In dryland ecosystems, land degradation and erosion pose severe threats to ecosystem productivity and human wellbeing. Bio‐inoculation of degraded soils with native biological soil crusts ('biocrusts') is a promising yet relatively untested means to improve soil stability and hydrologic function (i.e. increase infiltration and reduce runoff). In a degraded semi‐arid grassland on the Colorado Plateau, we studied the establishment and hydrologic function (via simulated rainfall) of induced biocrusts grown with and without an organic soil stabilizer (psyllium, derived from Plantago sp.), after a period of four months. We found evidence of biocrust establishment, including significantly higher biocrust cover, chlorophyll a, and exopolysaccarides (EPS) in inoculated plots compared to controls. Plots inoculated with biocrust had higher runoff and sediment yields than controls during rainfall simulation. However, this effect was mitigated in plots where stabilizer was added, resulting in greater soil aggregate stability and higher levels of infiltration (reduced total runoff). The time to ponding was significantly greater than control for all inoculated plots, suggesting that induced biocrusts may be most effective at improving infiltration under low‐intensity, smaller precipitation events. Notably, the biocrusts in this study lacked the rough surface microtopography which is common in well‐developed biocrusts regionally and likely instrumental in slowing overland flow and increasing infiltration for larger rain events. These results highlight the temporal lag that may exist between apparent and functional restoration of biocrusts. In addition, the simultaneous additions of stabilizing amendments with biocrust inoculum may work collectively to achieve both short and long‐term restoration targets.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.2089","usgsCitation":"Fick, S.E., Barger, N.N., and Duniway, M.C., 2019, Hydrologic function of rapidly induced biocrusts: Ecohydrology, v. 12, no. 4, e2089, https://doi.org/10.1002/eco.2089.","productDescription":"e2089","ipdsId":"IP-102716","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":362814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Fick, Stephen E. 0000-0002-3548-6966","orcid":"https://orcid.org/0000-0002-3548-6966","contributorId":214319,"corporation":false,"usgs":true,"family":"Fick","given":"Stephen","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":760498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barger, Nichole N.","contributorId":193039,"corporation":false,"usgs":false,"family":"Barger","given":"Nichole","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":760499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":760497,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202929,"text":"70202929 - 2019 - Residence time controls on the fate of nitrogen in flow‐through lakebed sediments","interactions":[],"lastModifiedDate":"2019-06-18T11:21:20","indexId":"70202929","displayToPublicDate":"2019-04-05T09:05:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Residence time controls on the fate of nitrogen in flow‐through lakebed sediments","docAbstract":"For many glacial lakes with highly permeable sediments, water exchange rates control hydrologic residence times within the sediment‐water interface (SWI) and the removal of reactive compounds such as nitrate, a common pollutant in lakes and groundwater. Here we conducted a series of focused tracer injection experiments in the upper 20 cm of the naturally downwelling SWI in a flow‐through lake on Cape Cod, MA. We systematically varied residence time and reactant controls on nitrate processing, using isotopically labeled 15N nitrate to monitor the effect of these changes on nitrate removal via denitrification. The addition of acetate, a labile carbon compound, triggered the lake SWI to switch from net production to net removal of nitrate. When acetate was combined with increased residence time created by controlled reductions in water flux, we observed a fivefold increase in nitrate removal, a 26‐fold increase in N2 production, and a 42‐fold increase in N2O production. We demonstrate that water residence time is an important control on the fate of nitrate in these lake SWIs and illustrate that seasonal conditions that alter lake exchange rates and variability in lake carbon may predict dynamic nitrate removal across the SWI. Additionally, observed N2O production during the oxic pore water experiments paired with geophysical characterization of the sediment porosity revealed that the lake SWI has less mobile pores occupying upward of 50% of the total porosity volume, which function as reactive microzones for nitrate processing.
","language":"English","publisher":"Wiley","doi":"10.1029/2018JG004741","usgsCitation":"Hampton, T.B., Zarentske, J.P., Briggs, M.A., Singha, K., Harvey, J.W., Day-Lewis, F.D., Dehkordy, F.M., and Lane, J.W., 2019, Residence time controls on the fate of nitrogen in flow‐through lakebed sediments: Journal of Geophysical Research: Biogeosciences, v. 124, no. 3, p. 689-707, https://doi.org/10.1029/2018JG004741.","productDescription":"19 p.","startPage":"689","endPage":"707","ipdsId":"IP-103407","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jg004741","text":"Publisher Index Page"},{"id":362813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Hampton, Tyler B.","contributorId":210072,"corporation":false,"usgs":false,"family":"Hampton","given":"Tyler","email":"","middleInitial":"B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zarentske, Jay P.","contributorId":214658,"corporation":false,"usgs":false,"family":"Zarentske","given":"Jay","email":"","middleInitial":"P.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760509,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":760512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":760514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":760513,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dehkordy, Farzaneh MahmoodPoor","contributorId":214661,"corporation":false,"usgs":false,"family":"Dehkordy","given":"Farzaneh","email":"","middleInitial":"MahmoodPoor","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":760515,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":760516,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202931,"text":"70202931 - 2019 - Multi-scale preferential flow processes in an urban streambed under variable hydraulic conditions","interactions":[],"lastModifiedDate":"2019-04-05T12:54:14","indexId":"70202931","displayToPublicDate":"2019-04-05T08:59:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale preferential flow processes in an urban streambed under variable hydraulic conditions","docAbstract":"Spatially preferential flow processes occur at nested scales at the sediment-water interface (SWI), due in part to sediment heterogeneities, which may be enhanced in flashy urban streams with heavy road sand influence. However, several factors, including the flow-rate dependence of preferential hyporheic flow and discrete groundwater discharge zones are commonly overlooked in reach-scale models of groundwater/surface water exchange. Using a series of controlled-head tracer-injection experiments coupled with cm-scale geophysics within the highly reactive upper 30 cm of the hyporheic zone of an urban stream, we quantified the flow dependence of local less-mobile porosity volume, mass-transfer rate coefficient, and the resulting local residence time in the less-mobile pore space at three controlled downward fluid fluxes (0.8, 2, and 3 m/d). Experiments were performed in two adjacent streambed locations, representing different sediment bulk vertical permeability. Less-mobile porosity parameters were generally substantial and similar between the two streambed locations; though a more competent, thin, organic layer at ∼15 cm depth in one location strongly impacted tracer loading, flushing dynamics, and local residence times. Increased downward flux led to (1) a decrease in less-mobile porosity residence time in all experiments, and (2) an increase in less-mobile porosity fraction for most experiments. Additionally, at the larger stream reach-scale, surface electrodes for electrical resistivity measurement were installed along 22 m of the wetted stream channel. These surface electrode measurements were collected during a natural storm flow event, which revealed widespread, short-term, flushing (e.g. <3 h) of the hyporheic zone with stream water, followed by longer-term (e.g. >60 h) flushing of the SWI with riparian zone groundwater. Flow dependence of preferential hyporheic zone flowpaths, like in the controlled tracer experiments, was also observed in these reach-scale electrical resistivity tomography measurements. Our findings reveal that the spatial and temporal dependence of preferential flow processes create highly dynamic SWI conditions that will affect the physical and coupled biogeochemical functions of the SWI in urbanized, sand-impacted streams.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.03.022","usgsCitation":"Dehkordy, F.M., Briggs, M.A., Day-Lewis, F.D., Singha, K., Krajnovich, A., Hampton, T.B., Zarnetske, J.P., Scruggs, C.R., and Bagtzoglou, A.C., 2019, Multi-scale preferential flow processes in an urban streambed under variable hydraulic conditions: Journal of Hydrology, v. 573, p. 168-179, https://doi.org/10.1016/j.jhydrol.2019.03.022.","productDescription":"12 p.","startPage":"168","endPage":"179","ipdsId":"IP-104970","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2019.03.022","text":"Publisher Index Page"},{"id":362811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"573","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dehkordy, Farzaneh MahmoodPoor","contributorId":214661,"corporation":false,"usgs":false,"family":"Dehkordy","given":"Farzaneh","email":"","middleInitial":"MahmoodPoor","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":760524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":760525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":760526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krajnovich, Ashton","contributorId":214671,"corporation":false,"usgs":false,"family":"Krajnovich","given":"Ashton","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":760527,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hampton, Tyler B.","contributorId":210072,"corporation":false,"usgs":false,"family":"Hampton","given":"Tyler","email":"","middleInitial":"B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760528,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zarnetske, Jay P.","contributorId":210073,"corporation":false,"usgs":false,"family":"Zarnetske","given":"Jay","email":"","middleInitial":"P.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760529,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Scruggs, Courtney R. 0000-0002-1744-3233 cscruggs@usgs.gov","orcid":"https://orcid.org/0000-0002-1744-3233","contributorId":190406,"corporation":false,"usgs":true,"family":"Scruggs","given":"Courtney","email":"cscruggs@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":760530,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bagtzoglou, Amvrossios C.","contributorId":211518,"corporation":false,"usgs":false,"family":"Bagtzoglou","given":"Amvrossios","email":"","middleInitial":"C.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":760531,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70203038,"text":"70203038 - 2019 - Estimating quick-flow runoff at the monthly timescale for the conterminous United States","interactions":[],"lastModifiedDate":"2019-06-18T11:29:24","indexId":"70203038","displayToPublicDate":"2019-04-04T09:43:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating quick-flow runoff at the monthly timescale for the conterminous United States","docAbstract":"The quantitative estimation of the quick-flow runoff component of streamflow is required for many hydrologic applications. Estimation at the monthly timescale and national spatial scale would be particularly useful for national water availability modeling. This paper reviews a sample of commonly used equations for quick-flow runoff, including several currently in use in continental-scale models. The review shows the wide range of equation forms or heuristics currently in use to predict quick-flow runoff, the limited spatial scale over which these equations are often developed or calibrated, and the scarcity of well-tested equations available for quick-flow runoff at the monthly timescale. Data were gathered from a set of 1301 gaged watersheds across the United States to test a range of equations from the literature, along with several alternative equations, to assess and compare their performance in predicting quick-flow runoff at the monthly timescale. The highest-performing equation was selected for application to monthly maps of explanatory variables to produce monthly quick-flow runoff water budget contribution maps. This equation is a regression against precipitation, soil saturated hydraulic conductivity, surficial geology type, and slope data. Its application indicates that average quick-flow runoff across the conterminous United States in the winter exceeds that in the summer by up to a factor of three. The monthly maps were explored and evaluated for the timespan of 2000-2015. The comparison of equation forms and produced monthly maps will be useful for a variety of hydrologic modeling and monitoring applications.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.04.010","usgsCitation":"Reitz, M., and Sanford, W.E., 2019, Estimating quick-flow runoff at the monthly timescale for the conterminous United States: Journal of Hydrology, v. 573, p. 841-854, https://doi.org/10.1016/j.jhydrol.2019.04.010.","productDescription":"14 p.","startPage":"841","endPage":"854","ipdsId":"IP-102672","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":467732,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2019.04.010","text":"Publisher Index Page"},{"id":437509,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y1RP02","text":"USGS data release","linkHelpText":"Monthly timescale quick-flow runoff maps for 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,{"id":70206425,"text":"70206425 - 2019 - Holocene thermokarst lake dynamics in northern Interior Alaska: The interplay of climate, fire, and subsurface hydrology","interactions":[],"lastModifiedDate":"2019-11-05T06:57:24","indexId":"70206425","displayToPublicDate":"2019-04-03T11:32:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Holocene thermokarst lake dynamics in northern Interior Alaska: The interplay of climate, fire, and subsurface hydrology","docAbstract":"The current state of permafrost in Alaska and meaningful expectations for its future evolution are informed by long-term perspectives of previous permafrost degradation. Thermokarst processes in permafrost landscapes often lead to widespread lake formation and the spatial and temporal evolution of thermokarst lake landscapes reflects the combined effects of climate, ground conditions, vegetation, and fire. This study provides detailed analyses of thermokarst lake sediments of Holocene age from the southern loess uplands of the Yukon Flats; including bathymetry and sediment core analyses across a water depth transect. The sediment core results, dated by radiocarbon and 210Pb, indicate the onset of finely laminated lacustrine sedimentation between ~10,000 and 9,000 cal yr BP following basin development through inferred thermokarst processes. Thermokarst expansion to modern shoreline configurations continued until ~5000 cal yr BP, which may have been influenced by increased fire. Between ~5000 and 2000 cal yr BP, the preservation of fine laminations at intermediate and deep-water depths indicate higher lake levels than present. At that time, the lake likely overflowed into an over-deepened gully system that is no longer occupied by perennial streams. By ~2000 cal yr BP, massive sedimentation at intermediate water depths indicates that lake levels lowered, which is interpreted to reflect a response to drier conditions based on correspondence with Yukon Flats regional fire and local paleoclimate reconstructions. Consideration of additional contributing mechanisms include the possible influence of catastrophic lake drainages on downgradient base flow levels that may have enhanced subsurface water loss, although this mechanism is untested. The overall consistency between the millennial lake level trends documented here with regional paleoclimate trends indicates that after lakes formed, their size and depth has likely been affected directly by North Pacific atmospheric circulation changes and indirectly through evolution of permafrost, ground ice and sub-surface hydrology. As the first detailed study of Holocene thermokarst basin expansion, stabilization and subsequent climate-driven lake level variations in a loess upland, results provide a framework for future investigations of paleoclimatic signals from similar lake systems that characterize large regions of Alaska and Siberia.","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2019.00053","usgsCitation":"Anderson, L., Edwards, M.E., Mark D. Shapley, Bruce P. Finney, and Langdon, C., 2019, Holocene thermokarst lake dynamics in northern Interior Alaska: The interplay of climate, fire, and subsurface hydrology: Frontiers in Earth Science, v. 7, p. 1-22, https://doi.org/10.3389/feart.2019.00053.","productDescription":"53, 22 p.","startPage":"1","endPage":"22","ipdsId":"IP-102292","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467736,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2019.00053","text":"Publisher Index Page"},{"id":437512,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O7255D","text":"USGS data release","linkHelpText":"Data Release for "Holocene thermokarst lake dynamics in northern Interior Alaska: the interplay of climate, fire, and subsurface hydrology""},{"id":368921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Habanero pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -146.75811767578125,\n 66.07962172153299\n ],\n [\n -146.7121124267578,\n 66.07962172153299\n ],\n [\n -146.7121124267578,\n 66.10772577267431\n ],\n [\n -146.75811767578125,\n 66.10772577267431\n ],\n [\n -146.75811767578125,\n 66.07962172153299\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":220214,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":774501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Mary E.","contributorId":220215,"corporation":false,"usgs":false,"family":"Edwards","given":"Mary","email":"","middleInitial":"E.","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":774502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mark D. Shapley","contributorId":220216,"corporation":false,"usgs":false,"family":"Mark D. Shapley","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":774503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruce P. Finney","contributorId":220217,"corporation":false,"usgs":false,"family":"Bruce P. Finney","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":774504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Langdon, Catherine","contributorId":220218,"corporation":false,"usgs":false,"family":"Langdon","given":"Catherine","email":"","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":774505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203046,"text":"70203046 - 2019 - Effects of climate, regulation, and urbanization on historical flood trends in the United States","interactions":[],"lastModifiedDate":"2019-04-15T10:57:39","indexId":"70203046","displayToPublicDate":"2019-04-01T10:57:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of climate, regulation, and urbanization on historical flood trends in the United States","docAbstract":"Many studies have analyzed historical trends in annual peak flows in the United States because of the importance of flooding to bridges and other structures, and the concern that human influence may increase flooding. To help attribute causes of historical peak-flow changes, it is important to separate basins by characteristics that have different influences on peak flows. We analyzed historical trends by basin type: minimally altered basins, regulated basins (substantial reservoir storage but low urbanization), and urbanized basins (with low reservoir storage). Although many peak-flow magnitude changes were found in the last century across the conterminous United States, the trend magnitude and direction vary strongly by basin type and region. In general, there was a low percentage of significant increases and decreases for minimally altered basins while many regulated basins had significant decreases and the limited number of urbanized basins with long-term record showed a high percentage of increases. For urbanized basins, which are concentrated in the Northeast and Midwest, trend magnitude was significantly correlated with the amount of basin urbanization. For all basins regardless of type, parts of the Northeast quadrant of the U.S. had high concentrations of basins with large and significant increases while parts of the Southwest quadrant had high concentrations of basins with large and significant decreases. Basin regulation appears to have heavily influenced the decreasing trends in the Southwest quadrant; there were many large decreases for this basin type despite overall increases in heavy precipitation in this area. Changes over time in the number of 2-per-year and 1-per-5-year peaks over threshold are consistent with changes in the magnitude of annual peak flows.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.03.102","usgsCitation":"Hodgkins, G., Dudley, R., Archfield, S., and Renard, B., 2019, Effects of climate, regulation, and urbanization on historical flood trends in the United States: Journal of Hydrology, v. 573, p. 697-709, https://doi.org/10.1016/j.jhydrol.2019.03.102.","productDescription":"13 p.","startPage":"697","endPage":"709","ipdsId":"IP-099282","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":362951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n 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Robert","contributorId":214834,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":214835,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":760922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Renard, Benjamin","contributorId":177291,"corporation":false,"usgs":false,"family":"Renard","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":760923,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204653,"text":"70204653 - 2019 - Assessing seasonal changes in microgravity at Yellowstone caldera","interactions":[],"lastModifiedDate":"2019-08-09T10:45:59","indexId":"70204653","displayToPublicDate":"2019-04-01T07:51:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Assessing seasonal changes in microgravity at Yellowstone caldera","docAbstract":"Microgravity time series at active volcanoes can provide an indication of mass change related to subsurface magmatic processes, but uncertainty is often introduced by hydrologic variations and other noise sources that cannot easily be isolated. We empirically assessed seasonality and noise by conducting four surveys over the course of May-October 2017 at Yellowstone caldera, Wyoming. Yellowstone experiences frequent changes in the rates and styles of seismicity and surface deformation, but the mechanisms of these changes are poorly understood because the characteristics of the driving fluids are not clear. Past gravity data from the caldera have yielded ambiguous results, possibly due to hydrologic noise. Given the strong visually observable changes in surface water and snow conditions over the course of our surveys, we expected to see significant variations in gravity. The net change in gravity, however, was less than 20 µGal at most sites, and there was no strong correlation with river and lake levels or snow conditions. Seasonal changes in gravity are therefore small compared to those that would be expected from magmatic activity, although they may be on the same order as those associated with Yellowstone’s hydrothermal system. We did find that noise levels in gravity data were highly dependent on site characteristics, with bedrock sites away from trees yielding the lowest levels of noise, and thin concrete pads in forested areas the highest. These results can be used to plan future surveys at Yellowstone and to reinterpret past data, and they provide guidance in terms of best practices for repeat gravity work on volcanoes worldwide.","language":"English","publisher":"Wiley","doi":"10.1029/2018JB017061","usgsCitation":"Poland, M.P., and de Zeeuw-van Dalfsen, E., 2019, Assessing seasonal changes in microgravity at Yellowstone caldera: Journal of Geophysical Research, v. 124, no. 4, p. 4174-4188, https://doi.org/10.1029/2018JB017061.","productDescription":"15 p.","startPage":"4174","endPage":"4188","ipdsId":"IP-103468","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467754,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb017061","text":"Publisher Index Page"},{"id":366351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.28051757812499,\n 43.79488907226601\n ],\n [\n -109.3304443359375,\n 43.79488907226601\n ],\n [\n -109.3304443359375,\n 45.14717913418674\n ],\n [\n -111.28051757812499,\n 45.14717913418674\n ],\n [\n -111.28051757812499,\n 43.79488907226601\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":767930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Zeeuw-van Dalfsen, Elske 0000-0003-2527-4932","orcid":"https://orcid.org/0000-0003-2527-4932","contributorId":217967,"corporation":false,"usgs":false,"family":"de Zeeuw-van Dalfsen","given":"Elske","email":"","affiliations":[{"id":39727,"text":"KNMI","active":true,"usgs":false}],"preferred":false,"id":767931,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203230,"text":"70203230 - 2019 - Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region","interactions":[],"lastModifiedDate":"2019-05-02T08:07:59","indexId":"70203230","displayToPublicDate":"2019-04-01T07:46:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region","docAbstract":"Understanding how bird populations respond to changes in waterbody availability in the climatically variable Prairie Pothole Region (PPR) of North America hinges on being able to couple hydrological and climate modeling to represent potential future landscapes. Model experiments run with the Pothole Complex Hydrologic Model using downscaled climate data (variables relating to precipitation, temperature, and potential evapotranspiration at 1/8° spatial resolution under four general circulation climate models and two gas emissions scenarios) were used to forecast the abundances of six focal wetland‐dependent bird species in the Missouri Coteau portion of the PPR, providing ensemble scenarios at a spatial scale relevant to resource management. Although the projected number of May ponds (waterbodies present during bird breeding season) fluctuated through time with some decadal periodicity (and with the number present in a given year reflecting abundance over the previous three years), the ensemble model average indicated an increase in the average number of waterbodies present by the turn of the next century. Overall, the model experiments conservatively projected an 11.75% increase in the number of waterbodies present by 2090–2099 compared to a baseline period from 1967 to 2005 in the PPR. Wetland‐dependent bird occurrence and abundance were significantly associated with temporal patterns and decadal periodicity in waterbody dynamics. Because of the strong associations between wetland‐dependent bird occurrence and abundance and the number of prairie potholes, projected waterbody increases are forecasted to result in an 11.97% overall increase in occurrence and 8.63% increase in abundance of the six focal species by the end of the 21st century; these results contrast with forecasted drought‐associated declines in waterbodies and birds in the PPR. This integrated hydrological–climatological approach offers a means of assessing how wetland‐dependent bird populations may respond to changes in wetland habitat availability due to a changing climate. Our results provide information that can help managers decide how to mitigate the effects of climate shifts on the distribution of wetland habitat and biota.
The biogeochemistry of nitrogen (N) and phosphorus (P) in tropical streams and rivers is strongly regulated by the pronounced seasonality of rainfall and associated changes in hydrology. Land use and land cover change (LULCC) can also be a dominant driver of changes in stream biogeochemistry yet responses are not fully understood and vary across different LULCC scenarios. We measured dissolved and total nitrogen (N) and phosphorus (P) concentrations in four tributary streams of the Temash River watershed in southern Belize, Central America. The dominant land use practice in each of the four study catchments was swidden agriculture. We documented a strong seasonal control on the export of nutrients from these study systems with daily N fluxes increasing approximately 10-fold during the onset of the rainy season. P fluxes increased almost 4-fold during the same time period. Comparisons with nutrient export coefficients from other tropical streams suggest that nutrient export in streams of the Temash River watershed is similar or slightly lower. Establishing improved understanding of the terrestrial and hydrologic controls of N and P transport across the terrestrial-aquatic boundary and developing a comprehensive nutrient budget that includes inputs and outputs associated with crop production is warranted in future work.
","language":"English","publisher":"MDPI","doi":"10.3390/w11040664","usgsCitation":"Buck, D.G., Esselman, P., Jiang, S., Wainwright, J.D., Brenner, M., and Cohen, M.J., 2019, Seasonal fluxes of dissolved nutrients in streams of catchments dominated by swidden agriculture in the Maya Forest of Belize, Central America: Water, v. 11, no. 4, 664, 24 p., https://doi.org/10.3390/w11040664.","productDescription":"664, 24 p.","ipdsId":"IP-106287","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467757,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11040664","text":"Publisher Index Page"},{"id":381004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Belize","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.21722412109374,\n 15.890017659698243\n ],\n [\n -88.90411376953125,\n 15.890017659698243\n ],\n [\n -88.90411376953125,\n 16.151368535968885\n ],\n [\n -89.21722412109374,\n 16.151368535968885\n ],\n [\n -89.21722412109374,\n 15.890017659698243\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Buck, David G.","contributorId":245403,"corporation":false,"usgs":false,"family":"Buck","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":806134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":806135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jiang, Shiguo 0000-0001-9088-883X","orcid":"https://orcid.org/0000-0001-9088-883X","contributorId":244799,"corporation":false,"usgs":false,"family":"Jiang","given":"Shiguo","email":"","affiliations":[{"id":48981,"text":"State University of New York","active":true,"usgs":false}],"preferred":false,"id":806136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wainwright, Joel D.","contributorId":245404,"corporation":false,"usgs":false,"family":"Wainwright","given":"Joel","email":"","middleInitial":"D.","affiliations":[{"id":49186,"text":"University of Ohio","active":true,"usgs":false}],"preferred":false,"id":806137,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brenner, Mark","contributorId":245405,"corporation":false,"usgs":false,"family":"Brenner","given":"Mark","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":806138,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cohen, Matthew J.","contributorId":138990,"corporation":false,"usgs":false,"family":"Cohen","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":806139,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70234300,"text":"70234300 - 2019 - Understanding the central Great Plains as a coupled climatic-hydrological-human system: Lessons learned in operationalizing interdisciplinary collaboration","interactions":[],"lastModifiedDate":"2022-08-08T13:21:37.152162","indexId":"70234300","displayToPublicDate":"2019-03-31T08:15:30","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Understanding the central Great Plains as a coupled climatic-hydrological-human system: Lessons learned in operationalizing interdisciplinary collaboration","docAbstract":"This chapter discusses an interdisciplinary and transdisciplinary project to understand the interactions of agriculture, climate, and water resources in the Central Great Plains as a coupled natural-human system. We focus on the Smoky Hills Watershed in Kansas, where we gathered socioeconomic, hydrological, and climatic data, along with ecological data on fish species. The project involved substantial stakeholder engagement, which was complicated by post-truth attitudes about climate science and environmental regulation by some groups. We discuss the challenges of team management, stakeholder engagement, and data integration for modeling, notably the incorporation of stakeholder support for environmental policy in the context of extreme climatic events. We conclude by offering a framework for good collaborative practice to manage the complications of crossing boundaries in transdisciplinary research and outreach.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Collaboration across boundaries for social-ecological systems science","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-13827-1_8","usgsCitation":"Caldas, M.M., Mather, M.E., Bergtold, J.S., Daniels, M., Granco, G., Aistrup, J., Haukos, D.A., Sheshukov, A.Y., Sanderson, M.R., and Heier Stamm, J.L., 2019, Understanding the central Great Plains as a coupled climatic-hydrological-human system: Lessons learned in operationalizing interdisciplinary collaboration, chap. of Collaboration across boundaries for social-ecological systems science, p. 265-294, https://doi.org/10.1007/978-3-030-13827-1_8.","productDescription":"30 p.","startPage":"265","endPage":"294","ipdsId":"IP-102166","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":404915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Smoky Hills Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.942138671875,\n 38.35888785866677\n ],\n [\n -97.261962890625,\n 38.35888785866677\n ],\n [\n -97.261962890625,\n 39.67337039176558\n ],\n [\n -101.942138671875,\n 39.67337039176558\n ],\n [\n -101.942138671875,\n 38.35888785866677\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2019-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Caldas, Marcellus M.","contributorId":200844,"corporation":false,"usgs":false,"family":"Caldas","given":"Marcellus","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":848494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":848493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergtold, Jason S.","contributorId":200846,"corporation":false,"usgs":false,"family":"Bergtold","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":848495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daniels, Melinda","contributorId":294671,"corporation":false,"usgs":false,"family":"Daniels","given":"Melinda","affiliations":[],"preferred":false,"id":848496,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Granco, Gabriel","contributorId":242802,"corporation":false,"usgs":false,"family":"Granco","given":"Gabriel","affiliations":[{"id":48532,"text":"swrc","active":true,"usgs":false}],"preferred":false,"id":848497,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aistrup, Joseph","contributorId":200847,"corporation":false,"usgs":false,"family":"Aistrup","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":848498,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":848492,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sheshukov, Aleksey Y.","contributorId":172092,"corporation":false,"usgs":false,"family":"Sheshukov","given":"Aleksey","email":"","middleInitial":"Y.","affiliations":[],"preferred":false,"id":848499,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sanderson, Matthew R.","contributorId":200845,"corporation":false,"usgs":false,"family":"Sanderson","given":"Matthew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":848500,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Heier Stamm, Jessica L.","contributorId":200848,"corporation":false,"usgs":false,"family":"Heier Stamm","given":"Jessica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":848501,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70203550,"text":"70203550 - 2019 - Comparison of groundwater age models for assessing nitrate loading, transport pathways, and management options in a complex aquifer system","interactions":[],"lastModifiedDate":"2019-11-14T13:45:05","indexId":"70203550","displayToPublicDate":"2019-03-30T16:38:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of groundwater age models for assessing nitrate loading, transport pathways, and management options in a complex aquifer system","docAbstract":"In an aquifer system with complex hydrogeology, mixing of groundwater with different ages could occur associated with various flow pathways. In this study, we applied different groundwater age estimation techniques (lumped parameter model, and numerical model) to characterize groundwater age distributions and the major pathways of nitrate contamination in the Gosan agricultural field, Jeju Island. According to the lumped parameter model, groundwater age in the study area could be explained by the binary mixing of the young groundwater (4-33 years) and the old water component (>60 years). The complex hydrogeologic regimes and local heterogeneity observed in the study area (multi-layered aquifer, well leakage hydraulics) were particularly well reflected in the numerical model. The numerical model predicted that the regional aquifer of Gosan responded to the fertilizer applications more rapidly (mean age: 9.7-22.3 years) than as estimated by other models. Our study results demonstrated that application and comparison of multiple age estimation methods can be useful to understand better the flow regimes and the mixing characteristics of groundwater with different ages (pathways), hence, to reduce the risk of improper groundwater management plan arising from the aquifer heterogeneity.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11465","usgsCitation":"Koh, E., Lee, E., Kaown, D., Green, C., Koh, D., Lee, K., and Lee, S., 2019, Comparison of groundwater age models for assessing nitrate loading, transport pathways, and management options in a complex aquifer system: Hydrological Processes, v. 32, p. 923-938, https://doi.org/10.1002/hyp.11465.","productDescription":"16 p.","startPage":"923","endPage":"938","ipdsId":"IP-086017","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":364068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"South Korea","otherGeospatial":"Jeju Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 125.9527587890625,\n 33.10534697199519\n ],\n [\n 127.0458984375,\n 33.10534697199519\n ],\n [\n 127.0458984375,\n 33.69235234723729\n ],\n [\n 125.9527587890625,\n 33.69235234723729\n ],\n [\n 125.9527587890625,\n 33.10534697199519\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Koh, E.H.","contributorId":215736,"corporation":false,"usgs":false,"family":"Koh","given":"E.H.","email":"","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":763106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, E.","contributorId":215737,"corporation":false,"usgs":false,"family":"Lee","given":"E.","email":"","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":763107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaown, D.","contributorId":215738,"corporation":false,"usgs":false,"family":"Kaown","given":"D.","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":763108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":763105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koh, D.C.","contributorId":215739,"corporation":false,"usgs":false,"family":"Koh","given":"D.C.","affiliations":[{"id":24820,"text":"Korea Institute of Geoscience and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":763109,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, K.K","contributorId":215740,"corporation":false,"usgs":false,"family":"Lee","given":"K.K","email":"","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":763110,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lee, Sangil","contributorId":215741,"corporation":false,"usgs":false,"family":"Lee","given":"Sangil","affiliations":[{"id":39310,"text":"Korea Polar Research Institute","active":true,"usgs":false}],"preferred":false,"id":763111,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228106,"text":"70228106 - 2019 - The accuracy of ecological flow metrics derived using a physics-based distributed rainfall-runoff model in the Great Plains, USA","interactions":[],"lastModifiedDate":"2022-02-07T14:40:52.157488","indexId":"70228106","displayToPublicDate":"2019-03-30T14:46:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"The accuracy of ecological flow metrics derived using a physics-based distributed rainfall-runoff model in the Great Plains, USA","docAbstract":"The development of a hydrologic foundation, essential for advancing our understanding of flow-ecology relationships, was developed using the high-resolution physics-based distributed rainfall–runoff model Vflo in a semi-arid region. We compared the accuracy and bias associated with flow metrics that were generated using Vflo, gauge data, and drainage area ratios at both a daily and monthly time step in the Canadian River basin, USA. First, we calibrated and applied bias correction to the Vflo model to simulate streamflow at ungauged catchment locations. Next, flow metrics were calculated using simulated and observed data from stream gauge locations. We found discharge predictions using Vflo were more accurate than drainage area ratios. General correspondence between predicted discharge and the gauge data was apparent; however, flow metrics calculated using the Vflo output did not accurately represent flow variability. Results from the Vflo model showed systematic discharge over-predictions in the upper basin and isolated over-predictions in the lower basin, likely due to hail events and sparse rainfall data across the large catchment. Goodness-of-fit statistics (Nash–Sutcliffe efficiency, root-mean square error, and the coefficient of variation) indicated the drainage area ratio and Vflo were more accurate at a monthly rather than daily time step, even after quantile mapping. This finding limits the number of streamflow metrics available to develop ecological models, but more importantly, the coarser resolution may hinder our understanding of ecological processes that occur at a submonthly time step. Our approach provides a framework for selecting flow metrics that best represent hydrologic patterns across a large semi-arid catchment with the necessary accuracy to address the ecological questions of interest.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.2090","usgsCitation":"Worthington, T.A., Brewer, S.K., Viex, B., and Kennen, J., 2019, The accuracy of ecological flow metrics derived using a physics-based distributed rainfall-runoff model in the Great Plains, USA: Ecohydrology, v. 12, no. 5, e2090, 17 p., https://doi.org/10.1002/eco.2090.","productDescription":"e2090, 17 p.","ipdsId":"IP-097660","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Oklahoma, Texas","otherGeospatial":"Canadian River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.447021484375,\n 34.615126683462194\n ],\n [\n -95.00976562499999,\n 34.615126683462194\n ],\n [\n -95.00976562499999,\n 35.39800594715108\n ],\n [\n -104.447021484375,\n 35.39800594715108\n ],\n [\n -104.447021484375,\n 34.615126683462194\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"5","noUsgsAuthors":false,"publicationDate":"2019-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Worthington, Thomas A.","contributorId":140662,"corporation":false,"usgs":false,"family":"Worthington","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":833135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Viex, Baxter","contributorId":274567,"corporation":false,"usgs":false,"family":"Viex","given":"Baxter","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":833136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833137,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202858,"text":"70202858 - 2019 - Geology and biostratigraphy of the Upper Floridan aquifer in the greater Savannah region, Georgia and South Carolina","interactions":[],"lastModifiedDate":"2020-10-22T20:38:40.180425","indexId":"70202858","displayToPublicDate":"2019-03-29T10:34:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Geology and biostratigraphy of the Upper Floridan aquifer in the greater Savannah region, Georgia and South Carolina","docAbstract":"The Upper Floridan aquifer (UFA) of South Carolina, Georgia, Alabama, Mississippi, and Florida has been considered a regionally continuous stratigraphic sequence of Eocene to Miocene carbonate strata, with documented unconformities based on lithology and biostratigraphy. As part of an investigation of the regional subsurface geologic framework in the Atlantic Coastal Plain Province, three deep cores were drilled by the U.S. Geological Survey at Pineora, Effingham County, Georgia; Cockspur Island, Chatham County, Georgia; and Palm Dunes, Beaufort County, South Carolina. The age of the UFAbased on calcareous nannofossil biostratigraphy ranges from early Oligocene to early Miocene in Pineora, late Eocene to late Oligocene in Cockspur Island, and late Eocene to questionably Miocene in Palm Dunes. Thin section analyses identified eleven unique microfacies across the study area and suggests that the sediments were most likely transported by oceanic currents at the time of deposition. Disconformities are identified from the Pineora and Palm Dunes cores and channel incision is documented at the top of the UFA in the Palm Dunes core. This study 1) documents how existing formation and time stratigraphic boundaries cross hydrogeologic units, 2) shows the complex geologic nature of the Upper Floridan aquifer across a relatively limited area, 3) sets forth a better understanding of how lateral and vertical changes in the lithologic units of the UFA affect permeability and porosity, and thus subsurface hydrologic flow, across the region, and 4) highlights the problems faced by legislators when implementing groundwater use regulations intended to slow salt water intrusion and drawdown.
","language":"English","publisher":"Micropaleontology Press","doi":"10.29041/strat.16.1.41-62","usgsCitation":"Self-Trail, J., Parker, M., Haynes, J.T., Schultz, A., and Huddleston, P.F., 2019, Geology and biostratigraphy of the Upper Floridan aquifer in the greater Savannah region, Georgia and South Carolina: Stratigraphy, v. 16, no. 1, p. 41-62, https://doi.org/10.29041/strat.16.1.41-62.","productDescription":"22 p.","startPage":"41","endPage":"62","ipdsId":"IP-101631","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":362647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, South Carolina","otherGeospatial":"Upper Floridan aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.28440856933594,\n 31.983035484210404\n ],\n [\n -80.72685241699217,\n 31.983035484210404\n ],\n [\n -80.72685241699217,\n 32.29525895520317\n ],\n [\n -81.28440856933594,\n 32.29525895520317\n ],\n [\n -81.28440856933594,\n 31.983035484210404\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Self-Trail, Jean 0000-0002-3018-4985 jstrail@usgs.gov","orcid":"https://orcid.org/0000-0002-3018-4985","contributorId":147370,"corporation":false,"usgs":true,"family":"Self-Trail","given":"Jean","email":"jstrail@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":760292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Mercer 0000-0001-6683-6458 mercerparker@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-6458","contributorId":203174,"corporation":false,"usgs":true,"family":"Parker","given":"Mercer","email":"mercerparker@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":760293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haynes, John T.","contributorId":197407,"corporation":false,"usgs":false,"family":"Haynes","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":760294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Arthur P.","contributorId":212837,"corporation":false,"usgs":false,"family":"Schultz","given":"Arthur P.","affiliations":[],"preferred":false,"id":760295,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huddleston, Paul. F.","contributorId":214584,"corporation":false,"usgs":false,"family":"Huddleston","given":"Paul.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":760296,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202853,"text":"70202853 - 2019 - Lakes as paleoseismic records in a seismically-active, low-relief area (Rieti Basin, central Italy)","interactions":[],"lastModifiedDate":"2019-06-18T11:14:23","indexId":"70202853","displayToPublicDate":"2019-03-29T09:47:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Lakes as paleoseismic records in a seismically-active, low-relief area (Rieti Basin, central Italy)","docAbstract":"Small lakes in low relief areas are atypical candidates for studies on paleoseismicity, but their sediments can contain seismically induced event layers (seismites) generated through strong ground shaking, sediment transport, hydrological reorganization and/or changes in groundwater chemistry and flow. Lakes Lungo and Ripasottile are shallow lakes (<10m deep) located in the tectonically active Rieti Basin in the central Apennines, Italy, where strong normal faulting earthquakes (Mw 6.5 to 7.0) regularly occur. Sediment cores from these lakes provide paleoseismic indicators for the past ~1000 years. Sedimentological and geochemical analysis reveals four event layers identified in both lakes that correspond with documented large-scale earthquakes in 1298, 1349, 1639, and 1703 AD. Chronological correlation between earthquakes and possible seismites is reliable because of the unusually high resolution of sediment dating available for the studied cores. The common physical structure is a physically homogenous bed (homogenite) of re-suspended sediment consisting of a denser, high magnetic susceptibility (MS) clastic base, with organic matter concentrated above. Chemical signatures are associated with some event layers and may represent abrupt or transient shifts to a groundwater-dominated system, or permanent changes in groundwater flow and/or spring discharge. Excursions in δ13Corg may represent disruptions or changes in carbon source. Not all event layers show the same features, a result attributed to differences in seismic processes as well as the lake attributes, and anthropogenic modification. The observations made here may provide a new means of detecting paleoseismicity and may be applied to other low relief lakes in seismically active areas.","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2019.03.004","usgsCitation":"Archer, C., Noble, P., Rosen, M.R., Sagnotti, L., Fiorindo, F., Piovesan, G., Mensing, S., and Michetti, A., 2019, Lakes as paleoseismic records in a seismically-active, low-relief area (Rieti Basin, central Italy): Quaternary Science Reviews, v. 211, p. 186-207, https://doi.org/10.1016/j.quascirev.2019.03.004.","productDescription":"22 p.","startPage":"186","endPage":"207","ipdsId":"IP-098465","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2019.03.004","text":"Publisher Index Page"},{"id":362567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","otherGeospatial":"Rieti Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 12.677536010742188,\n 42.30727643850873\n ],\n [\n 13.454132080078125,\n 42.30727643850873\n ],\n [\n 13.454132080078125,\n 42.628906895633456\n ],\n [\n 12.677536010742188,\n 42.628906895633456\n ],\n [\n 12.677536010742188,\n 42.30727643850873\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"211","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Archer, Claire","contributorId":198952,"corporation":false,"usgs":false,"family":"Archer","given":"Claire","email":"","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":760267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noble, Paula","contributorId":198953,"corporation":false,"usgs":false,"family":"Noble","given":"Paula","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":760268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sagnotti, Leonardo","contributorId":214577,"corporation":false,"usgs":false,"family":"Sagnotti","given":"Leonardo","email":"","affiliations":[{"id":39077,"text":"National Institute of Geophysics and Volcanology; Rome, Italy","active":true,"usgs":false}],"preferred":false,"id":760269,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fiorindo, Fabio","contributorId":214578,"corporation":false,"usgs":false,"family":"Fiorindo","given":"Fabio","email":"","affiliations":[{"id":39077,"text":"National Institute of Geophysics and Volcanology; Rome, Italy","active":true,"usgs":false}],"preferred":false,"id":760270,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piovesan, Gianluca","contributorId":198957,"corporation":false,"usgs":false,"family":"Piovesan","given":"Gianluca","email":"","affiliations":[{"id":35390,"text":"Tuscia University","active":true,"usgs":false}],"preferred":false,"id":760271,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mensing, Scott","contributorId":198958,"corporation":false,"usgs":false,"family":"Mensing","given":"Scott","affiliations":[{"id":33212,"text":"Department of Geography, University of NV","active":true,"usgs":false}],"preferred":false,"id":760273,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Michetti, Alessandro 0000-0002-1775-1340","orcid":"https://orcid.org/0000-0002-1775-1340","contributorId":206792,"corporation":false,"usgs":false,"family":"Michetti","given":"Alessandro","email":"","affiliations":[{"id":37402,"text":"Università degli Studi dell’Insubria","active":true,"usgs":false}],"preferred":false,"id":760272,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202570,"text":"70202570 - 2019 - Wetland drying linked to variations in snowmelt runoff across Grand Teton and Yellowstone national parks","interactions":[],"lastModifiedDate":"2019-03-28T13:27:57","indexId":"70202570","displayToPublicDate":"2019-03-28T13:25:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Wetland drying linked to variations in snowmelt runoff across Grand Teton and Yellowstone national parks","docAbstract":"In Grand Teton and Yellowstone national parks wetlands offer critical habitat and play a key role in supporting biological diversity. The shallow depths and small size of many wetlands make them vulnerable to changes in climate compared with larger and deeper aquatic habitats. Here, we use a simple water balance model to generate estimates of biophysical drivers of wetland change. We then examine the relationship between wetland inundation status and four principal drivers (i.e., temperature, precipitation, evapotranspiration, and runoff) spanning varying meteorological conditions over an 8-year time series from Grand Teton and Yellowstone national parks. We found that a higher percentage of surveyed wetlands were dry in years characterized by lower snowmelt runoff. While runoff-based models were most supported, wetland drying was also related to variations in April to June precipitation and temperatures. Our work shows that wetland drying was widespread across both parks, but sub-regional variations were best described at the hydrologic subbasin-level. Documenting the varying responses of wetlands to meteorological drivers is a necessary first step to identifying which subbasins are most sensitive to recent change and contemplating how future change may alter the distribution of wetlands and their dependent taxa.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.02.296","usgsCitation":"Ray, A.M., Sepulveda, A.J., Irvine, K.M., Wilmoth, S.K., Thoma, D.P., and Patla, D.A., 2019, Wetland drying linked to variations in snowmelt runoff across Grand Teton and Yellowstone national parks: Science of the Total Environment, v. 666, p. 1188-1197, https://doi.org/10.1016/j.scitotenv.2019.02.296.","productDescription":"10 p.","startPage":"1188","endPage":"1197","ipdsId":"IP-097789","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":460429,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.02.296","text":"Publisher Index Page"},{"id":362508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United states","state":"Idaho, Montana, Wyoming","otherGeospatial":"Grand Teton National Park, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.642822265625,\n 43.32517767999296\n ],\n [\n -108.8525390625,\n 43.35713822211053\n ],\n [\n -108.86352539062499,\n 45.460130637921004\n ],\n [\n -112.642822265625,\n 45.51404592560424\n ],\n [\n -112.642822265625,\n 43.32517767999296\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"666","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ray, Andrew M.","contributorId":167601,"corporation":false,"usgs":false,"family":"Ray","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":759146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":759145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":759147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilmoth, Siri K.C.","contributorId":214102,"corporation":false,"usgs":false,"family":"Wilmoth","given":"Siri","email":"","middleInitial":"K.C.","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":759148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thoma, David P.","contributorId":197256,"corporation":false,"usgs":false,"family":"Thoma","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":759149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Patla, Debra A.","contributorId":214103,"corporation":false,"usgs":false,"family":"Patla","given":"Debra","email":"","middleInitial":"A.","affiliations":[{"id":38924,"text":"Northern Rockies Conservation Cooperative","active":true,"usgs":false}],"preferred":false,"id":759150,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222523,"text":"70222523 - 2019 - Snowmelt-triggered earthquake swarms at the margin of Long Valley Caldera, California","interactions":[],"lastModifiedDate":"2021-08-03T13:08:55.847945","indexId":"70222523","displayToPublicDate":"2019-03-22T08:02:54","publicationYear":"2019","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":"Snowmelt-triggered earthquake swarms at the margin of Long Valley Caldera, California","docAbstract":"Fluids are well known to influence earthquakes, yet rarely are earthquakes convincingly linked to precipitation. Weak modulation or limited data often leads to ambiguous interpretations. In contrast, here we find that shallow seismicity in the Sierra Nevada range near Long Valley Caldera is strongly modulated by snowmelt. Over 33 years, shallow seismicity rates were ~37 times higher during very wet periods versus very dry periods. Relative earthquake relocations from a swarm in 2017 reveal downward migration from ~1- to 3-km depth along a steeply inclined plane. Steeply dipping strata may provide high-permeability pathways and faulting plane. Here we combine the correlated seismicity and hydrologic time series with the propagation observed in the relatively relocated earthquakes. From this combined evidence, we infer that pressure diffusion from groundwater recharge dramatically accelerated shallow seismicity rates, causing seismic swarms unrelated to volcanic processes.
The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a network of monitoring stations on streams and springs throughout Missouri known as the Ambient Water-Quality Monitoring Network. During water year 2017 (October 1, 2016, through September 30, 2017), data presented in this report were collected at 72 stations: 70 Ambient Water-Quality Monitoring Network stations and 2 U.S. Geological Survey National Stream Quality Assessment Network stations. Among the 72 stations in this report, 4 stations have data presented from additional sampling performed in cooperation with the U.S. Army Corps of Engineers. Summaries of the concentrations of dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and selected pesticide compounds are presented. Most of the stations have been classified based on the physiographic province or primary land use in the watershed represented by the station. Some stations have been classified based on the unique hydrology of the waterbodies they monitor. A summary of hydrologic conditions in the State including peak streamflows, monthly mean streamflows, and 7-day low flows also are presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1108","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Barr, M.N., and Bartels, K.A., 2019, Quality of surface water in Missouri, water year 2017: U.S. Geological Survey Data Series 1108, 25 p., https://doi.org/10.3133/ds1108.","productDescription":"v, 24 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-101659","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":362075,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1108/coverthb.jpg"},{"id":362076,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1108/ds1108.pdf","text":"Report","size":"2.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1108"}],"country":"United 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\"}}]}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Recent increases in earthquake occurrence rates in Oklahoma have been linked to the injection of large volumes of saltwater, a byproduct of oil and gas extraction. Here we present a detailed study of remote earthquake triggering in an area of active injection‐induced seismicity in northern Oklahoma using data from the LArge‐n Seismic Survey in Oklahoma (LASSO) temporary array and nearby permanent broadband seismic stations. We estimate changes in earthquake rates and calculate the Coulomb failure stress changes on potential receiver faults due to passing teleseismic surface waves. A statistically significant increase in seismicity is observed ∼8 hr after the 16 April 2016 Mw 7.8 Ecuador earthquake. The Coulomb stress changes associated with the Ecuador earthquake are on the order of ∼1 kPa. Physical mechanisms consistent with the observed dynamic stress threshold include failure driven by activation of aseismic slip or hydrological response of the fault system.
Mercury monitoring results from about 300 Morone saxatilis (striped bass) muscle tissue samples collected by the State of Utah from Lake Powell resulted in a Utah/Arizona fish consumption advisory issued in 2012 for approximately the lower 100 kilometers of the reservoir. Chemical, physical, and biological data were collected during two synoptic sampling cruises on Lake Powell during May/June 2014 and August 2015 to test three hypotheses associated with a conceptual model developed to explain the observed geographic concentration gradient of Hg in fish tissue samples. This model proposes that in the transition from a primarily riverine system to a reservoir, there is a change in the concentration and composition of water-column particulate material, increasing in the proportion of organic content moving downstream, as the larger size fractions of the inorganic particulate load are deposited in the upper reservoir. This change alleviates light limitation of phytoplankton production and leads to a higher proportion of autochthonous primary production in the downstream direction. This, in turn, drives increased microbial methylmercury (MeHg) production in the benthos and potentially the water column, in the downstream direction, and results in the observed elevated fish Hg levels in the lower part of the reservoir. The model also proposes that there are differences between the main stem of Lake Powell and side canyons, embayments, or secondary rivers entering the reservoir, in terms of Hg cycling dynamics and bioaccumulations, driven mainly by differences in hydrology. Finally, seasonal differences in Hg dynamics within the reservoir are proposed, based on seasonal dynamics associated with primary production and the physical process of seasonal stratification.
A total of three statistically testable hypotheses were proposed and postulated that measurable differences in key Hg and non-Hg metrics exist between: (1) the upper and lower reservoir; (2) main stem and river arm/side canyon/embayment sites; and (3) early-season (May/June 2014, less stratified) and late-season (August 2015, stratified) conditions. Statistically modeled least square means in combination with the graphical analysis of Hg and non-Hg parameters were used to examine the data collected during the study and test these hypotheses. Data collected during the study are included in a U.S. Geological Survey data release and are available online at https://doi.org/10.5066/F74X560J.
In general, water-column, plankton, and surface sediment samples collected during the synoptic sampling cruises are supportive of the three hypotheses associated with the conceptual model. In support of hypothesis 1 (comparing upper and lower reservoir sites), the least square mean for turbidity was higher in the upper reservoir. In contrast, surface water particulate organic carbon (as a percentage of total particulate mass), particulate MeHg (by mass [in nanograms per gram] and as a percentage of total mercury [THg]), and particulate-dissolved partitioning coefficients for THg and MeHg were higher in the lower reservoir. Plankton THg concentrations also were significantly (probability [p] less than (<) 0.05) higher in the lower reservoir. Surface sediment metrics in support of hypothesis 1 include higher MeHg production potential rates in the lower reservoir. In contrast, there were no statistically significant differences between the upper and lower reservoir for surface sediment percent of MeHg and MeHg concentration, percent MeHg, or methylation rate constants. These spatial trends associated with hypothesis 1 indicate a pathway for enhanced Hg bioavailability in the lower reservoir.
Hypothesis 2, which tested for differences between main stem and river arm/side canyon/embayment sites, was supported by a number of water-column parameters, including particulate THg and MeHg concentrations by mass (in nanograms per gram) and percent particulate MeHg being significantly (p<0.05) higher in the river arms, side canyons, and embayments relative to the main stem channel. Plankton MeHg concentrations (by mass [in nanograms per gram] and volume [in nanograms per liter] and as a percentage of THg) were elevated in river arm/side canyon/embayment sites compared to main stem sites, indicating an enhanced potential for MeHg bioaccumulation at the base of the pelagic food web in river arms, side canyons, and embayments. In contrast, few of the sediment metrics differed between main stem and river arm/side canyon/embayment sampling sites; however, the potential for MeHg degradation in surface sediment was significantly higher in the main stem. The data indicate that river arm/side canyon/embayment sites may experience enhanced Hg bioaccumulation, compared to the main stem, because of higher MeHg levels at the base of the pelagic food web. This conclusion is supported by the elevated Hg detected in striped bass muscle tissue samples collected in the San Juan Arm during this study (2014). Fish collected from the lower reservoir exhibited a distinct Hg isotopic signature that was enriched in delta (δ)202Hg and capital delta (Δ)199Hg relative to fish samples collected from either Good Hope Bay or the San Juan Arm.
Hypothesis 3 tested for differences between early (May/June) high-flow and late (August) low-flow seasons. This test was supported by a range of non-Hg metrics (nitrate, phosphate, chlorophyll a, dissolved oxygen, fluorescent dissolved organic matter, temperature, and pH) that reflect the increase in chlorophyll a, decrease in nutrients, and buildup of stratified conditions in the transition from early- to late-season sampling periods. Significant seasonal differences also were noted for multiple Hg metrics, including (a) water-column filtered and particulate (by mass) MeHg and THg concentrations; (b) plankton MeHg and THg concentration (by mass); and (c) sediment percent MeHg, Hg(II)-methylation rate constant, and microbial ribosomal ribonucleic acid, small subunit 16 (16S rRNA) abundance, all of which were higher during the late-season synoptic sampling. Overall, the surface sediment metrics are consistent with a seasonal shift from the early-season synoptic results, when the availability of Hg(II) exerts a primary control on MeHg production, to the late-season synoptic sampling, when microbial activity is a dominant driver of MeHg production.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181159","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Naftz, D.L., Marvin-DiPasquale, M., Krabbenhoft, D.P., Aiken, G., Boyd, E.S., Conaway, C.H., Ogorek, J., and Anderson, G.M., 2019, Biogeochemical and physical processes controlling mercury methylation and bioaccumulation in Lake Powell, Glen Canyon National Recreation Area, Utah and Arizona, 2014 and 2015: U.S. Geological Survey Open-File Report 2018–1159, 81 p., https://doi.org/10.3133/ofr20181159.","productDescription":"Report: xi, 81 p.; Data Release","numberOfPages":"98","onlineOnly":"Y","ipdsId":"IP-095917","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":359576,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1159/coverthb.jpg"},{"id":359577,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1159/ofr20181159.pdf","text":"Report","size":"9.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1159"},{"id":359578,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74X560J","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for Biogeochemical and Physical Processes Controlling Mercury Methylation and Bioaccumulation in Lake Powell, Glen Canyon National Recreation Area, Utah and Arizona, 2014–2015"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"Glen Canyon, Lake Powell","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.63551330566406,\n 36.75594019674357\n ],\n [\n -111.14044189453124,\n 36.75594019674357\n ],\n [\n -111.14044189453124,\n 37.020646433887805\n ],\n [\n -111.63551330566406,\n 37.020646433887805\n ],\n [\n -111.63551330566406,\n 36.75594019674357\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle West
Valley City, UT 84119
About one-quarter of the water supply for the Village of Ruidoso, New Mexico, is derived from groundwater pumping along North Fork Eagle Creek in the Eagle Creek Basin near Alto, New Mexico. Because of concerns regarding the effects of groundwater pumping on surface-water hydrology in the Eagle Creek Basin and the effects of the 2012 Little Bear Fire, which resulted in substantial losses of vegetation in the basin, the monitoring of North Fork Eagle Creek for short-term geomorphic change has been required by the U.S. Department of Agriculture Forest Service, Lincoln National Forest, as part of the permitting decision that allows for the continued pumping of the production wells. The monitoring of short-term geomorphic change in North Fork Eagle Creek began in June 2017 with a geomorphic survey of the stream reach located between the North Fork Eagle Creek near Alto, New Mexico, streamflow-gaging station (USGS site 08387550) and the Eagle Creek below South Fork near Alto, New Mexico, streamflow-gaging station (USGS site 08387600). The 2017 geomorphic survey was conducted by the U.S. Geological Survey (USGS), in cooperation with the Village of Ruidoso, and was the first in a planned series of five annual geomorphic surveys. The results of the 2017 geomorphic survey are summarized and interpreted in this report and are provided in their entirety in its companion data release.
The study reach is 1.86 miles long, and large sections of the reach are characterized by intermittent streamflow. Where water is normally present (including at the upper and lower portions of the reach near the streamflow-gaging stations), the discharge typically remains below 2 cubic feet per second throughout the year. Therefore, if geomorphic change is to occur, it will likely be driven by seasonal high-flow events. Discharge records from streamflow-gaging stations in the Eagle Creek Basin indicated that high-flow events in the basin (with peaks above 50 cubic feet per second) typically occurred during the North American monsoon months of July, August, and September. Additionally, the records appear to indicate that, as expected, overland runoff and “flashy” responses to rainfall have increased in the 5 years since the 2012 Little Bear Fire.
For the 2017 geomorphic survey of North Fork Eagle Creek, cross sections were established and surveyed at 14 locations along the study reach. Cross-section survey results indicated that channel characteristics (including channel width and area) varied widely along the study reach. Also, as part of the survey, woody debris accumulations and pools in the channel of the study reach were identified, cataloged, photographed, and surveyed for location. There were 58 woody debris accumulations and 14 pools found in the study reach. On the basis that debris jams could be a driver of geomorphic change in North Fork Eagle Creek, woody debris accumulations were classified according to their debris jam potential. The burn marks found on some woody debris indicated that the 2012 Little Bear Fire may be a contributing factor to the volume of debris in North Fork Eagle Creek. However, the woody debris present at the time of the survey did not appear to have substantially affected the geomorphic state of the study reach. Further, the structure and composition of the woody debris accumulations indicated that, under high-flow conditions, most woody debris would likely be transported downstream and out of the study reach without causing substantial geomorphic change through further jamming.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181187","collaboration":"Prepared in cooperation with the Village of Ruidoso, New Mexico","usgsCitation":"Graziano, A.P., 2019, Geomorphic survey of North Fork Eagle Creek, New Mexico, 2017: U.S. Geological Survey Open-File Report 2018–1187, 28 p., https://doi.org/10.3133/ofr20181187.","productDescription":"Report: v., 28 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","ipdsId":"IP-093851","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":362041,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PR7TX3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data supporting the 2017 geomorphic survey of North Fork Eagle Creek, New Mexico"},{"id":362039,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1187/coverthb.jpg"},{"id":362040,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1187/ofr20181187.pdf","text":"Report","size":"18.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1187"}],"country":"United States","state":"New Mexico","otherGeospatial":"North Fork Eagle Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.98236083984375,\n 33.02939031998959\n ],\n [\n -104.98260498046875,\n 33.02939031998959\n ],\n [\n -104.98260498046875,\n 33.68549637289138\n ],\n [\n -105.98236083984375,\n 33.68549637289138\n ],\n [\n -105.98236083984375,\n 33.02939031998959\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd NE
Albuquerque, NM 87113
Digital flood-inundation maps for a 16.4-mile reach of the Yellow River in Gwinnett County, Georgia, from 0.5 mile upstream from River Drive to Centerville Highway (Georgia State Route 124) were developed to depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at two U.S. Geological Survey (USGS) streamgages in the mapped area. The maps for the 9.0-mile reach from 0.5 mile upstream from River Drive to Stone Mountain Highway (U.S. Route 78) are referenced to the streamgage Yellow River near Snellville, Ga. (station 02206500), and the maps for the 7.4-mile reach from Stone Mountain Highway to Centerville Highway are referenced to the streamgage Yellow River at Ga. 124, near Lithonia, Ga. (02207120). Real-time stage information from these streamgages can be used with these maps to estimate near real-time areas of inundation. The forecasted peak-stage information for the USGS streamgages Yellow River near Snellville, Ga. (02206500), and Yellow River at Ga. 124, near Lithonia, Ga. (02207120), can be used in conjunction with the maps developed for this study to show predicted areas of flood inundation.
A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers Hydrologic Engineering Center's River Analysis System (HEC–RAS) software for the Yellow River and was used to compute flood profiles for a 16.4-mile reach of the Yellow River. The hydraulic model was then used to simulate 16 water-surface profiles at 1.0-foot (ft) intervals at the Yellow River near Snellville streamgage and 17 water-surface profiles at 1.0-ft intervals at the Yellow River near Lithonia streamgage. At the Yellow River near Snellville streamgage, the profiles ranged from a stage of 18.0 ft, which is 819.1 ft above the North American Vertical Datum of 1988 (NAVD 88), to a stage of 33.0 ft, which is 834.1 ft above NAVD 88. At the Yellow River near Lithonia streamgage, the profiles ranged from the National Weather Service action stage of 13.0 ft, which is 732.5 ft above NAVD 88, to a stage of 29.0 ft, which is 748.5 ft above NAVD 88. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging (lidar) data having a 5.0-ft horizontal resolution—to delineate the area flooded at each 1.0-ft interval of stream stage for both streamgages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195009","collaboration":"Prepared in cooperation with Gwinnett County, Georgia","usgsCitation":"Musser, J.W., 2019, Flood-inundation maps for the Yellow River from River Drive to Centerville Highway, Gwinnett County, Georgia: U.S. Geological Survey Scientific Investigations Report 2019–5009, 15 p., https://doi.org/10.3133/sir20195009.","productDescription":"Report: vi, 15 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-100804","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":361975,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KKB3H2","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood inundation and flood depth for the Yellow River in Gwinnett County, Georgia based on water-surface elevation at the U.S. Geological Survey streamgages Yellow River, near Snellville, Georgia (02206500) and Yellow River at Ga. 124, near Lithonia, Georgia (02207120)"},{"id":361973,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5009/coverthb.jpg"},{"id":361974,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5009/sir20195009.pdf","text":"Report","size":"1.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5009"}],"country":"United States","state":"Georgia","county":"Gwinnett County","otherGeospatial":"Yellow River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.1667,\n 33.75\n ],\n [\n -84,\n 33.75\n ],\n [\n -84,\n 33.9167\n ],\n [\n -84.1667,\n 33.9167\n ],\n [\n -84.1667,\n 33.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210