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":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest 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":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western 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. 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":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":477620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"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":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":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","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":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":70045360,"text":"sir20135052 - 2013 - Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10","interactions":[],"lastModifiedDate":"2013-04-10T21:52:21","indexId":"sir20135052","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":"2013-5052","title":"Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10","docAbstract":"Elevated levels of fluvial sediment can reduce the biological productivity of aquatic systems, impair freshwater quality, decrease reservoir storage capacity, and decrease the capacity of hydraulic structures. The need to measure fluvial sediment has led to the development of sediment surrogate technologies, particularly in locations where streamflow alone is not a good estimator of sediment load because of regulated flow, load hysteresis, episodic sediment sources, and non-equilibrium sediment transport. An effective surrogate technology is low maintenance and sturdy over a range of hydrologic conditions, and measured variables can be modeled to estimate suspended-sediment concentration (SSC), load, and duration of elevated levels on a real-time basis. Among the most promising techniques is the measurement of acoustic backscatter strength using acoustic Doppler velocity meters (ADVMs) deployed in rivers. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, Walla Walla District, evaluated the use of acoustic backscatter, turbidity, laser diffraction, and streamflow as surrogates for estimating real-time SSC and loads in the Clearwater and Snake Rivers, which adjoin in Lewiston, Idaho, and flow into Lower Granite Reservoir. The study was conducted from May 2008 to September 2010 and is part of the U.S. Army Corps of Engineers Lower Snake River Programmatic Sediment Management Plan to identify and manage sediment sources in basins draining into lower Snake River reservoirs.\n\nCommercially available acoustic instruments have shown great promise in sediment surrogate studies because they require little maintenance and measure profiles of the surrogate parameter across a sampling volume rather than at a single point. The strength of acoustic backscatter theoretically increases as more particles are suspended in the water to reflect the acoustic pulse emitted by the ADVM. ADVMs of different frequencies (0.5, 1.5, and 3 Megahertz) were tested to target various sediment grain sizes. Laser diffraction and turbidity also were tested as surrogate technologies. Models between SSC and surrogate variables were developed using ordinary least-squares regression. Acoustic backscatter using the high frequency ADVM at each site was the best predictor of sediment, explaining 93 and 92 percent of the variability in SSC and matching sediment sample data within +8.6 and +10 percent, on average, at the Clearwater River and Snake River study sites, respectively. Additional surrogate models were developed to estimate sand and fines fractions of suspended sediment based on acoustic backscatter. Acoustic backscatter generally appears to be a better estimator of suspended sediment concentration and load over short (storm event and monthly) and long (annual) time scales than transport curves derived solely from the regression of conventional sediment measurements and streamflow. Changing grain sizes, the presence of organic matter, and aggregation of sediments in the river likely introduce some variability in the model between acoustic backscatter and SSC.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135052","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Wood, M.S., and Teasdale, G.N., 2013, Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10: U.S. Geological Survey Scientific Investigations Report 2013-5052, vi, 30 p., https://doi.org/10.3133/sir20135052.","productDescription":"vi, 30 p.","numberOfPages":"40","additionalOnlineFiles":"N","temporalStart":"2008-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":270796,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5052/"},{"id":270797,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5052/pdf/sir20135052.pdf"},{"id":270798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135052.jpg"}],"country":"United States","state":"Idaho;Washington","otherGeospatial":"Clearwater River;Snake River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,42.0 ], [ -124.8,49.0 ], [ -111.0,49.0 ], [ -111.0,42.0 ], [ -124.8,42.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51667bdae4b0bba30b388bae","contributors":{"authors":[{"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":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teasdale, Gregg N.","contributorId":77440,"corporation":false,"usgs":true,"family":"Teasdale","given":"Gregg","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":477286,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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}]}} ,{"id":70044568,"text":"70044568 - 2013 - A quantitative assessment of the conservation benefits of the Wetlands Reserve Program to amphibians","interactions":[],"lastModifiedDate":"2013-04-10T22:36:56","indexId":"70044568","displayToPublicDate":"2013-04-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A quantitative assessment of the conservation benefits of the Wetlands Reserve Program to amphibians","docAbstract":"The Mississippi Alluvial Valley (MAV) originally consisted of nearly contiguous bottomland hardwood (BLH) forest encompassing approximately 10 million hectares. Currently, only 20–25% of the historical BLH forests remain in small patches fragmented by agricultural lands. The Wetlands Reserve Program (WRP) was established to restore and protect the functions and values of wetlands in agricultural landscapes. To assess the potential benefit of WRP restoration to amphibians, we surveyed 30 randomly selected WRP sites and 20 nearby agricultural sites in the Mississippi Delta. We made repeat visits to each site from May to August 2008 and performed both visual encounter and vocalization surveys. We analyzed the encounter history data for 11 anuran species using a Bayesian hierarchical occupancy model that estimated detection probability and probability of occurrence simultaneously for each species. Nine of the 11 species had higher probabilities of occurrence at WRP sites compared to agriculture. Derived estimates of species richness were also higher for WRP sites. Five anuran species were significantly more likely to occur in WRP than in agriculture, four of which were among the most aquatic species. It appears that the restoration of a more permanent hydrology at the WRP sites may be the primary reason for this result. Although amphibians represent only one group of wildlife species, they are useful for evaluating restoration benefits for wildlife because of their intermediate trophic position. The methods used in this study to evaluate the benefit of restoration could be used in other locations and with other groups of indicator species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Restoration Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1526-100X.2012.00881.x","usgsCitation":"Waddle, J., Glorioso, B.M., and Faulkner, S.P., 2013, A quantitative assessment of the conservation benefits of the Wetlands Reserve Program to amphibians: Restoration Ecology, v. 21, no. 2, p. 200-206, https://doi.org/10.1111/j.1526-100X.2012.00881.x.","productDescription":"7 p.","startPage":"200","endPage":"206","ipdsId":"IP-029595","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":269264,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1526-100X.2012.00881.x"},{"id":270803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.66,30.17 ], [ -91.66,35.0 ], [ -88.1,35.0 ], [ -88.1,30.17 ], [ -91.66,30.17 ] ] ] } } ] }","volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-07-05","publicationStatus":"PW","scienceBaseUri":"51667bcfe4b0bba30b388b9e","contributors":{"authors":[{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":89982,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[],"preferred":false,"id":475877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glorioso, Brad M. 0000-0002-5400-7414 gloriosob@usgs.gov","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":4241,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","email":"gloriosob@usgs.gov","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":475876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulkner, Stephen P. 0000-0001-5295-1383 faulkners@usgs.gov","orcid":"https://orcid.org/0000-0001-5295-1383","contributorId":374,"corporation":false,"usgs":true,"family":"Faulkner","given":"Stephen","email":"faulkners@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":475875,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048497,"text":"70048497 - 2013 - Adaptive management of flows from dams: a win-win framework for water users","interactions":[],"lastModifiedDate":"2014-03-19T10:01:04","indexId":"70048497","displayToPublicDate":"2013-04-09T08:42:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Adaptive management of flows from dams: a win-win framework for water users","docAbstract":"Alabama is blessed with more than 77,000 miles of rivers and streams that carve through the terrestrial landscape of the state. When you think about it, every road you drive on crosses a river and many of our major cities are located on the bank of a river. In fact, Alabama's capital cities - Cahawba (Dallas County; 1820-1826), Tuscaloosa (Tuscaloosa County; 1826-1846), and Montgomery County; 1846-present) - were all located on major rivers. It is estimated by the U.S. Geological Survey that 10 percent of the freshwater resources in the continental United States flows through Alabama. When you look at a map of its hydrology, the state is blue!","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Auburn Speaks: On Water","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Auburn University","usgsCitation":"Irwin, E.R., 2013, Adaptive management of flows from dams: a win-win framework for water users, chap. of Auburn Speaks: On Water, p. 264-271.","productDescription":"8 p.","startPage":"264","endPage":"271","ipdsId":"IP-043022","costCenters":[{"id":104,"text":"Alabama Cooperative Fish & Wildlife Unit","active":false,"usgs":true}],"links":[{"id":284202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284201,"type":{"id":11,"text":"Document"},"url":"https://www.auburnspeaks.org/on-water/"}],"country":"United States","state":"Alabama","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.4732,30.1941 ], [ -88.4732,35.0079 ], [ -84.8882,35.0079 ], [ -84.8882,30.1941 ], [ -88.4732,30.1941 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4b2ce4b0b290850f034e","contributors":{"authors":[{"text":"Irwin, Elise R. 0000-0002-6866-4976 eirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-6866-4976","contributorId":2588,"corporation":false,"usgs":true,"family":"Irwin","given":"Elise","email":"eirwin@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":484838,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045326,"text":"fs20133016 - 2013 - Effects of past and future groundwater development on the hydrologic system of Verde Valley, Arizona","interactions":[],"lastModifiedDate":"2013-04-09T15:15:34","indexId":"fs20133016","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3016","title":"Effects of past and future groundwater development on the hydrologic system of Verde Valley, Arizona","docAbstract":"Communities in central Arizona’s Verde Valley must manage limited water supplies in the face of rapidly growing populations. Developing groundwater resources to meet human needs has raised questions about the effects of groundwater withdrawals by pumping on the area’s rivers and streams, particularly the Verde River. U.S. Geological Survey hydrologists used a regional groundwater flow model to simulate the effects of groundwater pumping on streamflow in the Verde River. The study found that streamflow in the Verde River between 1910 and 2005 had been reduced as the result of streamflow depletion by groundwater pumping, also known as capture. Additionally, using three hypothetical scenarios for a period from 2005 to 2110, the study’s findings suggest that streamflow reductions will continue and may increase in the future.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133016","usgsCitation":"Garner, B.D., and Pool, D.R., 2013, Effects of past and future groundwater development on the hydrologic system of Verde Valley, Arizona: U.S. Geological Survey Fact Sheet 2013-3016, 2 p., https://doi.org/10.3133/fs20133016.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":270715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133016.gif"},{"id":270713,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3016/"},{"id":270714,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3016/fs2013-3016.pdf"}],"scale":"100000","projection":"Universal transverse mercator, Zone 12","country":"United States","state":"Arizona","otherGeospatial":"Dry Creek;Oak Creek;Verde River;Verde Valley;West Clear Creek;Wet Beaver Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.081146,34.565383 ], [ -112.081146,35.145740 ], [ -111.277771,35.145740 ], [ -111.277771,34.565383 ], [ -112.081146,34.565383 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51652a5ee4b077fa94dadf47","contributors":{"authors":[{"text":"Garner, Bradley D. 0000-0002-6912-5093 bdgarner@usgs.gov","orcid":"https://orcid.org/0000-0002-6912-5093","contributorId":2133,"corporation":false,"usgs":true,"family":"Garner","given":"Bradley","email":"bdgarner@usgs.gov","middleInitial":"D.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":477224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pool, D. R.","contributorId":75581,"corporation":false,"usgs":true,"family":"Pool","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":477225,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045327,"text":"sir20135029 - 2013 - Human effects on the hydrologic system of the Verde Valley, central Arizona, 1910–2005 and 2005–2110, using a regional groundwater flow model","interactions":[],"lastModifiedDate":"2018-03-23T14:28:22","indexId":"sir20135029","displayToPublicDate":"2013-04-09T00:00:00","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":"2013-5029","title":"Human effects on the hydrologic system of the Verde Valley, central Arizona, 1910–2005 and 2005–2110, using a regional groundwater flow model","docAbstract":"Water budgets were developed for the Verde Valley of central Arizona in order to evaluate the degree to which human stresses have affected the hydrologic system and might affect it in the future. The Verde Valley is a portion of central Arizona wherein concerns have been raised about water availability, particularly perennial base flow of the Verde River. The Northern Arizona Regional Groundwater Flow Model (NARGFM) was used to generate the water budgets and was run in several configurations for the 1910–2005 and 2005–2110 time periods. The resultant water budgets were subtracted from one another in order to quantify the relative changes that were attributable solely to human stresses; human stresses included groundwater withdrawals and incidental and artificial recharge but did not include, for example, human effects on the global climate. Three hypothetical and varied conditions of human stresses were developed and applied to the model for the 2005–2110 period. On the basis of this analysis, human stresses during 1910–2005 were found to have already affected the hydrologic system of the Verde Valley, and human stresses will continue to affect the hydrologic system during 2005–2110. Riparian evapotranspiration decreased and underflow into the Verde Valley increased because of human stresses, and net groundwater discharge to the Verde River in the Verde Valley decreased for the 1910–2005 model runs. The model also showed that base flow at the upstream end of the study area, as of 2005, was about 4,900 acre-feet per year less than it would have been in the absence of human stresses. At the downstream end of the Verde Valley, base flow had been reduced by about 10,000 acre-feet per year by the year 2005 because of human stresses. For the 2005–2110 period, the model showed that base flow at the downstream end of the Verde Valley may decrease by an additional 5,400 to 8,600 acre-feet per year because of past, ongoing, and hypothetical future human stresses. The process known as capture (or streamflow depletion caused by the pumping of groundwater) was the reason for these human-stress-induced changes in water-budget components.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135029","collaboration":"Prepared in cooperation with the Verde River Basin Partnership and the Town of Clarkdale","usgsCitation":"Garner, B.D., Pool, D.R., Tillman, F., and Forbes, B., 2013, Human effects on the hydrologic system of the Verde Valley, central Arizona, 1910–2005 and 2005–2110, using a regional groundwater flow model: U.S. Geological Survey Scientific Investigations Report 2013-5029, vi, 47 p., https://doi.org/10.3133/sir20135029.","productDescription":"vi, 47 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":270718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135029.gif"},{"id":270716,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5029/"},{"id":270717,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5029/sir2013-5029.pdf"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.82,31.33 ], [ -114.82,37.0 ], [ -109.0,37.0 ], [ -109.0,31.33 ], [ -114.82,31.33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f314e4b0bc0bec0a077b","contributors":{"authors":[{"text":"Garner, Bradley D. 0000-0002-6912-5093 bdgarner@usgs.gov","orcid":"https://orcid.org/0000-0002-6912-5093","contributorId":2133,"corporation":false,"usgs":true,"family":"Garner","given":"Bradley","email":"bdgarner@usgs.gov","middleInitial":"D.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":477227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pool, D. R.","contributorId":75581,"corporation":false,"usgs":true,"family":"Pool","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":477229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":1629,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred D.","email":"ftillman@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forbes, Brandon T. bforbes@usgs.gov","contributorId":4625,"corporation":false,"usgs":true,"family":"Forbes","given":"Brandon T.","email":"bforbes@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477228,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042906,"text":"70042906 - 2013 - An isotope-dilution standard GC/MS/MS method for steroid hormones in water","interactions":[],"lastModifiedDate":"2021-05-27T16:01:28.036606","indexId":"70042906","displayToPublicDate":"2013-04-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"An isotope-dilution standard GC/MS/MS method for steroid hormones in water","docAbstract":"An isotope-dilution quantification method was developed for 20 natural and synthetic steroid hormones and additional compounds in filtered and unfiltered water. Deuterium- or carbon-13-labeled isotope-dilution standards (IDSs) are added to the water sample, which is passed through an octadecylsilyl solid-phase extraction (SPE) disk. Following extract cleanup using Florisil SPE, method compounds are converted to trimethylsilyl derivatives and analyzed by gas chromatography with tandem mass spectrometry. Validation matrices included reagent water, wastewater-affected surface water, and primary (no biological treatment) and secondary wastewater effluent. Overall method recovery for all analytes in these matrices averaged 100%; with overall relative standard deviation of 28%. Mean recoveries of the 20 individual analytes for spiked reagent-water samples prepared along with field samples analyzed in 2009–2010 ranged from 84–104%, with relative standard deviations of 6–36%. Detection levels estimated using ASTM International’s D6091–07 procedure range from 0.4 to 4 ng/L for 17 analytes. Higher censoring levels of 100 ng/L for bisphenol A and 200 ng/L for cholesterol and 3-beta-coprostanol are used to prevent bias and false positives associated with the presence of these analytes in blanks. Absolute method recoveries of the IDSs provide sample-specific performance information and guide data reporting. Careful selection of labeled compounds for use as IDSs is important because both inexact IDS-analyte matches and deuterium label loss affect an IDS’s ability to emulate analyte performance. Six IDS compounds initially tested and applied in this method exhibited deuterium loss and are not used in the final method.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Evaluating Veterinary Pharmaceutical Behavior in the Environment: ACS Symposium Series","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/bk-2013-1126.ch004","usgsCitation":"Foreman, W., Gray, J.L., ReVello, R., Lindley, C.E., and Losche, S.A., 2013, An isotope-dilution standard GC/MS/MS method for steroid hormones in water, chap. of Evaluating Veterinary Pharmaceutical Behavior in the Environment: ACS Symposium Series, v. 1126, p. 57-136, https://doi.org/10.1021/bk-2013-1126.ch004.","productDescription":"80 p.","startPage":"57","endPage":"136","ipdsId":"IP-038162","costCenters":[{"id":140,"text":"Branch of Analytical Serv (National Water Quality Laboratory)","active":false,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":270671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270670,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/bk-2013-1126.ch004"}],"volume":"1126","noUsgsAuthors":false,"publicationDate":"2013-03-14","publicationStatus":"PW","scienceBaseUri":"5163d8dae4b0b7010f820135","contributors":{"authors":[{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":472561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":true,"id":472560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"ReVello, Rhiannon C. rcrevell@usgs.gov","contributorId":4128,"corporation":false,"usgs":true,"family":"ReVello","given":"Rhiannon C.","email":"rcrevell@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindley, Chris E. clindley@usgs.gov","contributorId":2337,"corporation":false,"usgs":true,"family":"Lindley","given":"Chris","email":"clindley@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":472562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Losche, Scott A. salosche@usgs.gov","contributorId":4694,"corporation":false,"usgs":true,"family":"Losche","given":"Scott","email":"salosche@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":472564,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045265,"text":"ds756 - 2013 - A compilation of U.S. Geological Survey pesticide concentration data for water and sediment in the Sacramento–San Joaquin Delta region: 1990–2010","interactions":[],"lastModifiedDate":"2015-07-07T07:21:40","indexId":"ds756","displayToPublicDate":"2013-04-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"756","title":"A compilation of U.S. Geological Survey pesticide concentration data for water and sediment in the Sacramento–San Joaquin Delta region: 1990–2010","docAbstract":"Beginning around 2000, abundance indices of four pelagic fishes (delta smelt, striped bass, longfin smelt, and threadfin shad) within the San Francisco Bay and Sacramento–San Joaquin Delta began to decline sharply (Sommer and others, 2007). These declines collectively became known as the pelagic organism decline (POD). No single cause has been linked to this decline, and current theories suggest that combinations of multiple stressors are likely to blame. Contaminants (including current-use pesticides) are one potential stressor being investigated for its role in the POD (Anderson, 2007). Pesticide concentration data collected by the U.S. Geological Survey (USGS) at multiple sites in the delta region over the past two decades are critical to understanding the potential effects of current-use pesticides on species of concern as well as the overall health of the delta ecosystem. In April 2010, a compilation of contaminant data for the delta region was published by the State Water Resources Control Board (Johnson and others, 2010). Pesticide occurrence was the major focus of this report, which concluded that “there was insufficient high quality data available to make conclusions about the potential role of specific contaminants in the POD.” The report cited multiple sources; however, data collected by the USGS were not included in the publication even though these data met all criteria listed for inclusion in the report. What follows is a summary of publicly available USGS data for pesticide concentrations in surface water and sediments within the Sacramento–San Joaquin Delta region from the years 1990 through 2010. Data were retrieved though the USGS National Water Information System (NWIS) database, a publicly available online-data repository (U.S. Geological Survey, 1998), and from published USGS reports (also available online at http://pubs.er.usgs.gov/). The majority of the data were collected in support of two long term USGS monitoring programs—National Water Quality Assessment Program (NAWQA; http://water.usgs.gov/ nawqa/) and National Stream Quality Accounting Network (NASQAN; http://water.usgs.gov/nasqan/)—and through projects associated with the USGS Toxics Substances Hydrology Program (http://toxics.usgs.gov/). In addition, data were collected during multiple research projects that were supported by various federal, state, and local agencies. Although these data have been previously published in some form, it is hoped that by focusing on samples collected within the delta region and presenting these data in a concise format, they will be a valuable resource for scientists, resource managers, and members of the public working to understand the role of pesticides in the POD and their potential effects on the overall health of the delta ecosystem.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds756","usgsCitation":"Orlando, J., 2013, A compilation of U.S. Geological Survey pesticide concentration data for water and sediment in the Sacramento–San Joaquin Delta region: 1990–2010: U.S. Geological Survey Data Series 756, Report: v, 48 p.; Appendixes, https://doi.org/10.3133/ds756.","productDescription":"Report: v, 48 p.; Appendixes","numberOfPages":"55","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":270596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds756.jpg"},{"id":270595,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/756/ds756_appendixes.xlsx"},{"id":270593,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/756/"},{"id":270594,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/756/pdf/ds756.pdf"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-san Joaquin Delta Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.47695922851562,\n 37.80327385185868\n ],\n [\n -122.47695922851562,\n 38.381498197198816\n ],\n [\n -121.48818969726561,\n 38.591113776147445\n ],\n [\n -121.05697631835938,\n 38.052416771864834\n ],\n [\n -121.53762817382814,\n 37.80327385185868\n ],\n [\n -122.47695922851562,\n 37.80327385185868\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515fe720e4b03707eea09cfd","contributors":{"authors":[{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":477162,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045266,"text":"sir20125229 - 2013 - The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model","interactions":[],"lastModifiedDate":"2013-04-05T10:25:18","indexId":"sir20125229","displayToPublicDate":"2013-04-05T00:00:00","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":"2012-5229","title":"The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model","docAbstract":"This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include: assessment of model functionality, brief descriptions of the 7 basic output tables, assessment of the rate of change in land-use allocation pools over time, locations and amounts of the spatially explicit probabilities of land-use transitions by real estate commodity, and analysis of the state change from today’s existing land cover to potential land uses in the future. Assumptions and limitations of the model are presented. This report concludes with suggested next steps to support the continued utility of the LUSM and additional research avenues.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125229","usgsCitation":"Forney, W.M., Oldham, I.B., and Crescenti, N., 2013, The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model: U.S. Geological Survey Scientific Investigations Report 2012-5229, vi, 54 p., https://doi.org/10.3133/sir20125229.","productDescription":"vi, 54 p.","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":270599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125229.gif"},{"id":270597,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5229/"},{"id":270598,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5229/sir2012-5229.pdf"}],"country":"United States","state":"Nevada","otherGeospatial":"Lake Tahoe Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.25,38.66 ], [ -120.25,39.33 ], [ -119.83,39.33 ], [ -119.83,38.66 ], [ -120.25,38.66 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515fe728e4b03707eea09d01","contributors":{"authors":[{"text":"Forney, William M.","contributorId":43490,"corporation":false,"usgs":true,"family":"Forney","given":"William","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oldham, I. Benson","contributorId":101377,"corporation":false,"usgs":true,"family":"Oldham","given":"I.","email":"","middleInitial":"Benson","affiliations":[],"preferred":false,"id":477165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crescenti, Neil","contributorId":86239,"corporation":false,"usgs":true,"family":"Crescenti","given":"Neil","email":"","affiliations":[],"preferred":false,"id":477164,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045208,"text":"70045208 - 2013 - Using the KINEROS2 modeling framework to evaluate the increase in storm runoff from residential development in a semi-arid environment","interactions":[],"lastModifiedDate":"2013-05-20T13:43:30","indexId":"70045208","displayToPublicDate":"2013-04-02T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Using the KINEROS2 modeling framework to evaluate the increase in storm runoff from residential development in a semi-arid environment","docAbstract":"The increase in runoff from urbanization is well known; one extreme example comes from a 13 hectare residential neighborhood in southeast Arizona where runoff was 27 times greater than an adjacent grassland watershed over a forty‐month period from 2005 to 2008. Rainfall‐runoff modeling using the newly‐described KINEROS2 urban element and tension infiltrometer measurements indicate that 17±14 percent of this increase in runoff is due to a 53 percent decrease in the saturated hydraulic conductivity of constructed pervious areas, as compared to the undeveloped grassland. Directly connected impervious areas, primarily streets and driveways, cause 56 percent of the increase in runoff, and indirectly connected impervious areas, primarily rooftops and sidewalks, and a decrease in canopy interception account for the remaining 27 percent increase. Tension infiltrometer measurements show that saturated hydraulic conductivity (Ks) is about double in the grassland watershed than in the urban watershed, 6.2 ± 3.5mm/hr and 2.9 ± 1.6mm/hr, respectively. Ks in the urban watershed identified from calibrating the rainfall‐runoff model to measured runoff is 9.5 ± 2.8 mm/hr—higher than what was measured but much lower than the 26 mm/hr value indicated by a soil‐texture based KINEROS2 parameter look‐up table. A new component of the KINEROS2 modeling framework, the urban element, forms the basis for the model by simulating a contiguous row of houses and the adjoining street as a series of pervious and impervious overland flow planes. Tests using different levels of discretization found that watershed geometry can be represented in a simplified manner, although more detailed discretization led to better model performance.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrologic Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ASCE","doi":"10.1061/(ASCE)HE.1943-5584.0000655","usgsCitation":"Kennedy, J.R., Goodrich, D.C., and Unkrich, C.L., 2013, Using the KINEROS2 modeling framework to evaluate the increase in storm runoff from residential development in a semi-arid environment: Journal of Hydrologic Engineering, v. 18, no. 6, p. 698-706, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000655.","productDescription":"9 p.","startPage":"698","endPage":"706","numberOfPages":"9","additionalOnlineFiles":"N","ipdsId":"IP-032532","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":270497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270494,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000655"}],"country":"United States","state":"Arizona","county":"Cochise","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.46,31.33 ], [ -110.46,32.43 ], [ -109.0,32.43 ], [ -109.0,31.33 ], [ -110.46,31.33 ] ] ] } } ] }","volume":"18","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515befe0e4b075500ee5ca12","contributors":{"authors":[{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodrich, David C.","contributorId":65552,"corporation":false,"usgs":false,"family":"Goodrich","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":477025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Unkrich, Carl L.","contributorId":73479,"corporation":false,"usgs":true,"family":"Unkrich","given":"Carl","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":477026,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148175,"text":"70148175 - 2013 - Effects of hydrologic connectivity and environmental nariables on nekton assemblage in a coastal marsh system","interactions":[],"lastModifiedDate":"2015-05-26T11:16:35","indexId":"70148175","displayToPublicDate":"2013-04-01T12:15:00","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":"Effects of hydrologic connectivity and environmental nariables on nekton assemblage in a coastal marsh system","docAbstract":"Hydrologic connectivity and environmental variation can influence nekton assemblages in coastal ecosystems. We evaluated the effects of hydrologic connectivity (permanently connected pond: PCP; temporary connected pond: TCP), salinity, vegetation coverage, water depth and other environmental variables on seasonal nekton assemblages in freshwater, brackish, and saline marshes of the Chenier Plain, Louisiana, USA. We hypothesize that 1) nekton assemblages in PCPs have higher metrics (density, biomass, assemblage similarity) than TCPs within all marsh types and 2) no nekton species would be dominant across all marsh types. In throw traps, freshwater PCPs in Fall (36.0 ± 1.90) and Winter 2009 (43.2 ± 22.36) supported greater biomass than freshwater TCPs (Fall 2009: 9.1 ± 4.65; Winter 2009: 8.3 ± 3.42). In minnow traps, saline TCPs (5.9 ± 0.85) in Spring 2009 had higher catch per unit effort than saline PCPs (0.7 ± 0.67). Our data only partially support our first hypothesis as freshwater marsh PCPs had greater assemblage similarity than TCPs. As predicted by our second hypothesis, no nekton species dominated across all marsh types. Nekton assemblages were structured by individual species responses to the salinity gradient as well as pond habitat attributes (submerged aquatic vegetation coverage, dissolved oxygen, hydrologic connectivity).
","language":"English","publisher":"Society of Wetland Scientists","publisherLocation":"McClean, VA","doi":"10.1007/s13157-013-0386-0","collaboration":"Louisiana Department of Wildlife and Fisheries; U.S. Fish and Wildlife Service; International Crane Foundation","usgsCitation":"Kang, S., and King, S.L., 2013, Effects of hydrologic connectivity and environmental nariables on nekton assemblage in a coastal marsh system: Wetlands, v. 33, no. 2, p. 321-334, https://doi.org/10.1007/s13157-013-0386-0.","productDescription":"14 p.","startPage":"321","endPage":"334","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-036540","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-02-05","publicationStatus":"PW","scienceBaseUri":"5565993ee4b0d9246a9eb61b","contributors":{"authors":[{"text":"Kang, Sung-Ryong","contributorId":140927,"corporation":false,"usgs":false,"family":"Kang","given":"Sung-Ryong","email":"","affiliations":[],"preferred":false,"id":547609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547533,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70041624,"text":"70041624 - 2013 - Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon","interactions":[],"lastModifiedDate":"2013-11-14T11:31:44","indexId":"70041624","displayToPublicDate":"2013-04-01T11:27:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon","docAbstract":"We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect interannual changes in total recharge. These results provide insights into the possible impacts of climate change to other regional aquifer systems, and the streams they support, where discharge points represent a range of flow system scales.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2013.01.019","usgsCitation":"Waibel, M.S., Gannett, M.W., Chang, H., and Hulbe, C.L., 2013, Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon: Journal of Hydrology, v. 486, p. 187-201, https://doi.org/10.1016/j.jhydrol.2013.01.019.","productDescription":"15 p.","startPage":"187","endPage":"201","numberOfPages":"15","ipdsId":"IP-040209","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":279076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279075,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2013.01.019"}],"country":"United States","state":"Oregon","otherGeospatial":"Deschutes Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5,43.0 ], [ -122.5,45.0 ], [ -120.5,45.0 ], [ -120.5,43.0 ], [ -122.5,43.0 ] ] ] } } ] }","volume":"486","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528607a5e4b00926c21865bf","contributors":{"authors":[{"text":"Waibel, Michael S.","contributorId":19984,"corporation":false,"usgs":true,"family":"Waibel","given":"Michael","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":470001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gannett, Marshall W. 0000-0003-2498-2427 mgannett@usgs.gov","orcid":"https://orcid.org/0000-0003-2498-2427","contributorId":2942,"corporation":false,"usgs":true,"family":"Gannett","given":"Marshall","email":"mgannett@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chang, Heejun","contributorId":14705,"corporation":false,"usgs":true,"family":"Chang","given":"Heejun","email":"","affiliations":[],"preferred":false,"id":470000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hulbe, Christina L.","contributorId":93371,"corporation":false,"usgs":true,"family":"Hulbe","given":"Christina","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":470002,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70129183,"text":"70129183 - 2013 - Symposium 9: Rocky Mountain futures: preserving, utilizing, and sustaining Rocky Mountain ecosystems","interactions":[],"lastModifiedDate":"2014-10-21T10:45:01","indexId":"70129183","displayToPublicDate":"2013-04-01T10:43:55","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1121,"text":"Bulletin of the Ecological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Symposium 9: Rocky Mountain futures: preserving, utilizing, and sustaining Rocky Mountain ecosystems","docAbstract":"In 2002 we published Rocky Mountain Futures, an Ecological Perspective (Island Press) to examine the cumulative ecological effects of human activity in the Rocky Mountains. We concluded that multiple local activities concerning land use, hydrologic manipulation, and resource extraction have altered ecosystems, although there were examples where the “tyranny of small decisions” worked in a positive way toward more sustainable coupled human/environment interactions. Superimposed on local change was climate change, atmospheric deposition of nitrogen and other pollutants, regional population growth, and some national management policies such as fire suppression.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Ecological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/0012-9623-94.2.195","usgsCitation":"Baron, J., Seastedt, T., Fagre, D.B., Hicke, J.A., Tomback, D., Garcia, E., Bowen, Z.H., and Logan, J.A., 2013, Symposium 9: Rocky Mountain futures: preserving, utilizing, and sustaining Rocky Mountain ecosystems: Bulletin of the Ecological Society of America, v. 94, no. 2, p. 195-199, https://doi.org/10.1890/0012-9623-94.2.195.","productDescription":"5 p.","startPage":"195","endPage":"199","numberOfPages":"5","ipdsId":"IP-043738","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":473890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/0012-9623-94.2.195","text":"Publisher Index Page"},{"id":295537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295467,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/0012-9623-94.2.195"},{"id":295468,"type":{"id":15,"text":"Index Page"},"url":"https://www.esajournals.org/doi/abs/10.1890/0012-9623-94.2.195"}],"volume":"94","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"544775c1e4b0f888a81b834c","contributors":{"authors":[{"text":"Baron, Jill S. 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":822,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seastedt, Timothy","contributorId":11972,"corporation":false,"usgs":true,"family":"Seastedt","given":"Timothy","email":"","affiliations":[],"preferred":false,"id":503529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":503528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hicke, Jeffrey A.","contributorId":36475,"corporation":false,"usgs":true,"family":"Hicke","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":503531,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tomback, Diana","contributorId":32850,"corporation":false,"usgs":true,"family":"Tomback","given":"Diana","affiliations":[],"preferred":false,"id":503530,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garcia, Elizabeth","contributorId":91426,"corporation":false,"usgs":true,"family":"Garcia","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":503533,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bowen, Zachary H. 0000-0002-8656-1831 bowenz@usgs.gov","orcid":"https://orcid.org/0000-0002-8656-1831","contributorId":821,"corporation":false,"usgs":true,"family":"Bowen","given":"Zachary","email":"bowenz@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503526,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Logan, Jesse A.","contributorId":66617,"corporation":false,"usgs":true,"family":"Logan","given":"Jesse","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":503532,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70046394,"text":"70046394 - 2013 - Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes","interactions":[],"lastModifiedDate":"2013-07-25T10:25:57","indexId":"70046394","displayToPublicDate":"2013-04-01T10:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"title":"Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes","docAbstract":"The Water Availability Tool for Environmental Resources (WATER) is a TOPMODEL-based hydrologic model that depends on spatially accurate soils data to function in diverse terranes. In Kentucky, this includes mountainous regions, karstic plateau, and alluvial plains. Soils data are critical because they quantify the space to store water, as well as how water moves through the soil to the stream during storm events. We compared how the model performs using two different sources of soils data--Soil Survey Geographic Database (SSURGO) and State Soil Geographic Database laboratory data (STATSGO)--for 21 basins ranging in size from 17 to 1564 km2. Model results were consistently better when SSURGO data were used, likely due to the higher field capacity, porosity, and available-water holding capacity, which cause the model to store more soil-water in the landscape and improve streamflow estimates for both low- and high-flow conditions. In addition, there were significant differences in the conductivity multiplier and scaling parameter values that describe how water moves vertically and laterally, respectively, as quantified by TOPMODEL. We also evaluated whether partitioning areas that drain to streams via sinkholes in karstic basins as separate hydrologic modeling units (HMUs) improved model performance. There were significant differences between HMUs in properties that control soil-water storage in the model, although the effect of partitioning these HMUs on streamflow simulation was inconclusive.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Soil Science Society of America Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj2012.0069","usgsCitation":"Williamson, T., Taylor, C.J., and Newson, J.K., 2013, Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes: Soil Science Society of America Journal, v. 77, no. 3, p. 877-889, https://doi.org/10.2136/sssaj2012.0069.","productDescription":"13 p.","startPage":"877","endPage":"889","numberOfPages":"13","ipdsId":"IP-036109","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":275377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275376,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2136/sssaj2012.0069"}],"country":"United States","state":"Kentucky","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.5715,36.4972 ], [ -89.5715,39.1475 ], [ -81.965,39.1475 ], [ -81.965,36.4972 ], [ -89.5715,36.4972 ] ] ] } } ] }","volume":"77","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-04-19","publicationStatus":"PW","scienceBaseUri":"51f25422e4b0279fe2e1c026","contributors":{"authors":[{"text":"Williamson, Tanja N. tnwillia@usgs.gov","contributorId":452,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja N.","email":"tnwillia@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":479605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Charles J.","contributorId":93100,"corporation":false,"usgs":true,"family":"Taylor","given":"Charles","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":479607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Newson, Jeremy K. jknewson@usgs.gov","contributorId":4159,"corporation":false,"usgs":true,"family":"Newson","given":"Jeremy","email":"jknewson@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":479606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189267,"text":"70189267 - 2013 - A refined index of model performance: a rejoinder","interactions":[],"lastModifiedDate":"2017-07-07T10:23:43","indexId":"70189267","displayToPublicDate":"2013-04-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"A refined index of model performance: a rejoinder","docAbstract":"Willmott et al. [Willmott CJ, Robeson SM, Matsuura K. 2012. A refined index of model performance. International Journal of Climatology, forthcoming. DOI:10.1002/joc.2419.] recently suggest a refined index of model performance (dr) that they purport to be superior to other methods. Their refined index ranges from − 1.0 to 1.0 to resemble a correlation coefficient, but it is merely a linear rescaling of our modified coefficient of efficiency (E1) over the positive portion of the domain of dr. We disagree with Willmott et al. (2012) that dr provides a better interpretation; rather, E1 is more easily interpreted such that a value of E1 = 1.0 indicates a perfect model (no errors) while E1 = 0.0 indicates a model that is no better than the baseline comparison (usually the observed mean). Negative values of E1 (and, for that matter, dr < 0.5) indicate a substantially flawed model as they simply describe a ‘level of inefficacy’ for a model that is worse than the comparison baseline. Moreover, while dr is piecewise continuous, it is not continuous through the second and higher derivatives. We explain why the coefficient of efficiency (E or E2) and its modified form (E1) are superior and preferable to many other statistics, including dr, because of intuitive interpretability and because these indices have a fundamental meaning at zero.
We also expand on the discussion begun by Garrick et al. [Garrick M, Cunnane C, Nash JE. 1978. A criterion of efficiency for rainfall-runoff models. Journal of Hydrology 36: 375-381.] and continued by Legates and McCabe [Legates DR, McCabe GJ. 1999. Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resources Research 35(1): 233-241.] and Schaefli and Gupta [Schaefli B, Gupta HV. 2007. Do Nash values have value? Hydrological Processes 21: 2075-2080. DOI: 10.1002/hyp.6825.]. This important discussion focuses on the appropriate baseline comparison to use, and why the observed mean often may be an inadequate choice for model evaluation and development.
","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/joc.3487","usgsCitation":"Legates, D.R., and McCabe, G., 2013, A refined index of model performance: a rejoinder: International Journal of Climatology, v. 33, no. 4, p. 1053-1056, https://doi.org/10.1002/joc.3487.","productDescription":"4 p.","startPage":"1053","endPage":"1056","ipdsId":"IP-034043","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-04-18","publicationStatus":"PW","scienceBaseUri":"59609db9e4b0d1f9f0594c46","contributors":{"authors":[{"text":"Legates, David R.","contributorId":194273,"corporation":false,"usgs":false,"family":"Legates","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","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":false,"id":703819,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045064,"text":"tm4C3 - 2013 - Stochastic empirical loading and dilution model (SELDM) version 1.0.0","interactions":[],"lastModifiedDate":"2014-06-10T15:49:42","indexId":"tm4C3","displayToPublicDate":"2013-03-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-C3","title":"Stochastic empirical loading and dilution model (SELDM) version 1.0.0","docAbstract":"The Stochastic Empirical Loading and Dilution Model (SELDM) is designed to transform complex scientific data into meaningful information about the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks. The U.S. Geological Survey developed SELDM in cooperation with the Federal Highway Administration to help develop planning-level estimates of event mean concentrations, flows, and loads in stormwater from a site of interest and from an upstream basin. Planning-level estimates are defined as the results of analyses used to evaluate alternative management measures; planning-level estimates are recognized to include substantial uncertainties (commonly orders of magnitude). SELDM uses information about a highway site, the associated receiving-water basin, precipitation events, stormflow, water quality, and the performance of mitigation measures to produce a stochastic population of runoff-quality variables. SELDM provides input statistics for precipitation, prestorm flow, runoff coefficients, and concentrations of selected water-quality constituents from National datasets. Input statistics may be selected on the basis of the latitude, longitude, and physical characteristics of the site of interest and the upstream basin. The user also may derive and input statistics for each variable that are specific to a given site of interest or a given area. SELDM is a stochastic model because it uses Monte Carlo methods to produce the random combinations of input variable values needed to generate the stochastic population of values for each component variable. SELDM calculates the dilution of runoff in the receiving waters and the resulting downstream event mean concentrations and annual average lake concentrations. Results are ranked, and plotting positions are calculated, to indicate the level of risk of adverse effects caused by runoff concentrations, flows, and loads on receiving waters by storm and by year. Unlike deterministic hydrologic models, SELDM is not calibrated by changing values of input variables to match a historical record of values. Instead, input values for SELDM are based on site characteristics and representative statistics for each hydrologic variable. Thus, SELDM is an empirical model based on data and statistics rather than theoretical physiochemical equations. SELDM is a lumped parameter model because the highway site, the upstream basin, and the lake basin each are represented as a single homogeneous unit. Each of these source areas is represented by average basin properties, and results from SELDM are calculated as point estimates for the site of interest. Use of the lumped parameter approach facilitates rapid specification of model parameters to develop planning-level estimates with available data. The approach allows for parsimony in the required inputs to and outputs from the model and flexibility in the use of the model. For example, SELDM can be used to model runoff from various land covers or land uses by using the highway-site definition as long as representative water quality and impervious-fraction data are available.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Water Quality in Book 4 Hydrologic Analysis and Interpretation","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4C3","collaboration":"Prepared in cooperation with the Department of Transportation Federal Highway Administration, Office of Project Development and Environmental Review. This report is Chapter 3 of Section C: Water Quality in Book 4 Hydrologic Analysis and Interpretation","usgsCitation":"Granato, G., 2013, Stochastic empirical loading and dilution model (SELDM) version 1.0.0: U.S. Geological Survey Techniques and Methods 4-C3, Manual: xii, 112 p.; 5 Appendices; Digital Media Directory, https://doi.org/10.3133/tm4C3.","productDescription":"Manual: xii, 112 p.; 5 Appendices; Digital Media Directory","numberOfPages":"124","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":270337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm4C3.jpg"},{"id":270332,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_apdx1_v030813.pdf"},{"id":270330,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/04/c03/"},{"id":270333,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_apdx2_v030813.pdf"},{"id":270331,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_main_v031913.pdf"},{"id":270334,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_apdx3_pages_v030813.pdf"},{"id":270335,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/c03/tm4-C3_final_508_files/tm4-C3_apdx4_v030813.pdf"},{"id":270336,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/tm/04/c03/virtual_CD/index.html"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5156a9ece4b06ea905cdc006","contributors":{"authors":[{"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":476716,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}