization analysis, 22 percent (107 fields) of the total number of oil and gas fields in California were ranked as high priority, 23 percent (114 fields) as moderate priority, and 55 percent (266 fields) as low priority. These results indicate that between 100 and 200 oil fields are principal candidates for the next steps in the regional monitoring program. The land area of fields that ranked high priority accounted for 41 percent of the total field area (3,392 square miles). More than half of the high priority fields were in the southern San Joaquin Valley and the Los Angeles Basin. Some of the larger fields tended to have higher rankings because of greater intensity of petroleum development, sometimes coupled with proximity to groundwater resources.
The U.S. Geological Survey, in collaboration with the California State Water Resources Control Board and other agencies, has begun regional groundwater monitoring near oil and gas fields selected for study through the California Oil, Gas, and Groundwater cooperative program. Groundwater monitoring includes compiling, analyzing, and developing three-dimensional visualizations of existing data, including geological frameworks, salinity mapping, identification of surface features that could potentially affect groundwater quality, locations and depths of oil/gas and water wells, cataloging well-construction integrity issues, and evaluating the directions of groundwater flow. These analyses are required to determine where existing wells should be monitored and where new monitoring wells may need to be drilled.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185065","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Davis, T.A., Landon, M.K., and Bennett, G.L., 2018, Prioritization of oil and gas fields for regional groundwater monitoring based on a preliminary assessment of petroleum resource development and proximity to California’s groundwater resources: U.S. Geological Survey Scientific Investigations Report 2018–5065, 115 p.,\nhttps://doi.org/10.3133/sir20185065.","productDescription":"Report: viii, 115 p.; Tables 1-6; Appendix Tables 1-7","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073272","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437823,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FJ2DV3","text":"USGS data release","linkHelpText":"Data analyzed for the preliminary prioritization of California oil and gas fields for regional groundwater monitoring"},{"id":355611,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5065/sir20185065_appendixtables_.xlsx","text":"Appendix Tables 1–7","size":"500 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5065"},{"id":355610,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2018/5065/sir20185065_tables_.xlsx","text":"Tables 1–6","size":"23 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018-5065"},{"id":355609,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5065/sir20185065.pdf","text":"Report","size":"62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5065"},{"id":355608,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5065/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"As the Nation’s principal earth-science information agency, the U.S. Geological Survey (USGS) is depended upon to collect accurate data and produce factual and impartial interpretive reports. Methods for data collection and analysis that were developed by the USGS have become standard techniques used by numerous Federal, State, and local agencies and by private enterprises. The USGS has implemented a program designed to ensure that all scientific work done by or for USGS Water Science Centers is done in accordance with a quality-assurance plan. The implementation of a groundwater quality-assurance plan will enhance groundwater data collected by the USGS. This report is a quality-assurance plan for groundwater activities conducted by the USGS Dakota Water Science Center and is meant to complement qualityassurance plans for surface-water and water-quality activities and similar plans for the Dakota Water Science Center and general project activities throughout the USGS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181103","usgsCitation":"Valder, J.F., Carter, J.M., Robinson, S.M., Laveau, C.D., and Petersen, J.A., 2018, Quality-assurance plan for groundwater activities, U.S. Geological Survey Dakota Water Science Center: U.S. Geological Survey Open-File Report 2018–1103, 28 p., https://doi.org/10.3133/ofr20181103.","productDescription":"v, 28 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-097126","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":355869,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1103/ofr20181103.pdf","text":"Report","size":"1.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1103"},{"id":355868,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1103/coverthb.jpg"}],"contact":"Director, Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
The giant gartersnake (Thamnophis gigas) is a semi-aquatic species of snake precinctive to the Central Valley of California. Because the Central Valley has experienced a substantial loss of wetland habitat, giant gartersnake populations are largely found in aquatic habitats associated with rice agriculture. In dry years, less water may be available for rice agriculture, resulting in less aquatic habitat, which could have cascading effects on giant gartersnake populations. We present 2 years of data intended to examine how the demography of giant gartersnakes is affected by the availability of aquatic habitat on the landscape (2016–17), along with 2 years of (sparse) preliminary data (2014–15) collected as part of an earlier radio-telemetry study on giant gartersnake movement behavior. We sampled agricultural canals near rice fields for giant gartersnakes at 8 sites distributed throughout the Sacramento Valley. Five sites were sampled from 2014–17, and 3 sites were sampled from 2015–17. In total, we made 2,995 captures of 1,011 snakes from 2014–17. We used these capture data to fit a multi-site Jolly-Seber model to estimate the abundance of giant gartersnakes as well as the daily and annual probability of capture at each site. We used remotely sensed Landsat data to characterize the extent of flooded rice fields surrounding each site in each year. In addition, we collected 175 females from 2014–17 and delivered them to the Sacramento Zoo for health assessments and reproductive exams.
The abundance of giant gartersnakes varied among sites, and abundance estimates were more precise in 2016 and 2017 when sampling effort was greatest. The probability of a giant gartersnake being captured at least once in a year was higher in 2016 and 2017 than 2014 and 2015, and recaptures of snakes marked the previous year were highest in 2016 and 2017 as well. Mean annual apparent survival was estimated to be 0.40 but varied among sites from a low of 0.14 to a high of 0.63. Five sites had diverse size distributions that included abundant sub-adult and large adult female snakes. One site had a truncated size distribution with few large adult female snakes, and 2 sites had mostly large adult-sized snakes and few small individuals. Both the probability a female was gravid and a female’s litter size were positively related to the female’s snout-vent length. Somatic growth rates varied more among years than among sites, and females grew faster (in millimeters per day) than male snakes.
The proportion of the landscape around each site under active rice cultivation fluctuated over time (generally between 60–90 percent of the landscape was active rice growing, although this proportion was lower for some sites in some years), and variation in rice growing was asynchronous among sites. This study demonstrates that intensive demographic sampling enables estimation of several key demographic variables at each study site. Continued sampling would allow for investigating potential relationships between the amount of rice growing at a site and demographic parameters such as growth, survival, and reproduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181114","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Rose, J.P., Ersan, J.S.M., Reyes, G.A., Gustafson, K.B., Fulton, A.M., Fouts, K.J., Wack, R.F., Wylie, G.D., Casazza, M.L., and Halstead, B.J., 2018, Findings from a preliminary investigation of the effects of aquatic habitat (water) availability on giant gartersnake (Thamnophis gigas) demography in the Sacramento Valley, California, 2014–17: U.S. Geological Survey Open-File Report 2018–1114, 48 p., https://doi.org/10.3133/ofr20181114.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-097068","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":355890,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1114/coverthb.jpg"},{"id":355891,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1114/ofr20181114.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1114"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.33,\n 38.8333\n ],\n [\n -121.5833,\n 38.8333\n ],\n [\n -121.5833,\n 39.6667\n ],\n [\n -122.33,\n 39.6667\n ],\n [\n -122.33,\n 38.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Streams within the Coeur d’Alene River drainage basin in northern Idaho have been extensively affected by historical mining activities and are subject to ongoing remedial actions as part of the Bunker Hill Mining & Metallurgical Complex Superfund Site. The U.S. Geological Survey (USGS) operates 12 real-time streamgages and collects surface-water-quality samples two to four times annually at 20 sites in the Spokane River and Coeur d’Alene River drainage basins. These data are used by the U.S. Environmental Protection Agency (USEPA) to monitor cleanup progress and to support decisions related to implementing remedial actions throughout the basin. USGS data collection highlights from water year 2017 include: • A rain-on-snow event in March 2017 produced high streamflows and flooding in the basin. • The March event mobilized high concentrations of total metals (cadmium, lead, zinc, and others) in the Coeur d’Alene River near Cataldo, at Rose Lake, and near Harrison; these concentrations were among the highest that have been measured at these sites during flood events sampled by the USGS. • Total lead and dissolved zinc and cadmium concentrations decreased in Canyon Creek in 2017 when compared with water years 2007–16; in contrast, concentrations of dissolved zi
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181113","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Zinsser, L.M., 2018, Coeur d’Alene Basin Environmental Monitoring Program, surface water, northern Idaho—Annual data summary, water year 2017: U.S. Geological Survey Open-File Report 2018-1113, 15 p., https://doi.org/10.3133/ofr20181113.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-098458","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":355896,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1113/ofr20181113.pdf","text":"Report","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1113"},{"id":355895,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1113/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Coeur d’Alene Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 47.25\n ],\n [\n -115.5,\n 47.25\n ],\n [\n -115.5,\n 47.75\n ],\n [\n -117,\n 47.75\n ],\n [\n -117,\n 47.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
The Ukinrek Maars erupted 30 March to 9 April 1977, forming two maars, a line of small pit craters and a tephra blanket extending to ~2 km from the vents. We combine photographic and written observations with stratigraphic analysis to reconstruct the eruption. The eruption began with very low (a few meters high) fountaining from small craters above an inferred east-west-trending dike, creating local scoria/spatter agglomerate ramparts with a sandy matrix. The eruption very quickly (in minutes to hours) centered on the West Maar. The West Maar eruption lasted 1–2 days, starting and ending with phreatomagmatic explosions with weak phreato-Strombolian activity in between. Initial explosions formed a 30-m-wide crater, enlarged by crater-wall collapse, and columns as high as 6500 m. Phreato-Strombolian activity produced ~72% of the erupted volume, including a small spatter cone and a scoria blanket around the vent. A final explosion series emplaced a lithic-rich breccia as ballistic blocks, possibly as the northern half of the final crater collapsed into the southern vent area. The East Maar formed over the last nine days of the eruption and represents ~93% of the total volume (4.6 × 106 m3) of the Ukinrek eruption. Initial explosions were probably shallower than 10–20 m but most of the eruption occurred from explosions at 50–60 m below the pre-eruptive surface, with evidence of explosions to 90 m depth only at the very end of the eruption. The East Maar eruption mostly produced columns of lapilli, ash, and steam and the deposits are mostly fallout. Winds blew fallout mostly to the north for the first 5–6 days and to the south for the last three days of the eruption. Wind-directed pyroclastic density currents collapsed from the column, producing fines-rich layers within the coarser fallout. Sporadic explosions produced weak density currents in the first few days and lithic-and juvenile-block-rich breccias in the last few days of the eruption. We interpret that collapse of the crater walls made a slurry that in part provided the water for phreatomagmatic interaction. Explosions came from depths <90 m below the pre-eruptive surface except for a few explosions at the end of the eruption, with most occurring at <70 m depth. The East Maar crater was open to 40–60 m depth throughout most of the eruption, so the explosions were rarely, if ever, deeper than 30 m below the crater floor. Thus, we infer there is no classic, well-formed diatreme structure below the maar. Collapse of the East Maar crater walls provided a supply of water-saturated sediment for much of the phreatomagmatic activity, which came from two vents that did not migrate much, if at all, during the eruption. The Ukinrek Maars deposits were nearly entirely emplaced by fallout, rather than density currents, from explosions and low columns.
National Research Program
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2017 to December 2017. These append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2017 data within the context of the longer, multi-decadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
Significant reductions in silver and copper concentrations in sediment and M. petalum occurred at the site in the 1980s following the implementation by PARWQCP of advanced wastewater treatment and source control measures. Since the 1990s, concentrations of these elements appear to have stabilized at concentrations somewhat above silver (Ag) or near copper (Cu) regional background concentrations. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2017, concentrations of silver and copper in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. This record suggests that legacy contamination and regional-scale factors now largely control sedimentary and bioavailable concentrations of silver and copper, as well as other elements of regulatory interest, at the Palo Alto site.
Analyses of the benthic community structure of a mudflat in south San Francisco Bay over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2017), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2017. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2017. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like M. petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or anoxia. The reproductive mode of most species that were present in 2017 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2017 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181107","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Parchaso, F., Pearson, S., Stewart, R., Turner, M., Barasch, D., Slabic, A., and Luoma, S.N., 2018, Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017: U.S. Geological Survey Open-File Report 2018–1107, 71 p., https://doi.org/10.3133/ofr20181107.","productDescription":"vi, 71 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-098497","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":416196,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416195,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416197,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416194,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016"},{"id":416193,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015"},{"id":355780,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1107/ofr20181107_.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1107"},{"id":355779,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1107/coverthb.jpg"}],"country":"United States","state":"California","city":"Palo Alto","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.27371215820312,\n 37.315567502511044\n ],\n [\n -121.827392578125,\n 37.315567502511044\n ],\n [\n -121.827392578125,\n 37.655557695625056\n ],\n [\n -122.27371215820312,\n 37.655557695625056\n ],\n [\n -122.27371215820312,\n 37.315567502511044\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Hydro-Eco Interactions Branch
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
Empirical nutrient models that describe lake nutrient, productivity, and water clarity relationships among lakes play a prominent role in limnology. Landscape-based regressions are also used to understand macroscale variability of lake nutrients, clarity, and productivity (hereafter referred to as nutrient-productivity). Predictions from both models are used to inform eutrophication management globally. To date, these two classes of models are generally conducted separately, which ignores the known dependencies among nutrient-productivity variables. We present a statistical model that integrates nutrient-productivity and landscape-based regressions—where lake nutrients, productivity, and clarity variables are modeled jointly. We fitted a joint nutrient-productivity model to over 7000 lakes with three nutrients (total phosphorus, total nitrogen, nitrate concentrations), chlorophyll a concentrations, and Secchi disk depth as response variables and landscape features as predictor variables. Because lakes in different regions respond to landscape features differently, we focused our analysis on two subregions with different dominant land uses, the agricultural Midwest and the forested Northeast U.S. Predictive performance was enhanced by modeling nutrient-productivity variables jointly. We also found strong evidence that nutrient-productivity variables were coupled, and that only nitrate may be decoupled from other nutrient-productivity variables in the forested region. We speculate that these regional differences may be related to differences in the strength of biogeochemical cycles and stoichiometric controls between these regions. Jointly modeling nutrient-productivity variables in lakes effectively integrates the two dominant approaches for studying lakes nutrient-productivity relationships and provides novel insight into macroscale patterns of the coupling of nutrients, chlorophyll, and water clarity in lakes.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.10944","usgsCitation":"Wagner, T., and Schliep, E.M., 2018, Combining nutrient, productivity, and landscape-based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales: Limnology and Oceanography, v. 63, no. 6, p. 2372-2383, https://doi.org/10.1002/lno.10944.","productDescription":"12 p.","startPage":"2372","endPage":"2383","ipdsId":"IP-093432","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468575,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10944","text":"Publisher Index Page"},{"id":395248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schliep, Erin M.","contributorId":171525,"corporation":false,"usgs":false,"family":"Schliep","given":"Erin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":832536,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197647,"text":"sir20185077 - 2018 - Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","interactions":[],"lastModifiedDate":"2018-07-20T10:23:35","indexId":"sir20185077","displayToPublicDate":"2018-07-18T12:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5077","displayTitle":"Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","title":"Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013","docAbstract":"As the population of the Triangle area in central North Carolina increases, the demand for good quality drinking water from streams and lakes within the upper Neuse and upper Cape Fear River Basins also increases. The Triangle area includes Raleigh, Cary, Research Triangle Park, Durham, Chapel Hill, and the surrounding communities. The U.S. Geological Survey examined temporal trends in water quality for 13 stream and 8 reservoir sites in the two basins on the basis of data collected during 1989–2013. Trends were analyzed using a fitted time-series model that accommodated for shifting trends and variations in streamflow at multiple time scales. Seventeen water-quality properties and constituents were evaluated, including specific conductance and major ions, nutrients, and organic carbon. Suspended solids and suspended sediment were examined at stream sites; chlorophyll a and Secchi transparency were examined at lake sites.
The investigation identified considerable changes in population, land cover, streamflow, and selected water-quality characteristics in the study area over the 25-year period. Specific conductance and concentrations of calcium, magnesium, potassium, sodium, and chloride tended to increase throughout the study area. Area-wide increases were also observed for organic nitrogen. Trends for other water-quality constituents varied on a more site-specific basis because of local watershed influences such as changes to wastewater-treatment processes and substantial shifts from rural to urban land use. Water quality is influenced by multiple, often confounding factors, and thus may change in a non-uniform manner over time. Long-term monitoring is critical for tracking these trends and ensuring resiliency of water supplies for the future. Results from this study may promote the understanding of water-quality response to a growing population and land-cover changes and can assist water-resource managers in the Triangle area in tracking progress toward water-quality goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185077","collaboration":"Prepared in cooperation with the Triangle Area Water Supply Monitoring Project Steering Committee","usgsCitation":"Giorgino, M.J., Cuffney, T.F., Harden, S.L., and Feaster, T.D., 2018, Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013: U.S. Geological Survey Scientific Investigations Report 2018–5077, 67 p., https://doi.org/10.3133/sir20185077.","productDescription":"Report: viii, 67 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095343","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":355697,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5077/coverthb.jpg"},{"id":355698,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5077/sir20185077.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5077"},{"id":355835,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MS3S17","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets for trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989-2013"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Fear River basin, Neuse River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.79919433593749,\n 35.02099970111467\n ],\n [\n -77.84912109375,\n 35.02099970111467\n ],\n [\n -77.84912109375,\n 36.32397712011264\n ],\n [\n -79.79919433593749,\n 36.32397712011264\n ],\n [\n -79.79919433593749,\n 35.02099970111467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Suite 129
Columbia, SC 29210
The purpose of this study was to evaluate the effects of irrigation and cover crops as conservation practices on water quality in groundwater and streams. Bucks Branch, a stream in the Nanticoke River watershed in southwestern Delaware, was identified as having one of the highest concentrations of nitrate in all surface-water sites sampled by the Delaware Department of Natural Resources and Environmental Control (DNREC). The study site is on two adjacent fields bordering Bucks Branch, one that has used irrigation since 2000 and one with dryland farming; both under conservation tillage and long-term rotation of corn, soybean, and small grain crops. A streamgage was installed near the study site fields to measure streamflow and water quality. The study area is typical of farming practices and environmental conditions throughout much of the intensively farmed agricultural land of the Coastal Plain of Delaware and surrounding parts of Maryland. Monitoring was conducted from January 2014 through June 2016. Corn was grown on both fields during the two growing seasons of the study period, and cover crops were planted before or shortly after harvest on both fields. During the second year of data collection, the effects of radish and rye grass cover crops on nutrient transport were studied.
The combined results from data collected for this study show that water and nitrate moved below the root zone year round when soil moisture was high, especially after significant rainfall and frequently after irrigation. Soil water sampled 2 to 3 weeks after nutrients were applied had nitrate concentrations greater than 50 milligrams per liter as nitrogen (mg/L as N) and may be a significant source of nitrate to groundwater. Whereas recharge containing elevated nitrate concentrations also occurred under the dryland field, it was less frequent and of lower concentration than recharge under the irrigated field.
Nitrate was present in all groundwater samples from these sites. Groundwater estimated to have recharged within 10 years or less had higher median concentrations of nitrate than in older water samples. The oldest groundwater encountered was over 30 years old, and had traveled along the longest, deep flowpaths from upland fields to the stream. The median nitrate concentration was 18 mg/L as N in younger water (less than 10 years old) beneath the irrigated field, compared to about 10 mg/L as N in younger water beneath the dryland field. Samples from the shallow upland wells in both study fields showed little, if any, evidence of denitrification. Several samples from deeper wells and from wells near forested riparian zone wetlands that border both fields did show partial denitrification.
A mixing model estimated that between 12 and 22 percent of the nitrate discharging to the stream was lost through uptake and denitrification upstream of the streamgage on Bucks Branch. Continuous data collected at this site and evidence of denitrification in the surface-water samples showed a greater potential for loss of nitrate during the warmer months than the colder months. This pattern was similar to that seen below the streamgage at the most downstream site in the watershed.
A mixed cover crop of radishes and rye was planted prior to removal (radishes) and just after harvest (rye) of the corn crop on the irrigated field. Rye grass was planted shortly after crop harvest on the dryland field. Cover crop biomass samples collected while radishes were growing and after they were killed by freezing temperatures indicates that the early planted radish crop effectively scavenged available nitrogen from the soil. Whereas radish biomass initially held more nitrogen than rye, at 55 to 8 pounds per acre, respectively, leaching of inorganic nitrate following radish die-off was minimal. Soil-water nitrate concentrations during the cover-crop growing period were lower than during the growing season prior to planting of the cover crop. There also was an increase in soil fertility and dissolved organic nitrate in samples of soil water that was likely related to increased soil microbial metabolism. Results indicate that cover crops stored plant nutrients over the winter and did not increase shallow groundwater concentrations of nitrate.
Although conservation practices such as cover crops and nutrient management have been applied to these fields, there was still significant leaching of nitrate to groundwater, especially under the irrigated field. This will likely continue to be a challenge in this area and other parts of the Coastal Plain where soil moisture capacity is relatively low and managing irrigation around rainfall is difficult. Cover crops, when planted in standing corn, are one practice that can effectively pull nitrate from below the root zone to the top layer of soil, thus limiting the amount of potential nitrate leaching to groundwater. Irrigation management that would lower average soil moisture conditions during the growing season also could potentially limit nitrogen transport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185020","collaboration":"Prepared in cooperation with the Delaware Department of Natural Resources and Environmental Control and the Delaware Geological Survey","usgsCitation":"Denver, J.M., Soroka, A.M., Reyes, B., Lester, T.R., Bringman, D.A., and Brownley, M.S., 2018, Monitoring the water-quality response of agricultural conservation practices in the Bucks Branch watershed, Sussex County, Delaware, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5020, 43 p., https://doi.org/10.3133/sir20185020.","productDescription":"ix, 43 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088518","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":355731,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5020/sir20185020.pdf","text":"Report","size":"8.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5020"},{"id":355732,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77H1HK5","text":"USGS data release","description":"USGS data release","linkHelpText":"Chemistry analysis results for groundwater, soil-pore water, soil and plant material collected from two agricultural sites in the Nanticoke and Chester River watersheds on the Delmarva Peninsula from 2013 to 2016"},{"id":355730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5020/coverthb.jpg"}],"country":"United States","state":"Delaware","county":"Sussex County","otherGeospatial":"Bucks Branch Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.6833,\n 38.6833\n ],\n [\n -75.6167,\n 38.6833\n ],\n [\n -75.6167,\n 38.7333\n ],\n [\n -75.6833,\n 38.7333\n ],\n [\n -75.6833,\n 38.6833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
The ability to quantify water resources hinges on the understanding of water use by the population. The demand humans place on the water cycle varies across the United States, driven by both need and availability. The U.S. Geological Survey quantifies water use nationally, at the county scale, with estimates of water withdrawals and deliveries, by category of use (for example, irrigation, thermoelectric power, industrial, public supply, including domestic deliveries and self-supply domestic, livestock, mining, and aquaculture) and source (fresh and saline groundwater or surface water) every 5 years. Estimates of water use are an important component of the water budget to help manage water supplies and plan for the future. Understanding water use in Idaho is important not only at the local (county) and State scales, but also at the National level because Idaho ranked third in the Nation for total water use in 2015.
This fact sheet describes calendar year 2015 freshwater withdrawals by source and by each Idaho county. An associated data release provides the data discussed herein. Freshwater withdrawals totaled 17,737 million gallons per day during 2015. Surface water accounted for 70 percent of total withdrawals for all categories of use, mostly for irrigation of crops and aquaculture production. Withdrawals for mining activities were mostly from surface water, whereas the remaining categories of use—public supply, domestic, industrial, livestock, irrigation of golf courses, and thermoelectric power—relied largely on groundwater withdrawals. Most withdrawals occurred in southern Idaho counties to support irrigated agriculture.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183036","usgsCitation":"Murray, E.M., 2018, Idaho water use, 2015: U.S. Geological Survey Fact Sheet 2018-3036, 4 p., https://doi.org/10.3133/fs20183036.","productDescription":"Report: 4 p.; Data release","onlineOnly":"Y","ipdsId":"IP-093323","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":355834,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92AXN0O","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water use by source and category in Idaho counties, 2015"},{"id":355822,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3036/fs20183036.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3036"},{"id":355821,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3036/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
An understanding of the spatial and temporal extent of groundwater recharge is critical for many types of hydrologic assessments involving water quality, contaminant transport, ecosystem health, and sustainable use of groundwater. Annual potential groundwater recharge was simulated at a 1-kilometer resolution with the Soil-Water-Balance (SWB) model for the glacial aquifer system east of the Rocky Mountains, from central Montana east to Maine, for calendar years 1980–2011. The SWB model used high resolution meteorological, land cover, and soil hydrology datasets that are nationally consistent and publicly available. The SWB model computed daily potential groundwater recharge as precipitation in excess of interception, runoff, evapotranspiration, and soil-water storage capacity. Daily potential recharge values within each year of the simulation were summed to produce annual potential recharge rates. Potential recharge as described in this report is water that infiltrates vertically below the plant rooting zone and is assumed to reach the water table.
The calibrated SWB model in this report is called the glacial SWB model. Model calibration assumed that the area contributing to groundwater discharge equaled the surface watershed. The model was calibrated to stream base flows from 39 watersheds throughout the model domain that had hydrologic conditions appropriate for hydrograph separation. Base flows were calculated from daily streamflow records with the HYSEP local minimum hydrograph separation method The glacial SWB model reproduced the mean annual base-flow calibration targets well; the Nash-Sutcliffe efficiency coefficient was 0.94, and the root mean squared error was 1.28 inches per year.
The glacial SWB model provides insight into the spatial and temporal variability in potential annual recharge across the glacial aquifer system. About 20 percent of the active model area had an average potential recharge rate of less than 1 inch per year. Total precipitation, total recharge, and recharge as a percentage of precipitation increased from west to east. A substantial amount of the recharge water (39 percent) entering the glacial aquifer system travels through developed (urbanized) and agricultural landscapes, which are known to cause water-quality impairments. Regional climatic events, such as the 1988 to 1989 drought, are apparent in the potential recharge time series. Potential recharge generally increased across the glacial aquifer system between 2001 and 2011.
A comparison of the potential recharge from the glacial SWB model to previous broad-scale recharge estimates reveals several important considerations for future SWB modeling applications. Shifts in the overall distribution of potential recharge between separate models can be explained by methods used to generate base-flow calibration target datasets. Spatial patterns in potential recharge simulated by SWB models are strongly dependent on the data and assumptions used to assign model cells to hydrologic soil groups. A review of several SWB models used to estimate groundwater recharge (and not surface runoff) revealed that model results are most sensitive to input climatic data, followed by surface runoff (curve number) and root-zone depth parameters.
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Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
No abstract available.
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viewing waterfowl in the U.S. differ among species?","interactions":[],"lastModifiedDate":"2019-10-28T14:14:10","indexId":"70206268","displayToPublicDate":"2018-07-17T15:13:39","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1909,"text":"Human Dimensions of Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"Do economic values and expenditures for viewing waterfowl in the U.S. differ among species?","docAbstract":"Many economic studies value birdwatching in general and often do not account for potential differences in viewers’ benefits from observing different species. But, how different are economic values of viewing various bird species? To answer that question, we surveyed Ducks Unlimited (DU) members using an online questionnaire to estimate trip expenditures and consumer surplus per trip for viewing pintail ducks, waterfowl in general, and other species of waterfowl. Expenditures per trip were USD $231, $199, and $182, respectively. Consumer surpluses per trip, estimated using the contingent valuation method, were $28, $32, and $29, respectively. Neither expenditures nor consumer surplus were statistically different among species for DU members who are adept at species differentiation. Our results suggest that it may be reasonable to use a general economic value for waterfowl viewing when formulating management alternatives for a variety of waterfowl.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/10871209.2018.1496371","usgsCitation":"Loomis, J., Haefele, M., Dubovsky, J., Lien, A.M., Thogmartin, W.E., Diffendorfer, J., Humburg, D.D., Mattsson, B., Bagstad, K.J., Semmens, D.J., Lopez-Hoffman, L., and Merideth, R., 2018, Do economic values and expenditures for viewing waterfowl in the U.S. differ among species?: Human Dimensions of Wildlife, v. 23, no. 6, p. 587-596, https://doi.org/10.1080/10871209.2018.1496371.","productDescription":"10 p.","startPage":"587","endPage":"596","numberOfPages":"10","ipdsId":"IP-090370","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":368676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Loomis, 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M.","contributorId":171643,"corporation":false,"usgs":false,"family":"Lien","given":"Aaron","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":774008,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":774009,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774010,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":774011,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mattsson, Brady J.","contributorId":171612,"corporation":false,"usgs":false,"family":"Mattsson","given":"Brady J.","affiliations":[{"id":26928,"text":"Univ. of Vienna","active":true,"usgs":false}],"preferred":false,"id":774012,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774013,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774014,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":774015,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Merideth, Robert","contributorId":220060,"corporation":false,"usgs":false,"family":"Merideth","given":"Robert","affiliations":[{"id":33382,"text":"Udall Center for Studies in Public Policy","active":true,"usgs":false}],"preferred":false,"id":774016,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70198118,"text":"70198118 - 2018 - Soil water dynamics at 15 locations distributed across a desert landscape: insights from a 27‐yr dataset","interactions":[],"lastModifiedDate":"2018-07-17T10:04:44","indexId":"70198118","displayToPublicDate":"2018-07-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Soil water dynamics at 15 locations distributed across a desert landscape: insights from a 27‐yr dataset","docAbstract":"Desert ecosystems are primarily limited by water availability. Within a climatic regime, topography, soil characteristics, and vegetation are expected to determine how the combined effects of precipitation, temperature, and evaporative demand of the atmosphere shape the spatial and temporal patterns of water within the soil profile and across a landscape. To forecast how desert landscapes may respond to future climatic conditions, it is imperative to improve our understanding of these ecohydrologic processes. Here, we report on 27 yr of monthly soil volumetric water content (VWC) measurements and associated soils data from a site in the northern Chihuahuan Desert of North America. The dataset includes VWC and soil properties measured to 3 m in depth across 15 locations that encompass a range of Chihuahuan Desert vegetation types. We use this unique dataset (1) to generate insights into general temporal and depth patterns in VWC, (2) to analyze how VWC corresponds to measures of climatic conditions, and (3) to qualitatively evaluate the relative importance of soils, topographic setting, and vegetation type in mediating temporal patterns in VWC. Analyses of this unique dataset emphasize the importance of soil and topographic setting in determining depth and temporal patterns in VWC across time. Results emphasize the episodic nature of deep wetting events in our study system—essentially limited to three large events over the 27‐yr record driven primarily by wetter than normal winters. Comparison of soil water dynamics between mesquite shrub coppice dunes and interspace soils suggests the “island of fertility” concept does not extend to soil water. Median VWC was strongly coupled to climatic conditions over surprisingly long windows at most locations (6–18 months), suggesting that soil water at depth is decoupled from short climatic pulses. However, VWC dynamics and VWC–climate relationships varied among locations, depths, and seasons, with unexpected similarities in ecohydrologic dynamics observed among very different vegetation types (e.g., an eroded creosote shrubland and a playa grassland). These results further underscore the importance of ecohydrological investigations in these ecosystems, given forecasts for a warmer and more variable climate in deserts globally.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2335","usgsCitation":"Duniway, M.C., Petrie, M., Peters, D., Anderson, J.P., Crossland, K., and Herrick, J.E., 2018, Soil water dynamics at 15 locations distributed across a desert landscape: insights from a 27‐yr dataset: Ecosphere, v. 9, no. 7, p. 1-36, https://doi.org/10.1002/ecs2.2335.","productDescription":"e02335; 36 p.","startPage":"1","endPage":"36","ipdsId":"IP-091071","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2335","text":"Publisher Index Page"},{"id":355722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-10","publicationStatus":"PW","scienceBaseUri":"5b6fc411e4b0f5d57878e9c5","contributors":{"authors":[{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":740092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petrie, Matthew D.","contributorId":206328,"corporation":false,"usgs":false,"family":"Petrie","given":"Matthew D.","affiliations":[{"id":37312,"text":"Department of Plant & Environmental Sciences, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":740097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Debra P. C.","contributorId":36903,"corporation":false,"usgs":false,"family":"Peters","given":"Debra P. C.","affiliations":[{"id":25579,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM 88003","active":true,"usgs":false}],"preferred":false,"id":740096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, John P.","contributorId":206326,"corporation":false,"usgs":false,"family":"Anderson","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":37311,"text":"Jornada Experimental Range Department, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":740094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crossland, Keith","contributorId":206327,"corporation":false,"usgs":false,"family":"Crossland","given":"Keith","email":"","affiliations":[{"id":17659,"text":"Natural Resources Conservation Service","active":true,"usgs":false}],"preferred":false,"id":740095,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herrick, Jeffrey E.","contributorId":26054,"corporation":false,"usgs":false,"family":"Herrick","given":"Jeffrey","email":"","middleInitial":"E.","affiliations":[{"id":12627,"text":"USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, NM 88003-8003, USA","active":true,"usgs":false}],"preferred":false,"id":740093,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198151,"text":"70198151 - 2018 - Assessing the effectiveness of riparian restoration projects using Landsat and precipitation data from the cloud-computing application ClimateEngine.org","interactions":[],"lastModifiedDate":"2018-07-18T09:48:42","indexId":"70198151","displayToPublicDate":"2018-07-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the effectiveness of riparian restoration projects using Landsat and precipitation data from the cloud-computing application ClimateEngine.org","docAbstract":"Riparian vegetation along streams provides a suite of ecosystem services in rangelands and thus is the target of restoration when degraded by over-grazing, erosion, incision, or other disturbances. Assessments of restoration effectiveness depend on defensible monitoring data, which can be both expensive and difficult to collect. We present a method and case study to evaluate the effectiveness of restoration of riparian vegetation using a web-based cloud-computing and visualization tool (ClimateEngine.org) to access and process remote sensing and climate data. Restoration efforts on an Eastern Oregon ranch were assessed by analyzing the riparian areas of four creeks that had in-stream restoration structures constructed between 2008 and 2011. Within each study area, we retrieved spatially and temporally aggregated values of summer (June, July, August) normalized difference vegetation index (NDVI) and total precipitation for each water year (October-September) from 1984 to 2017. We established a pre-restoration (1984–2007) linear regression between total water year precipitation and summer NDVI for each study area, and then compared the post-restoration (2012–2017) data to this pre-restoration relationship. In each study area, the post-restoration NDVI-precipitation relationship was statistically distinct from the pre-restoration relationship, suggesting a change in the fundamental relationship between precipitation and NDVI resulting from stream restoration. We infer that the in-stream structures, which raised the water table in the adjacent riparian areas, provided additional water to the streamside vegetation that was not available before restoration and reduced the dependence of riparian vegetation on precipitation. This approach provides a cost-effective, quantitative method for assessing the effects of stream restoration projects on riparian vegetation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2018.06.024","usgsCitation":"Hausner, M.B., Huntington, J., Nash, C., Morton, C., McEvoy, D.J., Pilliod, D.S., Hegewisch, K.C., Daudert, B., Abatzoglou, J.T., and Grant, G., 2018, Assessing the effectiveness of riparian restoration projects using Landsat and precipitation data from the cloud-computing application ClimateEngine.org: Ecological Engineering, v. 120, p. 432-440, https://doi.org/10.1016/j.ecoleng.2018.06.024.","productDescription":"9 p.","startPage":"432","endPage":"440","ipdsId":"IP-087503","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468582,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2018.06.024","text":"Publisher Index Page"},{"id":355750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Silvies Valley Ranch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.2783203125,\n 43.54854811091286\n ],\n [\n -117.59765625,\n 43.54854811091286\n ],\n [\n -117.59765625,\n 45.767522962149876\n ],\n [\n -120.2783203125,\n 45.767522962149876\n ],\n [\n -120.2783203125,\n 43.54854811091286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc410e4b0f5d57878e9bb","contributors":{"authors":[{"text":"Hausner, Mark B.","contributorId":204145,"corporation":false,"usgs":false,"family":"Hausner","given":"Mark","email":"","middleInitial":"B.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":740264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huntington, Justin L.","contributorId":206374,"corporation":false,"usgs":false,"family":"Huntington","given":"Justin L.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":740265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nash, Caroline","contributorId":204146,"corporation":false,"usgs":false,"family":"Nash","given":"Caroline","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":740266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morton, Charles","contributorId":178787,"corporation":false,"usgs":false,"family":"Morton","given":"Charles","affiliations":[],"preferred":false,"id":740267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McEvoy, Daniel J.","contributorId":206375,"corporation":false,"usgs":false,"family":"McEvoy","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":740268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":149254,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","email":"dpilliod@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":740263,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hegewisch, Katherine C.","contributorId":195698,"corporation":false,"usgs":false,"family":"Hegewisch","given":"Katherine","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":740269,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Daudert, Britta","contributorId":206376,"corporation":false,"usgs":false,"family":"Daudert","given":"Britta","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":740270,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Abatzoglou, John T.","contributorId":191729,"corporation":false,"usgs":false,"family":"Abatzoglou","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":33345,"text":" University of Idaho","active":true,"usgs":false}],"preferred":false,"id":740271,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Grant, Gordon E.","contributorId":30881,"corporation":false,"usgs":false,"family":"Grant","given":"Gordon E.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":740272,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70199381,"text":"70199381 - 2018 - Stronger peak ground motion, beyond the threshold to initiate a response, does not lead to larger stream discharge responses to earthquakes","interactions":[],"lastModifiedDate":"2018-09-17T13:58:37","indexId":"70199381","displayToPublicDate":"2018-07-16T13:58:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Stronger peak ground motion, beyond the threshold to initiate a response, does not lead to larger stream discharge responses to earthquakes","docAbstract":"The impressive number of stream gauges in Chile, combined with a suite of past and recent large earthquakes, makes Chile a unique natural laboratory to study several streams that recorded responses to multiple seismic events. We document changes in discharge in eight streams in Chile following two or more large earthquakes. In all cases, discharge increases. Changes in discharge occur for peak ground velocities greater than about 7–11 cm/s. Above that threshold, the magnitude of both the increase in discharge and the total excess water do not increase with increasing peak ground velocities. While these observations are consistent with previous work in California, they conflict with lab experiments that show that the magnitude of permeability changes increases with increasing amplitude of ground motion. Instead, our study suggests that streamflow responses are binary.
","language":"English","publisher":"AGU","doi":"10.1029/2018GL078621","usgsCitation":"Mohr, C.H., Manga, M., and Wald, D.J., 2018, Stronger peak ground motion, beyond the threshold to initiate a response, does not lead to larger stream discharge responses to earthquakes: Geophysical Research Letters, v. 45, no. 13, p. 6523-6531, https://doi.org/10.1029/2018GL078621.","productDescription":"9 p.","startPage":"6523","endPage":"6531","ipdsId":"IP-098848","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468586,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gl078621","text":"Publisher Index Page"},{"id":357402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","volume":"45","issue":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-12","publicationStatus":"PW","scienceBaseUri":"5bc02fcbe4b0fc368eb53984","contributors":{"authors":[{"text":"Mohr, Christian H.","contributorId":198746,"corporation":false,"usgs":false,"family":"Mohr","given":"Christian","email":"","middleInitial":"H.","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":745121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manga, Michael","contributorId":131168,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":745122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745123,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210222,"text":"70210222 - 2018 - Effects of land use on summer thermal regimes in critical salmonid habitats of the Pacific Northwest","interactions":[],"lastModifiedDate":"2020-05-21T14:16:29.700544","indexId":"70210222","displayToPublicDate":"2018-07-16T09:06:03","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Effects of land use on summer thermal regimes in critical salmonid habitats of the Pacific Northwest","docAbstract":"The effect of climate change on stream temperature regimes is of significant concern to natural resource managers focused on protecting cold-water-dependent species. Nevertheless, understanding of how human land-use activities may act to exacerbate the effects of climate change on stream temperature regimes is limited. Using extensive stream temperature data with high-resolution climate and habitat data, we quantified how land management activities are related to summer stream temperatures across the Pacific Northwest, USA. We then described the distribution of land management practices influencing summer thermal regimes relative to the distribution of salmonid fish species of conservation concern. After accounting for climatic and geophysical variation, we detected a strong relationship between livestock grazing and summer thermal regimes. Maximum, average, and diel variation in water temperature was greater where livestock grazing was present. Livestock grazing was widespread, occurring in 43%–100% of sites supporting salmonid species of conservation concern. Thus, current land management practices may be intensifying the effects of ongoing climate change in freshwater habitats, acting to further threaten cold-water fishes of conservation concern.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0165","usgsCitation":"Kovach, R., Muhlfeld, C.C., Al-Chokhachy, R., Ojala, J.V., and Archer, E., 2018, Effects of land use on summer thermal regimes in critical salmonid habitats of the Pacific Northwest: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 5, p. 753-761, https://doi.org/10.1139/cjfas-2018-0165.","productDescription":"9 p.","startPage":"753","endPage":"761","ipdsId":"IP-093115","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":374983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington, Oregon, Idaho, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.92578125,\n 41.77131167976407\n ],\n [\n -111.26953125,\n 41.77131167976407\n ],\n [\n -111.26953125,\n 49.095452162534826\n ],\n [\n -123.92578125,\n 49.095452162534826\n ],\n [\n -123.92578125,\n 41.77131167976407\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kovach, Ryan 0000-0001-5402-2123 rkovach@usgs.gov","orcid":"https://orcid.org/0000-0001-5402-2123","contributorId":145914,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":789619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":216140,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":789620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ojala, Jeffrey V.","contributorId":224816,"corporation":false,"usgs":false,"family":"Ojala","given":"Jeffrey","email":"","middleInitial":"V.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":789621,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Archer, Eric","contributorId":167603,"corporation":false,"usgs":false,"family":"Archer","given":"Eric","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":789622,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198125,"text":"70198125 - 2018 - Outburst floods provide erodability estimates consistent with long-term landscape evolution","interactions":[],"lastModifiedDate":"2018-07-17T09:56:50","indexId":"70198125","displayToPublicDate":"2018-07-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Outburst floods provide erodability estimates consistent with long-term landscape evolution","docAbstract":"Most current models for the landscape evolution over geological timescales are based on semi-empirical laws that consider riverbed incision proportional to rock erodability (dependent on lithology) and to the work performed by water flow (stream power). However, the erodability values obtained from these models are entangled with poorly known conditions of past climate and streamflow. Here we use the erosion reported for 82 outburst floods triggered by overtopping lakes as a way to estimate the outlet erodability. This avoids the common assumptions regarding past hydrology because water discharge from overtopping floods is often well constrained from geomorphological evidence along the spillway. This novel methodology yields values of erodability that show a quantitative relation to lithology similar to previous river erosion analyses, expanding the range of hydrological and temporal scales of fluvial incision models and suggesting some consistency between the mathematical formulations of long-term and catastrophic erosional mechanisms. Our results also clarify conditions leading to the runaway erosion responsible for outburst floods triggered by overtopping lakes.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-28981-y","usgsCitation":"Garcia-Castellanos, D., and O'Connor, J., 2018, Outburst floods provide erodability estimates consistent with long-term landscape evolution: Scientific Reports, v. 8, p. 1-9, https://doi.org/10.1038/s41598-018-28981-y.","productDescription":"Article number: 10573; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-098874","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":468587,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-28981-y","text":"Publisher Index Page"},{"id":355719,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-12","publicationStatus":"PW","scienceBaseUri":"5b6fc413e4b0f5d57878e9c7","contributors":{"authors":[{"text":"Garcia-Castellanos, Daniel","contributorId":203800,"corporation":false,"usgs":false,"family":"Garcia-Castellanos","given":"Daniel","email":"","affiliations":[{"id":36720,"text":"Instituto de Ciencias de la Tierra Jaume Almera, ICTJA-CSIC, Solé i Sabarís s/n, 08028 Barcelona, Spain","active":true,"usgs":false}],"preferred":false,"id":740150,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":740149,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197877,"text":"sir20185084 - 2018 - Water budget of the upper Chehalis River Basin, southwestern Washington","interactions":[],"lastModifiedDate":"2018-07-17T10:32:26","indexId":"sir20185084","displayToPublicDate":"2018-07-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5084","title":"Water budget of the upper Chehalis River Basin, southwestern Washington","docAbstract":"Groundwater and surface water collectively supply the domestic, agricultural, and industrial needs of the 895-square mile upper Chehalis River Basin upstream of Grand Mound, Washington, while providing streamflow for fish and other aquatic species in the Chehalis River and its tributaries. To support sustainable water management decision-making, a water budget (including precipitation, interception, groundwater recharge, surface runoff, and groundwater pumping) was developed for the upper Chehalis River Basin during October 2001–September 2015. Water-budget components were estimated from the U.S. Geological Survey Soil-Water-Balance (SWB) model except for groundwater pumping, which was estimated from public water purveyor records, annual system data from the Washington State Department of Health, census population data, and water-use estimates. Groundwater recharge estimated from the SWB model was compared to base flow, a proxy for groundwater recharge, independently estimated from separation of the hydrograph recorded by the U.S. Geological Survey streamgage at the outlet of the basin. Mean annual precipitation for the basin was estimated at 72.6 inches, of which 35 percent was lost to evapotranspiration, 30 percent was recharged to groundwater, 30 percent was surface runoff, and 5 percent was lost to interception. SWB model estimates of groundwater recharge were 17 percent less than estimates of base flow from hydrograph separation. Groundwater pumpage in the basin was estimated at 1 percent of groundwater recharge estimated by SWB and 0.8 percent of base flow estimated by hydrograph separation. These estimates form a baseline for understanding future changes to components of water use and may be used to inform numerical groundwater models to support sustainable management of water resources in the upper Chehalis River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185084","collaboration":"Prepared in cooperation with the City of Centrailia","usgsCitation":"Gendaszek, A.S., and Welch, W.B., 2018, Water budget of the upper Chehalis River Basin, southwestern Washington: U.S. Geological Survey Scientific Investigations Report 2018-5084, 17 p., https://doi.org/10.3133/sir20185084.","productDescription":"v, 17 p.","onlineOnly":"Y","ipdsId":"IP-096130","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":437827,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78G8K1F","text":"USGS data release","linkHelpText":"Soil Water Balance Model of Upper Chehalis River Basin, Southwestern Washington"},{"id":355593,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5084/coverthb.jpg"},{"id":355594,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5084/sir20185084.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5084"}],"country":"United States","state":"Washington","otherGeospatial":"Chehalis River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.1667,\n 46.8333\n ],\n [\n -122.3333,\n 46.8333\n ],\n [\n -122.3333,\n 46.3333\n ],\n [\n -123.1667,\n 46.3333\n ],\n [\n -123.1667,\n 46.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402