Geographic Information Systems (GIS) layers of current, and likely former, tidal wetlands in two Oregon estuaries were generated by enhancing the 2010 National Wetlands Inventory (NWI) data with expert local field knowledge, Light Detection and Ranging-derived elevations, and 2009 aerial orthophotographs. Data were generated for two purposes: First, to enhance the NWI by recommending revised Cowardin classifications for certain NWI wetlands within the study area; and second, to generate GIS data for the 1999 Yaquina and Alsea River Basins Estuarine Wetland Site Prioritization study. Two sets of GIS products were generated: (1) enhanced NWI shapefiles; and (2) shapefiles of prioritization sites. The enhanced NWI shapefiles contain recommended changes to the Cowardin classification (system, subsystem, class, and/or modifiers) for 286 NWI polygons in the Yaquina estuary (1,133 acres) and 83 NWI polygons in the Alsea estuary (322 acres). These enhanced NWI shapefiles also identify likely former tidal wetlands that are classified as upland in the current NWI (64 NWI polygons totaling 441 acres in the Yaquina estuary; 16 NWI polygons totaling 51 acres in the Alsea estuary). The former tidal wetlands were identified to assist strategic planning for tidal wetland restoration. Cowardin classifications for the former tidal wetlands were not provided, because their current hydrology is complex owing to dikes, tide gates, and drainage ditches. The scope of this project did not include the field evaluation that would be needed to determine whether the former tidal wetlands are currently wetlands, and if so, determine their correct Cowardin classification. The prioritization site shapefiles contain 49 prioritization sites totaling 2,177 acres in the Yaquina estuary, and 39 prioritization sites totaling 1,045 acres in the Alsea estuary. The prioritization sites include current and former (for example, diked) tidal wetlands, and provide landscape units appropriate for basin-scale wetland restoration and conservation action planning. Several new prioritization sites (not included in the 1999 prioritization) were identified in each estuary, consisting of NWI polygons formerly classified as nontidal wetland or upland. The GIS products of this project improve the accuracy and utility of the NWI data, and provide useful tools for estuarine resource management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121038","collaboration":"Prepared in cooperation with Green Point Consulting and the U.S. Environmental Protection Agency","usgsCitation":"Brophy, L.S., Reusser, D.A., and Janousek, C.N., 2013, Tidal wetlands of the Yaquina and Alsea River estuaries, Oregon: Geographic Information Systems layer development and recommendations for National Wetlands Inventory revisions: U.S. Geological Survey Open-File Report 2012-1038, vi, 60 p., https://doi.org/10.3133/ofr20121038.","productDescription":"vi, 60 p.","numberOfPages":"68","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":272177,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121038.gif"},{"id":272323,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1038/"},{"id":272176,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1038/pdf/ofr2012-1038.pdf","text":"Report","size":"18.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Oregon","otherGeospatial":"Yaquina And Alsea Estuaries","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.16,44.16 ], [ -124.16,44.5 ], [ -123.5,44.5 ], [ -123.5,44.16 ], [ -124.16,44.16 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518e08f7e4b05ebc8f7cc2de","contributors":{"authors":[{"text":"Brophy, Laura S.","contributorId":47266,"corporation":false,"usgs":false,"family":"Brophy","given":"Laura","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":478548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reusser, Deborah A. dreusser@usgs.gov","contributorId":2423,"corporation":false,"usgs":true,"family":"Reusser","given":"Deborah","email":"dreusser@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":547809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Janousek, Christopher N. 0000-0003-2124-6715","orcid":"https://orcid.org/0000-0003-2124-6715","contributorId":103951,"corporation":false,"usgs":false,"family":"Janousek","given":"Christopher","email":"","middleInitial":"N.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":478549,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045859,"text":"70045859 - 2013 - Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China","interactions":[],"lastModifiedDate":"2013-06-17T09:24:06","indexId":"70045859","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China","docAbstract":"Hydrological models have been increasingly used by hydrologists and water resource managers to understand natural processes and human activities that affect watersheds. In this study, we use the physically based model, Soil and Water Assessment Tool (SWAT), to investigate the hydrological processes in the East River Basin in South China, a coastal area dominated by monsoonal climate. The SWAT model was calibrated using 8-year (1973–1980) record of the daily streamflow at the basin outlet (Boluo station), and then validated using data collected during the subsequent 8 years (1981–1988). Statistical evaluation shows that SWAT can consistently simulate the streamflow of the East River with monthly Nash–Sutcliffe efficiencies of 0.93 for calibration and 0.90 for validation at the Boluo station. We analyzed the model simulations with calibrated parameters, presented the spatiotemporal distribution of the key hydrological components, and quantified their responses to different land uses. Watershed managers can use the results of this study to understand hydrological features and evaluate water resources of the East River in terms of sustainable development and effective management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00267-013-0045-5","usgsCitation":"Wu, Y., and Chen, J., 2013, Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China: Environmental Management, v. 51, no. 6, p. 1174-1186, https://doi.org/10.1007/s00267-013-0045-5.","productDescription":"13 p.","startPage":"1174","endPage":"1186","ipdsId":"IP-042191","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272012,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00267-013-0045-5"}],"country":"China","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 73.5,18.2 ], [ 73.5,53.6 ], [ 134.8,53.6 ], [ 134.8,18.2 ], [ 73.5,18.2 ] ] ] } } ] }","volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-04-23","publicationStatus":"PW","scienceBaseUri":"518a1451e4b061e1bd533337","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":478446,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045851,"text":"sir20135071 - 2013 - Continuous real-time water-quality monitoring and regression analysis to compute constituent concentrations and loads in the North Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999–2012","interactions":[],"lastModifiedDate":"2013-05-07T13:25:37","indexId":"sir20135071","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5071","title":"Continuous real-time water-quality monitoring and regression analysis to compute constituent concentrations and loads in the North Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999–2012","docAbstract":"Cheney Reservoir, located in south-central Kansas, is the primary water supply for the city of Wichita. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station since 1998 on the North Fork Ninnescah River, the main source of inflow to Cheney Reservoir. Continuously measured water-quality physical properties include streamflow, specific conductance, pH, water temperature, dissolved oxygen, and turbidity. Discrete water-quality samples were collected during 1999 through 2009 and analyzed for sediment, nutrients, bacteria, and other water-quality constituents. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to compute concentrations of those constituents of interest that are not easily measured in real time because of limitations in sensor technology and fiscal constraints. Regression models were published in 2006 that were based on data collected during 1997 through 2003. This report updates those models using discrete and continuous data collected during January 1999 through December 2009. Models also were developed for four new constituents, including additional nutrient species and indicator bacteria. In addition, a conversion factor of 0.68 was established to convert the Yellow Springs Instruments (YSI) model 6026 turbidity sensor measurements to the newer YSI model 6136 sensor at the North Ninnescah River upstream from Cheney Reservoir site. Newly developed models and 14 years of hourly continuously measured data were used to calculate selected constituent concentrations and loads during January 1999 through December 2012. The water-quality information in this report is important to the city of Wichita because it allows the concentrations of many potential pollutants of interest to Cheney Reservoir, including nutrients and sediment, to be estimated in real time and characterized over conditions and time scales that would not be possible otherwise. In general, model forms and the amount of variance explained by the models was similar between the original and updated models. The amount of variance explained by the updated models changed by 10 percent or less relative to the original models. Total nitrogen, nitrate, organic nitrogen, E. coli bacteria, and total organic carbon models were newly developed for this report. Additional data collection over a wider range of hydrological conditions facilitated the development of these models. The nitrate model is particularly important because it allows for comparison to Cheney Reservoir Task Force goals. Mean hourly computed total suspended solids concentration during 1999 through 2012 was 54 milligrams per liter (mg/L). The total suspended solids load during 1999 through 2012 was 174,031 tons. On an average annual basis, the Cheney Reservoir Task Force runoff (550 mg/L) and long-term (100 mg/L) total suspended solids goals were never exceeded, but the base flow goal was exceeded every year during 1999 through 2012. Mean hourly computed nitrate concentration was 1.08 mg/L during 1999 through 2012. The total nitrate load during 1999 through 2012 was 1,361 tons. On an annual average basis, the Cheney Reservoir Task Force runoff (6.60 mg/L) nitrate goal was never exceeded, the long-term goal (1.20 mg/L) was exceeded only in 2012, and the base flow goal of 0.25 mg/L was exceeded every year. Mean nitrate concentrations that were higher during base flow, rather than during runoff conditions, suggest that groundwater sources are the main contributors of nitrate to the North Fork Ninnescah River above Cheney Reservoir. Mean hourly computed phosphorus concentration was 0.14 mg/L during 1999 through 2012. The total phosphorus load during 1999 through 2012 was 328 tons. On an average annual basis, the Cheney Reservoir Task Force runoff goal of 0.40 mg/L for total phosphorus was exceeded in 2002, the year with the largest yearly mean turbidity, and the long-term goal (0.10 mg/L) was exceeded in every year except 2011 and 2012, the years with the smallest mean streamflows. The total phosphorus base flow goal of 0.05 mg/L was exceeded every year. Given that base flow goals for total suspended solids, nitrate, and total phosphorus were exceeded every year despite hydrologic conditions, the established base flow goals are either unattainable or substantially more best management practices will need to be implemented to attain them. On an annual average basis, no discernible patterns were evident in total suspended sediment, nitrate, and total phosphorus concentrations or loads over time, in large part because of hydrologic variability. However, more rigorous statistical analyses are required to evaluate temporal trends. A more rigorous analysis of temporal trends will allow evaluation of watershed investments in best management practices.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135071","collaboration":"Prepared in cooperation with the city of Wichita, Kansas","usgsCitation":"Stone, M.L., Graham, J.L., and Gatotho, J.W., 2013, Continuous real-time water-quality monitoring and regression analysis to compute constituent concentrations and loads in the North Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999–2012: U.S. Geological Survey Scientific Investigations Report 2013-5071, viii, 46 p., https://doi.org/10.3133/sir20135071.","productDescription":"viii, 46 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":272007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135071.gif"},{"id":272005,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5071/"},{"id":272006,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5071/sir13-5071.pdf"}],"country":"United States","state":"Kansas","otherGeospatial":"Cheney Reservoir;North Fork Ninnescah River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.25,37.5 ], [ -99.25,38.16 ], [ -97.75,38.16 ], [ -97.75,37.5 ], [ -99.25,37.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145be4b061e1bd53333b","contributors":{"authors":[{"text":"Stone, Mandy L. 0000-0002-6711-1536 mstone@usgs.gov","orcid":"https://orcid.org/0000-0002-6711-1536","contributorId":4409,"corporation":false,"usgs":true,"family":"Stone","given":"Mandy","email":"mstone@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":478424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gatotho, Jackline W.","contributorId":76616,"corporation":false,"usgs":true,"family":"Gatotho","given":"Jackline","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":478425,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045856,"text":"70045856 - 2013 - Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China","interactions":[],"lastModifiedDate":"2013-05-07T14:25:21","indexId":"70045856","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China","docAbstract":"Understanding the physical processes of point source (PS) and nonpoint source (NPS) pollution is critical to evaluate river water quality and identify major pollutant sources in a watershed. In this study, we used the physically-based hydrological/water quality model, Soil and Water Assessment Tool, to investigate the influence of PS and NPS pollution on the water quality of the East River (Dongjiang in Chinese) in southern China. Our results indicate that NPS pollution was the dominant contribution (>94%) to nutrient loads except for mineral phosphorus (50%). A comprehensive Water Quality Index (WQI) computed using eight key water quality variables demonstrates that water quality is better upstream than downstream despite the higher level of ammonium nitrogen found in upstream waters. Also, the temporal (seasonal) and spatial distributions of nutrient loads clearly indicate the critical time period (from late dry season to early wet season) and pollution source areas within the basin (middle and downstream agricultural lands), which resource managers can use to accomplish substantial reduction of NPS pollutant loadings. Overall, this study helps our understanding of the relationship between human activities and pollutant loads and further contributes to decision support for local watershed managers to protect water quality in this region. In particular, the methods presented such as integrating WQI with watershed modeling and identifying the critical time period and pollutions source areas can be valuable for other researchers worldwide.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2013.04.002","usgsCitation":"Wu, Y., and Chen, J., 2013, Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China: Ecological Indicators, v. 32, p. 294-304, https://doi.org/10.1016/j.ecolind.2013.04.002.","productDescription":"11 p.","startPage":"294","endPage":"304","ipdsId":"IP-044856","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272011,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2013.04.002"}],"country":"China","otherGeospatial":"Dongjiang","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 73.5,18.2 ], [ 73.5,53.6 ], [ 134.8,53.6 ], [ 134.8,18.2 ], [ 73.5,18.2 ] ] ] } } ] }","volume":"32","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145be4b061e1bd53333f","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":478441,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045855,"text":"70045855 - 2013 - Parallelization of a hydrological model using the message passing interface","interactions":[],"lastModifiedDate":"2013-05-07T14:33:07","indexId":"70045855","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Parallelization of a hydrological model using the message passing interface","docAbstract":"With the increasing knowledge about the natural processes, hydrological models such as the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with increasing computation time. Additionally, other procedures such as model calibration, which may require thousands of model iterations, can increase running time and thus further reduce rapid modeling and analysis. Using the widely-applied SWAT as an example, this study demonstrates how to parallelize a serial hydrological model in a Windows® environment using a parallel programing technology—Message Passing Interface (MPI). With a case study, we derived the optimal values for the two parameters (the number of processes and the corresponding percentage of work to be distributed to the master process) of the parallel SWAT (P-SWAT) on an ordinary personal computer and a work station. Our study indicates that model execution time can be reduced by 42%–70% (or a speedup of 1.74–3.36) using multiple processes (two to five) with a proper task-distribution scheme (between the master and slave processes). Although the computation time cost becomes lower with an increasing number of processes (from two to five), this enhancement becomes less due to the accompanied increase in demand for message passing procedures between the master and all slave processes. Our case study demonstrates that the P-SWAT with a five-process run may reach the maximum speedup, and the performance can be quite stable (fairly independent of a project size). Overall, the P-SWAT can help reduce the computation time substantially for an individual model run, manual and automatic calibration procedures, and optimization of best management practices. In particular, the parallelization method we used and the scheme for deriving the optimal parameters in this study can be valuable and easily applied to other hydrological or environmental models.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modelling and Software","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2013.02.002","usgsCitation":"Wu, Y., Li, T., Sun, L., and Chen, J., 2013, Parallelization of a hydrological model using the message passing interface: Environmental Modelling and Software, v. 43, p. 124-132, https://doi.org/10.1016/j.envsoft.2013.02.002.","productDescription":"9 p.","startPage":"124","endPage":"132","ipdsId":"IP-044027","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272010,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envsoft.2013.02.002"}],"volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145de4b061e1bd533347","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Tiejian","contributorId":25437,"corporation":false,"usgs":true,"family":"Li","given":"Tiejian","email":"","affiliations":[],"preferred":false,"id":478438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Liqun","contributorId":18249,"corporation":false,"usgs":true,"family":"Sun","given":"Liqun","email":"","affiliations":[],"preferred":false,"id":478437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":478439,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045769,"text":"sir20135084 - 2013 - Groundwater conditions in Georgia, 2010–2011","interactions":[],"lastModifiedDate":"2017-01-17T20:46:02","indexId":"sir20135084","displayToPublicDate":"2013-05-03T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5084","title":"Groundwater conditions in Georgia, 2010–2011","docAbstract":"The U.S. Geological Survey collects groundwater data and conducts studies to monitor hydrologic conditions, better define groundwater resources, and address problems related to water supply, water use, and water quality. In Georgia, water levels were monitored continuously at 186 wells during calendar year 2010 and at 181 wells during calendar year 2011. Because of missing data or short periods of record (less than 3 years) for several of these wells, a total of 168 wells are discussed in this report. These wells include 17 in the surficial aquifer system, 19 in the Brunswick aquifer system and equivalent sediments, 70 in the Upper Floridan aquifer, 16 in the Lower Floridan aquifer and underlying units, 10 in the Claiborne aquifer, 1 in the Gordon aquifer, 11 in the Clayton aquifer, 14 in the Cretaceous aquifer system, 2 in Paleozoic-rock aquifers, and 8 in crystalline-rock aquifers. Data from the well network indicate that water levels generally declined during the 2010 through 2011 calendar-year period, with water levels declining in 158 wells and rising in 10. Water levels declined over the period of record at 106 wells, increased at 56 wells, and remained relatively constant at 6 wells. In addition to continuous water-level data, periodic water-level measurements were collected and used to construct potentiometric-surface maps for the Upper Floridan aquifer in Camden, Charlton, and Ware Counties, Georgia, and adjacent counties in Florida during May–June 2010, and in the following areas in Georgia: the Brunswick area during August 2010 and August 2011, in the Albany–Dougherty County area during November 2010 and November 2011, and in the Augusta–Richmond County area during October 2010 and August 2011. In general, water levels in these areas were lower during 2011 than during 2010; however, the configuration of the potentiometric surfaces in each of the areas showed little change. Groundwater quality in the Floridan aquifer system is monitored in the Albany, Savannah, and Brunswick areas of Georgia. In the Albany area, nitrate as nitrogen concentrations in the Upper Floridan aquifer during 2011 generally decreased from 2010; however, concentrations in two wells remained above the U.S. Environmental Protection Agency (USEPA) 10-milligrams-per-liter (mg/L) drinking-water standard. In the Savannah area, specific conductance and chloride concentrations were measured in water samples from discrete depths in two wells completed in the Upper Floridan aquifer. Data from the two wells indicate that chloride concentrations in the Upper Floridan aquifer showed little change during calendar years 2010 through 2011 and remained below the 250 mg/L USEPA secondary drinking-water standard. During calendar years 2010 through 2011, chloride concentrations in the Lower Floridan aquifer increased slightly at Tybee Island and Skidaway Island, remaining above the drinking-water standard. In the Brunswick area, maps showing the chloride concentration of water in the Upper Floridan aquifer constructed using data collected from 32 wells during August 2010 and from 30 wells during August 2011 indicate that chloride concentrations remained above the USEPA secondary drinking-water standard in an approximately 2-square-mile area. During calendar years 2010 through 2011, chloride concentrations generally decreased in over 70 percent of the wells sampled during 2011, with a maximum decrease of 200 mg/L in a well located in the north-central part of the Brunswick area.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135084","usgsCitation":"Peck, M., Gordon, D., and Painter, J.A., 2013, Groundwater conditions in Georgia, 2010–2011: U.S. Geological Survey Scientific Investigations Report 2013-5084, iv, 65 p., https://doi.org/10.3133/sir20135084.","productDescription":"iv, 65 p.","numberOfPages":"71","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135084.gif"},{"id":271796,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5084/"},{"id":271797,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5084/pdf/sir2013-5084.pdf"}],"country":"United States","state":"Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.640625,\n 43.34116005412307\n ],\n [\n -76.640625,\n 44.85586880735725\n ],\n [\n -72.97119140625,\n 44.85586880735725\n ],\n [\n -72.97119140625,\n 43.34116005412307\n ],\n [\n -76.640625,\n 43.34116005412307\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.562255859375,\n 33.96158628979907\n ],\n [\n -82.430419921875,\n 33.87041555094183\n ],\n [\n -82.210693359375,\n 33.779147331286474\n ],\n [\n -82.1337890625,\n 33.660353121928814\n ],\n [\n -82.210693359375,\n 33.62376800118811\n ],\n [\n -82.056884765625,\n 33.55055114384406\n ],\n [\n -81.925048828125,\n 33.44977658311846\n ],\n [\n -81.93603515625,\n 33.358061612778876\n ],\n [\n -81.84814453125,\n 33.293803558346596\n ],\n [\n -81.7822265625,\n 33.211116472416855\n ],\n [\n -81.705322265625,\n 33.17434155100208\n ],\n [\n -81.6064453125,\n 33.100745405144245\n ],\n [\n -81.54052734375,\n 33.04550781490999\n ],\n [\n -81.463623046875,\n 32.90726224488304\n ],\n [\n -81.441650390625,\n 32.80574473290688\n ],\n [\n -81.4306640625,\n 32.69486597787505\n ],\n [\n -81.34277343749999,\n 32.61161640317033\n ],\n [\n -81.298828125,\n 32.54681317351514\n ],\n [\n -81.1669921875,\n 32.43561304116276\n ],\n [\n -81.903076171875,\n 32.03602003973755\n ],\n [\n -83.1884765625,\n 31.82156451492074\n ],\n [\n -83.265380859375,\n 33.00866349457558\n ],\n [\n -82.96875,\n 33.50475906922609\n ],\n [\n -82.781982421875,\n 34.15272698011818\n ],\n [\n -82.6611328125,\n 34.125447565116126\n ],\n [\n -82.584228515625,\n 34.016241889667015\n ],\n [\n -82.562255859375,\n 33.96158628979907\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5184ce60e4b04d6ec94d6299","contributors":{"authors":[{"text":"Peck, Michael F. mfpeck@usgs.gov","contributorId":1467,"corporation":false,"usgs":true,"family":"Peck","given":"Michael F.","email":"mfpeck@usgs.gov","affiliations":[],"preferred":false,"id":478325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gordon, Debbie W. 0000-0002-5195-6657","orcid":"https://orcid.org/0000-0002-5195-6657","contributorId":79591,"corporation":false,"usgs":true,"family":"Gordon","given":"Debbie W.","affiliations":[],"preferred":false,"id":478326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Painter, Jaime A. 0000-0001-8883-9158 jpainter@usgs.gov","orcid":"https://orcid.org/0000-0001-8883-9158","contributorId":1466,"corporation":false,"usgs":true,"family":"Painter","given":"Jaime","email":"jpainter@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478324,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045740,"text":"70045740 - 2013 - Extending airborne electromagnetic surveys for regional active layer and permafrost mapping with remote sensing and ancillary data, Yukon Flats ecoregion, central Alaska","interactions":[],"lastModifiedDate":"2018-01-12T17:20:50","indexId":"70045740","displayToPublicDate":"2013-05-02T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3032,"text":"Permafrost and Periglacial Processes","active":true,"publicationSubtype":{"id":10}},"title":"Extending airborne electromagnetic surveys for regional active layer and permafrost mapping with remote sensing and ancillary data, Yukon Flats ecoregion, central Alaska","docAbstract":"Machine-learning regression tree models were used to extrapolate airborne electromagnetic resistivity data collected along flight lines in the Yukon Flats Ecoregion, central Alaska, for regional mapping of permafrost. This method of extrapolation (r = 0.86) used subsurface resistivity, Landsat Thematic Mapper (TM) at-sensor reflectance, thermal, TM-derived spectral indices, digital elevation models and other relevant spatial data to estimate near-surface (0–2.6-m depth) resistivity at 30-m resolution. A piecewise regression model (r = 0.82) and a presence/absence decision tree classification (accuracy of 87%) were used to estimate active-layer thickness (ALT) (< 101 cm) and the probability of near-surface (up to 123-cm depth) permafrost occurrence from field data, modelled near-surface (0–2.6 m) resistivity, and other relevant remote sensing and map data. At site scale, the predicted ALTs were similar to those previously observed for different vegetation types. At the landscape scale, the predicted ALTs tended to be thinner on higher-elevation loess deposits than on low-lying alluvial and sand sheet deposits of the Yukon Flats. The ALT and permafrost maps provide a baseline for future permafrost monitoring, serve as inputs for modelling hydrological and carbon cycles at local to regional scales, and offer insight into the ALT response to fire and thaw processes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Permafrost and Periglacial Processes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/ppp.1775","usgsCitation":"Pastick, N.J., Jorgenson, M., Wylie, B.K., Minsley, B.J., Ji, L., Walvoord, M.A., Smith, B.D., Abraham, J., and Rose, J.R., 2013, Extending airborne electromagnetic surveys for regional active layer and permafrost mapping with remote sensing and ancillary data, Yukon Flats ecoregion, central Alaska: Permafrost and Periglacial Processes, v. 24, no. 3, p. 184-199, https://doi.org/10.1002/ppp.1775.","productDescription":"16 p.","startPage":"184","endPage":"199","ipdsId":"IP-037584","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":271728,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ppp.1775"},{"id":271729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -149.55,65.47 ], [ -149.55,67.47 ], [ -142.43,67.47 ], [ -142.43,65.47 ], [ -149.55,65.47 ] ] ] } } ] }","volume":"24","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-04-29","publicationStatus":"PW","scienceBaseUri":"51837ce5e4b0a21483941a49","contributors":{"authors":[{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":478219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgenson, M. Torre","contributorId":40486,"corporation":false,"usgs":true,"family":"Jorgenson","given":"M. Torre","affiliations":[],"preferred":false,"id":478220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":478216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":478215,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":2832,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":478218,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walvoord, Michelle Ann 0000-0003-4269-8366 walvoord@usgs.gov","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":147211,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"walvoord@usgs.gov","middleInitial":"Ann","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":478223,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Bruce D. 0000-0002-1643-2997 bsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1643-2997","contributorId":845,"corporation":false,"usgs":true,"family":"Smith","given":"Bruce","email":"bsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":478217,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Abraham, Jared D.","contributorId":42630,"corporation":false,"usgs":true,"family":"Abraham","given":"Jared D.","affiliations":[],"preferred":false,"id":478221,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rose, Joshua R.","contributorId":90147,"corporation":false,"usgs":true,"family":"Rose","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":478222,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70042887,"text":"70042887 - 2013 - Short-term variability of 7Be atmospheric deposition and watershed response in a Pacific coastal stream, Monterey Bay, California, USA","interactions":[],"lastModifiedDate":"2013-05-10T10:30:22","indexId":"70042887","displayToPublicDate":"2013-05-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2263,"text":"Journal of Environmental Radioactivity","active":true,"publicationSubtype":{"id":10}},"title":"Short-term variability of 7Be atmospheric deposition and watershed response in a Pacific coastal stream, Monterey Bay, California, USA","docAbstract":"Beryllium-7 is a powerful and commonly used tracer for environmental processes such as watershed sediment provenance, soil erosion, fluvial and nearshore sediment cycling, and atmospheric fallout. However, few studies have quantified temporal or spatial variability of 7Be accumulation from atmospheric fallout, and parameters that would better define the uses and limitations of this geochemical tracer. We investigated the abundance and variability of 7Be in atmospheric deposition in both rain events and dry periods, and in stream surface-water samples collected over a ten-month interval at sites near northern Monterey Bay (37°N, 122°W) on the central California coast, a region characterized by a rainy winters, dry summers, and small mountainous streams with flashy hydrology. The range of 7Be activity in rainwater samples from the main sampling site was 1.3–4.4 Bq L−1, with a mean (±standard deviation) of 2.2 ± 0.9 Bq L−1, and a volume-weighted average of 2.0 Bq L−1. The range of wet atmospheric deposition was 18–188 Bq m−2 per rain event, with a mean of 72 ± 53 Bq m−2. Dry deposition fluxes of 7Be ranged from less than 0.01 up to 0.45 Bq m−2 d−1, with an estimated dry season deposition of 7 Bq m−2 month−1. Annualized 7Be atmospheric deposition was approximately 1900 Bq m−2 yr−1, with most deposition via rainwater (>95%) and little via dry deposition. Overall, these activities and deposition fluxes are similar to values found in other coastal locations with comparable latitude and Mediterranean-type climate. Particulate 7Be values in the surface water of the San Lorenzo River in Santa Cruz, California, ranged from <0.01 Bq g−1 to 0.6 Bq g−1, with a median activity of 0.26 Bq g−1. A large storm event in January 2010 characterized by prolonged flooding resulted in the entrainment of 7Be-depleted sediment, presumably from substantial erosion in the watershed. There were too few particulate 7Be data over the storm to accurately model a 7Be load, but the results suggest enhanced watershed export of 7Be from small, mountainous river systems compared to other watershed types.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Radioactivity","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvrad.2013.02.004","usgsCitation":"Conaway, C., Storlazzi, C., Draut, A.E., and Swarzenski, P.W., 2013, Short-term variability of 7Be atmospheric deposition and watershed response in a Pacific coastal stream, Monterey Bay, California, USA: Journal of Environmental Radioactivity, v. 120, p. 94-103, https://doi.org/10.1016/j.jenvrad.2013.02.004.","startPage":"94","endPage":"103","numberOfPages":"10","ipdsId":"IP-041747","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":272171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272170,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jenvrad.2013.02.004"}],"country":"United States","state":"California","otherGeospatial":"Monterey Bay;San Lorenzo River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.3,36.9 ], [ -122.3,37.3 ], [ -122.9,37.3 ], [ -122.9,36.9 ], [ -122.3,36.9 ] ] ] } } ] }","volume":"120","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518e16e1e4b05ebc8f7cc2ff","contributors":{"authors":[{"text":"Conaway, Christopher H.","contributorId":52620,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher H.","affiliations":[],"preferred":false,"id":472506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":77889,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","affiliations":[],"preferred":false,"id":472507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Draut, Amy E.","contributorId":92215,"corporation":false,"usgs":true,"family":"Draut","given":"Amy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":472508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472505,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188365,"text":"70188365 - 2013 - Annual modulation of non-volcanic tremor in northern Cascadia","interactions":[],"lastModifiedDate":"2017-06-07T11:42:08","indexId":"70188365","displayToPublicDate":"2013-05-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Annual modulation of non-volcanic tremor in northern Cascadia","docAbstract":"Two catalogs of episodic tremor events in northern Cascadia, one from 2006 to 2012 and the other from 1997 to 2011, reveal two systematic patterns of tremor occurrence in southern Vancouver Island: (1) most individual events tend to occur in the third quarter of the year; (2) the number of events in prolonged episodes (i.e., episodic tremor and slip events), which generally propagate to Vancouver Island from elsewhere along the Cascadia subduction zone, is inversely correlated with the amount of precipitation that occurred in the preceding 2 months. We rationalize these patterns as the product of hydrologic loading of the crust of southern Vancouver Island and the surrounding continental region, superimposed with annual variations from oceanic tidal loading. Loading of the Vancouver Island crust in the winter (when the land surface receives ample precipitation) and unloading in the summer tends to inhibit and enhance downdip shear stress, respectively. Quantitatively, for an annually variable surface load, the predicted stress perturbation depends on mantle viscoelastic rheology. A mechanical model of downdip shear stress on the transition zone beneath Vancouver Island—driven predominantly by the annual hydrologic cycle—is consistent with the 1997–2012 tremor observations, with peak-to-peak downdip shear stress of about 0.4 kPa. This seasonal dependence of tremor occurrence appears to be restricted to southern Vancouver Island because of its unique situation as an elongated narrow-width land mass surrounded by ocean, which permits seasonal perturbations in shear stress at depth.
","language":"English","publisher":"AGU","doi":"10.1002/jgrb.50181","usgsCitation":"Pollitz, F., Wech, A.G., Kao, H., and Burgmann, R., 2013, Annual modulation of non-volcanic tremor in northern Cascadia: Journal of Geophysical Research B: Solid Earth, v. 118, no. 5, p. 2445-2459, https://doi.org/10.1002/jgrb.50181.","productDescription":"15 p.","startPage":"2445","endPage":"2459","ipdsId":"IP-045029","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":473858,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrb.50181","text":"Publisher Index Page"},{"id":342223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128.5400390625,\n 46.28622391806706\n ],\n [\n -121.1572265625,\n 46.28622391806706\n ],\n [\n -121.1572265625,\n 50.958426723359935\n ],\n [\n -128.5400390625,\n 50.958426723359935\n ],\n [\n -128.5400390625,\n 46.28622391806706\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-05-13","publicationStatus":"PW","scienceBaseUri":"593910b4e4b0764e6c5e88e6","contributors":{"authors":[{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wech, Aaron G. 0000-0003-4983-1991 awech@usgs.gov","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":5344,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","email":"awech@usgs.gov","middleInitial":"G.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":697411,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kao, Honn","contributorId":105419,"corporation":false,"usgs":true,"family":"Kao","given":"Honn","email":"","affiliations":[],"preferred":false,"id":697412,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Burgmann, Roland","contributorId":192700,"corporation":false,"usgs":false,"family":"Burgmann","given":"Roland","affiliations":[],"preferred":false,"id":697413,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70187305,"text":"70187305 - 2013 - Assessing the potential of reservoir outflow management to reduce sedimentation using continuous turbidity monitoring and reservoir modelling","interactions":[],"lastModifiedDate":"2017-04-27T14:31:57","indexId":"70187305","displayToPublicDate":"2013-05-01T00:00:00","publicationYear":"2013","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":"Assessing the potential of reservoir outflow management to reduce sedimentation using continuous turbidity monitoring and reservoir modelling","docAbstract":"In-stream sensors are increasingly deployed as part of ambient water quality-monitoring networks. Temporally dense data from these networks can be used to better understand the transport of constituents through streams, lakes or reservoirs. Data from existing, continuously recording in-stream flow and water quality monitoring stations were coupled with the two-dimensional hydrodynamic CE-QUAL-W2 model to assess the potential of altered reservoir outflow management to reduce sediment trapping in John Redmond Reservoir, located in east-central Kansas. Monitoring stations upstream and downstream from the reservoir were used to estimate 5.6 million metric tons of sediment transported to John Redmond Reservoir from 2007 through 2010, 88% of which was trapped within the reservoir. The two-dimensional model was used to estimate the residence time of 55 equal-volume releases from the reservoir; sediment trapping for these releases varied from 48% to 97%. Smaller trapping efficiencies were observed when the reservoir was maintained near the normal operating capacity (relative to higher flood pool levels) and when average residence times were relatively short. An idealized, alternative outflow management scenario was constructed, which minimized reservoir elevations and the length of time water was in the reservoir, while continuing to meet downstream flood control end points identified in the reservoir water control manual. The alternative scenario is projected to reduce sediment trapping in the reservoir by approximately 3%, preventing approximately 45 000 metric tons of sediment from being deposited within the reservoir annually. This article presents an approach to quantify the potential of reservoir management using existing in-stream data; actual management decisions need to consider the effects on other reservoir benefits, such as downstream flood control and aquatic life.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.9284","usgsCitation":"Lee, C.J., and Foster, G.M., 2013, Assessing the potential of reservoir outflow management to reduce sedimentation using continuous turbidity monitoring and reservoir modelling: Hydrological Processes, v. 27, no. 10, p. 1426-1439, https://doi.org/10.1002/hyp.9284.","productDescription":"14 p.","startPage":"1426","endPage":"1439","ipdsId":"IP-026625","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":340523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"10","noUsgsAuthors":false,"publicationDate":"2012-04-23","publicationStatus":"PW","scienceBaseUri":"59030329e4b0e862d230f753","contributors":{"authors":[{"text":"Lee, Casey J. 0000-0002-5753-2038 cjlee@usgs.gov","orcid":"https://orcid.org/0000-0002-5753-2038","contributorId":2627,"corporation":false,"usgs":true,"family":"Lee","given":"Casey","email":"cjlee@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":693240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, Guy M. 0000-0002-9581-057X gfoster@usgs.gov","orcid":"https://orcid.org/0000-0002-9581-057X","contributorId":149145,"corporation":false,"usgs":true,"family":"Foster","given":"Guy","email":"gfoster@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693241,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045697,"text":"sir20135042 - 2013 - Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008","interactions":[],"lastModifiedDate":"2013-04-30T10:39:05","indexId":"sir20135042","displayToPublicDate":"2013-04-30T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5042","title":"Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008","docAbstract":"The Equus Beds aquifer is a primary water-supply source for Wichita, Kansas and the surrounding area because of shallow depth to water, large saturated thickness, and generally good water quality. Substantial water-level declines in the Equus Beds aquifer have resulted from pumping groundwater for agricultural and municipal needs, as well as periodic drought conditions. In March 2006, the city of Wichita began construction of the Equus Beds Aquifer Storage and Recovery project to store and later recover groundwater, and to form a hydraulic barrier to the known chloride-brine plume near Burrton, Kansas. In October 2009, the U.S. Geological Survey, in cooperation with the city of Wichita, began a study to determine groundwater flow in the area of the Wichita well field, and chloride transport from the Arkansas River and Burrton oilfield to the Wichita well field. Groundwater flow was simulated for the Equus Beds aquifer using the three-dimensional finite-difference groundwater-flow model MODFLOW-2000. The model simulates steady-state and transient conditions. The groundwater-flow model was calibrated by adjusting model input data and model geometry until model results matched field observations within an acceptable level of accuracy. The root mean square (RMS) error for water-level observations for the steady-state calibration simulation is 9.82 feet. The ratio of the RMS error to the total head loss in the model area is 0.049 and the mean error for water-level observations is 3.86 feet. The difference between flow into the model and flow out of the model across all model boundaries is -0.08 percent of total flow for the steady-state calibration. The RMS error for water-level observations for the transient calibration simulation is 2.48 feet, the ratio of the RMS error to the total head loss in the model area is 0.0124, and the mean error for water-level observations is 0.03 feet. The RMS error calculated for observed and simulated base flow gains or losses for the Arkansas River for the transient simulation is 7,916,564 cubic feet per day (91.6 cubic feet per second) and the RMS error divided by (/) the total range in streamflow (7,916,564/37,461,669 cubic feet per day) is 22 percent. The RMS error calculated for observed and simulated streamflow gains or losses for the Little Arkansas River for the transient simulation is 5,610,089 cubic feet per day(64.9 cubic feet per second) and the RMS error divided by the total range in streamflow (5,612,918/41,791,091 cubic feet per day) is 13 percent. The mean error between observed and simulated base flow gains or losses was 29,999 cubic feet per day (0.34 cubic feet per second) for the Arkansas River and -1,369,250 cubic feet per day (-15.8 cubic feet per second) for the Little Arkansas River. Cumulative streamflow gain and loss observations are similar to the cumulative simulated equivalents. Average percent mass balance difference for individual stress periods ranged from -0.46 to 0.51 percent. The cumulative mass balance for the transient calibration was 0.01 percent. Composite scaled sensitivities indicate the simulations are most sensitive to parameters with a large areal distribution. For the steady-state calibration, these parameters include recharge, hydraulic conductivity, and vertical conductance. For the transient simulation, these parameters include evapotranspiration, recharge, and hydraulic conductivity. The ability of the calibrated model to account for the additional groundwater recharged to the Equus Beds aquifer as part of the Aquifer Storage and Recovery project was assessed by using the U.S. Geological Survey subregional water budget program ZONEBUDGET and comparing those results to metered recharge for 2007 and 2008 and previous estimates of artificial recharge. The change in storage between simulations is the volume of water that estimates the recharge credit for the aquifer storage and recovery system. The estimated increase in storage of 1,607 acre-ft in the basin storage area compared to metered recharge of 1,796 acre-ft indicates some loss of metered recharge. Increased storage outside of the basin storage area of 183 acre-ft accounts for all but 6 acre-ft or 0.33 percent of the total. Previously estimated recharge credits for 2007 and 2008 are 1,018 and 600 acre-ft, respectively, and a total estimated recharge credit of 1,618 acre-ft. Storage changes calculated for this study are 4.42 percent less for 2007 and 5.67 percent more for 2008 than previous estimates. Total storage change for 2007 and 2008 is 0.68 percent less than previous estimates. The small difference between the increase in storage from artificial recharge estimated with the groundwater-flow model and metered recharge indicates the groundwater model correctly accounts for the additional water recharged to the Equus Beds aquifer as part of the Aquifer Storage and Recovery project. Small percent differences between inflows and outflows for all stress periods and all index cells in the basin storage area, improved calibration compared to the previous model, and a reasonable match between simulated and measured long-term base flow indicates the groundwater model accurately simulates groundwater flow in the study area. The change in groundwater level through recent years compared to the August 1940 groundwater level map has been documented and used to assess the change of storage volume of the Equus Beds aquifer in and near the Wichita well field for three different areas. Two methods were used to estimate changes in storage from simulation results using simulated change in groundwater levels in layer 1 between stress periods, and using ZONEBUDGET to calculate the change in storage in the same way the effects of artificial recharge were estimated within the basin storage area. The three methods indicate similar trends although the magnitude of storage changes differ. Information about the change in storage in response to hydrologic stresses is important for managing groundwater resources in the study area. The comparison between the three methods indicates similar storage change trends are estimated and each could be used to determine relative increases or decreases in storage. Use of groundwater level changes that do not include storage changes that occur in confined or semi-confined parts of the aquifer will slightly underestimate storage changes; however, use of specific yield and groundwater level changes to estimate storage change in confined or semi-confined parts of the aquifer will overestimate storage changes. Using only changes in shallow groundwater levels would provide more accurate storage change estimates for the measured groundwater levels method. The value used for specific yield is also an important consideration when estimating storage. For the Equus Beds aquifer the reported specific yield ranges between 0.08 and 0.35 and the storage coefficient (for confined conditions) ranges between 0.0004 and 0.16. Considering the importance of the value of specific yield and storage coefficient to estimates of storage change over time, and the wide range and substantial overlap for the reported values for specific yield and storage coefficient in the study area, further information on the distribution of specific yield and storage coefficient within the Equus Beds aquifer in the study area would greatly enhance the accuracy of estimated storage changes using both simulated groundwater level, simulated groundwater budget, or measured groundwater level methods.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135042","collaboration":"Prepared in cooperation with the city of Wichita, Kansas, as part of the Equus Beds Groundwater Recharge Project","usgsCitation":"Kelly, B.P., Pickett, L.L., Hansen, C.V., and Ziegler, A., 2013, Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008: U.S. Geological Survey Scientific Investigations Report 2013-5042, Report: viii, 92 p.; Downloads Directory, https://doi.org/10.3133/sir20135042.","productDescription":"Report: viii, 92 p.; Downloads Directory","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042806","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":271633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/SIR20135042.gif"},{"id":271632,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5042/downloads/"},{"id":271630,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5042/"},{"id":271631,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5042/sir2013-5042.pdf"}],"country":"United States","state":"Kansas","city":"Wichita","otherGeospatial":"Equus Beds Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.3,37.6 ], [ -98.3,38.05 ], [ -97.16,38.05 ], [ -97.16,37.6 ], [ -98.3,37.6 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180d9dce4b0df838b924d35","contributors":{"authors":[{"text":"Kelly, Brian P. 0000-0001-6378-2837 bkelly@usgs.gov","orcid":"https://orcid.org/0000-0001-6378-2837","contributorId":897,"corporation":false,"usgs":true,"family":"Kelly","given":"Brian","email":"bkelly@usgs.gov","middleInitial":"P.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pickett, Linda L.","contributorId":108377,"corporation":false,"usgs":true,"family":"Pickett","given":"Linda","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Cristi V. chansen@usgs.gov","contributorId":435,"corporation":false,"usgs":true,"family":"Hansen","given":"Cristi","email":"chansen@usgs.gov","middleInitial":"V.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":478068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":478067,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045518,"text":"70045518 - 2013 - Detecting unfrozen sediments below thermokarst lakes with surface nuclear magnetic resonance","interactions":[],"lastModifiedDate":"2013-04-24T15:22:16","indexId":"70045518","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","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":"Detecting unfrozen sediments below thermokarst lakes with surface nuclear magnetic resonance","docAbstract":"A talik is a layer or body of unfrozen ground that occurs in permafrost due to an anomaly in thermal, hydrological, or hydrochemical conditions. Information about talik geometry is important for understanding regional surface water and groundwater interactions as well as sublacustrine methane production in thermokarst lakes. Due to the direct measurement of unfrozen water content, surface nuclear magnetic resonance (NMR) is a promising geophysical method for noninvasively estimating talik dimensions. We made surface NMR measurements on thermokarst lakes and terrestrial permafrost near Fairbanks, Alaska, and confirmed our results using limited direct measurements. At an 8 m deep lake, we observed thaw bulb at least 22 m below the surface; at a 1.4 m deep lake, we detected a talik extending between 5 and 6 m below the surface. Our study demonstrates the value that surface NMR may have in the cryosphere for studies of thermokarst lake hydrology and their related role in the carbon cycle.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","publisherLocation":"Washington, D.C.","doi":"10.1002/grl.50137","usgsCitation":"Parsekian, A.D., Grosse, G., Walbrecker, J.O., Muller-Petke, M., Keating, K., Liu, L., Jones, B.M., and Knight, R., 2013, Detecting unfrozen sediments below thermokarst lakes with surface nuclear magnetic resonance: Geophysical Research Letters, v. 40, no. 3, p. 535-540, https://doi.org/10.1002/grl.50137.","productDescription":"6 p.","startPage":"535","endPage":"540","ipdsId":"IP-043197","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473864,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/grl.50137","text":"Publisher Index Page"},{"id":271419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271418,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/grl.50137"}],"volume":"40","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-02-11","publicationStatus":"PW","scienceBaseUri":"5178f0dbe4b0d842c705f6a8","contributors":{"authors":[{"text":"Parsekian, Andrew D.","contributorId":23829,"corporation":false,"usgs":false,"family":"Parsekian","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":477709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":477715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walbrecker, Jan O.","contributorId":32061,"corporation":false,"usgs":true,"family":"Walbrecker","given":"Jan","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":477710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muller-Petke, Mike","contributorId":80996,"corporation":false,"usgs":true,"family":"Muller-Petke","given":"Mike","email":"","affiliations":[],"preferred":false,"id":477712,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keating, Kristina","contributorId":34018,"corporation":false,"usgs":true,"family":"Keating","given":"Kristina","affiliations":[],"preferred":false,"id":477711,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Lin","contributorId":92950,"corporation":false,"usgs":false,"family":"Liu","given":"Lin","email":"","affiliations":[{"id":36342,"text":"Earth System Science Programme, Faculty of Science, Chinese University of Hong Kong, Hong Kong, China","active":true,"usgs":false}],"preferred":false,"id":477714,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":477708,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knight, Rosemary","contributorId":84245,"corporation":false,"usgs":true,"family":"Knight","given":"Rosemary","email":"","affiliations":[],"preferred":false,"id":477713,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70045583,"text":"sir20125077 - 2013 - Numerical simulation of groundwater and surface-water interactions in the Big River Management Area, central Rhode Island","interactions":[],"lastModifiedDate":"2018-05-17T13:30:55","indexId":"sir20125077","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5077","title":"Numerical simulation of groundwater and surface-water interactions in the Big River Management Area, central Rhode Island","docAbstract":"The Rhode Island Water Resources Board is considering use of groundwater resources from the Big River Management Area in central Rhode Island because increasing water demands in Rhode Island may exceed the capacity of current sources. Previous water-resources investigations in this glacially derived, valley-fill aquifer system have focused primarily on the effects of potential groundwater-pumping scenarios on streamflow depletion; however, the effects of groundwater withdrawals on wetlands have not been assessed, and such assessments are a requirement of the State’s permitting process to develop a water supply in this area.\n\nA need for an assessment of the potential effects of pumping on wetlands in the Big River Management Area led to a cooperative agreement in 2008 between the Rhode Island Water Resources Board, the U.S. Geological Survey, and the University of Rhode Island. This partnership was formed with the goal of developing methods for characterizing wetland vegetation, soil type, and hydrologic conditions, and monitoring and modeling water levels for pre- and post-water-supply development to assess potential effects of groundwater withdrawals on wetlands. This report describes the hydrogeology of the area and the numerical simulations that were used to analyze the interaction between groundwater and surface water in response to simulated groundwater withdrawals.\n\nThe results of this analysis suggest that, given the hydrogeologic conditions in the Big River Management Area, a standard 5-day aquifer test may not be sufficient to determine the effects of pumping on water levels in nearby wetlands. Model simulations showed water levels beneath Reynolds Swamp declined by about 0.1 foot after 5 days of continuous pumping, but continued to decline by an additional 4 to 6 feet as pumping times were increased from a 5-day simulation period to a simulation period representative of long-term average monthly conditions. This continued decline in water levels with increased pumping time is related to the shift from the primary source of water to the pumped wells being derived from aquifer storage during the early-time (5 days) simulation to being derived more from induced infiltration from the flooded portion of the Big River (southernmost extent of the Flat River Reservoir) during the months of March through October or from captured groundwater discharge to this portion of the Big River when the downstream Flat River Reservoir is drained for weed control during the months of November through February, as was the case for the long-term monthly conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125077","collaboration":"Prepared in cooperation with the Rhode Island Water Resources Board","usgsCitation":"Masterson, J., and Granato, G., 2013, Numerical simulation of groundwater and surface-water interactions in the Big River Management Area, central Rhode Island: U.S. Geological Survey Scientific Investigations Report 2012-5077, vi, 53 p., https://doi.org/10.3133/sir20125077.","productDescription":"vi, 53 p.","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":271417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125077.jpg"},{"id":271416,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5077/pdf/sir2012-5077_508.pdf"},{"id":271415,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5077/"}],"country":"United States","state":"Rhode Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.8923,41.1467 ], [ -71.8923,42.0188 ], [ -71.1205,42.0188 ], [ -71.1205,41.1467 ], [ -71.8923,41.1467 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5178f0dfe4b0d842c705f6c0","contributors":{"authors":[{"text":"Masterson, John P. 0000-0003-3202-4413 jpmaster@usgs.gov","orcid":"https://orcid.org/0000-0003-3202-4413","contributorId":1865,"corporation":false,"usgs":true,"family":"Masterson","given":"John P.","email":"jpmaster@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":1692,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","email":"ggranato@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477872,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045584,"text":"70045584 - 2013 - Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA","interactions":[],"lastModifiedDate":"2013-04-24T16:57:38","indexId":"70045584","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA","docAbstract":"We present a conceptual and analytical framework for predicting the spatial distribution of floodplain sedimentation for the Laguna de Santa Rosa, Sonoma County, CA. We assess the role of the floodplain as a sink for fine-grained sediment and investigate concerns regarding the potential loss of flood storage capacity due to historic sedimentation. We characterized the spatial distribution of sedimentation during a post-flood survey and developed a spatially distributed sediment deposition potential map that highlights zones of floodplain sedimentation. The sediment deposition potential map, built using raster files that describe the spatial distribution of relevant hydrologic and landscape variables, was calibrated using 2 years of measured overbank sedimentation data and verified using longer-term rates determined using dendrochronology. The calibrated floodplain deposition potential relation was used to estimate an average annual floodplain sedimentation rate (3.6 mm/year) for the ~11 km2 floodplain. This study documents the development of a conceptual model of overbank sedimentation, describes a methodology to estimate the potential for various parts of a floodplain complex to accumulate sediment over time, and provides estimates of short and long-term overbank sedimentation rates that can be used for ecosystem management and prioritization of restoration activities.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wetlands","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s13157-012-0350-4","usgsCitation":"Curtis, J.A., Flint, L.E., and Hupp, C.R., 2013, Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA: Wetlands, v. 33, no. 1, p. 29-45, https://doi.org/10.1007/s13157-012-0350-4.","productDescription":"17 p.","startPage":"29","endPage":"45","ipdsId":"IP-018988","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":271425,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271424,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s13157-012-0350-4"}],"country":"United States","state":"California","county":"Sonoma County","city":"Santa Rosa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.8341,38.3637 ], [ -122.8341,38.5074 ], [ -122.573,38.5074 ], [ -122.573,38.3637 ], [ -122.8341,38.3637 ] ] ] } } ] }","volume":"33","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-12-20","publicationStatus":"PW","scienceBaseUri":"5178f0dee4b0d842c705f6b8","contributors":{"authors":[{"text":"Curtis, Jennifer A. 0000-0001-7766-994X jacurtis@usgs.gov","orcid":"https://orcid.org/0000-0001-7766-994X","contributorId":927,"corporation":false,"usgs":true,"family":"Curtis","given":"Jennifer","email":"jacurtis@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":477876,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045552,"text":"sir20135044 - 2013 - Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","interactions":[],"lastModifiedDate":"2015-10-16T13:47:34","indexId":"sir20135044","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5044","title":"Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","docAbstract":"The U.S. Geological Survey, in cooperation with the White Bear Lake Conservation District, the Minnesota Pollution Control Agency, the Minnesota Department of Natural Resources, and other State, county, municipal, and regional planning agencies, watershed organizations, and private organizations, conducted a study to characterize groundwater and surface-water interactions near White Bear Lake through 2011. During 2010 and 2011, White Bear Lake and other lakes in the northeastern part of the Twin Cities Metropolitan Area were at historically low levels. Previous periods of lower water levels in White Bear Lake correlate with periods of lower precipitation; however, recent urban expansion and increased pumping from the Prairie du Chien-Jordan aquifer have raised the question of whether a decline in precipitation is the primary cause for the recent water-level decline in White Bear Lake. Understanding and quantifying the amount of groundwater inflow to a lake and water discharge from a lake to aquifers is commonly difficult but is important in the management of lake levels. Three methods were used in the study to assess groundwater and surface-water interactions on White Bear Lake: (1) a historical assessment (1978-2011) of levels in White Bear Lake, local groundwater levels, and their relation to historical precipitation and groundwater withdrawals in the White Bear Lake area; (2) recent (2010-11) hydrologic and water-quality data collected from White Bear Lake, other lakes, and wells; and (3) water-balance assessments for White Bear Lake in March and August 2011. An analysis of covariance between average annual lake-level change and annual precipitation indicated the relation between the two variables was significantly different from 2003 through 2011 compared with 1978 through 2002, requiring an average of 4 more inches of precipitation per year to maintain the lake level. This shift in the linear relation between annual lake-level change and annual precipitation indicated the net effect of the non-precipitation terms on the water balance has changed relative to precipitation. The average amount of precipitation required each year to maintain the lake level has increased from 33 inches per year during 1978-2002 to 37 inches per year during 2003-11. The combination of lower precipitation and an increase in groundwater withdrawals can explain the change in the lake-level response to precipitation. Annual and summer groundwater withdrawals from the Prairie du Chien-Jordan aquifer have more than doubled from 1980 through 2010. Results from a regression model constructed with annual lake-level change, annual precipitation minus evaporation, and annual volume of groundwater withdrawn from the Prairie du Chien-Jordan aquifer indicated groundwater withdrawals had a greater effect than precipitation minus evaporation on water levels in the White Bear Lake area for all years since 2003. The recent (2003-11) decline in White Bear Lake reflects the declining water levels in the Prairie du Chien-Jordan aquifer; increases in groundwater withdrawals from this aquifer are a likely cause for declines in groundwater levels and lake levels. Synoptic, static groundwater-level and lake-level measurements in March/April and August 2011 indicated groundwater was potentially flowing into White Bear Lake from glacial aquifers to the northeast and south, and lake water was potentially discharging from White Bear Lake to the underlying glacial and Prairie du Chien-Jordan aquifers and glacial aquifers to the northwest. Groundwater levels in the Prairie du Chien-Jordan aquifer below White Bear Lake are approximately 0 to 19 feet lower than surface-water levels in the lake, indicating groundwater from the aquifer likely does not flow into White Bear Lake, but lake water may discharge into the aquifer. Groundwater levels from March/April to August 2011 declined more than 10 feet in the Prairie du Chien-Jordan aquifer south of White Bear Lake and to the north in Hugo, Minnesota. Water-quality analyses of pore water from nearshore lake-sediment and well-water samples, seepage-meter measurements, and hydraulic-head differences measured in White Bear Lake also indicated groundwater was potentially flowing into White Bear Lake from shallow glacial aquifers to the east and south. Negative temperature anomalies determined in shallow waters in the water-quality survey conducted in White Bear Lake indicated several shallow-water areas where groundwater may be flowing into the lake from glacial aquifers below the lake. Cool lake-sediment temperatures (less than 18 degrees Celsius) were measured in eight areas along the northeast, east, south, and southwest shores of White Bear Lake, indicating potential areas where groundwater may flow into the lake. Stable isotope analyses of well-water, precipitation, and lake-water samples indicated wells downgradient from White Bear Lake screened in the glacial buried aquifer or open to the Prairie du Chien-Jordan aquifer receive a mixture of surface water and groundwater; the largest surface-water contributions are in wells closer to White Bear Lake. A wide range in oxygen-18/oxygen-16 and deuterium/protium ratios was measured in well-water samples, indicating different sources of water are supplying water to the wells. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot close to the meteoric water line consisted mostly of groundwater because deuterium/protium ratios for most groundwater usually are similar to ratios for rainwater and snow, plotting close to meteoric water lines. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot between the meteoric water line and ratios for the surface-water samples from White Bear Lake consists of a mixture of surface water and groundwater; the percentage of each source varies relative to its ratios. White Bear Lake is the likely source of the surface water to the wells that have a mixture of surface water and groundwater because (1) it is the only large, deep lake near these wells; (2) these wells are near and downgradient from White Bear Lake; and (3) these wells obtain their water from relatively deep depths, and White Bear Lake is the deepest lake in that area. The percentages of surface-water contribution to the three wells screened in the glacial buried aquifer receiving surface water were 16, 48, and 83 percent. The percentages of surface-water contribution ranged from 5 to 79 percent for the five wells open to the Prairie du Chien-Jordan aquifer receiving surface water; wells closest to White Bear Lake had the largest percentages of surface-water contribution. Water-balance analysis of White Bear Lake in March and August 2011 indicated a potential discharge of 2.8 and 4.5 inches per month, respectively, over the area of the lake from the lake to local aquifers. Most of the sediments from a 12.4-foot lake core collected at the deepest part of White Bear Lake consisted of silts, sands, and gravels likely slumped from shallower waters, with a very low amount of low-permeability, organic material.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135044","collaboration":"Prepared in cooperation with the White Bear Lake Conservation District, Minnesota Pollution Control Agency, Minnesota Department of Natural Resources, Minnesota Board of Water and Soil Resources, Twin Cities Metropolitan Council, and the Groundwater/Surface-Water Interaction Partners","usgsCitation":"Jones, P.M., Trost, J.J., Rosenberry, D.O., Jackson, P., Bode, J.A., and O’Grady, R.M., 2013, Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011: U.S. Geological Survey Scientific Investigations Report 2013-5044, ix, 73 p.; Downloads Directory, https://doi.org/10.3133/sir20135044.","productDescription":"ix, 73 p.; Downloads Directory","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-030440","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":271388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135044.gif"},{"id":271385,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5044/"},{"id":271387,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5044/downloads/"},{"id":271386,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5044/sir2013-5044.pdf"}],"country":"United States","state":"Minnesota","county":"Anoka County, Ramsey County, Washington County","city":"Minneapolis","otherGeospatial":"White Bear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.2080078125,\n 44.92883525162427\n ],\n [\n -93.2080078125,\n 45.2004253589021\n ],\n [\n -92.80357360839842,\n 45.2004253589021\n ],\n [\n -92.80357360839842,\n 44.92883525162427\n ],\n [\n -93.2080078125,\n 44.92883525162427\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51779f59e4b095699adf272a","contributors":{"authors":[{"text":"Jones, Perry M. 0000-0002-6569-5144 pmjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6569-5144","contributorId":2231,"corporation":false,"usgs":true,"family":"Jones","given":"Perry","email":"pmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477837,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":477835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, P. Ryan","contributorId":68571,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":477839,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bode, Jenifer A. jabode@usgs.gov","contributorId":3857,"corporation":false,"usgs":true,"family":"Bode","given":"Jenifer","email":"jabode@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":477838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Grady, Ryan M.","contributorId":83433,"corporation":false,"usgs":true,"family":"O’Grady","given":"Ryan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477840,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045470,"text":"70045470 - 2013 - Complex resistivity signatures of ethanol in sand-clay mixtures","interactions":[],"lastModifiedDate":"2013-04-21T19:27:31","indexId":"70045470","displayToPublicDate":"2013-04-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Complex resistivity signatures of ethanol in sand-clay mixtures","docAbstract":"We performed complex resistivity (CR) measurements on laboratory columns to investigate changes in electrical properties as a result of varying ethanol (EtOH) concentration (0% to 30% v/v) in a sand–clay (bentonite) matrix. We applied Debye decomposition, a phenomenological model commonly used to fit CR data, to determine model parameters (time constant: τ, chargeability: m, and normalized chargeability: mn). The CR data showed a significant (P ≤ 0.001) time-dependent variation in the clay driven polarization response (~ 12 mrad) for 0% EtOH concentration. This temporal variation probably results from the clay–water reaction kinetics trending towards equilibrium in the sand–clay–water system. The clay polarization is significantly suppressed (P ≤ 0.001) for both measured phase (ϕ) and imaginary conductivity (σ″) with increasing EtOH concentration. Normalized chargeability consistently decreases (by up to a factor of ~ 2) as EtOH concentration increases from 0% to 10% and 10 to 20%, respectively. We propose that such suppression effects are associated with alterations in the electrical double layer (EDL) at the clay–fluid interface due to (a) strong EtOH adsorption on clay, and (b) complex intermolecular EtOH–water interactions and subsequent changes in ionic mobility on the surface in the EDL. Changes in the CR data following a change of the saturating fluid from EtOH 20% to plain water indicate strong hysteresis effects in the electrical response, which we attribute to persistent EtOH adsorption on clay. Our results demonstrate high sensitivity of CR measurements to clay–EtOH interactions in porous media, indicating the potential application of this technique for characterization and monitoring of ethanol contamination in sediments containing clays.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Contaminant Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jconhyd.2013.03.005","usgsCitation":"Personna, Y.R., Slater, L., Ntarlagiannis, D., Werkema, D.D., and Szabo, Z., 2013, Complex resistivity signatures of ethanol in sand-clay mixtures: Journal of Contaminant Hydrology, v. 149, p. 76-87, https://doi.org/10.1016/j.jconhyd.2013.03.005.","productDescription":"12 p.","startPage":"76","endPage":"87","ipdsId":"IP-045055","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":271323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271322,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2013.03.005"}],"volume":"149","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5174fc5ee4b074c2b055647d","contributors":{"authors":[{"text":"Personna, Yves Robert","contributorId":77820,"corporation":false,"usgs":false,"family":"Personna","given":"Yves","email":"","middleInitial":"Robert","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slater, Lee","contributorId":55707,"corporation":false,"usgs":false,"family":"Slater","given":"Lee","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ntarlagiannis, Dimitrios","contributorId":55303,"corporation":false,"usgs":false,"family":"Ntarlagiannis","given":"Dimitrios","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":477575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":2240,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":477574,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045491,"text":"sir20135083 - 2013 - Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11","interactions":[],"lastModifiedDate":"2013-04-19T09:29:00","indexId":"sir20135083","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5083","title":"Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11","docAbstract":"Sedimentation is an ongoing maintenance problem for reservoirs, limiting reservoir storage capacity and navigation. Because Lower Granite Reservoir in Washington is the most upstream of the four U.S. Army Corps of Engineers reservoirs on the lower Snake River, it receives and retains the largest amount of sediment. In 2008, in cooperation with the U.S. Army Corps of Engineers, the U.S. Geological Survey began a study to quantify sediment transport to Lower Granite Reservoir. Samples of suspended sediment and bedload were collected from streamgaging stations on the Snake River near Anatone, Washington, and the Clearwater River at Spalding, Idaho. Both streamgages were equipped with an acoustic Doppler velocity meter to evaluate the efficacy of acoustic backscatter for estimating suspended-sediment concentrations and transport. In 2009, sediment sampling was extended to 10 additional locations in tributary watersheds to help identify the dominant source areas for sediment delivery to Lower Granite Reservoir. Suspended-sediment samples were collected 9–15 times per year at each location to encompass a range of streamflow conditions and to capture significant hydrologic events such as peak snowmelt runoff and rain-on-snow. Bedload samples were collected at a subset of stations where the stream conditions were conducive for sampling, and when streamflow was sufficiently high for bedload transport. At most sampling locations, the concentration of suspended sediment varied by 3–5 orders of magnitude with concentrations directly correlated to streamflow. The largest median concentrations of suspended sediment (100 and 94 mg/L) were in samples collected from stations on the Palouse River at Hooper, Washington, and the Salmon River at White Bird, Idaho, respectively. The smallest median concentrations were in samples collected from the Selway River near Lowell, Idaho (11 mg/L), the Lochsa River near Lowell, Idaho (11 mg/L), the Clearwater River at Orofino, Idaho (13 mg/L), and the Middle Fork Clearwater River at Kooskia, Idaho (15 mg/L). The largest measured concentrations of suspended sediment (3,300 and 1,400 mg/L) during a rain-on-snow event in January 2011 were from samples collected at the Potlatch River near Spalding, Idaho, and the Palouse River at Hooper, Washington, respectively. Generally, samples collected from agricultural watersheds had a high percentage of silt and clay-sized suspended sediment, whereas samples collected from forested watersheds had a high percentage of sand. During water years 2009–11, Lower Granite Reservoir received about 10 million tons of suspended sediment from the combined loads of the Snake and Clearwater Rivers. The Snake River accounted for about 2.97 million tons per year (about 89 percent) of the total suspended sediment, 1.48 million tons per year (about 90 percent) of the suspended sand, and about 1.52 million tons per year (87 percent) of the suspended silt and clay. Of the suspended sediment transported to Lower Granite Reservoir, the Salmon River accounted for about 51 percent of the total suspended sediment, about 56 percent of the suspended sand, and about 44 percent of the suspended silt and clay. About 6.2 million tons (62 percent) of the sediment contributed to Lower Granite Reservoir during 2009–11 entered during water year 2011, which was characterized by an above average winter snowpack and sustained spring runoff. A comparison of historical data collected from the Snake River near Anatone with data collected during this study indicates that concentrations of total suspended sediment and suspended sand in the Snake River were significantly smaller during water years 1972–79 than during 2008–11. Most of the increased sediment content in the Snake River is attributable to an increase of sand-size material. During 1972–79, sand accounted for an average of 28 percent of the suspended-sediment load; during 2008–11, sand accounted for an average of 48 percent. Historical data from the Clearwater River at Spalding indicates that the concentrations of total suspended sediment collected during 1972–79 were not significantly different from the concentrations measured during this study. However, the suspended-sand concentrations in the Clearwater River were significantly smaller during 1972–79 than during 2008–11. The increase in suspended-sand concentrations in the Snake and Clearwater Rivers are probably attributable to numerous severe forest fires that burned large areas of central Idaho from 1980–2010. Acoustic backscatter from an acoustic Doppler velocity meter proved to be an effective method of estimating suspended-sediment concentration and load for most streamflow conditions in the Snake and Clearwater Rivers. Models based on acoustic backscatter were able to simulate most of the variability in suspended-sediment concentrations in the Clearwater River at Spalding (coefficient of determination [R2]=0.93) and the Snake River near Anatone (R2=0.92). Acoustic backscatter seems to be especially effective for estimating suspended-sediment concentration and load over short (monthly and single storm event) and long (annual) time scales when sediment load is highly variable. However, during high streamflow events acoustic surrogate tools may be unable to capture the contribution of suspended sand moving near the bottom of the water column and thus, underestimate the total load of suspended sediment. At the stations where bedload was collected, the particle-size distribution at low streamflows typically was unimodal with sand comprising the dominant particle size. At higher streamflows and during peak bedload discharge, the particle size typically was bimodal and was comprised primarily of sand and coarse gravel. About 55,000 tons of bedload was discharged from the Snake River to Lower Granite Reservoir during water years 2009–11, about 0.62 percent of the total sediment load delivered by the Snake River. About 9,500 tons of bedload was discharged from the Clearwater River to Lower Granite Reservoir during 2009–11, about 0.83 percent of the total sediment load discharged by the Clearwater River during 2009–11.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135083","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Clark, G.M., Fosness, R.L., and Wood, M.S., 2013, Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11: U.S. Geological Survey Scientific Investigations Report 2013-5083, vi, 58 p., https://doi.org/10.3133/sir20135083.","productDescription":"vi, 58 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":271216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135083.jpg"},{"id":271214,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5083/"},{"id":271215,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5083/pdf/sir20135083.pdf"}],"country":"United States","state":"Idaho;Washington","otherGeospatial":"Lower Snake And Clearwater River Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119,44 ], [ -119,47.5 ], [ -113,47.5 ], [ -113,44 ], [ -119,44 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595de4b0c173799e78f2","contributors":{"authors":[{"text":"Clark, Gregory M. gmclark@usgs.gov","contributorId":1377,"corporation":false,"usgs":true,"family":"Clark","given":"Gregory","email":"gmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045509,"text":"70045509 - 2013 - Wetland fire scar monitoring and analysis using archival Landsat data for the Everglades","interactions":[],"lastModifiedDate":"2013-04-19T21:06:46","indexId":"70045509","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Wetland fire scar monitoring and analysis using archival Landsat data for the Everglades","docAbstract":"The ability to document the frequency, extent, and severity of fires in wetlands, as well as the dynamics of post-fire wetland land cover, informs fire and wetland science, resource management, and ecosystem protection. Available information on Everglades burn history has been based on field data collection methods that evolved through time and differ by land management unit. Our objectives were to (1) design and test broadly applicable and repeatable metrics of not only fire scar delineation but also post-fire land cover dynamics through exhaustive use of the Landsat satellite data archives, and then (2) explore how those metrics relate to various hydrologic and anthropogenic factors that may influence post-fire land cover dynamics. Visual interpretation of every Landsat scene collected over the study region during the study time frame produced a new, detailed database of burn scars greater than 1.6 ha in size in the Water Conservation Areas and post-fire land cover dynamics for Everglades National Park fires greater than 1.6 ha in area. Median burn areas were compared across several landscape units of the Greater Everglades and found to differ as a function of administrative unit and fire history. Some burned areas transitioned to open water, exhibiting water depths and dynamics that support transition mechanisms proposed in the literature. Classification tree techniques showed that time to green-up and return to pre-burn character were largely explained by fire management practices and hydrology. Broadly applicable as they use data from the global, nearly 30-year-old Landsat archive, these methods for documenting wetland burn extent and post-fire land cover change enable cost-effective collection of new data on wetland fire ecology and independent assessment of fire management practice effectiveness.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Fire Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Association for Fire Ecology","publisherLocation":"Eugene, OR","doi":"10.4996/fireecology.0901133","usgsCitation":"Jones, J., Hall, A.E., Foster, A.M., and Smith, T.J., 2013, Wetland fire scar monitoring and analysis using archival Landsat data for the Everglades: Fire Ecology, v. 9, no. 1, p. 133-150, https://doi.org/10.4996/fireecology.0901133.","productDescription":"18 p.","startPage":"133","endPage":"150","ipdsId":"IP-040357","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473873,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4996/fireecology.0901133","text":"Publisher Index Page"},{"id":271273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271272,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4996/fireecology.0901133"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.5205,24.851 ], [ -81.5205,25.8915 ], [ -80.3887,25.8915 ], [ -80.3887,24.851 ], [ -81.5205,24.851 ] ] ] } } ] }","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-04-01","publicationStatus":"PW","scienceBaseUri":"5172595ee4b0c173799e78fa","contributors":{"authors":[{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":477670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Annette E. ahall@usgs.gov","contributorId":4791,"corporation":false,"usgs":true,"family":"Hall","given":"Annette","email":"ahall@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":477672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foster, Ann M. amfoster@usgs.gov","contributorId":3545,"corporation":false,"usgs":true,"family":"Foster","given":"Ann","email":"amfoster@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":477671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Thomas J. III tom_j_smith@usgs.gov","contributorId":1615,"corporation":false,"usgs":true,"family":"Smith","given":"Thomas","suffix":"III","email":"tom_j_smith@usgs.gov","middleInitial":"J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":477669,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045494,"text":"ofr20131086 - 2013 - Estimation of capture zones and drawdown at the Northwest and West Well Fields, Miami-Dade County, Florida, using an unconstrained Monte Carlo analysis: recent (2004) and proposed conditions","interactions":[],"lastModifiedDate":"2013-04-19T10:55:31","indexId":"ofr20131086","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1086","title":"Estimation of capture zones and drawdown at the Northwest and West Well Fields, Miami-Dade County, Florida, using an unconstrained Monte Carlo analysis: recent (2004) and proposed conditions","docAbstract":"Travel-time capture zones and drawdown for two production well fields, used for drinking-water supply in Miami-Dade County, southeastern Florida, were delineated by the U.S Geological Survey using an unconstrained Monte Carlo analysis. The well fields, designed to supply a combined total of approximately 250 million gallons of water per day, pump from the highly transmissive Biscayne aquifer in the urban corridor between the Everglades and Biscayne Bay. A transient groundwater flow model was developed and calibrated to field data to ensure an acceptable match between simulated and observed values for aquifer heads and net exchange of water between the aquifer and canals. Steady-state conditions were imposed on the transient model and a post-processing backward particle-tracking approach was implemented. Multiple stochastic realizations of horizontal hydraulic conductivity, conductance of canals, and effective porosity were simulated for steady-state conditions representative of dry, average and wet hydrologic conditions to calculate travel-time capture zones of potential source areas of the well fields. Quarry lakes, formed as a product of rock-mining activities, whose effects have previously not been considered in estimation of capture zones, were represented using high hydraulic-conductivity, high-porosity cells, with the bulk hydraulic conductivity of each cell calculated based on estimates of aquifer hydraulic conductivity, lake depths and aquifer thicknesses. A post-processing adjustment, based on calculated residence times using lake outflows and known lake volumes, was utilized to adjust particle endpoints to account for an estimate of residence-time-based mixing of lakes. Drawdown contours of 0.1 and 0.25 foot were delineated for the dry, average, and wet hydrologic conditions as well. In addition, 95-percent confidence intervals (CIs) were calculated for the capture zones and drawdown contours to delineate a zone of uncertainty about the median estimates. Results of the Monte Carlo simulations indicate particle travel distances at the Northwest Well Field (NWWF) and West Well Field (WWF) are greatest to the west, towards the Everglades. The man-made quarry lakes substantially affect particle travel distances. In general near the NWWF, the capture zones in areas with lakes were smaller in areal extent than capture zones in areas without lakes. It is possible that contamination could reach the well fields quickly, within 10 days in some cases, if it were introduced into lakes nearest to supply wells, with one of the lakes being only approximately 650 feet from the nearest supply well. In addition to estimating drawdown and travel-time capture zones of 10, 30, 100, and 210 days for the NWWF and the WWF under more recent conditions, two proposed scenarios were evaluated with Monte Carlo simulations: the potential hydrologic effects of proposed Everglades groundwater seepage mitigation and quarry-lake expansion. The seepage mitigation scenario included the addition of two proposed anthropogenic features to the model: (1) an impermeable horizontal flow barrier east of the L-31N canal along the western model boundary between the Everglades and the urban areas of Miami-Dade County, and (2) a recharge canal along the Dade-Broward Levee near the NWWF. Capture zones and drawdown for the WWF were substantially affected by the addition of the barrier, which eliminates flow from the western boundary into the active model domain, shifting the predominant capture zone source area from the west more to the north and south. The 95-percent CI for the 210-day capture zone moved slightly in the NWWF as a result of the recharge canal. The lake-expansion scenario incorporated a proposed increase in the number and surface area of lakes by an additional 25 square miles. This scenario represents a 150-percent increase from the 2004 lake surface area near both well fields, but with the majority of increase proposed near the NWWF. The lake-expansion scenario substantially decreased the extent of the 210-day capture zone of the NWWF, which is limited to the lakes nearest the well field under proposed conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131086","collaboration":"Prepared in cooperation with the Miami-Dade County Water and Sewer Department and Department of Regulatory and Economic Resources","usgsCitation":"Brakefield, L.K., Hughes, J.D., Langevin, C.D., and Chartier, K., 2013, Estimation of capture zones and drawdown at the Northwest and West Well Fields, Miami-Dade County, Florida, using an unconstrained Monte Carlo analysis: recent (2004) and proposed conditions: U.S. Geological Survey Open-File Report 2013-1086, x, 127 p., https://doi.org/10.3133/ofr20131086.","productDescription":"x, 127 p.","numberOfPages":"140","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":271256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131086.gif"},{"id":271254,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1086/"},{"id":271255,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1086/pdf/ofr2013-1086.pdf"}],"country":"United States","state":"Florida","county":"Miami-dade","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.35,25.40 ], [ -80.35,25.60 ], [ -80.15,25.60 ], [ -80.15,25.40 ], [ -80.35,25.40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595be4b0c173799e78de","contributors":{"authors":[{"text":"Brakefield, Linzy K. lbrake@usgs.gov","contributorId":2080,"corporation":false,"usgs":true,"family":"Brakefield","given":"Linzy","email":"lbrake@usgs.gov","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":477630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":477628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chartier, Kevin","contributorId":64128,"corporation":false,"usgs":true,"family":"Chartier","given":"Kevin","affiliations":[],"preferred":false,"id":477631,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045451,"text":"70045451 - 2013 - A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?","interactions":[],"lastModifiedDate":"2016-11-30T13:14:40","indexId":"70045451","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?","docAbstract":"Successful environmental/water quality-monitoring programs usually require a balance between analytical capabilities, the collection and preservation of representative samples, and available financial/personnel resources. Due to current economic conditions, monitoring programs are under increasing pressure to do more with less. Hence, a review of current sampling and analytical methodologies, and some of the underlying assumptions that form the bases for these programs seems appropriate, to see if they are achieving their intended objectives within acceptable error limits and/or measurement uncertainty, in a cost-effective manner. That evaluation appears to indicate that several common sampling/processing/analytical procedures (e.g., dip (point) samples/measurements, nitrogen determinations, total recoverable analytical procedures) are generating biased or nonrepresentative data, and that some of the underlying assumptions relative to current programs, such as calendar-based sampling and stationarity are no longer defensible. The extensive use of statistical models as well as surrogates (e.g., turbidity) also needs to be re-examined because the hydrologic interrelationships that support their use tend to be dynamic rather than static. As a result, a number of monitoring programs may need redesigning, some sampling and analytical procedures may need to be updated, and model/surrogate interrelationships may require recalibration.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/es304058q","usgsCitation":"Horowitz, A.J., 2013, A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?: Environmental Science & Technology, v. 47, no. 6, p. 2471-2486, https://doi.org/10.1021/es304058q.","productDescription":"16 p.","startPage":"2471","endPage":"2486","ipdsId":"IP-043699","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271276,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es304058q"}],"volume":"47","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-03-01","publicationStatus":"PW","scienceBaseUri":"51725951e4b0c173799e78d6","contributors":{"authors":[{"text":"Horowitz, Arthur J. 0000-0002-3296-730X horowitz@usgs.gov","orcid":"https://orcid.org/0000-0002-3296-730X","contributorId":1400,"corporation":false,"usgs":true,"family":"Horowitz","given":"Arthur","email":"horowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477514,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045469,"text":"sir20135059 - 2013 - Sources of suspended-sediment loads in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary, south Texas, 1958–2010","interactions":[],"lastModifiedDate":"2016-08-05T14:08:52","indexId":"sir20135059","displayToPublicDate":"2013-04-18T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5059","title":"Sources of suspended-sediment loads in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary, south Texas, 1958–2010","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe-Blanco River Authority; San Antonio River Authority; and San Antonio Water System, developed, calibrated, and tested a Hydrological Simulation Program-FORTRAN (HSPF) watershed model to simulate streamflow and suspended-sediment concentrations and loads during 1958-2010 in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary in south Texas. Data available to simulate suspended-sediment concentrations and loads consisted of historical sediment data collected during 1942-82 in the study area and suspended-sediment concentration data collected periodically by the USGS during 2006-7 and 2010 at three USGS streamflow-gaging stations (08211000 Nueces River near Mathis, Tex. [the Mathis gage], 08211200 Nueces River at Bluntzer, Tex. [the Bluntzer gage], and 08211500 Nueces River at Calallen, Tex. [the Calallen gage]), and at one ungaged location on a Nueces River tributary (USGS station 08211050 Bayou Creek at Farm Road 666 near Mathis, Tex.). The Mathis gage is downstream from Wesley E. Seale Dam, which was completed in 1958 to impound Lake Corpus Christi. Suspended-sediment data collected before and after completion of Wesley E. Seale Dam provide insights to the effects of the dam and reservoir on suspended-sediment loads transported by the lower Nueces River downstream from the dam to the Nueces Estuary. Annual suspended-sediment loads at the Nueces River near the Mathis, Tex., gage were considerably lower for a given annual mean discharge after the dam was completed than before the dam was completed.
\nMost of the suspended sediment transported by the Nueces River downstream from Wesley E. Seale Dam occurred during high-flow releases from the dam or during floods. During October 1964-September 1971, about 536,000 tons of suspended sediment were transported by the Nueces River past the Mathis gage. Of this amount, about 473,000 tons, or about 88 percent, were transported by large runoff events (mean streamflow exceeding 1,000 cubic feet per second).
\nTo develop the watershed model to simulate suspended-sediment concentrations and loads in the lower Nueces River watershed during 1958-2010, streamflow simulations were calibrated and tested with available data for 2001-10 from the Bluntzer and Calallen gages. Streamflow data for the Nueces River obtained from the Mathis gage were used as input to the model at the upstream boundary of the model. Simulated streamflow volumes for the Bluntzer and Calallen gages showed good agreement with measured streamflow volumes. For 2001-10, simulated streamflow at the Calallen gage was within 3 percent of measured streamflow.
\nThe HSPF model was calibrated to simulate suspended sediment using suspended-sediment data collected at the Mathis, Bluntzer, and Calallen gages during 2006-7. Model simulated suspended-sediment loads at the Calallen gage were within 5 percent of loads that were estimated, by regression, from suspended-sediment sample analysis and measured streamflow. The calibrated watershed model was used to estimate streamflow and suspended-sediment loads for 1958-2010, including loads transported to the Nueces Estuary. During 1958-2010, on average, an estimated 288 tons per day (tons/d) of suspended sediment were delivered to the lower Nueces River; an estimated 278 tons/d were delivered to the estuary. The annual suspended-sediment load was highly variable, depending on the occurrence of runoff events and high streamflows. During 1958-2010, the annual total sediment loads to the estuary varied from an estimated 3.8 to 2,490 tons/d. On average, 113 tons/d, or about 39 percent of the estimated annual suspended-sediment contribution, originated from cropland in the study watershed. Releases from Lake Corpus Christi delivered an estimated 94 tons/d of suspended sediment or about 33 percent of the 288 tons/d estimated to have been delivered to the lower Nueces River. Erosion of stream-channel bed and banks accounted for 44 tons/d or about 15 percent of the estimated total suspended-sediment load. All other land categories, except cropland, accounted for an estimated 36 tons/d, or about 12 percent of the total. An estimated 10 tons/d of suspended sediment or about 3 percent of the suspended-sediment load delivered to the lower Nueces River were removed by water withdrawals before reaching the Nueces Estuary.
\nDuring 2010, additional suspended-sediment data were collected during selected runoff events to provide new data for model testing and to help better understand the sources of suspended-sediment loads. The model was updated and used to estimate and compare sediment yields from each of 64 subwatersheds comprising the lower Nueces River watershed study area for three selected runoff events: November 20-21, 2009, September 7-8, 2010, and September 20-21, 2010. These three runoff events were characterized by heavy rainfall centered near the study area and during which minimal streamflow and suspended-sediment load entered the lower Nueces River upstream from Wesley E. Seale Dam. During all three runoff events, model simulations showed that the greatest sediment yields originated from the subwatersheds, which were largely cropland. In particular, the Bayou Creek subwatersheds were major contributors of suspended-sediment load to the lower Nueces River during the selected runoff events. During the November 2009 runoff event, high suspended-sediment concentrations in the Nueces River water withdrawn for the City of Corpus Christi public-water supply caused problems during the water-treatment process, resulting in failure to meet State water-treatment standards for turbidity in drinking water. Model simulations of the November 2009 runoff event showed that the Bayou Creek subwatersheds were the primary source of suspended-sediment loads during that runoff event.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135059","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe-Blanco River Authority; San Antonio River Authority; and San Antonio Water System","usgsCitation":"Ockerman, D.J., Heitmuller, F.T., and Wehmeyer, L.L., 2013, Sources of suspended-sediment loads in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary, south Texas, 1958–2010: U.S. Geological Survey Scientific Investigations Report 2013-5059, ix, 57 p., https://doi.org/10.3133/sir20135059.","productDescription":"ix, 57 p.","numberOfPages":"67","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":271052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135059.gif"},{"id":271053,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5059/"},{"id":271054,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5059/pdf/sir2013-5059.pdf"}],"country":"United States","state":"Texas","otherGeospatial":"Lower Nueces River Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.15,27.72 ], [ -98.15,28.26 ], [ -97.15,28.26 ], [ -97.15,27.72 ], [ -98.15,27.72 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517107dee4b0053160634243","contributors":{"authors":[{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heitmuller, Franklin T.","contributorId":67476,"corporation":false,"usgs":true,"family":"Heitmuller","given":"Franklin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":477572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wehmeyer, Loren L.","contributorId":90412,"corporation":false,"usgs":true,"family":"Wehmeyer","given":"Loren","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":477573,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045467,"text":"70045467 - 2013 - The influence of regional hydrology on nesting behavior and nest fate of the American alligator","interactions":[],"lastModifiedDate":"2013-04-18T09:11:58","indexId":"70045467","displayToPublicDate":"2013-04-15T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"The influence of regional hydrology on nesting behavior and nest fate of the American alligator","docAbstract":"Hydrologic conditions are critical to the nesting behavior and reproductive success of crocodilians. In South Florida, USA, growing human settlement has led to extensive surface water management and modification of historical water flows in the wetlands, which have affected regional nesting of the American alligator (Alligator mississippiensis). Although both natural and anthropogenic factors are considered to determine hydrologic conditions, the aspects of hydrological patterns that affect alligator nest effort, flooding (partial and complete), and failure (no hatchling) are unclear. We deconstructed annual hydrological patterns using harmonic models that estimated hydrological matrices including mean, amplitude, timing of peak, and periodicity of surface water depth and discharge and examined their effects on alligator nesting using survey data from Shark Slough, Everglades National Park, from 1985 to 2005. Nest effort increased in years with higher mean and lesser periodicity of water depth. A greater proportion of nests were flooded and failed when peak discharge occurred earlier in the year. Also, nest flooding rates were greater in years with greater periodicity of water depth, and nest failure rate was greater when mean discharge was higher. This study guides future water management decisions to mitigate negative impacts on reproduction of alligators and provides wildlife managers with a tool for assessing and modifying annual water management plans to conserve crocodilians and other wetland species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/jwmg.463","usgsCitation":"Ugarte, C.A., Bass, O.L., Nuttle, W., Mazzotti, F., Rice, K.G., Fujisaki, I., and Whelan, K.R., 2013, The influence of regional hydrology on nesting behavior and nest fate of the American alligator: Journal of Wildlife Management, v. 77, no. 1, p. 192-199, https://doi.org/10.1002/jwmg.463.","productDescription":"8 p.","startPage":"192","endPage":"199","numberOfPages":"8","ipdsId":"IP-026739","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":271050,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.463"},{"id":271051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Shark Slough Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81,5.555555555555556E-4 ], [ -81,5.555555555555556E-4 ], [ -80.00694444444444,5.555555555555556E-4 ], [ -80.00694444444444,5.555555555555556E-4 ], [ -81,5.555555555555556E-4 ] ] ] } } ] }","volume":"77","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-09-27","publicationStatus":"PW","scienceBaseUri":"517115e2e4b005316063424d","contributors":{"authors":[{"text":"Ugarte, Cristina A.","contributorId":11913,"corporation":false,"usgs":true,"family":"Ugarte","given":"Cristina","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":477560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bass, Oron L.","contributorId":108004,"corporation":false,"usgs":true,"family":"Bass","given":"Oron","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":477565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nuttle, William","contributorId":63685,"corporation":false,"usgs":true,"family":"Nuttle","given":"William","affiliations":[],"preferred":false,"id":477563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":477564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rice, Kenneth G. 0000-0001-8282-1088 krice@usgs.gov","orcid":"https://orcid.org/0000-0001-8282-1088","contributorId":117,"corporation":false,"usgs":true,"family":"Rice","given":"Kenneth","email":"krice@usgs.gov","middleInitial":"G.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":477559,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fujisaki, Ikuko","contributorId":31108,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":477561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whelan, Kevin R.T.","contributorId":53894,"corporation":false,"usgs":true,"family":"Whelan","given":"Kevin","email":"","middleInitial":"R.T.","affiliations":[],"preferred":false,"id":477562,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70045353,"text":"sir20135031 - 2013 - Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011","interactions":[],"lastModifiedDate":"2018-01-08T12:22:23","indexId":"sir20135031","displayToPublicDate":"2013-04-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5031","title":"Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011","docAbstract":"The lower Platte River corridor provides important habitats for two State- and federally listed bird species: the interior least tern (terns; Sternula antillarum athallassos) and the piping plover (plovers; Charadrius melodus). However, many of the natural morphological and hydrological characteristics of the Platte River have been altered substantially by water development, channelization, hydropower operations, and invasive vegetation encroachment, which have decreased the abundance of high-quality nesting and foraging habitat for terns and plovers. The lower Platte River (LPR), defined as 103 miles (mi) of the Platte River between its confluence with the Loup River and its confluence with the Missouri River, has narrowed since the late-19th and early-20th centuries, yet it partially retains many geomorphologic and hydrologic characteristics important to terns and plovers. These birds nest on the sandbars in the river and along shorelines at sand- and gravel-pit lakes in the adjacent valley. The need to balance continued economic, infrastructure, and resource development with the conservation of important physical and aquatic habitat resources requires increased understanding of the physical and biological dynamics of the lower Platte River. Spatially and temporally rich datasets for emergent sandbar habitats are necessary to quantify emergent sandbar dynamics relative to hypothesized controls and stressors. In cooperation with the Lower Platte South Natural Resources District, the U.S. Geological Survey initiated a pilot study of emergent sandbar dynamics along a 22-mi segment of the LPR downstream from its confluence with Salt Creek, near Ashland, Nebraska. The purposes of the study were to: (1) develop methods to rapidly assess sandbar geometries and locations in a wide, sand-bed river, and (2) apply and validate the method to assess emergent sandbar dynamics over three seasons in 2011. An examination of the height of sandbars relative to the local stage of the formative discharge event, and how subsequent river discharges, of both high and low magnitude, alter sandbar geometries and abundance within the LPR was of particular interest. A “rapid-assessment” method was developed with the goal of characterizing the spatial distribution and habitat-relevant geometries of the complete population of sandbars along the study segment. Three primary measures were used to assess emergent sandbar dynamics in the study segment: sandbar area, sandbar height, and sandbar location. Data to derive these measures were collected during three, week-long survey periods in 2011, herein named “spring survey period,” “summer survey period,” and “fall survey period.” Emergent sandbars were grouped into one of three generalized types: (1) bank-attached, (2) island-attached, and (3) mid-channel.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135031","collaboration":"Prepared in cooperation with the Lower Platte South Natural Resources District","usgsCitation":"Alexander, J.S., Schultze, D.M., and Zelt, R.B., 2013, Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011: U.S. Geological Survey Scientific Investigations Report 2013-5031, vi, 42 p., https://doi.org/10.3133/sir20135031.","productDescription":"vi, 42 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-043639","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":270773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135031.gif"},{"id":270771,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5031/"},{"id":270772,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5031/sir13_5031.pdf"}],"scale":"100000","projection":"Universal Transverse Mercator projection, Zone 15","datum":"North American Datum of 1983","country":"United States","state":"Nebraska","county":"Cass;Sarpy;Saunders","otherGeospatial":"Platte River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.416667,40.966667 ], [ -96.416667,41.166667 ], [ -95.916667,41.166667 ], [ -95.916667,40.966667 ], [ -96.416667,40.966667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51667bd9e4b0bba30b388baa","contributors":{"authors":[{"text":"Alexander, Jason S. 0000-0002-1602-482X jalexand@usgs.gov","orcid":"https://orcid.org/0000-0002-1602-482X","contributorId":2802,"corporation":false,"usgs":true,"family":"Alexander","given":"Jason","email":"jalexand@usgs.gov","middleInitial":"S.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schultze, Devin M.","contributorId":90191,"corporation":false,"usgs":true,"family":"Schultze","given":"Devin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zelt, Ronald B. 0000-0001-9024-855X rbzelt@usgs.gov","orcid":"https://orcid.org/0000-0001-9024-855X","contributorId":300,"corporation":false,"usgs":true,"family":"Zelt","given":"Ronald","email":"rbzelt@usgs.gov","middleInitial":"B.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477276,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}